Every machine which contains rotating elements, such as bearings, shafts, and gears, exhibits reasonable levels of vibration which are characteristic of its normal operation. Based upon knowledge of the rotational speed of individual machine elements, machine maintenance personnel can monitor the machine's vibration level at certain characteristic frequencies to acquire an indication of the overall condition of the machine. As the mechanical integrity of a machine element begins to degrade, the vibration level associated with that element changes from its normal characteristic level, indicating to the machine maintenance personnel that corrective action will soon be necessary. By implementing a machine monitoring program, the machine's vibration levels can be measured on a regular schedule, and early detection of abnormal machine operation is possible. With such early warning, repair of the machine may be scheduled well before a machine breakdown and the associated work stoppage occurs. In this manner, machine "down-time" may be scheduled well in advance so as to minimize the impact on manufacturing operations.
A machine monitoring program typically includes dozens or even hundreds of rotating machines. For each of these machines, vibration spectra are typically collected at a number of locations on the machine. Specific spectral features in the measured data may include harmonic families or difference families, which are associated with certain types of machinery faults. From this collected data, an analyst determines which machines are operating with a fault condition. For the machines that are in fact operating with a fault condition, the type of fault, its location, and its severity must be determined. After the severity of the individual faults on a machine are identified and ranked, the severities of all of the machines included in the machine monitoring program which have been identified with a fault condition are then ranked relative to each other. This relative ranking aids the maintenance technician in identifying those machines that are in the greatest danger of a catastrophic failure so that action may be taken in the appropriate time period. Relative rankings also enable the technician to observe whether a particular machine's performance is improving or degrading compared to previous measurements.
One well-known method of determining a measure of severity for a machine's vibration spectrum involves comparison of the spectral overall value to a chart which defines acceptable overall vibration levels for rotating machines. For example, the Rathbone chart provides an allowable level of overall vibration that a machine can exhibit by ranking the machine's operating condition from extremely smooth to very rough in nine incremental steps. One weakness to this approach is that there are machinery faults, such as bearing defects, that generate only small changes in the overall power of a vibration spectrum. In addition, observing only the overall changes in vibration level gives little, if any, indication as to the exact type of fault that is present. Without knowing the type of fault that is present, an accurate measure of machine fault severity is typically not possible. Another significant weakness of this prior approach is that it does not consider the design of the machinery. The physical design and configuration of a machine determines the frequencies at which vibration peaks will exist under normal operation. By making no attempt to examine individual peaks, this prior method is generally unable to isolate which component of the machine has caused an overall increase in the vibration power.
Another known method of determining fault severity based upon a machine's vibration spectrum involves the calculation of values that represent the amount of energy present in certain regions, or bands, of the vibration spectrum. Several of these analysis parameter bands may be specified, each with an associated alarm limit to which a calculated parameter value can be compared. The machine's fault severity can be crudely characterized by examining the deviation of the calculated values from their associated alarm limit, with a severity value in the range of A-D assigned for each band.
One problem associated with the analysis parameter band method is imprecision. Machinery faults do not necessarily generate significant changes in the overall energy of a particular band of a vibration spectrum. Moreover, examining the energy of a particular band of a spectrum still does not provide detailed information about the peaks themselves. As a result, this approach also gives little information as to the type of fault that is present. Once such a scheme has indicated that there is a significant increase in vibration levels in particular bands, an analysis of the peaks must still be performed manually to isolate the cause of the fault. Such manual peak analysis is a tedious and time consuming task.
Other existing predictive vibration monitoring systems typically report that a machine's vibration level has exceeded a limit level, and that the severity of the reported fault falls into one of a few categories of severity, such as "slight", "moderate", "serious", or "extreme". However, in order to adequately rank the severity of fault conditions, it is desirable to assign a value to the fault severity. Such a value, which allows differentiation of fault severity based on incremental differences between the severity values assigned to different vibration spectra, provides for a continuous ranking method. The severity value provides more useful information to an analyst than that provided by a scheme which simply lumps fault severity into broad categories. Also, if a fault severity value is assigned to a particular vibration spectrum of a particular machine, this value is available to the analyst for later comparison against subsequent vibration measurements on the same machine. A history of such directly comparable fault severity values gives an indication as to whether or not an abnormal condition is worsening.
