JP2963144B2 - Bearing abnormality detection device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial applications]

The present invention relates to a bearing abnormality detection device using acoustic emission (AE).

[Prior art]

2. Description of the Related Art Conventionally, as an apparatus for detecting an abnormality of a bearing by AE, there is the following apparatus (JP-A-63-304128). This bearing abnormality detection device comprises a comparing means for comparing the AE signal from the AE sensor with a threshold value, and a cycle calculation for calculating an occurrence cycle of the AE signal exceeding the threshold value based on an output from the comparing means. Means, a counting means for counting the number of occurrences of each AE signal generation cycle based on the output of the cycle calculation means, and whether or not the number of occurrences counted by the counting means exceeds a single threshold value AE signal is generated for each generation cycle, and if the accumulated value exceeds the threshold, it is determined that the bearing is abnormal and AEs other than bearings are generated. The system is designed to detect bearing abnormalities even in environments with high noise or high external noise.

[Problems to be solved by the invention]

However, in the conventional bearing abnormality detection device described above,
Since the abnormality is determined by comparing the number of occurrences of the AE signal in each generation cycle with a single threshold value, there is a problem that the detection accuracy is low for the following reasons. For example, if there is an abnormality in the inner ring during one rotation of the bearing, an AE signal exceeding the threshold is generated only once, but if there is an abnormality in the outer ring,
The AE signal exceeding the threshold is generated only about (number of rolling elements / 2) times. Therefore, the threshold value to be compared with the number of AE occurrences should be different for each part such as the inner ring and the outer ring. However, the above-described conventional bearing abnormality detection device compares the number of AE occurrences with a single threshold value for all parts, and therefore has a low accuracy of abnormality detection. Therefore, the object of the present invention is to provide an actual AE
An abnormality detection device for bearings that can detect bearing errors with high accuracy by dividing the number of occurrences by the theoretical number of occurrences of AE for each part to calculate the AE occurrence probability and comparing this AE occurrence probability with a single threshold value Is to provide.

[Means for Solving the Problems]

In order to achieve the above object, a bearing abnormality detection device according to the present invention includes an AE sensor that detects acoustic emission from a bearing and outputs an AE signal, and compares the AE signal from the AE sensor with a threshold value. Means for receiving a signal indicating that the AE signal has exceeded the threshold value from the comparing means, and calculating a generation cycle of an AE signal exceeding the threshold value; and the cycle calculating means. Tallying means for tallying the number of occurrences for each occurrence cycle calculated in the above, and dividing the number of occurrences for each occurrence cycle counted by the tallying means by the theoretical occurrence number for each part corresponding to each occurrence cycle, AE occurrence probability calculation means for calculating the AE occurrence probability for each part, and determination means for determining whether or not the AE occurrence probability output from the AE occurrence probability calculation means has exceeded a threshold value to determine whether the bearing is abnormal. And that It is set to.

[Action]

AE from a bearing or the like is detected by an AE sensor, and an AE signal is output. The AE signal is compared with a threshold value by the comparing means, and when the AE signal exceeds the threshold value, a signal indicating the threshold value is output. Upon receiving the signal from the comparing means, the cycle calculating means calculates the cycle of the AE signal. The counting means counts the number of occurrences of the AE signal for each occurrence cycle calculated by the cycle calculation means. The AE occurrence probability calculating means calculates the AE occurrence probability for each part by dividing the number of occurrences for each occurrence cycle counted by the counting means by the theoretical occurrence number for each part corresponding to the occurrence cycle. The determining means compares the AE occurrence probability output from the AE occurrence probability calculating means with a single threshold value, and determines that the bearing is abnormal when the AE occurrence probability in the occurrence cycle exceeds the threshold value. I do. Thus, since the AE occurrence probability is compared with the threshold,
There is no need to make the threshold different for each part, and the bearing can be diagnosed accurately with a single threshold. The occurrence cycle in which the AE occurrence probability exceeds the threshold value can determine which of the inner ring, the rolling element, and the outer ring is damaged.

