JP2009020090A - Abnormality diagnosis apparatus and abnormality diagnosis method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To accurately diagnose existence of abnormalities and specify the part of the abnormalities, in rotation components and sliding components that are incorporated in a machinery and equipment. <P>SOLUTION: Vibration generated during operation from a rolling bearing 11 of the machine facility 10 is detected by an acceleration sensor 12, is transmitted to a signal processor 21 and is converted into a digital signal, and then the level of a frequency spectrum is determined by performing envelope analysis and frequency analysis. Abnormal frequency of the vibration resulting from the abnormal part of the rolling bearing 11 is calculated, based on a predetermined relational expression, and the level of the frequency spectrum corresponding to the abnormal frequency is extracted. The extracted level of the frequency spectrum is compared and collated with a threshold which is set individually for each of the frequency of the fundamental wave and the harmonics of the abnormal frequency, and by determining each magnitude, thereby diagnosing the existence of the abnormality and the abnormal part. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an abnormality diagnosis apparatus and abnormality diagnosis method for diagnosing abnormality of rotating parts or sliding parts used in mechanical equipment, and in particular, diagnosis of presence / absence of abnormality without disassembling the mechanical equipment and the abnormality. The present invention relates to an abnormality diagnosis device and an abnormality diagnosis method that identify a rotating part or a sliding part corresponding to the above.

  In rolling stock, machine tools, windmills, and other mechanical equipment, many rotating parts such as rolling bearings and sliding parts such as ball screws and linear guides are used. If wear or damage occurs due to the use of these rotating parts and sliding parts for a long time, smooth rotation and sliding of the rotating parts and sliding parts will be hindered, and not only will abnormal noise be generated, There is a risk of damage resulting from a decline, resulting in failure of machinery or accidents. For this reason, conventionally, after using a mechanical equipment for a certain period, it was inspected for abnormalities such as wear and damage.

  This inspection is performed by disassembling the part of the machine equipment where the rotating parts and sliding parts are incorporated, or the entire machine equipment, and damage and wear occurring on the rotating parts or sliding parts are visually observed by the operator. Discovered by inspection. The main defects (abnormalities) discovered by inspection include indentations caused by foreign matter biting, peeling due to rolling fatigue, other wear, etc., in the case of gears, tooth defects, In the case of a wheel such as wear, there is flat wear or the like, and in any case, if irregularities or wear that are not found in a new article are found, it is replaced with a new one. That is, if abnormalities such as wear and damage are found as a result of the inspection, the parts are replaced with new ones to prevent machine equipment failures and accidents.

  However, in the inspection method in which a part or the whole of the mechanical equipment is disassembled and visually checked by the operator, the work for removing the rotating parts and sliding parts from the mechanical equipment and the rotating parts and sliding parts that have been inspected are again performed. There has been a problem that a large amount of labor is required for the work to be incorporated into the mechanical equipment, and the maintenance cost of the mechanical equipment increases.

  Further, when reassembling, the inspection itself has a possibility of causing defects in the rotating body and the sliding member, such as attaching a dent to the rotating body and the sliding member that was not present before the inspection. Further, since a large number of bearings are visually inspected within a limited time, there is a problem that a possibility of overlooking a defect remains. Further, the determination of the degree of this defect also varies from person to person, and parts are exchanged even if there is virtually no defect, resulting in unnecessary costs.

In order to solve such a problem, conventionally, various abnormality diagnosis apparatuses or abnormality diagnosis methods for performing abnormality diagnosis of rotating parts and sliding parts in an actual operating state of mechanical equipment have been proposed.
For example, the vibration acceleration signal of a rolling bearing measured by an acceleration sensor is subjected to FFT (Fast Fourier Transform) processing to extract a vibration generation frequency component signal, and a threshold value set in advance based on the type and age of the bearing There is an abnormality diagnosis device that diagnoses the presence or absence of an abnormality by comparing (see, for example, Patent Documents 1 and 2).

