JP2018155494A - Bearing abnormality diagnosis system and bearing abnormality diagnosis method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a bearing abnormality diagnosis system and a bearing abnormality diagnosis method capable of improving maintenance efficiency by exchanging a rolling bearing at necessary timing and by diagnosing presence or absence of bearing abnormality and kind of bearing abnormality by using one vibrating acceleration signal without decomposing the machine equipment.SOLUTION: There are provided a vibration acceleration sensor 12 for detecting the vibration acceleration of a bearing housing 10; a vibration analysis section 214 for performing frequency analysis on an envelope spectrum by envelope processing and FFT analysis on the basis of a vibration acceleration signal from the vibration acceleration sensor 12; a first abnormality diagnosing section 217 for diagnosing the presence or absence of a bearing abnormality on the basis of the envelope spectrum; and a second abnormality diagnosis section 218 for specifying the type of bearing abnormality according to the occurrence order pattern of the peak frequencies detected from the envelope spectrum, or the crest factor that is the ratio of the vibration maximum value of the vibration acceleration signal to the vibration RMS (root mean square) value.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a bearing abnormality diagnosis system and a bearing abnormality diagnosis method. More specifically, the present invention relates to a bearing abnormality diagnosis system capable of diagnosing the presence / absence of a bearing abnormality and the type of bearing failure with one vibration acceleration signal without disassembling mechanical equipment. And a bearing abnormality diagnosis method.

  Conventionally, an AE waveform signal generated during operation of a rolling bearing is detected using an AE sensor, an envelope component obtained by envelope processing is amplified, and the value of the envelope component after the amplification processing reaches a predetermined threshold value. A method for diagnosing a rolling bearing that determines that an abnormality has occurred in the rolling bearing when exceeded is disclosed (for example, see Patent Document 1).

  In addition, the thrust force application mechanism performs a rotation test while applying a thrust force to the rolling bearing unit or bearing housing, and the thrust force is determined based on the effective value, peak value, or crest factor of the detection signal obtained from the vibration sensor. 2. Description of the Related Art A diagnosis device for a rolling bearing unit for diagnosing the presence or absence of an abnormality in a rolling bearing on which a sag acts is known (for example, see Patent Document 2).

JP 2012-78288 A JP 2004-233284 A

  According to Patent Documents 1 and 2, the presence or absence of an abnormality in the rolling bearing can be diagnosed, but the type of failure (for example, failure due to wear or failure due to scratches) cannot be determined. If the type of failure cannot be determined at the time of bearing failure, it is difficult to estimate the remaining life in detail and to identify the place where replacement is required. Depending on the type of bearing failure, the period from when the abnormality is detected by the diagnosis by the envelope analysis diagnosis until it is determined that it is not possible to rotate or is replaced is different, but if bearing abnormality is diagnosed, give priority to safety. Therefore, the bearings may be replaced at an earlier stage than necessary in accordance with the failure that becomes impossible to rotate at the earliest stage, and there is room for improvement from the viewpoint of maintenance efficiency and reduction of running costs.

  The present invention has been made in view of the above-described problems, and an object of the present invention is to provide a bearing capable of diagnosing the presence / absence of a bearing abnormality and the type of bearing failure with a single vibration acceleration signal without disassembling mechanical equipment. An object of the present invention is to provide an abnormality diagnosis system and a bearing abnormality diagnosis method.

