JP2003130763A - Method and device for evaluation - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method and device for evaluation by which the speed and reliability of diagnostic work can be improved by reducing the burden imposed on the analysis work of vibration signals detected from an installation containing one or a plurality of sliding members. SOLUTION: The device 1 for evaluation is provided with an A/D-converting means 9 which converts analog signals of sounds or vibrations generated by the installation 3 into digital signals, and an arithmetic processing means 13 which generates actually-measured frequency spectrum data by analyzing the output of the means 9 and, at the same time, diagnoses the presence/absence of abnormality in the installation 3 from the presence/absence of peaks in the actually-measured frequency spectrum data to the first order, second order, and fourth order values of a frequency component generated due to the abnormality of the installation 3.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention detects sound or vibration generated from mechanical equipment including one or a plurality of sliding members, analyzes the detected signal, and diagnoses the presence or absence of abnormality caused by mechanical equipment. It relates to an evaluation method and a device, and more specifically, reduces the burden of analyzing the detected signal,
The present invention relates to improvement for realizing speeding up of diagnostic work and improvement of reliability.

[0002]

2. Description of the Related Art Up to now, a sound generated from mechanical equipment has been used as an evaluation method for diagnosing the presence or absence of abnormality such as wear or damage of sliding members in mechanical equipment including one or a plurality of sliding members such as rotating bodies. Alternatively, an evaluation method for detecting the vibration, converting the detected signal into frequency spectrum data by appropriate waveform processing, and comparing the frequency component caused by the abnormality of the mechanical equipment with the frequency spectrum data described above to diagnose the presence or absence of abnormality. It has been known.

The frequency component caused by the abnormality of the mechanical equipment including the sliding member is determined by the design specifications and operating conditions of the sliding member. Can be obtained by calculation processing. Therefore, in the evaluation device for automatically diagnosing the presence / absence of abnormality in mechanical equipment, arithmetic processing means such as a computer is used,
In advance, the frequency component due to the abnormality of the mechanical equipment to be diagnosed is calculated and processed, and the arithmetic processing for converting the waveform of the sound or vibration signal generated by the mechanical equipment into the frequency spectrum data is performed. A calculation process for comparing and collating the frequency component caused by the abnormality of the mechanical equipment, which is calculated and stored in advance, with the frequency spectrum data is performed.

[0004]

By the way, in the conventional evaluation method, a large number of abnormal frequency components from primary to multi-order are obtained for each specific part of the mechanical equipment, and for each of these numerous frequency components. Then, a calculation process for diagnosing whether or not a peak appears on the measured frequency spectrum data of the mechanical equipment and a calculation process for diagnosing whether or not the peak value on the frequency spectrum data is a peak level indicating an abnormality. repeat. Therefore, the amount of arithmetic processing until the final diagnosis becomes enormous and the arithmetic processing means is heavily burdened, and an expensive computer with high arithmetic processing capability is required, which leads to an increase in device cost, and There is a problem that it is difficult to speed up the diagnostic work due to the increase in the time required for the arithmetic processing.

The present invention has been made in view of the above circumstances, and reduces the load of arithmetic processing when diagnosing the presence or absence of abnormality in mechanical equipment including one or a plurality of sliding members, and speeds up diagnostic work. It is also an object of the present invention to provide an evaluation method and device capable of realizing improvement in reliability.

[0006]

In order to achieve the above object, the evaluation method according to the present invention described in claim 1 detects a sound or vibration generated from mechanical equipment including a sliding member, and detects the detected signal. Is an evaluation method for diagnosing whether or not there is an abnormality caused by the mechanical equipment, wherein an analog signal of sound or vibration generated from the mechanical equipment is converted into a digital signal by AD conversion to generate measured digital data. Then, the measured digital data is subjected to appropriate analysis processing such as frequency analysis and envelope analysis to generate measured frequency spectrum data, and the primary, secondary, and quaternary values of the frequency component caused by the abnormality of the mechanical equipment are generated. The presence / absence of a peak on the actually measured frequency spectrum data is used to diagnose the presence / absence of abnormality in the mechanical equipment.