【Example】

Hereinafter, the present invention will be described in detail with reference to the illustrated embodiments. In FIG. 1, reference numeral 1 denotes an AE sensor for detecting an AE of a bearing or the like. The AE signal representing the magnitude of the AE output from the AE sensor 1 is amplified by the preamplifier 2, and then the AE signal in a band of, for example, 100 KHz to 500 KHz is passed through the bandpass filter 3 to remove noise. The AE signal from which the noise has been removed by the band-pass filter 3 is further amplified by the main amplifier 4, input to the envelope detection circuit 5, and subjected to envelope detection. The AE signal has, for example, a waveform as shown in FIG. 2 (a) and shows a spectrum as shown in FIG. 2 (b). The waveform after the envelope detection by the envelope detection circuit 5 is as shown in FIG. 2 (c). The AE signal after the envelope detection is compared with a threshold value in the comparator 6, and when the AE signal exceeds the threshold value, a pulse as shown in FIG. The rotation number of the bearing per unit time is input to the computer 7 from the rotation sensor 8. In the computer 7, processing is performed according to a flowchart shown in FIG. First, initial settings are made in step S1 of FIG. 3, and the process proceeds to step S2, where it is determined whether a predetermined time has elapsed. Here, when it is determined that the specified time has not elapsed, the process proceeds to step S3, and it is determined whether or not an AE has occurred, based on whether or not a pulse has been received from the comparator 6, and the AE has occurred. Step if not determined
Returning to S2, when it is determined that an AE has occurred, the process proceeds to step S4, the time A (I) at which this AE was detected is stored in the memory, and the process returns to step S2. Time A (I) at which this AE occurred
Is shown in FIG. After repeating the above steps S2, S3 and S4, if it is determined in step S2 that the specified time has elapsed, the process proceeds to step S5, where the AE occurrence time A stored in step S4 is stored as shown in FIGS. (1), A (2),…, A
(4) generation periods B (1), B (2),
.., B (6) are calculated. This generation cycle B (I) is calculated by a subroutine shown in FIG. First, in step S21, I = 1, N = 1, K
= 1 is set initially. Next, step S22
And the generation cycle B (1) is {A (2) −A (1)}.
Then, the process proceeds to step S23, where it is determined whether or not N has become {the number of occurrences-I}. Now, as shown in FIG. 5, since the number of occurrences is 4 and I = 1, it is determined whether N is 3 or not. Now, because N is 1,
Proceeding to step S24, assuming that K = 2 and N = 2, step S22
And the generation cycle B (2) = {A (3) -A (1)}.
, And through steps S23, S24 and S22, a generation cycle B (3) = {A (4) -A (1)} is calculated. Next, since N = 3 in step S23, step S23 is executed.
Proceeding to 25, it is determined whether or not I = {the number of occurrences-1}, that is, whether or not the occurrence cycle B (6) has already been obtained when I = 3. Now, since I = 1, the process proceeds to step S26, where I = 2, N = 1, the process returns to step S22, the generation cycle B (4) is obtained, and the generation cycle B (4) is further processed through steps S23, S24, and S22. B (5) is obtained. Further, steps S23 and S2
After 5, S26 and S22, the generation cycle B (6) is obtained, and step S
After 23 and S25, the calculation of the generation cycle shown in FIG. 5 is completed. Then, the process returns to step S6. In step S6, the number of rotations per unit time of the bearing during the lapse of the specified time received from the rotation sensor 8 is converted into a reference rotation number, and the cycle calculated in step S5 is corrected to the cycle at the reference rotation number. That is, a process of multiplying the period calculated in step S5 by the number of rotations of the bearing per unit time detected by the rotation sensor 8 and dividing by the reference rotation number is performed.
Next, the process proceeds to step S7, where the AE signals are totaled for each generation cycle. That is, as shown in FIG.
The number of occurrences of each AE occurrence cycle is calculated. Then step
Proceeding to S8, an AE occurrence probability is calculated by dividing the number of AEs generated per period (by site) by the number of theoretical AEs generated per period (by site). Here, the theoretical number of occurrences of AE means that one part of the inner ring, the outer ring, and the rolling element is assumed to be damaged,
The number of AEs generated from each part per rotation. Next, proceeding to step S9, as shown in FIG. 6, it is determined whether or not the AE occurrence probability for each occurrence period exceeds a single threshold value, and the AE occurrence probability If it exceeds, it is determined that the bearing is damaged, and the process proceeds to step S10 to output an alarm indicating a bearing abnormality. In this way, it differs by site
Since the AE occurrence probability obtained by dividing the AE occurrence number by the theoretical AE occurrence number is compared with a threshold value, damage to each part can be detected with a single threshold value with high accuracy. Damaged parts of the bearing can be identified based on the occurrence cycle in which the AE occurrence probability exceeds the threshold. That is,
If the above bearing is a roller bearing with the inner ring as a rotating ring, the frequency at which the roller passes through a certain portion of the inner ring is Fi, the rotational frequency of the shaft is Fr, the frequency at which the rolling element passes through a predetermined portion of the outer ring is F ₀
The rotation frequency of the roller Fb, when the rotational frequency of the cage was Fc, when the case if there is an abnormality in the inner ring there is an abnormality in the 1 / Fi, 1 / Fr outer ring there is abnormality in 1 / F ₀ Coro An AE occurs with a period of 1 / Fb, 1 / Fc. That is, inner ring, outer ring,
The occurrence cycle of AE differs depending on each damage of the roller. Therefore, it is possible to determine which of the inner ring, the outer ring, and the roller has peeled based on the occurrence cycle in which the AE occurrence probability exceeds the threshold value. If it is determined in step S9 that the AE occurrence probability does not exceed the threshold value in any occurrence period, the process returns to step S2. In this embodiment, after removing noise with a band-pass filter having a band of 100 KHz to 500 KHz, an AE signal having a certain amplitude or more is detected, and the number of occurrences of this AE signal in each cycle is calculated. When the AE occurrence probability exceeds a single threshold, it is determined that the bearing is abnormal, so it is possible to accurately detect abnormalities such as peeling occurring in the bearing,
In addition, it is possible to specify a separated portion of the bearing. Also, when the bearing rotation speed changes, it affects the AE generation cycle.However, since the rotation cycle is detected by the rotation sensor and the generation cycle is corrected, the effect of fluctuations in the bearing rotation rate is affected. It is possible to pinpoint a damaged portion of the bearing without receiving it. In addition, since the bearing abnormality is determined based on the AE occurrence probability of the AE signal that occurs with a specific period, the occurrence of AE in the bearing in an environment where AE other than the bearing occurs, such as at the time of metal in a rolling mill, etc. Abnormalities such as peeling can be accurately detected.
It is possible to specify a peeled portion of the bearing. In the above embodiment, the threshold value to be compared with the amplitude of the AE is a constant value, but the threshold value may be changed according to the magnitude of external noise or the like. In the above-described embodiment, the AE generation cycle is corrected after the end of the specified time. However, the AE generation cycle may be corrected each time an AE occurs. Further, when the rotation speed is constant or when a change in the rotation speed is predicted, the rotation speed or the predicted rotation speed is input to the computer 7 without using the rotation sensor 8 to correct the AE generation cycle. Good. If the rotational speed is constant and it is not necessary to determine the damaged part of the bearing, it is possible to not correct the AE generation cycle.