The above object of the present invention can be achieved by the following constitution.
(1) A vibration acceleration sensor that is attached to a bearing or a bearing housing that supports the bearing and detects vibration acceleration of the bearing or the bearing housing;
A vibration analysis unit for performing frequency analysis of a frequency spectrum based on a vibration acceleration signal from the vibration acceleration sensor;
A first abnormality diagnosis unit for diagnosing the presence or absence of a bearing abnormality based on the frequency spectrum;
A second abnormality diagnosing unit that identifies the type of bearing abnormality according to the generation order pattern of the peak frequency detected from the frequency spectrum;
A bearing abnormality diagnosis system comprising:
(2) detecting vibration acceleration of the bearing or the bearing housing from a vibration acceleration sensor attached to the bearing or the bearing housing supporting the bearing;
Perform frequency analysis of the frequency spectrum based on the vibration acceleration signal from the vibration acceleration sensor,
Based on the frequency spectrum, diagnose the presence or absence of bearing abnormality,
When the bearing abnormality is diagnosed, the type of the bearing abnormality is specified by the generation order pattern of the peak frequency detected from the frequency spectrum.
Bearing abnormality diagnosis method characterized by the above.
(3) When the bearing abnormality is diagnosed, the type of abnormality of the bearing is specified.
(2) The bearing abnormality diagnosis method according to (2).
(4) a vibration acceleration sensor that is attached to a bearing or a bearing housing that supports the bearing and detects vibration acceleration of the bearing or the bearing housing;
A vibration analysis unit for performing frequency analysis of a frequency spectrum based on a vibration acceleration signal from the vibration acceleration sensor;
A first abnormality diagnosis unit for diagnosing the presence or absence of a bearing abnormality based on the frequency spectrum;
A second abnormality diagnosing unit that determines the type of bearing abnormality based on a crest factor that is a ratio between a vibration maximum value of a vibration acceleration signal of the vibration acceleration sensor and a vibration RMS value (root mean square);
A bearing abnormality diagnosis system comprising:
(5) From the vibration acceleration sensor attached to the bearing or the bearing housing that supports the bearing, the vibration acceleration of the bearing or the bearing housing is detected,
Perform frequency analysis of the frequency spectrum based on the vibration acceleration signal from the vibration acceleration sensor,
Based on the frequency spectrum, diagnose the presence or absence of bearing abnormality,
When the bearing abnormality is diagnosed, the type of the bearing abnormality is specified by a crest factor that is a ratio between a vibration maximum value of a vibration acceleration signal of the vibration acceleration sensor and a vibration RMS value (root mean square).
Bearing abnormality diagnosis method characterized by the above.
(6) When the bearing abnormality is diagnosed, the type of abnormality of the bearing is specified.
(6) The bearing abnormality diagnosis method according to (5).

  According to the bearing abnormality diagnosis system and the bearing abnormality diagnosis method of the present invention, the vibration acceleration sensor includes a vibration acceleration sensor, a vibration analysis unit, a first abnormality diagnosis unit, and a second abnormality diagnosis unit. The frequency analysis of the frequency spectrum based on the vibration acceleration signal thus performed is performed, and the first abnormality diagnosis unit diagnoses whether there is a bearing abnormality based on the frequency spectrum. Further, since the second abnormality diagnosis unit identifies the type of bearing abnormality by the generation order pattern of the peak frequency detected from the frequency spectrum, the presence / absence of the bearing abnormality and the type of bearing abnormality are diagnosed by one vibration acceleration signal. be able to.

  According to the bearing abnormality diagnosis system and the bearing abnormality diagnosis method of the present invention, the vibration acceleration sensor includes a vibration acceleration sensor, a vibration analysis unit, a first abnormality diagnosis unit, and a second abnormality diagnosis unit. The frequency analysis of the frequency spectrum based on the vibration acceleration signal detected by is performed, and the first abnormality diagnosis unit diagnoses the presence or absence of a bearing abnormality based on the frequency spectrum. Further, since the second abnormality diagnosis unit identifies the type of bearing abnormality by the crest factor which is the ratio between the vibration maximum value of the vibration acceleration signal and the vibration RMS value (root mean square), the bearing abnormality is identified by one vibration acceleration signal. The presence or absence of abnormality and the type of bearing abnormality can be diagnosed.