According to a second aspect of the present invention for achieving the above object, an evaluation device according to the present invention detects a sound or a vibration generated from mechanical equipment including a sliding member, analyzes the detected signal, and analyzes the detected signal. An evaluation device for diagnosing the presence or absence of an abnormality caused by equipment, including AD conversion means for converting an analog signal of sound or vibration generated from the mechanical equipment into a digital signal to generate measured digital data, and the AD conversion means. The measured digital data output by the device is subjected to appropriate analysis processing such as frequency analysis and envelope analysis to generate measured frequency spectrum data, and the primary, secondary, and quaternary frequency components caused by the abnormality of the mechanical equipment are generated. By the presence or absence of a peak on the measured frequency spectrum data for the value,
Arithmetic processing means for diagnosing the presence or absence of abnormality in the mechanical equipment.

Further, according to the evaluation method and apparatus of the configurations described in claims 1 and 2, the collation processing for checking the presence or absence of a peak on the measured frequency spectrum data corresponding to the frequency component caused by the abnormality of the mechanical equipment. Is limited to three times of the primary, secondary, and quaternary values of the frequency component due to the abnormality of the mechanical equipment. Comparing with the conventional technology that repeats,
The burden on the arithmetic processing means is greatly reduced. Further, since the matching process is performed over three times of the primary, secondary, and quaternary values of the frequency component due to the abnormality of the mechanical equipment, noise is reduced compared to the case where only the primary of the frequency component is determined. A false diagnosis due to the influence of the above is unlikely to occur, and a highly reliable diagnosis is possible.

[0009] Preferably, claim 3 and claim 4
As described above, in the series of diagnostic processes performed by the arithmetic processing means in the above evaluation method and device according to the present invention,
After the generation of the actually measured frequency spectrum data, the effective value of the actually measured frequency spectrum data is calculated, and a threshold value is set based on the effective value, and the primary and secondary frequencies of the frequency components caused by the abnormality of the mechanical equipment are set. The peak on the measured frequency spectrum data for the fourth order value may be treated as a valid peak only when it exceeds the threshold value. By doing so, for example, before performing the calculation processing for matching on the peaks on the measured frequency spectrum data corresponding to the primary, secondary, and quaternary values of the frequency component caused by the abnormality of the mechanical equipment, By performing the extraction process of extracting the effective peaks by the threshold value, it is possible to eliminate the waste of performing the matching process for the insignificant peaks.

In order to achieve the above object, the evaluation method according to the present invention according to claim 5 detects sound or vibration generated from mechanical equipment including a sliding member and analyzes the detected signal. An evaluation method for diagnosing the presence or absence of an abnormality caused by the mechanical equipment, wherein an analog signal of sound or vibration generated from the mechanical equipment is converted into a digital signal by AD conversion to generate actually measured digital data. After performing appropriate analysis processing such as frequency analysis and envelope analysis on digital data to generate measured frequency spectrum data, calculate the effective value or average value of this measured frequency spectrum data, and calculate the calculated effective value or average value. The reference level is set, and the level on the measured frequency spectrum data for the primary value of the frequency component caused by the abnormality of the mechanical equipment and the reference value are set. Characterized in that the level difference between the level estimating the magnitude of the damage of the specific part of the machinery.

Generally, the increase of the peak level on the actually measured frequency spectrum due to the damage of the sliding member such as the rotating body is most remarkable at the peak corresponding to the primary value of the frequency component due to the abnormality. Therefore, as shown in the evaluation method of the structure described in claim 5, the level on the measured frequency spectrum data with respect to the primary value of the frequency component caused by the abnormality of the mechanical equipment and the effective value or the average of the measured frequency spectrum data. By calculating the level difference from the value, it is possible to efficiently estimate the magnitude of damage with a minimum amount of arithmetic processing, and it is possible to determine an appropriate replacement time for a damaged part from the estimated magnitude of damage.