JP 2002-22617 A Japanese Patent No. 3846560

However, in such a conventional abnormality diagnosis device, the threshold value is unique, that is, a single value is set as a predetermined constant value, and therefore there is an abnormality such as damage in a rotating part such as a rolling bearing. However, there was a problem that sufficient diagnostic accuracy could not be obtained.
For example, when an acceleration sensor is attached to the outer ring of a rolling bearing as a detecting means, vibration caused by a defect (abnormal vibration) generated from a certain abnormal part varies depending on the difference in the transmission path, and more specifically, The abnormal vibration tends to be smaller when the abnormality exists in the inner ring or the ball than when the abnormality exists in the outer ring. In addition, when the inner ring rotates, the rotating shaft is fitted with the inner ring, so that abnormal vibration tends to be attenuated in the rolling bearing.

  In this way, even if each abnormal part shows the same magnitude of abnormal vibration, the level of the signal measured varies depending on the part, and a unique threshold is used to diagnose and detect abnormalities. If the part is specified, a different diagnosis result is output for each part, and even if an abnormality occurs, this abnormality may not be detected. As a result, stable operation of the mechanical equipment is hindered. there is a possibility.

  In addition, the abnormality diagnosis apparatus described in the above-mentioned patent documents has a problem in that stable operation is hindered, for example, the diagnosis accuracy deteriorates due to the influence of ambient noise and the like, and an abnormality alarm is issued based on a false diagnosis.

  The present invention has been made in view of the above-described circumstances, and an object of the present invention is to accurately diagnose the presence / absence of an abnormality and to identify an abnormal part with respect to rotating parts and sliding parts incorporated in mechanical equipment. It is an object of the present invention to provide an abnormality diagnosis apparatus and abnormality diagnosis method.

In order to achieve the above-described object, the abnormality diagnosis apparatus according to the present invention is configured as follows. (1) A signal generated from a rotating part or a sliding part of mechanical equipment is detected by a detecting means, and the detection result is enveloped. Analysis and frequency analysis are performed to obtain the frequency component of the actual measurement data, and the abnormal frequency of vibration caused by the abnormality of the rotating part or the sliding part is calculated based on a predetermined relational expression to correspond to the abnormal frequency By extracting the frequency component of the actually measured data and comparing and comparing the extracted frequency component with a threshold value, it is possible to diagnose whether there is an abnormality and the rotating part or the sliding part corresponding to the abnormality. An abnormality diagnosis device that performs the identification of the site of
The abnormality diagnosis apparatus, wherein the threshold value is set individually for each frequency of a fundamental wave and a harmonic wave of the abnormal frequency.
(2) The abnormality diagnosis device according to (1), wherein the threshold value is set based on a rotational speed of the rotating part or a moving speed of the sliding part.
(3) The signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detecting means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the measured data, and the rotating part or the sliding part is obtained. An abnormal frequency of vibration caused by an abnormality of the moving part is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and the extracted frequency component and a threshold value By performing comparison and collation, an abnormality diagnosis apparatus that performs diagnosis of presence / absence of abnormality and identification of a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis apparatus, wherein the threshold value is set individually for each part.
(4) The abnormality diagnosis according to (3), wherein the threshold is individually set based on a transmission distance or a transmission path of the signal between the part and the detection means. apparatus.
(5) The threshold value is set such that a threshold value of a predetermined part of the rotating part or the sliding part is set with reference to a threshold value of another predetermined part. The abnormality diagnosis device according to any one of (1) to (4).
(6) The abnormality diagnosis apparatus according to any one of (1) to (5), further including transmission means for transmitting the diagnosis and the specific result.
(7) The process according to any one of (1) to (6), wherein at least one of the envelope analysis, the frequency analysis, and the comparison and collation is executed by a microcomputer program. Abnormality diagnosis device.
(8) A railcar bearing device to which any one of the abnormality diagnosis devices according to the above (1) to (7) is applied.
(9) A bearing device for a wind turbine to which any one of the abnormality diagnosis devices according to (1) to (7) is applied.
(10) A machine tool spindle bearing device to which any one of the abnormality diagnosis devices (1) to (7) is applied.