1 is a block diagram showing a schematic configuration of a bearing abnormality diagnosis system according to the present invention. It is a block diagram which shows the function structure of the diagnostic apparatus shown in FIG. It is a flowchart for demonstrating the operation | movement procedure of the bearing abnormality diagnostic system which concerns on 1st Embodiment of this invention. It is a table | surface which shows the relationship between the site | part of the damage | wound of the rolling bearing which concerns on this invention, and the vibration frequency which arises resulting from a damage | wound. (A) is a figure which shows an example of the vibration acceleration signal from the vibration acceleration sensor of 1st Embodiment, (b), (c) is a figure which shows an example of the spectrum data obtained by the envelope process, (d), ( e) is a diagram illustrating an example of a generation order pattern of a peak frequency. It is a flowchart for demonstrating the operation | movement procedure of the bearing abnormality diagnostic system which concerns on 2nd Embodiment of this invention. (A) is a figure which shows an example of the vibration acceleration signal from the vibration acceleration sensor of 2nd Embodiment, (b), (c) is a figure which shows an example of the spectrum data obtained by the envelope process, (d), (d) e) is a diagram of vibration waveforms shown by comparing crest factors.

  Hereinafter, an embodiment of a bearing abnormality diagnosis system according to the present invention will be described in detail with reference to the drawings.

(First embodiment)
The bearing abnormality diagnosis system of the present embodiment shown in FIG. 1 diagnoses an abnormality of the rolling bearing 11 that is a rotating component supported by the bearing housing 10, and detects vibration acceleration generated from the rolling bearing 11. Vibration analysis that performs frequency analysis of a frequency spectrum based on a detection signal of the acceleration sensor 12, a rotation sensor (not shown) that detects the rotation speed of the rolling bearing 11, and the vibration acceleration sensor 12 received via the data transmission means 13. When the first abnormality diagnosis unit 217 diagnoses the presence or absence of a bearing abnormality based on the unit 214, the frequency spectrum, and the first abnormality diagnosis unit 217 diagnoses that there is a bearing abnormality, the vibration acceleration sensor 12 detects A second type for determining the type of abnormality by confirming the generation order pattern of the peak frequency detected from the frequency spectrum based on the signal The error diagnostic portion 218, and an output device 30 comprising a monitor or alarm or the like.
The vibration analysis unit 214, the first abnormality diagnosis unit 217, and the second abnormality diagnosis unit 218 constitute the diagnosis device 20.

  The rolling bearing 11 includes an inner ring 111 that is externally fitted to the rotating shaft 101 of the mechanical equipment, an outer ring 112 that is internally fitted to the bearing housing 10, and a plurality of rolling rings that are arranged to be able to roll between the inner ring 111 and the outer ring 112. It has the moving body 113 and the holder | retainer not shown which hold | maintains the rolling body 113 so that rolling is possible.

The vibration acceleration sensor 12 is fixed to the bearing housing 10 that supports the bearing 11. The method for fixing the vibration acceleration sensor 12 includes bolt fixing, adhesion, combined use of bolt fixing and adhesion, and embedding with a resin material.
In addition, in the case of bolt fixation, you may make it provide a rotation stop function. In addition, by molding the vibration acceleration sensor 12 with a resin material, it is possible to prevent moisture from entering, and further to improve the anti-vibration performance against external vibration, thus dramatically improving the reliability of the sensor itself. can do.

FIG. 2 is a block diagram showing the main functional configuration of the diagnostic apparatus 20 according to this embodiment.
As shown in FIG. 2, the diagnostic device 20 mainly includes a data collection / distribution unit 211, a rotation analysis unit 212, a filter processing unit 213, a vibration analysis unit 214, an internal memory 216, a first abnormality diagnosis unit 217, and a first Two abnormality diagnosis units 218 are provided.
The diagnostic device 20 is composed of a microcomputer. That is, by executing a program recorded and held in the microcomputer, each processing unit such as the data collection / distribution unit 211 is as follows. Each process is executed.