[0012]

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of an evaluation method and apparatus according to the present invention will be described in detail below with reference to the accompanying drawings. FIG. 1 is a block diagram showing a schematic configuration of a first embodiment of an evaluation method and device according to the present invention, and FIG. 2 is a flowchart showing a procedure of a diagnostic process of the evaluation device shown in FIG.

First, a schematic structure of the evaluation apparatus according to the first embodiment will be described with reference to FIG. 1, and then an evaluation method by the evaluation apparatus will be described in detail. The evaluation device 1 according to the present embodiment includes a vibration detecting unit 5 that outputs an analog signal according to a sound or a vibration generated by a mechanical equipment 3 including one or a plurality of sliding members to be diagnosed, and this vibration detecting unit. Amplifying means 7 for amplifying the signal output by 5, A / D converting means 9 for converting the analog signal amplified by the amplifying means 7 into a digital signal to generate actually measured digital data, and this A
This is a configuration including arithmetic processing means 13 for diagnosing whether or not there is an abnormality in a specific part of the mechanical equipment 3 based on the measured digital data output by the D conversion means 9.

In the case of the present embodiment, a rolling bearing is applied as the sliding member of the mechanical equipment 3 to be diagnosed. Then, the wear and damage of the inner and outer races, rolling elements, cages, etc. constituting the rolling bearing are diagnosed from the sound or vibration when the rolling bearing is driven. In the present embodiment, the sound or vibration of the rolling bearing is meant to include ultrasonic vibration that appears when the rolling bearing is driven, so-called AE (Acoustic Emission).

The arithmetic processing means 13 is a diagnostic computer for arithmetically processing various data for processing stored in advance and actually measured digital data received from the AD converting means 9 based on a diagnostic program. This arithmetic processing means 13
Appropriate analysis processing such as frequency analysis and envelope analysis is performed on the actually measured digital data output from the AD conversion means 9 to generate actually measured frequency spectrum data, and the primary and second frequency components caused by the abnormality of the mechanical equipment 3 are generated. Next, 4
The presence / absence of a peak on the actually measured frequency spectrum data for the next value is used to diagnose the presence / absence of abnormality in the mechanical equipment 3.

The evaluation apparatus 1 described above uses the procedure shown in FIG.
Perform processing. First, the vibration detecting means 5 detects the sound or vibration generated by the mechanical equipment 3 (step S10).
1), and then the signal that has passed through the amplification means 7 is AD conversion means 9
Is converted into a digital signal by AD conversion (step S102) and passed to the arithmetic processing means 13. Arithmetic processing means 1
3 receives the signal received from the AD conversion means 9, for example, WA
It is converted into a digital file in a file format such as a V file (step S103), and if necessary, filtered processing is performed to remove extra signals, etc. to generate measured digital data.

In the case of the present embodiment, the filter processing is to perform predetermined processing on an input signal by a filter processing program incorporated in the arithmetic processing means 13 in advance, and to set the frequency band to be cut in advance. It is composed of a selection process (step S104) and a filtering process process (step S105) for cutting an extra signal according to the selected filter band. The filtering process in steps S104 and S105 is performed to improve the S / N ratio of the collected data, and is unnecessary if the S / N ratio of the input signal is sufficient.

Next, the generated measured digital data is subjected to analysis processing such as frequency analysis and envelope analysis (steps S106 and S107), and the measured frequency spectrum data d1 embodying the sound or vibration detected from the mechanical equipment 3 is obtained. Is obtained (step S108). The measured frequency spectrum data d1 obtained here is the waveform w1 shown in FIG.
Is. This waveform w1 is obtained when the outer ring is fixed and the inner ring is rotated at 150 revolutions per minute in the rolling bearing as the sliding member.

