The Current State of Vibroacoustical Machine Diagnostics

By
Natalia A. Barkova
VibroAcoustical Systems and Technologies (VAST,Inc.),
22, Rosenshteina, St. Petersburg, 198095, Russia

This paper is based on lectures delivered by the author at the
St. Petersburg Marine Technical University, Russia.

Abstract

In recent years, the differences between condition, control, and diagnostic systems for machinery have become more distinct. The control systems were the prototypes and currently are components of modern machinery monitoring systems. As a rule, modern condition monitoring system are based on the simplest methods of basic quantity measurements. Diagnostic systems require the maximum possible amount of information which derived by the analysis of signals, namely, from noise and vibration signals. This is the primary reason for diagnostic systems to employ new information techniques and more complicated methods for signal measurement and analysis. The peculiarities of the modern on- and off-line diagnostic systems design are analyzed in the paper together with the information techniques and methods used in these systems for diagnostics of the machines and units of various types.

1. Diagnostic Techniques

The methods and means for condition assessment were developed step by step. At first, different parameters of machines were controlled, then condition monitoring was used, and, finally, diagnostic and predictive systems were developed. With each new system type, the customer gains new possibilities to perform condition based maintenance.

The Control Systems are used to measure a number of parameters for comparison with standard levels. Condition Monitoring Systems present additional information on the development of machine parameters with time, reveal tendencies, and predict possible changes of parameters. Condition Diagnostics Systems use the analysis of measured signals to identify the possible defect type, severity and defect location. An even more difficult problem is solved by the Condition Prediction System. This problem is the prediction of the possible development of the existing combination of defects, forecasts of residual service life and prediction of non-failure operation time.

Recently, the term monitoring has been referred to as the application of the complete set of procedures for condition assessment, although some of the existing condition monitoring systems do not identify defect types nor do they predict defect development. For this reason, monitoring will be further referred to as the control of main parameters, analysis of their trends, and forecasts of possible changes. Diagnostics will be referred to as the identification of defect types and prediction of their development.

The modern condition monitoring and diagnostic systems (Fig. 1) are based on the nondestructive methods.

Fig. 1. On-line (left) and off-line (right) systems for vibration monitoring and diagnostics of machinery.

The diagnostic methods used in the condition monitoring and diagnostic systems may be divided in two main groups:

Next, we will consider the information techniques used only in the functional diagnostics. The number of these techniques is not very large and the variety of condition diagnostic systems is defined only by the combination of the techniques used.

The simplest of the basic techniques is the overall level technique based on the power and amplitude measurements. Temperature (temperature variance), pressure, noise, vibration and many other parameters can be used as a diagnostic signal. Here the condition of the equipment is derived by the comparison of the measured signal values with the standard levels.

The next step in the development of the overall level technique is the frequency technique which is based on signal conditioning prior to the use of overall level measurements. In this case, only the components in the measured signal within a certain frequency band are considered . The frequency analysis technique is used in both condition monitoring and diagnostics of machines and for breakdown protection as well. For example, frequency technique is used for electric arc protection by measuring high-frequency components in the current. Another example is machine protection by the vibration at rotation frequency. Electronic filters are not the only filters that are used to detect different frequency components. Resonance sensors of current, vibration, noise, light flux etc. can be used as well. A stethoscope is the simplest example of this kind of sensor. It transforms the low-frequency vibration of the machine unit into the noise perceived by human ear.

One more technique is the Phase and Time technique which is based on the comparison of the shapes of the signals measured in constant intervals. This technique is used successfully to control the condition of reciprocating machines with several identical parts (cylinders and pistons) loaded at constant intervals. For example, consider Fig. 2 which presents the vibration signal of a automobile engine. The operation quality of each of the cylinders can be estimated by the shape of the vibration signal.

Fig. 2. Vibration spectrum of automobile engine measured at the point between cylinder 2 and 3.

Another technique is used to compare the shape of the signal with a standard shape. This is a Spectrum technique that is based on narrow-band spectrum analysis. Here the diagnostic information can be found in the relationship between amplitudes and phases of certain components and their harmonics. This technique is applied for the analysis of vibration, noise, pressure as well as current and voltage from electric machines. For example, consider Fig. 3 that shows the shapes of the vibration signals measured on a transformer without defects and with magnetic saturation of the active core.

Fig. 3a. Time waveforms of a transformer's core vibration operating under normal conditions (top) and under overload with magnetic saturation of the active core (bottom).

Fig. 3b. Vibration spectra of the same transformer's core operating under normal conditions (top) and under overload with magnetic saturation of the active core (bottom).
(Here: MS is the frequency of mains supply)

Here you can see also the vibration spectra. The analysis of vibration signals shows that magnetic saturation of the active core is followed by the waveform deformation and the increase in vibration components at harmonics of power supply.

The above techniques had been in use to control steam engines for the last century. Only the spectrum technique became widely used in the middle of the present century with the invention of relatively simple spectrum analyzers for the analysis of signals. Nowadays, this technique became widely used in condition monitoring and control systems for machines and equipment.