The data collection / distribution unit 211 converts the signal Sig sent from the vibration acceleration sensor 12 into a digital signal by an A / D converter, and simultaneously collects and temporarily accumulates a signal related to the rotational speed, and sets the signal type. In response, it is distributed to either the rotation analysis unit 212 or the filter processing unit 213.
Note that the A / D converter may be integrated with the vibration acceleration sensor 12, and a digital signal may be received via the data transmission means 13 described above.

The rotation analysis unit 212 is caused by damage for each part of the rolling bearing 11 using the predetermined relational expression shown in FIG. 4 based on the design specification data of the rolling bearing 11 and the rotation speed signal from the rotation sensor. Calculate bearing damage frequency.
The bearing damage frequency may be calculated by using past data stored in the internal memory 216 if the same diagnosis has been performed previously.

  When the rotation sensor that detects the rotation speed of the rolling bearing 11 is composed of an encoder attached to the inner ring 111 and a magnet or magnetic detection element attached to the outer ring 112, the output signal is the shape of the encoder. And a pulse signal corresponding to the rotation speed. Therefore, the rotation analysis unit 212 has a predetermined conversion function or conversion table corresponding to the shape of the encoder, and calculates the rotation speed of the inner ring 111 from the pulse signal.

The filter processing unit 213 has a function of a bandpass filter (BPF), extracts a damage filter frequency band from the vibration acceleration signal Sig of the vibration acceleration sensor 12, and removes other unnecessary frequency bands. The damage filter frequency band is set according to the natural frequency band in each bearing device. This natural frequency can be easily obtained by exciting the object to be measured by an impact method using an impulse hammer or the like, and analyzing the frequency of the vibration detector attached to the object to be measured or the sound generated by the impact. it can.
When the object to be measured is the rolling bearing 11, a natural frequency due to any of the inner ring 111, the outer ring 112, the rolling element 113, the bearing housing 10, and the like is given. In general, there are a plurality of natural frequencies of mechanical parts, and the amplitude level at the natural frequency is high, so the sensitivity of measurement is good.

The vibration analysis unit 214 performs frequency analysis of the vibration acceleration signal generated from the rolling bearing 11 based on the output signal from the vibration acceleration sensor 12 from which the damage filter frequency band is extracted. The vibration analysis unit 214 is an FFT calculation unit that calculates the frequency spectrum of the vibration acceleration signal, and calculates the frequency spectrum of the vibration acceleration signal based on the FFT algorithm and envelope analysis.
The vibration analysis unit 214 may perform absolute value processing and envelope processing as preprocessing for performing FFT, and convert only to frequency components necessary for abnormality diagnosis.

The calculated frequency spectrum is output to the first abnormality diagnosis unit 217 as spectrum data as shown in FIG. 5B or FIG. 5C, for example. Further, if necessary, the spectrum data (envelope frequency spectrum) after the envelope processing is also output to the first abnormality diagnosis unit 217.
In FIG. 5, f is the frequency (Hz) and G is the acceleration (m / s ² ).

  The first abnormality diagnosing unit 217 diagnoses an abnormality of the bearing 11 based on the spectrum data obtained by the vibration analyzing unit 214 as follows, for example.

  That is, when the rolling element passing vibration (SD1) as shown in FIG. 5B, for example, is detected in the spectrum data obtained by the vibration analysis unit 214, the first abnormality diagnosis unit 217 is the rotation analysis unit. Based on the bearing damage frequency calculated in 212, it is diagnosed that there is some abnormality in any part of the bearing 11 (diagnosis of the abnormal part).

  On the other hand, when the spectrum data obtained by the vibration analysis unit 214 is such that the rolling element passing vibration SD1 is not detected, as shown in FIG. 5C, for example, there is no abnormality in the bearing 11. Diagnose.

  When the first abnormality diagnosis unit 217 diagnoses that there is an abnormality, the second abnormality diagnosis unit 218 determines the type of abnormality based on the generation frequency pattern of the peak frequency of the spectrum data (type of abnormality) Diagnosis).