Further, the arithmetic processing means 13 is provided for the primary, secondary, and frequency components of the frequency components generated when a specific portion of the mechanical equipment 3 is abnormal.
The presence / absence of a peak on the actually measured frequency spectrum data d1 for the quaternary value is used to diagnose the presence / absence of an abnormality in a specific part of the mechanical equipment 3 (step S109). As shown in FIG. 4, the bearing, which is a sliding member, determines the frequency component value that occurs when an abnormality occurs in a specific part, according to design specifications and usage conditions. The arithmetic processing means 13 relates to the mechanical equipment 3,
One of the frequency components that occurs when an abnormality occurs in a specific part shown in FIG.
Next, second, and fourth values are stored in advance as reference values, and step S109 is performed based on these reference values.

In step S109, specifically, FIG.
According to the procedure shown in FIG. 3, the collation processing for checking the presence or absence of a peak on the measured frequency spectrum data d1 with respect to the primary, secondary, and quaternary values of the frequency component occurring when a specific part of the mechanical equipment 3 is abnormal is performed, and the frequency component When both of the primary value and the secondary value of are coincident with the peak on the measured frequency spectrum data d1 (steps S201 and S202), or the primary value of the frequency component is not coincident with the peak on the measured frequency spectrum data d1. However, when both the secondary value and the quaternary value coincide with the peak on the measured frequency spectrum data d1 (steps S211, S212), the peak exists on the measured frequency spectrum data d1 in two or more frequency components. If it is confirmed, the specific part is diagnosed as abnormal (step S22).
1). On the other hand, when the number of frequency components having a peak on the measured frequency spectrum data d1 is one or less, it is possible that vibration or the like caused by an abnormality in another part influences as noise and happens to form a peak. Is high, a diagnosis of no abnormality is made (step S231).

FIG. 6 shows that in the rolling bearing as a sliding member, the outer ring is fixed and the waveform w1 is generated when the inner ring is rotated at 150 revolutions per minute due to damage to the outer ring which is a specific portion. Primary value Q ₁ of the frequency component to be generated, secondary value Q ₂ ,
The three frequency components of the fourth-order value Q ₄ are additionally shown by broken lines. In the case of FIG. 3 described above, with respect to the similar waveform w1, all the components from the primary value Q ₁ to the high order Q _n of the frequency component generated due to the damage of the outer ring are additionally indicated by broken lines. .

In the above-described evaluation method performed by the evaluation device 1 of the first embodiment, a check for checking whether or not there is a peak on the actually measured frequency spectrum data d1 corresponding to a frequency component occurring when a specific part of the mechanical equipment 3 is abnormal. Processing is mechanical equipment 3
Of the first, second, and fourth order frequency components due to the anomaly
Since it is limited to the number of times, for example, as shown in FIG. 3, as compared with the case of the conventional technique in which the matching process is repeated for all of a large number of frequency components from the first-order to high-order frequency components, the matching process The amount of calculation processing of is greatly reduced.

Therefore, the load on the arithmetic processing means 13 during the analysis work of the signal detected from the mechanical equipment 3 is greatly reduced, and the diagnosis work can be speeded up. Further, since the amount of arithmetic processing is reduced, it is possible to use an inexpensive computer with low arithmetic processing capability as the computer used as the arithmetic processing means 13, and it is also possible to reduce the apparatus cost.

Further, if only the first order of the frequency component generated at the time of abnormality is judged, the peak on the corresponding actually measured frequency spectrum may shift due to the influence of noise or the like.
On the contrary, since the peak is increasing, a misdiagnosis may occur. However, as described above, in the case where the matching process is performed over three times of the primary value, the secondary value, and the quaternary value of the frequency component generated when the specific part of the mechanical equipment 3 is abnormal, all the three times are performed. There is almost no probability of being affected by noise, and therefore, it is possible to improve the reliability of diagnosis by performing the matching process only twice.