Generally, machine fault conditions generate vibration peaks at specific frequencies, or more commonly, in a group or groups of related frequencies. Peaks occurring at harmonic frequencies and sideband (difference) frequencies are examples of complex features that can be directly related to specific machine fault conditions. Since vibration energy associated with a particular machine fault can be contained in an individual peak, as well as being distributed throughout the harmonic and sideband peaks, it is advantageous for the vibration analyst to have an indication of the severity of the features based on the total power contained in these spectral features. By monitoring the changes in the power contained in these specific spectral features, the analyst can assess whether the particular machine fault is worsening.
The known methods of specifying machine fault severity based on vibration spectra have not provided for the determination of the severity of faults associated with such specific spectral features within a vibration spectrum. The methods which consider only the overall increase in power across a complete spectrum provide little useful information about specific component faults. Those methods which detect vibration energy increases in particular bands in the spectrum do not differentiate between the peaks associated with different fault families that may fall within the same band.
In addition, prior fault severity determination schemes have not considered both the extent to which a peak level exceeds an alarm limit level and the ratio of this deviation magnitude to the limit level applied to the peak. The determination of fault severity values that are based on both peak excess magnitude and peak excess ratio enable determination of an accurate level of severity for peaks that are produced as a result of different types of fault conditions. This is desirable since some fault conditions can result in rather large changes in the energy of the peaks associated with the given fault, but generally small changes in excess ratio. An example of such a fault is rotor imbalance. When a machine is operating normally, with a balanced rotor, there is usually a significant vibration peak present at the running speed of the machine where most of the spectral vibration energy is concentrated. If the rotor becomes imbalanced, although the energy in the vibration peak may increase significantly, the ratio of this increase to the original level may not appear significant. However, if absolute levels are considered, the increase could be considerable. For example, if the original peak was 0.5 in/sec, and another 0.25 in/see is added due to a rotor imbalance, then the excess magnitude may be of significance since all of the energy associated with this fault is focused at a single frequency. Therefore, it is desireable to consider both the magnitude of the excess level as well as the ratio of the excess in order to accurately evaluate the severity of faults whose energy is concentrated at a single peak.
On the other hand, some fault conditions, such as bearing defects, result in large changes in the ratio of the excess to its envelope alarm limit, even though the change in the power of the excess was relatively small. With bearing defects, a high change in ratio results since peaks associated with bearing defect frequencies, which are not present when a machine is operating normally, appear in the measured test data. Thus, if a peak of even slight significance is suddenly present at a bearing defect frequency, the ratio of its value compared to its envelope alarm limit value will be significant. Therefore, the ratio of the excess vibration level to the limit level, as well as the excess magnitude should be taken into account when determining a fault severity value.
In order to provide an accurate assessment of fault severity, the frequency of the vibration peak under analysis should be considered. At higher frequencies, the machine feels the excessive vibration levels more often per shaft revolution. More specifically, since more oscillations occur in a given amount of time, the acceleration which is generated by these additional direction changed will increase. The acceleration of a machine is directly proportional to the force that it feels, and this force is what actually damages machinery components. However, prior fault severity determination schemes have not considered the frequency of the excess vibration peak when assigning a severity level. These prior schemes have not provided for normalizing the excess vibration level as a function of the vibration frequency prior to calculating the severity of the excess.
Therefore, considering the foregoing deficiencies in prior predictive machine vibration monitoring schemes, a need exists for a predictive vibration monitoring system which accounts for the magnitude of an excess vibration peak amplitude as well as the ratio of the excess peak amplitude to a limit amplitude. A need also exists for a predictive vibration monitoring system that provides for determination of the fault severity of individual fault conditions that may be manifested as individual peaks, or families of related peaks, within the vibration spectrum. A further need exists for a predictive vibration monitoring system that normalizes the magnitude of the excess vibration level on a frequency-dependent basis prior to determining a severity value for the excess. A need also exists for a predictive vibration monitoring system which determines a fault severity value for a vibration spectrum which, on an incremental scale, indicates the severity of fault conditions such that fault severities of several machines may be ranked. There is also a need for a predictive vibration monitoring system which provides for the analysis of vibration peaks which fall into particular regions of a vibration spectrum so that particular fault modes are isolated. In addition, a need exists for a predictive vibration monitoring system that compares a machine's test vibration spectrum to a limit envelope on an order-normalized basis, so that variations in machine running speed do not affect the fit of the limit envelope to the test vibration spectrum, thus ensuring that specific peaks are compared to the correct alarm limit level.