  For example, when the peak frequency of the rolling element passing vibration SD1 as shown in FIG. 5D appears up to the fifth order component, it is determined that a failure A (for example, a failure due to a flaw) has occurred. On the other hand, when the spectral data obtained by the vibration analysis unit 214 is, for example, as shown in FIG. 5E, the occurrence component of the peak frequency of the rolling element passing vibration SD1 is up to the third order component, the failure B (for example, It is determined that a failure due to wear has occurred.

  Note that the peak frequency serving as a discrimination index may be a discrete peak frequency such as a primary component, a tertiary component, or an eighth component, regardless of the continuity or regularity of the generation order. .

  For abnormality diagnosis, vibration frequency generated with rotation of the bearing, such as rolling element passing vibration frequency, rolling element revolution frequency, and rolling element rotation frequency, can be used as a diagnostic index to detect and diagnose the behavior when an abnormality occurs.

  The diagnosis result of the rolling bearing 11 determined as described above is stored in the internal memory 216 and sent to the output device 30 by the data transmission means 31 using wireless considering the wired or network.

  The internal memory 216 includes, for example, a memory or an HDD, and includes, for example, design specification data of each rotating part used for calculating the bearing damage frequency, the first abnormality diagnosis unit 217, and the second abnormality diagnosis unit 218. Each data relating to the presence / absence and type of abnormality of the determined rolling bearing 11 is stored.

The output device 30 displays the diagnosis result of the rolling bearing 11 on a monitor or the like in real time. In addition, when an abnormality is detected, an alarm device such as a light or a buzzer may be used to alert the user of the abnormality.
The signal data transmission means 13 may be wired or may be wireless considering the network, as long as it can transmit and receive signals accurately.

  Next, the operation of the bearing abnormality diagnosis system configured as described above will be described. FIG. 3 is a flowchart for explaining an operation procedure of the bearing abnormality diagnosis system of the first embodiment.

  First, in step S1, the vibration acceleration generated from the rolling bearing 11 by the vibration acceleration sensor 12 and the rotation speed of the rolling bearing 11 are detected by the rotation sensor. The detected vibration acceleration signal and rotation speed signal are used as data transmission means. 13 to the data collection / distribution unit 211.

  The data collection / distribution unit 211 amplifies the input analog vibration signal as necessary, converts it to a digital signal by an A / D converter, and performs rotation analysis unit 212, filter processing according to the type of signal. Sort to any of the sections 213.

  Next, the filter processing unit 213 extracts a diagnostic signal based on the data stored in the data collection / distribution unit 211 and the internal memory 216 and outputs the diagnostic signal to the vibration analysis unit 214. In step S2, the vibration analysis unit 214 calculates the frequency spectrum of the vibration acceleration signal based on the FFT algorithm and the envelope analysis based on the diagnostic signal from the filter processing unit 213, and performs frequency analysis.

  When the rolling element passing vibration SD1 is detected in the spectrum data obtained by the vibration analysis unit 214 (see FIG. 5B), the first abnormality diagnosis unit 217 is the rotation analysis unit 212 in step S3. Based on the calculated bearing damage frequency, the presence / absence of abnormality of the bearing 11 is diagnosed (diagnosis of abnormal parts such as an outer ring and an inner ring).

  If it is determined in step S3 that there is an abnormality, in step S4, the second abnormality diagnosing unit 218 determines the generation order pattern of the peak frequency of the frequency spectrum calculated by the vibration analyzing unit 214 (FIG. 5 (d), (See (e)), the type of abnormality such as scratches or wear on the bearing 11 is specified (diagnosis of the type of abnormality).

Next, in step S5, the diagnosis result is sent to the output device 30 by the data transmission means 31 using wireless considering the wired or network, the diagnosis result is displayed, and the process returns to step S1.
If it is determined in step S3 that there is no abnormality, the diagnosis result is displayed on the output device 30, and then the process returns to step S1. Thereby, the state of the bearing 11 can be constantly monitored.