All of the above techniques have a common limitation for condition diagnostics when you need to detect incipient defects. The problem is that variations of the measured parameters typically exceed the changes indicating incipient defects even in similar appearing non-defective machines. The results of vibration data statistics on good machines of various types give an example of this. These results were proved by independent research in many countries. It was found that a standard variation in many spectrum components lay in the range of 20 dB, i.e. differences of 10 times, and for some components, even higher. At the same time, the defects on the initial stage of their development can produce a considerably smaller influence, changing the values of their typical parameters by only two to three times.

Development of measurement means and computer engineering during recent years makes possible the partial solution of the problems of condition monitoring and diagnostics by creating systems for machine and equipment monitoring, based on the diagnostic techniques discussed above. Such systems are intended for on-line control (monitoring) of the diagnostic parameters of a particular machine or equipment. They have special modes for adaptation on the initial operating stage when defects are, as a rule, absent. During this stage, they also detect and evaluate the influence of the machine modes and environment, such as temperature, features of power or fuel supply on the parameters monitored. This reduces the probability of a false alert by the monitoring system due to the changes of operating modes or environment.

In parallel to the development of condition monitoring systems based on well known diagnostic techniques, new methods of signal analysis were also developed for the condition diagnostic purposes. This work was carried out in many countries. In 1968, Swedish specialists had patented a method that became the basis of the Shock Pulse technique. This started the development several generations of the condition diagnostic systems for rolling element bearings. The principles of this method are illustrated by the signal shown in Fig. 4.

Fig. 4. Vibration excited by shock pulses.

From the figure, you can see that vibration excited by shock pulses considerably varies in instantaneous (peak) signal amplitude and but does not change its root mean square value (power) significantly. The ratio between the peak value (peak) and the root means square value (RMS), which is called the peak factor, is the parameter indicating the presence of single short pulses. So, the value of peak factor for a random signal with no impacts is about 3 - 4. When infrequent, but strong shocks appear in the signal, this value may exceed 20-30. Such pulses appear within rolling element bearings due to improper lubrication or cavities on races. Since the pulses are of very short duration, they generate mostly high frequency vibration. The signal shown in Fig. 4 includes both high frequency vibration components excited by friction forces (temporally stable components) and shock pulses components. The number of shock pulses in a given time period should not be great because the RMS value of the vibration will increase and the peak factor of the measured signal will decrease.

The above technique makes possible the application of simple measurement means of diagnostics. The impact pulses technique finds wide use due to this factor. At the same time, this technique can not be used to detect a number of defects, for example in the rolling element bearings, that do not produce impacts. These are the defects of assembly or installation. Despite the absence of shock pulses, these defects may considerably reduce the service life of rolling element bearings. Moreover, a number of breakdown/dangerous defects of wear also do not produce shock pulses. The methods of shock pulses become less effective when applied to diagnostics of slow rotating equipment which speed is less than 100-200 RPM. One more limitation of the technique is the necessity to make measurements with the intervals not greater than 5-10 days. This is the minimum possible interval needed for a defect to develop to the stage with the maximum peak factor value. Finally, the impact pulses technique does not allow the defect type and severity to be identified, thus making it impossible to introduce long term condition prediction of the bearings.

In 1978, the specialists of VibroAcoustical Systems and Technologies, Inc. proposed a method for the diagnostics of rotating machines units of many types which is known as the Envelope technique. Recently, the use of this technique became widespread countries and has even been applied in medical diagnostics. The purpose of this technique is the analysis of signal power oscillations with time. Such a technique can be used for the high frequency signal which has power changes considerably slower than the period of the high frequency. Since the signal power is defined by its envelope value, this technique is based on the analysis of the envelope of high frequency signal. Fig. 5 contains a high frequency waveform and the corresponding envelope spectrum. The harmonic component in the envelope spectrum reveals periodic oscillations of the primary signal power.

Fig. 5. High frequency random vibration excited by the friction forces and its envelope spectrum for good bearing (left column) and bearing with the race wear (right column). (Here: Fm is the modulation frequency of friction forces)

The most success of the enveloping method, a much more advanced tool compared to the shock pulse method, was in the field of the rolling element bearing diagnostics. More recently, it has been applied to the diagnostics of all rotating machines units with friction forces and dynamic loads including rolling element and journal bearings, turbine and pump impellers, gears within gearboxes and many others.

The enveloping method is widely used in diagnostics but is almost unused in automatic operation, control and machine protection systems. This method has considerable advantages in the detection of the incipient defects. The main advantage of this method is the fact that features of the signals of interest appear only if a defect appears, thus there is no need for the system adaptation to detect possible defects by making and comparing several periodic measurements. The signal features of interest are detected by a single vibration measurement of, not absolute, but relative value, so the method is not sensitive to the accuracy of measurements. It allows detection and identification over 10 different defect types of installation and operation of rolling element bearings, many types of defects of journal bearings, gears, pump impellers and many other units with friction elements, and can provide long term condition prediction for each of them.