According to the abnormality diagnosis apparatus of the above (1), for example, sound, vibration, ultrasonic wave (AE) generated during operation from a rotating part or a sliding part incorporated in a mechanical device such as a speed reducer, an electric motor, a windmill, or a railway vehicle. The physical quantity (signal) such as distortion includes a frequency component indicating this defect or abnormality when there is a defect or abnormality in the mechanical equipment including the rotating part or the sliding part. For this reason, after detecting these physical quantities and converting them into electrical signals, envelope analysis and frequency analysis are performed to determine the frequency component of the measured data, and the abnormal frequency of vibration caused by abnormalities in the rotating part or sliding part is determined. Calculation is performed based on a predetermined relational expression, the frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and the extracted frequency component is compared with the threshold value. At this time, the threshold value is individually set for each of the fundamental frequency and the harmonic frequency of the abnormal frequency, so that it is difficult to be influenced by the surrounding noise, diagnosis of presence / absence of abnormality, and specific accuracy of the abnormal part Can be improved.
Further, according to the abnormality diagnosis device of (2) above, when setting the threshold value for each fundamental wave and higher harmonic wave, the threshold value is set based on the rotational speed of the rotating part or the moving speed of the sliding part. Become. That is, for example, this threshold value is increased or decreased in conjunction with these speeds, and the presence or absence of abnormality and the identification of the abnormal part are performed. It is possible to cope with changes due to the influence of wheel wear, and it is possible to improve the accuracy of diagnosis of presence / absence of abnormality and identification of an abnormal part.
According to the abnormality diagnosis apparatus described in (3) above, the physical quantity generated from the rotating part or sliding part incorporated in the mechanical equipment is detected, converted into an electrical signal, and then subjected to envelope analysis and frequency analysis, and actual measurement While calculating the frequency component of the data, the abnormal frequency of the vibration caused by the abnormality of the rotating part or the sliding part is calculated based on a predetermined relational expression, and the frequency component of the measured data corresponding to the abnormal frequency is extracted. Then, the extracted frequency component is compared with the threshold value. At this time, since the threshold value is individually set for each part of the rotating part or the sliding part, it is possible to accurately diagnose whether there is an abnormality and to identify the abnormal part.
When the threshold value is set for each part as in the abnormality diagnosis device of (4) above, it is individually set based on the transmission distance or transmission path of the signal between the part and the detection means. It is good to be. Thereby, the influence of signal attenuation or the like due to the arrangement of the parts is taken into consideration, so that the presence / absence of abnormality and the identification of the abnormal part can be performed with higher accuracy.
As in the abnormality diagnosis device of (5) above, the threshold value of a predetermined part of the rotating part or the sliding part may be set based on the threshold value of another predetermined part. Thereby, diagnosis of the presence or absence of abnormality and specification of the site | part of abnormality can be performed more accurately.
According to the abnormality diagnosis device of (6) above, since the transmission means for transmitting the diagnosis and the specific result is provided, the result can be transmitted to, for example, a data processing device, and data processing can be performed. Alternatively, it is possible to diagnose the presence / absence of an abnormality in a plurality of rotating parts or sliding parts of a mechanical facility and to specify an abnormal part with high accuracy and simultaneously in an actual operation state.
According to the abnormality diagnosis apparatus of (7) above, since at least one of the envelope analysis, the frequency analysis, and the comparison and collation is executed by a microcomputer program, the apparatus is simplified and miniaturized. And it can be configured at low cost.
By applying the abnormality diagnosis device according to the present invention to the railway vehicle bearing device as in the abnormality diagnosis device of (8) above, it is possible to contribute to the safe operation of the railway vehicle.
By applying the abnormality diagnosis device according to the present invention to the wind turbine bearing device as in the abnormality diagnosis device of (9) above, it is possible to contribute to safe operation of the wind turbine.
By applying the abnormality diagnosis device according to the present invention to the machine tool spindle bearing device as in the abnormality diagnosis of (10) above, it is possible to contribute to the safe operation of the machine tool.