As described above, according to the bearing abnormality diagnosis system and the bearing abnormality diagnosis method of the present embodiment, the following operational effects can be obtained.
(A) The presence or absence of abnormality of the bearing 11 is diagnosed based on the vibration acceleration signal of the vibration acceleration sensor 12 that detects the vibration acceleration of the bearing housing 10 that supports the bearing 11, and the type of abnormality is determined by checking the peak order component. Since the determination is made, the presence / absence and type of abnormality can be diagnosed based on the same signal. That is, a plurality of different diagnoses can be easily performed based on the same signal. Thereby, the bearing 11 can be replaced at an appropriate timing, and the maintenance efficiency is improved.
(B) Since a plurality of types of diagnosis can be performed with a single vibration acceleration signal, it is possible to obtain current saving, device compactness, and cost reduction effects due to the reduction in the number of sensors, input Ch, and signal input circuit.

(Second Embodiment)
Next, a bearing abnormality diagnosis system according to the second embodiment will be described with reference to FIGS. 1, 2, 4, 6, and 7. FIG. The bearing abnormality diagnosis system according to the second embodiment has many points in common with the bearing abnormality diagnosis system according to the first embodiment, and therefore, different points will be mainly described.

As shown in FIG. 1, the bearing abnormality diagnosis system of the second embodiment is fixed to a bearing housing 10 that supports a bearing 11, and detects a vibration acceleration sensor 12 that detects vibration acceleration generated from the rolling bearing 11, and a rolling bearing. 11, a rotation sensor (not shown) for detecting the rotation speed of 11, a vibration analysis unit 214 for performing frequency analysis of the frequency spectrum based on the detection signal of the vibration acceleration sensor 12 received via the data transmission means 13, and a frequency spectrum Based on the first abnormality diagnosing unit 217 for diagnosing the presence or absence of a bearing abnormality and the first abnormality diagnosing unit 217 diagnosing the abnormality, the type of abnormality is determined from the crest factor of the detection signal of the vibration acceleration sensor 12. A second abnormality diagnosis unit 218 for determining the output and an output device 30 including a monitor, an alarm device, and the like.
The vibration analysis unit 214, the first abnormality diagnosis unit 217, and the second abnormality diagnosis unit 218 constitute the diagnosis device 20. The crest factor is a ratio between the vibration maximum value of the vibration acceleration signal and the vibration RMS value (root mean square).

FIG. 2 is a block diagram showing the main functional configuration of the diagnostic apparatus 20 according to this embodiment.
As shown in FIG. 2, the diagnostic device 20 mainly includes a data collection / distribution unit 211, a rotation analysis unit 212, a filter processing unit 213, a vibration analysis unit 214, an internal memory 216, a first abnormality diagnosis unit 217, and a first Two abnormality diagnosis units 218 are provided.

Here, in the present embodiment, the functions of the second abnormality diagnosis unit 218 are different from those in the first embodiment, and other various configurations are the same as those in the first embodiment.
That is, in the second embodiment, as in the first embodiment, the first abnormality diagnosis unit 217 uses the rolling element as shown in FIG. 7B for example in the spectrum data obtained by the vibration analysis unit 214. When the passing vibration SD1 is detected, it is diagnosed that there is some abnormality in any part of the bearing 11 based on the bearing damage frequency calculated by the rotation analysis unit 212 (diagnosis of the abnormal part).

  On the other hand, when the spectrum data obtained by the vibration analysis unit 214 is such that the rolling element passing vibration SD1 is not detected as seen in FIG. 7C, for example, there is no abnormality in the bearing 11. Diagnose.

  When the first abnormality diagnosing unit 217 diagnoses that there is an abnormality, the crest factor varies depending on the type of bearing failure occurring in the bearing 11, so the second abnormality diagnosing unit 218 determines the vibration maximum value of the vibration acceleration signal. The crest factor is obtained as the ratio of the vibration RMS value (root mean square), and the type of abnormality (diagnosis of the type of abnormality) is determined based on this crest factor.