This brief analysis of the basic methods of signal processing allows an evaluation of practically all diagnostic techniques used in modern monitoring and diagnostic systems. One more promising technique should be noted in particular which is the Statistic Condition (Image) Recognition technique which was developed a few decades ago, and was not widely applied because of very high calculation requirements. Recently, the self-trained information techniques have been intensively developed to solve the problems of recognition of conditions described by a number of parameters, and have been named "neural networks". It is very possible that, during the next few years, the problem of identification of dynamic processes with the significant random components will be successfully solved. Naturally, this technique, due to its complexity, would be applied, at first, in on-line condition monitoring systems. It may reduce the probability of false alarms due to the changes of operation mode on the machines.

Note that none of the diagnostic techniques that require multi-channel vibration measurements were discussed above. This is because such measurements as correlation, coherence etc. are used to analyze distortions during vibration propagation and allow solutions of the test diagnostics problems. In functional diagnostics, a complex signal generated within machine units is used instead of a simple test signal with known parameters. That's why the efficiency of multi-channel techniques may be not very high in this case. These techniques can be used in particular occasions when sources of test signals are not available. These methods can be used instead of other test methods, for example, when the dimensions of the object under investigation does not allow exciter installation, but does allow installation of small transducers having dimensions which are several times less that exciter dimensions.

2. Instrumentation for measurements and signal analysis

The means of data measurement, analysis and input are part of any diagnostic technique based on any signal processing method. Three main stages can be listed in the development of the diagnostic instrumentation:

All means for measurement and signal analysis incorporate three types of devices with different functions. The first one is a vibration transducer or microphone which transforms mechanical oscillations into an electrical signal. The second is a filter that select the signal components in the desired frequency band. The third is a detector used for the evaluation of the magnitude (power) of the selected components. The filter is not necessarily connected after the transducer nor it is always an electronic circuit. It can be acoustic filter, e.g. resonator, or mechanical filter, e.g. flexible padding, installed before the transducer. Different instruments may contain different combinations of these devices according to the technique they use.

The simplest instruments are devices for measuring the overall level and peak factor, i.e. the shock pulse detector. If there are no special requirements for the frequency band of the measured signal, there may be no filter in the device for overall level measurements. The mechanical resonator typically is made of a metal bar with the resonance at the frequencies higher than 25 KHz. It can be found in most of peak factor devices. Such a high frequency of the resonance decreases the resonator dimensions and allows getting higher peak factor values. The reason for this is that, at high frequencies, the decay time constant in vibration components excited by friction forces that define the RMS value of the signal is minimal.

The simplest devices discussed in the previous paragraph had affordable prices at all stages of instrumentation development, therefore for a long time, practical diagnostics was oriented to them. Recently, the fast development of the computers and significant decreases in their prices allow the use of all the methods discussed in this paper including the more sophisticated diagnostic techniques. Digital signal analyzers are practically equal in price to the simple analog devices, dislodging them from diagnostic use.

The most frequently used measurement instruments based of the computers include waveform, spectrum, and envelope spectrum analyzers. The Waveform analyzer is used to measure the amplitudes and phases of the signal components and a comparative analysis of the particular signal waveforms that are defined by the shaft rotation angle. These analyzers are widely used for the diagnostics of the reciprocating machines and rotors during balancing. The Spectrum analyzer is used to monitor all types of machines and equipment. The Envelope spectrum analyzer is applied for the analysis of periodic changes in time of the power of random signals.

The personal computer with an analog to digital converters can be considered as the most accessible instrument for noise and vibration measurements. Such an instrument allow to use any of considered diagnostic techniques or their combinations. Professional quality sound cards can be used for this purpose. Some companies produce specialized computer boards and corresponding software.

This type of computer boards exists in both full size for use in desktop PCs in laboratories or stands and in PC-card (PCMCIA) to be used with portable computers like Portables, Notebooks or Penbooks for field measurements. For vibration measurements and analysis, it is enough to have A/D card, input circuit interfaced to a vibration transducer, a power supply for the transducer, the personal computer, and corresponding software. Similar systems are produced by a number of companies.

Portable systems based on Notebook and Penbook computers are not widely used because the prices for industrial computers of this type can be compared with the specialized digital signal analyzers. These analyzers are produced by many firms and are most widely used in the applied diagnostics. But modern tendencies in instrument development indicate that some companies are installing computers into their analyzers and some make analyzers from off-the-shelf computers which will probably result in the in very wide introduction of the computers in field measurements and diagnostics.

Digital analyzers are produced for particular groups of techniques with similar principles of signal processing and only a few of them are intended for using all known techniques. As a rule, the analyzers of all types provide narrow band spectrum analysis, but the envelope spectrum analysis of the band passed signal, required for information techniques by the envelope method, is made just by a few analyzers because this type of analysis requires special algorithms and significant calculation power. It can be achieved by the use of specialized signal processors in addition to the main processor that provides preliminary processing of high-frequency signals in real time. Such an analyzer is complicated and produced by a few instrument engineering companies including three Russian companies.

Analysis of the main tendencies of computers development shows that during the next couple of years, compact instruments with built in powerful computers and standard operating systems will be widely available on the market. It is obvious that the measurement and signal analysis instrumentation will develop in this direction. Another perspective is using the common diagnostic techniques in engineering and medical diagnostics which can cause growth in production with consequential reductions in prices of the analysis devices.