Preferably, the arithmetic processing means 13 is
After the actual measurement frequency spectrum data d1 is generated, the effective value f1 of the actual measurement frequency spectrum data d1 is calculated, and the threshold value t1 is set based on the effective value f1 to generate a frequency component when an abnormality occurs in a specific part of the mechanical equipment 3. peak on the measured frequency spectrum data d1 to the primary value Q _1, 2-order value Q _2, 4-order value Q ₄ of, may only configured treated as valid peaks exceed the threshold t1.

FIG. 7 shows an effective value f1 and a threshold value with respect to the waveform w2 of the measured frequency spectrum data d1 when the outer ring is fixed and the inner ring is rotated at 150 revolutions per minute in the rolling bearing as the sliding member. t1 is written. Further, the first-order value q ₁ , the second-order value q ₂ , and the fourth-order value q ₄ of the frequency component generated due to the scratches on the rolling elements of the rolling bearing as the sliding member are written on the waveform w 2 by a dotted line. . In this case, the effective value f1 is calculated by calculating the average level of the amplitude of the waveform w2, and is −8.5 dB. Further, since the threshold value t1 is set to t1 = (f1 + 10 dB) (1), the threshold value t1 becomes 1.5 dB. In this example, rolling primary value q ₁ wound on due to generate frequency components of the moving object (2 fb), of the secondary value q _2, 4-order value q _4, secondary value q ₂ is the threshold t1 Since it is smaller and buried in noise, it indicates that the collation process is necessary only for the first-order value q ₁ and the fourth-order value q _{4 which} are larger than the threshold value t1.

In this way, when the useful peak can be selected by the threshold value t1, for example, the first-order value, second-order value, and fourth-order value of the frequency component generated due to the abnormality at the specific portion of the sliding member are generated. Before performing arithmetic processing for matching on the peak on the measured frequency spectrum data corresponding to
If the extraction processing for extracting the effective peaks by the threshold value t1 is performed, it is possible to eliminate the waste of performing the matching processing for the insignificant peaks, further reduce the burden of the calculation processing amount, and speed up the diagnosis processing. Can be promoted.

In the above embodiment, the case of diagnosing the presence or absence of damage to a specific portion is shown. However, as described above, when the actually measured frequency spectrum data d1 is generated by performing appropriate analysis processing such as frequency analysis and envelope analysis on the actually measured digital data, for example, as shown in FIG. Data d1
Is calculated, and the calculated effective value f1 is set to the reference level L ₀ , and 1 of the frequency component generated due to the abnormality (in this example, the outer ring is damaged) of a specific part of the mechanical equipment 3 is generated. From the magnitude of the level difference 1 between the level L _h and the reference level L ₀ on the actually measured frequency spectrum data d1 with respect to the next value Q _1, the magnitude of damage to the outer ring that is causing an abnormality can be estimated. Note that FIG. 8 shows an envelope waveform of the rotating body that is a sliding member.

FIG. 9 shows the relationship between the magnitude of peeling and the peak and reference level appearing on the actually measured frequency spectrum data d1 when the rolling bearing as the sliding member is peeled, which is damage to the bearing ring. It shows the relationship with the level difference. Thus, in general, the level difference increases in proportion to the size of the damage. Therefore, conversely, the level difference at the peak on the actually measured frequency spectrum data d1 is obtained to estimate the size of the damage. Is possible. Moreover, the increase of the peak level on the actually measured frequency spectrum data d1 due to the damage of the mechanical equipment 3 becomes most remarkable at the peak corresponding to the primary value of the frequency component due to the abnormality.

Therefore, as described above, the level L _h on the actually measured frequency spectrum data d1 with respect to the primary value of the frequency component generated due to the abnormality at the specific portion of the mechanical equipment 3 and the actually measured frequency spectrum data d1. Effective value f of
By calculating the level difference 1 with 1, it is possible to efficiently estimate the damage size with a minimum of arithmetic processing, and by determining the replacement time of the damaged part from the estimated damage size, excessive replacement of parts can be performed. It is possible to reduce maintenance costs in equipment and facilities including sliding members by avoiding maintenance.