  For example, as shown in FIG. 7D, when the vibration maximum value is large and the vibration RMS value is small, the crest factor is equal to or higher than a predetermined upper limit threshold C. ) Has occurred.

  On the other hand, for example, as shown in FIG. 7 (e), when the vibration maximum value and the vibration RMS value are both large, the crest factor is less than the predetermined upper limit threshold C and exceeds the lower limit threshold D. It is determined that B (for example, a failure due to wear) has occurred.

On the other hand, when the spectrum data obtained by the vibration analysis unit 214 is, for example, as shown in FIG. 7C, the rolling element passing vibration SD1 is not detected, or the crest factor is not more than the lower limit threshold D. In this case, the bearing 11 is diagnosed as having no abnormality.
The setting of each threshold value of the crest factor can be set to an arbitrary value according to the type of failure to be diagnosed, and is set to an optimum range.

  Next, the operation of the bearing abnormality diagnosis system configured as described above will be described. FIG. 6 is a flowchart for explaining an operation procedure of the bearing abnormality diagnosis system of the second embodiment.

  First, in step S1, the vibration acceleration generated from the rolling bearing 11 by the vibration acceleration sensor 12 and the rotation speed of the rolling bearing 11 are detected by the rotation sensor. The detected vibration acceleration signal and rotation speed signal are used as data transmission means. 13 is input to the data collection / distribution unit 211 and distributed to either the rotation analysis unit 212 or the filter processing unit 213 according to the type of signal.

  Next, the filter processing unit 213 extracts a diagnostic signal based on the data stored in the data collection / distribution unit 211 and the internal memory 216 and outputs the diagnostic signal to the vibration analysis unit 214. In step S2, the vibration analysis unit 214 calculates the frequency spectrum of the vibration acceleration signal based on the FFT algorithm and the envelope analysis based on the diagnostic signal from the filter processing unit 213, and performs frequency analysis.

  When the rolling element passing vibration SD1 is detected in the spectrum data obtained by the vibration analysis unit 214 (see FIG. 7B), in step S3, the first abnormality diagnosis unit 217 is the rotation analysis unit 212. Based on the calculated bearing damage frequency, the presence / absence of abnormality of the bearing 11 is diagnosed (diagnosis of abnormal parts such as an outer ring and an inner ring).

  If it is determined in step S3 that there is an abnormality, in step S4, the second abnormality diagnosis unit 218 determines the type of abnormality (diagnosis of the type of abnormality such as a bearing flaw or wear) based on the crest factor. To do.

  Next, in step S5, the diagnosis result is sent to the output device 30 by the data transmission means 31, the diagnosis result is displayed, and the process returns to step S1. If it is determined in step S3 that there is no abnormality, the diagnosis result is displayed on the output device 30, and then the process returns to step S1. Thereby, the state of the bearing 11 can be constantly monitored.

As described above, according to the bearing abnormality diagnosis system and the bearing abnormality diagnosis method of the present embodiment, the following operational effects can be obtained.
(A) Diagnose the presence or absence of abnormality of the bearing 11 based on the vibration acceleration signal of the vibration acceleration sensor 12 that detects the vibration acceleration of the bearing housing 10 that supports the bearing 11, and determine the type of abnormality by checking the crest factor. Therefore, it is possible to diagnose the presence and type of abnormality based on the same signal. That is, a plurality of different diagnoses can be easily performed based on the same signal. Thereby, the bearing 11 can be replaced at an appropriate timing, and the maintenance efficiency is improved.
(B) Since a plurality of types of diagnosis can be performed with a single vibration acceleration signal, it is possible to obtain current saving, device compactness, and cost reduction effects due to the reduction in the number of sensors, input Ch, and signal input circuit.