The increase of computation power of standard personal computers stimulates one more direction in the development of diagnostic instrumentation which is a combination of functional and test diagnostics in one device. For this purpose, it is necessary to do multi-channel signal analysis including correlation, mutual-spectra, etc. Another possibility is to include a test signal generator into the same device.

The means for signal measurement and analysis in on-line condition monitoring and diagnostic systems have no functional difference from the ones in the portable systems discussed above. The only difference is in the necessity to repeat measurements of the same control points in small intervals in time to provide in-time machine shut down, even in case of avalanche like defects development, so as to prevent machine failure. The most common configuration of an on-line system is shown in Fig. 6.

Fig. 6. Configuration of the on-line condition monitoring and diagnostic system.

For on-line systems, the number of signal measurement and analysis blocks is determined by the number of measurement points and the maximum permissible interval between measurements. The number of transducers in one block may be from one to a few dozens. The measurement block provides analysis of vibration and other physical quantities according the queries of the diagnostic station. The program algorithms are automatically changed in accordance with diagnostic results, i.e. machine conditions. The measurement block may provide comparison between the measurement and analysis results and the preset levels of diagnostic parameters. When the intervals between measurements can be large, the system may contain one measurement block. In this case, all the transducers are connected to this block via a commutation circuit. The measurement block can reside in one housing together with the diagnostic station. The diagnostic station can be just one computer working in the network with the measurement blocks or a number of computers working in parallel or with divided functions.

The perspective of the on-line monitoring systems development is closely connected with the progress in microcomputer technology. The result can be division of functions between the measurement blocks and diagnostic station. The measurement block can provide condition monitoring and address the diagnostic station only in case of defect appearance for their identification. It is evident that one diagnostic system can work with many measurement blocks in this case, controlling conditions of the equipment within entire plant.

3. DIAGNOSTIC METHODS

For many years, the methods of machine control and diagnostics using any kind of diagnostic signals was based on comparison between the magnitude of the signal or its components and the levels that distinguish bad and good machine condition. Condition control and diagnostic systems designed on the basics of these methods select the informative components from the measured signal and detect the moments in time when they exceed preset levels. Any excess of the preset levels was registered as a defect. The defect type was defined according to the combination of components that exceeded the level. Modern systems for condition monitoring originated from the control systems and, until now, have been based on these principles. However, some of the condition monitoring systems allow, not only control of the parameter's magnitude, but also analyze the trends of these parameters, and even predict a date when they will exceed the levels for defects.

As mentioned, the task of the user of the condition monitoring system is to interpret changes in machine condition detected or forecast by the system. If we try to divide such systems of condition monitoring and condition diagnostics, the natural boundary may permit the ability of the system to divide all condition changes into two groups: reversible changes (changes of machine operation modes and conditions) and irreversible changes (defects). Unfortunately, the majority of the condition monitoring systems do not provides a complete solution of this problem which is why the condition diagnostic systems should be used before the condition changes detected by the monitoring system are divided into reversible or irreversible changes. In this respect, the degree of diagnostic system integration into the condition monitoring system should be considered as one of the main characteristics of the diagnostic systems.

The level of the required training of the operator in diagnostics is another very important feature of the condition diagnostic system. Using the level of operator training as a criteria, the diagnostic systems can be divided into three groups:

So, the methods of condition diagnostics by vibration should be classified according to the requirements for their integration in condition monitoring methods and problems in the task of a diagnostic systems user. No less important is the requirements for diagnostic measurement process and depth of the condition diagnostics.

Taking into consideration the requirements listed above, the existing diagnostic methods can be referred to the following groups:

Machine assembly diagnostics are used during and just after machine installation, in particular during field balancing of machines. These methods do not require any information from the condition monitoring systems and are used either in the portable diagnostic systems or in the stands of product inspection. One characteristic of these methods is a possibility to partially use the test diagnostics methods as well. For example, additional centrifugal forces that appear after mounting the trial and balancing weighs in the corresponding planes of the machine under balancing can be considered as the test signals. Dynamic forces of variable frequency that appear in the machine run-out can also be considered as test signals.

From the information techniques used in the considered diagnostic methods, it is necessary to emphasize the initial phase. As a rule, it supplemented by the spectrum and envelope ones. The task for diagnostic systems using this technique is, first of all, to detect the different types of shaft misalignment. This misalignment occurs at the connections of different rotors of the machine. Another task is to find possible causes that may reduce the efficiency of machine balancing. For example, if there are some defects in the machine, then there may be up to ten different reasons for vibration on the rotation frequency of the machine which may hinder balancing. Also, it is necessary to find other possible defects which appear due to the errors in production and assembly technology of different units and parts.

The task for the development of automatic diagnostics systems of machine assembly usually is not set for designers. Machine balancing is usually done by trained professionals who can also can diagnose machines by using expert techniques.

The methods for condition diagnostics by monitoring results are based on the information techniques used to monitor the vibration and acoustic state at the limited number of control points. As a rule, they aim to build either professional or expert diagnostic systems. The diagnosis provided by these methods is not very deep and they are typically applied to define the program for further investigations to identify the detected changes in vibration conditions.

The methods of joint condition diagnostics and monitoring are widely used in the on-line monitoring and diagnostic systems providing the higher accuracy of diagnosis than the previous methods. The positive result is obtained due to increase of the number of measurement points.