In order to achieve the above-described object, the abnormality diagnosis method according to the present invention is configured as follows.
(11) A signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detecting means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the actual measurement data. An abnormal frequency of vibration caused by an abnormality of the moving part is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and the extracted frequency component and a threshold value By performing comparison and collation, an abnormality diagnosis method for performing diagnosis of presence / absence of abnormality and specifying a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis method, wherein the threshold value is individually set for each frequency of a fundamental wave and a harmonic wave of the abnormal frequency.
(12) The abnormality diagnosis method according to (11), wherein the threshold value is set based on a rotational speed of the rotating part or a moving speed of the sliding part.
(13) The signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detecting means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the measured data, and the rotating part or the sliding part is obtained. An abnormal frequency of vibration caused by an abnormality of the moving part is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and the extracted frequency component and a threshold value By performing comparison and collation, an abnormality diagnosis method for performing diagnosis of presence / absence of abnormality and specifying a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis method, wherein the threshold is individually set for each part.
(14) The abnormality diagnosis according to (13), wherein the threshold is individually set based on a transmission distance or a transmission path of the signal between the part and the detection unit. Method.

According to the abnormality diagnosis method of (11) above, for example, sound, vibration, ultrasonic (AE) generated during operation from a rotating part or a sliding part incorporated in a mechanical equipment such as a speed reducer, an electric motor, a windmill, or a railway vehicle. The physical quantity (signal) such as distortion includes a frequency component indicating this defect or abnormality when there is a defect or abnormality in the mechanical equipment including the rotating part or the sliding part. For this reason, after detecting these physical quantities and converting them into electrical signals, envelope analysis and frequency analysis are performed to determine the frequency component of the measured data, and the abnormal frequency of vibration caused by abnormalities in the rotating part or sliding part is determined. Calculation is performed based on a predetermined relational expression, the frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and the extracted frequency component is compared with the threshold value. At this time, the threshold value is individually set for each of the fundamental frequency and the harmonic frequency of the abnormal frequency, so that it is difficult to be influenced by the surrounding noise, diagnosis of presence / absence of abnormality, and specific accuracy of the abnormal part Can be improved.
According to the abnormality diagnosis method of (12) above, when the threshold value is set for each fundamental wave and harmonic wave, it is set based on the rotational speed of the rotating part or the moving speed of the sliding part. That is, for example, this threshold value is increased or decreased in conjunction with these speeds, and the presence or absence of abnormality and the identification of the abnormal part are performed. It is possible to cope with changes due to the influence of wheel wear, and it is possible to improve the accuracy of diagnosis of presence / absence of abnormality and identification of an abnormal part.
According to the abnormality diagnosis method of (13) above, a physical quantity generated from a rotating part or a sliding part incorporated in a mechanical facility is detected, converted into an electrical signal, envelope analysis and frequency analysis are performed, While obtaining the frequency component, calculating the abnormal frequency of the vibration caused by the abnormality of the rotating part or the sliding part based on a predetermined relational expression, and extracting the frequency component of the actual measurement data corresponding to the abnormal frequency, The extracted frequency component is compared with the threshold value. At this time, since the threshold value is individually set for each part of the rotating part or the sliding part, it is possible to accurately diagnose whether there is an abnormality and to identify the abnormal part.
When the threshold value is set for each part as in the abnormality diagnosis method of (14) above, it is individually set based on the transmission distance or transmission path between the signal of the part and the detection means. It is good to be. Thereby, the influence of signal attenuation or the like due to the arrangement of the parts is taken into consideration, so that it is possible to more accurately diagnose whether there is an abnormality and to identify the abnormal part.

  According to the present invention, there are provided an abnormality diagnosis device and an abnormality diagnosis method capable of accurately diagnosing the presence / absence of an abnormality and specifying an abnormal part with respect to rotating parts and sliding parts incorporated in mechanical equipment. be able to.

Hereinafter, preferred embodiments of an abnormality diagnosis apparatus and an abnormality diagnosis method according to the present invention will be described with reference to the drawings.
FIG. 1 is a block diagram showing a schematic configuration of an abnormality diagnosis apparatus according to an embodiment of the present invention.