The reference level L ₀ has an effective value f
Instead of 1, the average value of the measured frequency spectrum data d1 may be adopted.

The sliding member to be diagnosed by the evaluation method and apparatus of the present invention is not limited to the rolling bearing shown in the above embodiment. Various types of sliding members other than bearings can be diagnosed, and for example, ball screws, linear guides, motors, etc. can be included. Even if the sliding member is still installed in the equipment or facility, if the sound or vibration generated when the sliding member is driven can be detected by the prescribed vibration detection means, remove it from the equipment or facility and directly Can be diagnosed.

[0033]

As described above, according to the evaluation method and apparatus of the present invention as set forth in claims 1 and 2, the frequency component generated when the specific part of the mechanical equipment including the sliding member is abnormal is detected. The matching process for checking the presence or absence of a peak on the corresponding actually-measured frequency spectrum data is limited to three times of the primary value, secondary value, and quaternary value of the frequency component caused by the abnormality. Compared with the case of the conventional technique in which the matching process is repeated for a large number of frequency components up to high-order frequency components, the amount of calculation processing during the matching process is significantly reduced. Therefore, the load on the arithmetic processing means during the analysis work of the vibration signal detected from the mechanical equipment is significantly reduced, and the diagnosis work can be speeded up. Moreover, since the amount of calculation processing is reduced, the computer used as calculation processing means
It is possible to use an inexpensive computer with low calculation processing capacity, and it is possible to reduce the device cost.

Further, if only the first-order value of the frequency component generated at the time of abnormality is judged, the peaks on the corresponding actually measured frequency spectrum may deviate due to the influence of noise or the like, or conversely the peaks may increase. May cause a false diagnosis. However, as described above, when the matching process is performed three times, that is, the first-order value, the second-order value, and the fourth-order value of the frequency component generated due to the abnormality, the influence of noise is generated in all three times. There is almost no probability of receiving it, and the reliability of diagnosis can be improved.

Further, according to the third and fourth aspects, for example, the primary, secondary, and quaternary values of the frequency component generated due to an abnormality in a specific part of the mechanical equipment are generated. If the extraction process that extracts valid peaks by the threshold value is performed before performing the calculation process for matching on the corresponding peaks on the measured frequency spectrum data, it is useless to perform the matching process on insignificant peaks. It is possible to omit the above, further reduce the load due to the amount of calculation processing, and accelerate the diagnosis processing.

In general, the increase of the peak level on the actually measured frequency spectrum due to the damage of the mechanical equipment becomes most remarkable at the peak corresponding to the primary value of the frequency component due to the abnormality. Therefore, as in the evaluation method according to claim 5, the level on the measured frequency spectrum data with respect to the primary value of the frequency component that occurs when a specific part of the mechanical equipment is abnormal and the effective value or average value of the measured frequency spectrum data. By calculating the level difference between and, the size of the damage can be estimated efficiently with a minimum of arithmetic processing. Therefore, by determining the replacement time of the damaged component based on the estimated damage size, it is possible to avoid excessive component replacement and maintenance, and reduce the maintenance cost of the equipment or facility including the sliding member.

[Brief description of drawings]

FIG. 1 is a block diagram showing a configuration of a first embodiment of an evaluation apparatus that realizes an evaluation method according to the present invention.

FIG. 2 is a flowchart showing a processing procedure by the evaluation device shown in FIG.

FIG. 3 is a waveform diagram showing an actually measured frequency spectrum when abnormal vibration occurs due to a scratch on the outer ring of the rolling bearing.

FIG. 4 is a diagram showing a relationship between a location of a scratch on a rolling bearing and a frequency.