The most frequently methods completely separate the condition monitoring and diagnostic functions. As a rule, the systems based on these methods consist of two different parts. The first part with vibration transducers stationary mounted on the machine provides condition monitoring which detects the changes in the vibration state of the machine and finds which of them reveal irreversible changes in machine conditions, and if necessary, predicts their development. After this, if the decision is made to prolong the machine operation, the second part of the condition diagnostic and monitoring system starts. This solves the task of identification of the detected irreversible changes and, if it is possible, prediction of the defect development. The second part of the system can work off-line due to the fact that, for the defect identification, sometimes it is necessary to make additional vibration measurements at the points where the expected defect would produce the strongest effect.

Modern condition monitoring systems may use diagnostic methods for both identification of the defects and changes in operating conditions as well. Such a combination of condition monitoring and diagnostics often increases the quality of the diagnosis because the change of modes very often changes most diagnostic symptoms of defects. At the same time, the diagnostic process is complicated, and requires the higher qualifications of an expert or more sophisticated machine automatic diagnostic systems. This way is chosen by the manufacturers of automatic condition monitoring and diagnostic systems of the leading companies in the world.

The sophistication of the methods for condition monitoring and diagnostics leads to the increase of the number of measurement points and, thus, the price for the systems. The optimum on-line condition monitoring and diagnostic system, from the economic point of view, must be the one with partially simultaneous monitoring and diagnostic functions. For both condition monitoring and diagnostics, a limited number of control points in the units can be chosen that are not necessarily the most powerful sources of machine vibration but that can define its service life. Most frequently, these are the points on the bearing housings. For high speed machines, in which the bearings are the main vibration sources, two to three points can be used additionally on the machine housing far from the bearing units.

The task of condition monitoring is still the detection of vibration state changes in machine and its units by frequent measurements. When even the smallest changes are detected, the condition diagnostic system starts and carries out the full diagnostic measurements using the stationary mounted transducers. Only when the monitoring and diagnostic data are not sufficient to identify the causes of the detected changes, the decision is made to take additional measurements by means of the off-line instruments included in the combined condition monitoring and diagnostic system.

Diagnostic and prediction methods using intermittent vibration measurements.

Most defects that develop in machine units start to influence the vibration pattern of the machine several months before a breakdown situation may occur. The exception to this is some assembly (installation) defects or defects caused by violation of operation instructions of the machine. They may appear at any stage of a machine service life and may rapidly develop up to the breakdown/dangerous situation. If these defects are absent, there is no need for very frequent measurements and an opportunity occurs to design the off-line systems for machine diagnostics. These systems require intermittent measurements once at intervals of several weeks or even months.

Similar to the condition monitoring methods, condition diagnostic and prediction methods are based on different combinations of the discussed diagnostic techniques and usually are intended to be used by skilled analysts. The best results can be obtained by methods based on both spectrum and envelope techniques.

The group of diagnostic methods under consideration requires detailed knowledge of the defect development processes and their influence on the vibration and noise parameters at all types of the machines under diagnosis. Since the given methods are based on the comparative analysis of measurements results made at different times, they require high-quality vibration and acoustic measurements. These measurements can be done a very experienced technician only; this fact limits the diagnostic possibilities and its efficiency. A particular difficulty is to keep the same operating mode of the machine during diagnostics, otherwise it is impossible to detect machine conditions changes effectively.

The development of the condition diagnostic and prediction methods for automatic condition diagnostics and prediction by intermittent vibration measurements faced the same problems as the methods that require operator's decisions. The most difficult problem is to choose the measurements that have certainty, especially if they vary from the previous measurements. This choice is rather difficult if we take into account that there may be several reasons for the change in the vibration state of the machine. These reasons are not only defect development but changes in the machine operating mode, operator's errors in choice of measurement point location, or errors in the attachment of the transducer. In addition, on most of machines, it is nearly impossible to keep the same load, rotation speed and environment conditions from measurement to measurement, especially if measurements are made at long intervals as several weeks or months.

Despite the difficulties examined here, methods of automatic machinery diagnostics by using intermittent vibration measurements have been developed in many countries and a number of diagnostic systems exists in which these methods are effectively used. The best possibilities in automation of diagnostic process with highly accurate diagnostic results use the methods designed by VAST, Inc. for a number of instrument building companies in Russia and other countries.

The methods of condition diagnostics and prediction from a single vibration measurement are the most popular and difficult methods and are based on different combinations of the diagnostic techniques discussed here and, in the majority of situations, can be used only by experienced experts. The peculiarity of this method is that machine is diagnosed from its units or from particular elements if they are the sources of vibration. The best efficiency is obtained when experts make maximum use of spectrum and enveloping techniques.

Any diagnostic method by the single vibration measurement expects the expert's deepest knowledge on the defect development peculiarities and their influence on the vibration (noise) of the object under diagnostics. It is necessary to know all the efficient diagnostic symptoms and levels for a particular machine type. Such tasks can be solved either by the experts on particular machine types or by the diagnostic method developed for a particular machine unit type.