【The invention's effect】

As apparent from the above description, the bearing abnormality detection device of the present invention includes a comparison unit that compares an AE signal from an AE sensor with a threshold value, and a period calculation unit that calculates a generation period of an AE signal exceeding the threshold value. Counting means for counting the number of occurrences for each generation cycle of the AE signal; and AEs for each occurrence site counted by the counting means.
AE occurrence probability calculation means for dividing the number of occurrences by the theoretical number of AE occurrences, and determination means for determining whether the AE occurrence probability exceeds a threshold value. Since the bearing abnormality is discriminated by comparing the threshold value with the threshold value, the occurrence of the bearing abnormality can be identified and detected with a single threshold value with high accuracy.

[Brief description of the drawings]

FIG. 1 is a block diagram of a bearing abnormality detecting device according to the present invention,
2 (a), (b), (c), (d), and (e) show waveforms in respective parts of this embodiment, FIG. 3 is a flowchart of the above embodiment, and FIG. FIG. 5 is a flowchart showing a subroutine for calculating the occurrence period, FIG. 5 is a diagram showing the relationship between the occurrence time and the occurrence period, and FIG. 6 is a diagram showing the relationship between the occurrence period, the AE occurrence probability, and the threshold value. 1 ... AE sensor, 3 ... Band pass filter, 5 ...
Envelope detection circuit 6 Comparator 7 Computer
8. Rotation sensor.

Continuation of the front page (72) Inventor Noriaki Inoue 1-chome, Mizushima-Kawasaki-dori, Kurashiki-shi, Okayama (No address is displayed) Kawasaki Steel Corporation Mizushima Steel Works (56) References JP-A-63-304132 (JP, A) JP-A-63-304128 (JP, A) JP-A-3-232230 (JP, A) JP-A-4-36633 (JP, A) (58) Fields investigated (Int. Cl. ⁶ , DB name) G01M 13 / 04

Claims (1)

(57) [Claims] An AE sensor for detecting an acoustic emission from a bearing and outputting an AE signal; a comparing means for comparing an AE signal from the AE sensor with a threshold value; Receiving a signal indicating that the threshold value has been exceeded, a cycle calculating means for calculating the occurrence cycle of the AE signal exceeding the threshold value, and counting the number of occurrences for each occurrence cycle calculated by the cycle calculation means Tallying means, and dividing the number of occurrences for each occurrence cycle totaled by the tallying means by the theoretical number of occurrences for each part corresponding to each occurrence cycle,
AE occurrence probability calculating means for calculating an AE occurrence probability for each part; determining means for determining whether or not the AE occurrence probability output from the AE occurrence probability calculating means has exceeded a threshold value to determine whether the bearing is abnormal And a bearing abnormality detecting device.