As shown in FIG. 1, the abnormality diagnosis device 1 according to the present embodiment diagnoses an abnormality in a rolling bearing 11 that is a rotating part incorporated in a mechanical equipment 10 such as a speed reducer, an electric motor, a windmill, or a railway vehicle. An acceleration sensor (detection means) 12 that detects vibration (signal) generated from the rolling bearing 11 and a signal detected by the acceleration sensor 12 are received via a data transmission means (transmission means) 13 to perform signal processing. A controller 20 comprising a signal processor 21 and a control device 22 for driving and controlling the mechanical equipment 10 and an output device comprising a monitor, an alarm device, etc. 30.
The controller 20 is composed of a microcomputer (IC chip, CPU, MPU, DSP, etc.). For this reason, each process to be described later can be executed by the program of the microcomputer, so that the apparatus can be simplified, downsized, and inexpensively configured.

  The rolling bearing 11 includes a plurality of inner rings 111 that are externally fitted to the rotating shaft 14 of the mechanical equipment 10, an outer ring 112 that is internally fitted to a housing or the like, and a plurality of rolling rings arranged between the inner ring 111 and the outer ring 112. The rolling element 113 and a retainer (not shown) that holds the rolling element 113 so as to freely roll are provided.

Here, FIG. 2 is a cross-sectional view showing a main configuration of a railway vehicle bearing device 40 which is an example of the mechanical equipment according to the present embodiment, and shows an example of application of the abnormality diagnosis device 1 described above. Show.
As shown in FIG. 2, the axle 44 is rotatably supported by a bearing box 45 constituting a part of a railway vehicle carriage via a double-row tapered roller bearing 41 as a rolling bearing 11, and The acceleration sensors 12 and 12 are fixed to the load side region of the bearing housing 45 where the radial load is applied. The acceleration sensors 12 and 12 detect vibration, and the detected signal is processed by the signal processor 21 described above, so that the abnormality of the double row tapered roller bearing 41 is diagnosed.

  In this way, the acceleration sensor 12 is fixed to the load side region of the radial load when the bearing raceway surface of the inner ring 411 or the outer ring 412 is damaged, and the collision that occurs when the rolling element 413 passes through the damaged portion. This is because the force is greater on the load side than on the no-load side, so that highly sensitive vibration detection is possible.

Methods for fixing the acceleration sensor 12 include bolt fixing, bonding, combined use of bolt fixing and bonding, and embedding with a resin material.
In addition, in the case of bolt fixation, you may make it provide a rotation stop function. Further, when the acceleration sensor 12 is embedded in the bearing box 45 with a resin material, the waterproofness and impact resistance are improved, which is preferable because the reliability of the acceleration sensor 12 itself is improved.

In the present embodiment, the acceleration sensor 12 is exemplified as a sensor for detecting vibration. However, other sensors capable of detecting vibration, for example, an AE (Acoustic Emission) sensor, an ultrasonic sensor, a shock pulse sensor, and the like can be used. In addition, by detecting acceleration, speed, strain, stress, displacement, etc., it is possible to appropriately use one that can detect vibration equivalently and convert it into an electrical signal.
In the following description, the physical quantity detected by the sensor is assumed to be vibration. However, the present invention is not limited to this, and other various sensors are used to detect physical quantities such as sound, ultrasound (AE), and distortion. Abnormality diagnosis can also be performed using these physical quantities.

  Further, when the sensor is attached to the mechanical equipment 10 that is expected to have a lot of ambient noise, it is preferable to use an insulating type because the influence of the ambient noise can be suppressed. Further, when a vibration detection element such as a piezoelectric element is used as the sensor, the element can be integrally molded with resin.

  Further, the acceleration sensor 12 that detects vibrations generated from the mechanical equipment 10 may be an integrated sensor in which a temperature sensor or a rotation speed sensor that detects the temperature of the mechanical equipment 10 is housed in a single casing. In this case, the integrated sensor is preferably fixed to a flat portion of the bearing housing 45, for example. The temperature sensor may be a temperature fuse of a type in which, when the temperature reaches a certain specified value, the bimetal contact is separated or the contact is blown to cause no conduction. As a result, if a temperature above a certain specified value is detected, the thermal fuse will not be conducted. Therefore, the abnormality can be detected by the temperature sensor and the abnormality diagnosis can be performed by two systems. It can be performed.