Recently, special attention has been paid to specialized diagnostic methods capable of automating the diagnostics of machines and their parts. The first of these automated methods is for the diagnostics of rolling element bearings using the envelope spectrum of high frequency vibration. This vibration is excited by the friction forces in the units under diagnostics. The first and most complete system of rolling element bearing automatic diagnostics based on these methods was designed by the specialists of VAST, Inc. in 1991.

Today, the automatic diagnostic systems for gearings, in particular gearboxes, by a single vibration measurement is being designed. There is also a basis for creating the similar diagnostic systems for the diagnostics of pumps and turbine impellers. All of these methods are based on the enveloping technique supplemented by the spectrum technique. Very soon, systems for diagnostics of AC electric machines by the single vibration measurement are expected.

The methods of detailed diagnostics by a single vibration (noise) measurement do not yet permit the solution of the problems of diagnostics and long-term condition prediction for all machine parts and, consequently, for machines as a whole. The exception is the most breakdown/dangerous parts, particularly rolling element bearings, for which systems of condition diagnostics and prediction were designed and effectively used for several years. These are based on the methods of detailed condition diagnostics using a single vibration measurement. These methods can be applied in condition monitoring systems and be a basis for a system that identifies reasons for the changes detected. Such methods are capable of separation of reversible changes in vibration state such as changes in operation mode and defects, thus reducing the number false alarms generated by condition monitoring system.

4. OBJECTS for Diagnostics

The main methods of vibration and acoustic diagnostics are intended to detect the incipient defects in the machine and equipment units. Detected defects can be divided into three main groups according to their influence on the vibration state of machines under diagnostics.

The functional diagnostic methods effectively detect defects of the first group. The test diagnostics methods are capable of most efficiently detecting the defects of the third group. The defects of the second group can be detected by both the functional and test diagnostics. If the defects have the features of the first and second defect groups, then, as a rule, the functional diagnostic methods must be used for their detection. Defects of all the three groups, at the final stage of their development, considerably influence the vibration and/or noise signals and, therefore, they can be detected by the condition monitoring systems before a breakdown situation appears.

Below is brief information about the peculiarities of diagnostics of the most important units of the different machine types by the use of the functional diagnostic methods.

During their initial stage of vibration and acoustic diagnostics development, the most significant success was achieved in the diagnostics of the cylinder and piston group of the internal combustion engines. In an engine, during its operation, impact pulses are generated at certain intervals. The pulses are determined by how fuel burns and how the pistons and valves work. Comparison of the different cylinder's vibration exited by impacts using criteria of initial time, shape and amplitude makes possible the detection of the defects of the cylinder and piston group and the ignition and distribution systems. This can be done by using very simple devices such as a vibration transducer and oscilloscope. An example of the oscillogram of a motorcar engine measured between second and third cylinders is shown in Fig. 2. The comparison of the impact pulse parameters such as the shape of waveform enables simple enough diagnostics of the units which are the sources of these impacts. But, at the same time, these strong pulses hamper the analysis of vibration generated by the other units, for example, crankshaft bearings. Therefore, the vibration technique is not the only one used in diagnostics of the internal combustion engines.

The next development stage of vibration diagnostics which can be considered as successful one is the development of methods and means for diagnostics of the rolling element bearings by the shock pulses. Notice, that this pulses appear only when the defects of rolling surfaces and lubrication appear.

Later, diagnostic methods were applied to the analysis of vibration excited by friction forces. The friction forces as well as high-frequency vibration excited by them are random processes in defect free bearings, and their power is constant in time. When the defects appear on rolling surfaces, the power of these processes have periodic changes with the rotation angle, i.e. the amplitude modulation of friction forces and high-frequency vibration appears. The modulation frequency defines the defect type and the modulation index defines the defect severity. The type and value of over ten different defect types are identified today by components of the spectrum of vibration envelope. Figure 7 illustrates the possibility of bearing diagnostics. It shows the spectra of high-frequency vibration envelope of a good bearing and and a bearing one with wear of the outer race.

Fig. 7. High frequency vibration envelope spectra of a good bearing (top) and a bearing with outer a worn outer race (bottom). (Here: BPFO is the ball pass frequency of the outer raceway)

Defects can be detected during their initial development stage, several month before the breakdown situation occurs. Modern automatic condition diagnostic systems designed by VAST, Inc. allow diagnosis using infrequent measurements of a defective bearing giving the defect type, its development stage, and give recommendations on required maintenance or bearing replacement and forecast of non-failure operation period or define the date of the next measurement, if the bearing does not need a replacement. This has led to a switch from time-based maintenance and scheduled repairs and maintenance determined by actual conditions, so called condition based maintenance. In this case, the number of diagnostic measurements during the whole life of the bearing does not exceed ten to fifteen, and each interval between measurements is settled by the system according to the diagnostic results, i.e. actual bearing conditions.