In addition, this invention is not limited to what was illustrated by each embodiment mentioned above, In the range which does not deviate from the summary of this invention, it can change suitably.
For example, the type of failure corresponding to the band setting value and diagnostic index (in the embodiment, occurrence order pattern, crest factor) is not limited to the above embodiment, but the target bearing, the failure to be detected, diagnostic conditions, required specifications, etc. The optimum setting can be made each time.
In the above embodiment, the type of abnormality is determined after diagnosing the presence or absence of abnormality. However, the present invention is not limited to this, and abnormality type diagnosis based on the generation order pattern and crest factor is abnormal. It may be performed prior to the diagnosis of the presence or absence.
The bearing abnormality diagnosis system of the present invention can be applied to machine equipment such as automobiles, railway vehicles, machine tools, wind power generators, and elevator devices.
Further, in the present embodiment, the case of diagnosing the abnormality of the rolling bearing in the case of the inner ring rotation has been mainly described. However, the bearing abnormality diagnosis system of the present invention can also be applied to one that monitors the state of the rolling bearing in the outer ring rotation. It is.
Furthermore, in this embodiment, the vibration acceleration sensor is attached to the bearing housing. However, the present invention is not limited to this, and the vibration acceleration sensor is embedded in the inner ring and the outer ring of the bearing to wirelessly transmit the vibration acceleration signal to the diagnostic device. May be.

DESCRIPTION OF SYMBOLS 10 Bearing housing 11 Bearing 12 Vibration acceleration sensor 20 Diagnosis apparatus 214 Vibration analysis part 217 1st abnormality diagnosis part 218 2nd abnormality diagnosis part

Claims (6)

A vibration acceleration sensor that is attached to a bearing or a bearing housing that supports the bearing and detects vibration acceleration of the bearing or the bearing housing;
A vibration analysis unit for performing frequency analysis of a frequency spectrum based on a vibration acceleration signal from the vibration acceleration sensor;
A first abnormality diagnosis unit for diagnosing the presence or absence of a bearing abnormality based on the frequency spectrum;
A second abnormality diagnosing unit that identifies the type of bearing abnormality according to the generation order pattern of the peak frequency detected from the frequency spectrum;
A bearing abnormality diagnosis system comprising: From the vibration acceleration sensor attached to the bearing or the bearing housing that supports the bearing, the vibration acceleration of the bearing or the bearing housing is detected,
Perform frequency analysis of the frequency spectrum based on the vibration acceleration signal from the vibration acceleration sensor,
Based on the frequency spectrum, diagnose the presence or absence of bearing abnormality,
Identifying the type of bearing abnormality by the generation order pattern of the peak frequency detected from the frequency spectrum,
Bearing abnormality diagnosis method characterized by the above. If the bearing abnormality is diagnosed, the type of the bearing abnormality is specified.
The bearing abnormality diagnosis method according to claim 2. A vibration acceleration sensor that is attached to a bearing or a bearing housing that supports the bearing and detects vibration acceleration of the bearing or the bearing housing;
A vibration analysis unit for performing frequency analysis of a frequency spectrum based on a vibration acceleration signal from the vibration acceleration sensor;
A first abnormality diagnosis unit for diagnosing the presence or absence of a bearing abnormality based on the frequency spectrum;
A second abnormality diagnosing unit that determines the type of bearing abnormality based on a crest factor that is a ratio between a vibration maximum value of a vibration acceleration signal of the vibration acceleration sensor and a vibration RMS value (root mean square);
A bearing abnormality diagnosis system comprising: Detecting a vibration acceleration of the bearing or the bearing housing from a vibration acceleration sensor attached to the bearing or the bearing housing supporting the bearing;
Perform frequency analysis of the frequency spectrum based on the vibration acceleration signal from the vibration acceleration sensor,
Based on the frequency spectrum, diagnose the presence or absence of bearing abnormality,
When the bearing abnormality is diagnosed, the type of the bearing abnormality is specified by a crest factor that is a ratio between a vibration maximum value of a vibration acceleration signal of the vibration acceleration sensor and a vibration RMS value (root mean square).
Bearing abnormality diagnosis method characterized by the above. If the bearing abnormality is diagnosed, the type of the bearing abnormality is specified.
The bearing abnormality diagnosis method according to claim 5.

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