FIG. 3 is a block diagram showing a main functional configuration of the signal processor 21 according to the present embodiment.
As shown in FIG. 3, the signal processor 21 includes a data collection / distribution unit 211, a rotation analysis unit 212, a filter processing unit 213, a vibration analysis unit 214, a comparison determination unit 215, and an internal memory 216. .
The signal processor 21 is composed of a microcomputer as described above, that is, each processing unit such as the data collection / distribution unit 211 is executed by executing a program recorded and held in the microcomputer. Performs the following processes.

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

The rotation analysis unit 212 calculates the rotation speed of the inner ring 111 based on a signal output from a rotation speed detection unit (not shown), and outputs the calculated rotation speed to the comparison determination unit 215.
When the rotational speed detecting means 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 a pulse corresponding to the shape and rotational speed of the encoder. Signal. 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 band-pass filter function, extracts only the frequency band corresponding to the natural frequency of the rolling bearing 11, gears, wheels, etc. from the output signal of the acceleration sensor 12, and other unnecessary processing. Remove frequency band. This natural frequency can be easily obtained by exciting the object to be measured by an impact method using an impal 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 box, 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 signal generated from the rolling bearing 11 based on the output signal (measured data) from the acceleration sensor 12. The vibration analysis unit 214 is an FFT calculation unit that calculates the frequency spectrum of the vibration signal, and calculates the frequency spectrum of the vibration signal based on the FFT algorithm and envelope analysis. The calculated frequency spectrum is output to the comparison determination unit 215 as spectrum data.
Note that 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. Further, the envelope data after the envelope processing is also output to the comparison determination unit 215 as necessary.

The comparison determination unit 215 calculates the abnormal frequency for each part of the rolling bearing 11 in advance using the predetermined relational expression shown in FIG. 4, extracts the level of the spectrum data corresponding to the calculated abnormal frequency, and sets the threshold. Compare with value.
In addition, the comparison determination unit 215 in the present embodiment calculates a reference value from the spectrum data, and calculates a threshold value based on this reference value. Here, as the reference value, in order to reduce the influence of noise such as spectrum data in a predetermined frequency range, for example, DC component, a plurality of spectrum levels, for example, the upper 10 and the lower 10 are obtained from the obtained frequency range. It can be an effective value calculated using the excluded one.
In addition, the abnormal frequency may be calculated by using past data stored in the internal memory 216 if a similar diagnosis has been performed previously.

Here, the threshold value used for comparison with the level of the extracted spectrum data is the fundamental frequency of the abnormal frequency and each frequency of the harmonic, and further, for each part of the rolling bearing 11 to be diagnosed (that is, the inner ring). 111, outer ring 112, rolling element 113, and cage). For example, the threshold Cx ₁ for the fundamental wave is Cx ₁ = effective value + δ, the threshold Cx ₂ for the second harmonic is Cx ₂ = Cx ₁ × α, and the threshold Cx _n for the nth harmonic. Can be calculated by Cx _n = Cx _n-1 × α. Furthermore, this threshold Cx _1, set separately for each region of the rolling bearing 11 to be detected.
Here, α is an arbitrary real number, n is a natural number of 2 or more, and X is an identifier indicating a part of the rolling bearing 11, that is, the inner ring 111, the outer ring 112, the rolling element 113, and the cage.
Note that the threshold value Cx _i is preferably set to about the fourth harmonic (i = 4), for example, in consideration of practicality.

  Also, when setting the threshold value for each fundamental wave and harmonic, it is better to increase or decrease in conjunction with the rotation speed detected by the rotation speed detection means, so that it is possible to cope with changes due to the actual rotation speed, etc. Thus, it is possible to improve the diagnosis of the presence / absence of abnormality and the identification accuracy of the abnormal part.