Currently, the diagnostics of gearboxes is a challenging problem. For many years, there were attempts to judge the condition of gearboxes by the appearance of impacts when defective teeth interact. However, impacts are far from been present every time there are teeth defects, in particular, if the defect is a crack or a broken tooth. Also, when the vibrations generated by the mesh impacts pass through gears, shaft and bearings, their attenuation can be random and significant which may cause considerable errors in the defect depth detection by measuring vibration. With the development of systems for bearing diagnostics, it became evident that dynamic loads on bearings produce amplitude modulation of friction forces and high frequency vibration in the same way as defects of friction surfaces. At the same time, defects of gears and gearmesh cause the appearance of the dynamic loads (impacts) on the gear bearings, the magnitude which is determined by the defect depth. Recent developments allow the diagnostics of gearboxes, not by vibration generated by gears interactions, but by impact loads on bearings detected by the analysis of the envelope spectrum of the bearing vibration. By using a combination of the components in the envelope spectrum of bearing high-frequency vibration, it is possible to identify gear wobbling, wear (cavities, spalls), and mesh defects for each of gearbox gears.

Fig ure8 shows envelope vibration spectra of defective gearbox bearings. In the spectra of either bearing pair, you can see the diagnostic symptoms of impact load appearance that indicates unequivocal development of a defect on the gear teeth of the first gear stage.

Fig. 8a. Envelope spectra from bearings on the first stage of the gearbox with defects of gear teeth on the first stage and a cavity on one of the bearings inner race on the second stage. (Here: RPM1 if the rotating speed of the gearbox first stage)

Fig. 8b. Envelope spectra from bearings in the second stage of the gearbox with defects of gear teeth on the first stage and a cavity on one of the bearings inner race on the second stage. (Here: RPM1 is the rotating speed of the gearbox first stage, RPM2 is the rotating speed of the gearbox second stage, BPFI is the ball pass frequency on the bearings inner raceway )

Impeller diagnostic problems within machines of the different types are equally important. Solution have been most successful using the analysis of the pulses of liquid or gas flowing along the impeller blade. Problems are produced, first of all, by the complexity of measurements of the pressure pulses from passing flow that occur very close to the impeller. A rather simple solution can be found for pumps and hydraulic turbines. This solution is to measure the housing vibration generated by pressure pulses of incompressible liquid. In fans, compressors, and gas (steam) turbines, the measurements of the housing vibration do not always produce the desired results and it becomes necessary pressure transducers (microphones) in the housing. Diagnosing the impellers by medium pulses makes it possible to detect such defects as impeller wobbling, blade wear, cavities. Fig. 9 gives an example of the envelope vibration spectra of the housing of a pump during normal operating conditions, and with wear of the impeller blade (b).

Fig. 9. Envelope vibration spectra from the housing of a pump without defects (top), and with wear of impeller blade (bottom). (Here: RPM is the rotating frequency of the impeller, BPF is the blade pass frequency)

The diagnostics of the electric machine circuit made an advancement in quality in 1982 as a result of the proposal of the specialists of VAST to diagnose these problems by using pulsing the electromagnetic torque that occur due to broken windings or air gap asymmetry.

One kind of defects (squirrel-cage of the asynchronous motor) causes pulsing to torque occur at infra-low frequencies followed by rotor operating speed pulses. The latter is easy revealed in narrow-band domain of the low-frequency vibration. The other defects (stator winding of DC machines) cause the pulsing torque at low frequencies that increase the machine vibration measured tangentially relative to the housing at the plane which is perpendicular to the rotating axis. Such increases of vibration are compared at the same point in radial and tangent directions to the axis. A number of defects (asymmetry of air gap) cause appearance of pulsing torque at higher frequencies at which the division of vibration generated by radial forces and pulsing torque is practically impossible. In this case, analysis of electromagnetic field pulses, which are some of the sources of the pulsing torque, produces a good effect. These electromagnetic field components excite the machine vibration at the slot pass frequency. In case of a defect, the slot pass vibration is modulated by the amplitude that is revealed through narrow-band spectral vibration analysis. Fig. 10 gives an example of vibration spectra of AC electric machines with the different defects of circuits.

Fig. 10a. Vibration spectra of the induction motor with no defects. In the balloon, you can see changes due to the break of a "squirrel-cage" rod. (Here: SF is the sliding frequency and RPM is the rotation speed)

Fig. 10b. Vibration spectra of the synchronous machine with no defects. In the balloon you can see changes due to the short- or open-circuit of the excitation winding. (Here MS is the mains supply frequency and SPF is the slot pass frequency)

The diagnostic methods of electric machines through vibration proposed and developed by the specialists of VAST are widely used today in Russia and in foreign countries as well, replacing more labor-consuming diagnostic methods using parameters of voltage, current, and electromagnetic field. By using vibration, practically all the defects of the electric machines are detected, excluding insulation problems. The last ones can be detected after passage of current through the damaged location.

In such a brief review, it is impossible to list all the types of machine parts and defects which can be diagnosed and identified by functional methods of vibration and acoustic diagnostics. Notice, however, that in the early stage of their development, the most defects are detected in the parts of rotor machines with few limitations . These limitations can be reduced to two requirements. The first is the absence of strong impact loads applied to the diagnostic parts during routine operating modes of machines without failure. The second is the absence or very weak presence of the high-frequency vibration, generated by impacts in the other zero-defect machine parts or machines, if it spreads to the part under diagnostics.