FIG. 5 is a flowchart showing a processing procedure of matching processing between a frequency component at the time of abnormality and a peak portion of the actually measured frequency spectrum data.

FIG. 6 is a waveform diagram showing the matching points of frequency components on the actually measured frequency spectrum when abnormal vibration occurs due to a scratch on the outer ring.

FIG. 7 is a waveform diagram showing a matching portion of frequency components on an actually measured frequency spectrum when abnormal vibration occurs due to a scratch on a rolling element.

FIG. 8 is an envelope waveform diagram of a frequency component caused by an abnormality and an actually measured frequency spectrum.

FIG. 9 is a correlation diagram between the magnitude of delamination on the surface of the rolling element and the level difference between the average levels of the peaks appearing in the actually measured frequency spectrum.

[Explanation of symbols]

1 Evaluation device 3 Mechanical equipment including one or more sliding members 5 Vibration detection means 7 Amplification means 9 AD conversion means 13 arithmetic processing means

Claims (5)

[Claims] 1. An evaluation method for detecting sound or vibration generated from mechanical equipment including a sliding member, analyzing the detected signal, and diagnosing whether or not there is an abnormality caused by the mechanical equipment. A sound or vibration analog signal generated from equipment is converted into a digital signal by AD conversion to generate measured digital data, and the measured digital data is subjected to appropriate analysis processing such as frequency analysis and envelope analysis to measure the measured frequency spectrum. Data is generated, and the presence / absence of abnormality of the mechanical equipment is diagnosed by the presence / absence of peaks on the measured frequency spectrum data for the primary, secondary, and quaternary values of the frequency component caused by the abnormality of the mechanical equipment. Evaluation method characterized by. 2. An evaluation device for detecting sound or vibration generated from mechanical equipment including a sliding member, analyzing the detected signal, and diagnosing whether or not there is an abnormality caused by the mechanical equipment. AD conversion means for converting an analog signal of sound or vibration generated from the digital signal into digital signal to generate measured digital data, and appropriate analysis processing such as frequency analysis and envelope analysis for the measured digital data output by the AD conversion means. To generate the measured frequency spectrum data, and determine whether or not there is a peak on the measured frequency spectrum data for the primary, secondary, and quaternary values of the frequency component caused by the abnormality of the mechanical equipment. An evaluation device, comprising: an arithmetic processing unit for diagnosing the presence or absence of 3. After generation of the actually measured frequency spectrum data, an effective value of the actually measured frequency spectrum data is calculated, and a threshold value is set based on the effective value to detect the frequency component caused by the abnormality of the mechanical equipment. Primary, secondary,
The evaluation method according to claim 1, wherein a peak on the measured frequency spectrum data for a quaternary value is treated as an effective peak only when the peak value exceeds the threshold value. 4. The calculation processing means calculates the effective value of the actually measured frequency spectrum data after generating the actually measured frequency spectrum data, and sets a threshold value based on the effective value to detect an abnormality of the mechanical equipment. 3. The evaluation apparatus according to claim 2, wherein the peaks on the measured frequency spectrum data for the primary, secondary, and quaternary values of the frequency component caused are treated as valid peaks only when the peaks exceed the threshold value. 5. An evaluation method for detecting a sound or vibration generated from mechanical equipment including a sliding member, analyzing the detected signal, and diagnosing whether or not there is an abnormality caused by the mechanical equipment. A sound or vibration analog signal generated from equipment is converted into a digital signal by AD conversion to generate measured digital data, and the measured digital data is subjected to appropriate analysis processing such as frequency analysis and envelope analysis to measure the measured frequency spectrum. After the data is generated, the effective value or average value of the measured frequency spectrum data is calculated, the calculated effective value or average value is set as a reference level, and the primary value of the frequency component caused by the abnormality of the mechanical equipment is calculated. Estimating the magnitude of damage to a specific part of the mechanical equipment from the level difference between the level on the measured frequency spectrum data and the reference level. Evaluation method according to claim.