Designing the systems for deep diagnostics and condition prediction of common machine types today is one of the promising trends in machinery diagnostics. In Russia, the more significant successes have been obtained by the specialists of VAST, Inc. (VibroAcoustical Systems and Technologies). They give much attention to designing on-line and off-line systems for automatic diagnostics and condition prediction of such rotors and other rotating parts as

The application software packages, designed for deep diagnostics and condition prediction of similar parts by the on-line and portable systems, can be used together with measuring and analyzing vibration means produced by many firms.

Currently, VAST supplies the systems with software for

To use completely the capabilities of deep diagnostics VAST, Inc. designs and produces a variety of measuring and analyzing devices, including devices for on-line monitoring systems and for rotor machine diagnostics. Cooperating with diagnostic devices developers of a number of the world-leading firms, the specialists of VAST work out the engineering solutions for updating the existing systems and creation of the new ones for the deep machine and equipment diagnostics by vibration and noise.

Today, the diagnostic systems and diagnostic software of VAST is efficiently used in the many enterprises of the different industries such as power including nuclear power, petroleum, wood-pulp and paper, iron and steel, aviation, railway transport, shipbuilding, etcetera.

CONCLUSIONS

  1. Capabilities of diagnostic systems depend on choosing the diagnostic signal and information technique. The vibration signal contains diagnostic information which is sufficient, by means of advanced information techniques, to detect the defective machine part, identify the type and depth of a defect, and make a long term prognosis of its development.
  2. The more efficient diagnostic hardware, both on-line and portable ones, is based on computer hardware and techniques which provide using all the capabilities of such promising methods on getting information as spectral analysis, envelope analysis, and statistic condition identification.
  3. The more promising diagnostic methods are, first of all, fast advanced methods for diagnostics and condition prediction of machine parts by using single vibration and noise measurements. They can be efficiently used, not only for portable diagnostic systems, but also for the monitoring systems having limited numbers of on-line fixed vibration and noise transducers.
  4. To expand considerably the application area of monitoring and diagnostic systems, inexpensive automatic diagnostic systems must be provided which do not require the user's diagnostic training. Experience in operating, the first such units in Russia verified their high efficiency.
  5. Any piece of machinery generated noise/vibration can be the object of deep diagnostics. Full information on practically all the breakdown/dangerous defects can be obtained, even during the initial development stage of defects in the machines without reciprocating parts. In machines with reciprocating parts, it is necessary to obtain additional information from the signals of other diagnostic types.

REFERENCES

  1. Barkov A.V. Diagnostics and Condition Prediction of Rolling Element Bearing by vibration signal, pp. 21-23, Shipbuilding No 3, 1985.
  2. Barkova N.A. Vibration and Acoustic Methods of Diagnostics of Ship Electric Devices. Manual: Leningrad Shipbuilding Institute, 1986.
  3. Aleksandrov A.A., Barkov A.V., Barkova N.A., Shafransky V.A. Vibration and Vibrodiagnostics of ship electric equipment: Shipbuilding, Leningrad, 1986.
  4. Mitchell John S., An Introduction to Machinery Analysis and Monitoring, Tulsa: Penn Well Books, 1993.
  5. Barkov A.V., Barkova N.A., Mitchell J.S., Condition Assessment and Life Prediction of Rolling Element Bearings, Sound & Vibration, 1995, June pp. 10-17, September, pp. 27-31.
  6. Azovtsev A.Yu., Barkov A.V., Automatic computer system for roller bearings diagnostics, Computers in Railways V , Proceedings of the COMPRAIL-96 conference, 21-23 August 1996, Berlin, Germany, volume 2, pp. 543-550.
  7. Barkov A.V., Rogov S.N., Ioudin I.A., Archmbault R., Algorithms for Automated Rolling Element Bearings Diagnostics, Proceedings of the 20th Annual Meeting of the Vibration Institute, Saint Louis, Missouri, USA, 1996, pp. 69-73.
  8. Barkov A.V. Optimization of Monitoring and Diagnostics Methods for the Rotating Machines by Vibration and Noise Measurements, Proceedings of the 4th International Congress on Sound and Vibration, St. Petersburg, Russia, June 24-27, 1996, Volume 3, pp. 1573-1578.
  9. Barkov A.V., Barkova N.A., Diagnostics of Gearings and Geared Couplings Using Envelope Spectrum Methods, Proceedings of the 20th Annual Meeting of the Vibration Institute, Saint Louis, Missouri, USA, 1996, pp. 75-83.
  10. Azovtsev A.Yu., Barkov A.V., Carter D.L., Improving the accuracy of Rolling Element Bearing Condition Assessment, Proceedings of the 20th Annual Meeting of the Vibration Institute, Saint Louis, Missouri, USA, 1996, pp. 27-30.
  11. Application Software for Assessment and Condition Prediction of Rolling Element Bearing. User's Manual. Part 3, 4: VAST, St. Petersburg, Russia, 1992.
  12. Application Software for Rotor Balancing in their own Supports. User's Manual. Part 3: VAST, St. Petersburg, Russia, 1993.
  13. Application Software for Condition Monitoring of Machines and Equipment. User's Manual. Part 3: VAST, St. Petersburg, Russia, 1994.