Further, when setting the threshold value for each part of the rolling bearing 11, the transmission distance of the vibration signal between the part, that is, the inner ring 111, the outer ring 112, the rolling element 113, the cage, and the acceleration sensor 12 or It is preferable that the setting is made individually based on the transmission path, so that the attenuation of the signal due to the arrangement of these parts is taken into consideration, and the presence / absence of abnormality and the identification of the abnormal part can be performed with higher accuracy. .
Note that the threshold value set for each part is not limited to the transmission distance or transmission path of vibration, but for each part according to the level difference of vibration response measured in advance by an impact test using an impulse hammer or the like for each part. Is a constant relationship {eg, Ci = Co × p = Cb × q, where Ci is the inner ring threshold, Co is the outer ring threshold, Cb is the rolling element threshold, and p and q are It is a constant. } May be set.

  The diagnosis result of the rolling bearing 11 determined in this way is stored in the internal memory 216 and is output to the control device 22 that controls the operation of the mechanical equipment 10 to feed back a control signal corresponding to the diagnosis result. Further, the data is transmitted to the output device 30 by the data transmission means 31 using wireless considering the wired or network.

  The internal memory 216 is constituted by, for example, a memory or an HDD, and the design specification data of each rotating part used for calculation of the abnormal frequency, diagnosis of presence / absence of the abnormality of the rolling bearing 11 determined by the comparison determination unit 215, and abnormality detection Each piece of data relating to site identification 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 prompt the user to be informed of the abnormality.

Next, the operation of the abnormality diagnosis apparatus 1 configured as described above will be described.
FIG. 5 is a flowchart for explaining an operation procedure of the abnormality diagnosis apparatus 1.

  First, in step S101, the vibration generated from the rolling bearing 11 is detected by the acceleration sensor 12, and the detected vibration signal is input to the data collection / distribution unit 211 of the signal processor 12 via the data transmission means 13. The

  The data collection / distribution unit 211 amplifies the input analog vibration signal as necessary, and converts it into a digital signal by an A / D converter (ie, step S102).

  Next, the filter processing unit 213 selects a filter band (ie, step S103), and performs a filter process for extracting only a predetermined frequency band corresponding to the natural frequency of the rotating component (ie, step S104). .

  In step S105, the vibration analysis unit 214 performs envelope processing on the digital signal after the filter processing is performed, and performs frequency analysis such as obtaining a frequency spectrum of the digital signal after the envelope processing by the FFT algorithm. Then, the frequency component of the actually measured data is obtained (step S106). If necessary, absolute value processing is performed after envelope processing.

  On the other hand, using the predetermined relational expression shown in FIG. 4, the abnormal frequency generated due to the abnormality of each rotating component is calculated based on the detected rotational speed (ie, step S107), and the obtained abnormal frequency is calculated. The level of the frequency component of each corresponding rotating component is extracted from the fundamental wave to the nth harmonic (ie, step S108). That is, the abnormal frequency components of the rolling bearing 11 include the bearing flaw component Sx, that is, the inner ring flaw component Si, the outer ring flaw component So, the rolling element flaw component Sb, and the cage component Sc. It will be extracted from the wave over the nth harmonic.

On the other hand, step S107, S108 in parallel with, obtains a reference value Cx ₁ for use in the diagnosis of abnormality from the frequency spectrum obtained by the vibration analysis unit 214, the threshold Cx _{i (i} = 2 based on the reference value, ... N) is calculated (step S109). At this time, as described above, this threshold value is individually set for each frequency of the fundamental wave and the nth harmonic and for each part of the rolling bearing 11.

  In step S110, the level of the frequency spectrum of each rotating component extracted in step S108 is compared with the threshold value Cxi (i = 1, 2,... N) calculated in step S109, and whether or not there is a large one. Determine.

  As a result of this determination, if all the extracted frequency spectrum levels of the rotating parts are smaller than the threshold value, it is determined that there is no abnormality in each part of the rolling bearing 11 (step S111).

  On the other hand, in the procedure of step S110, if the frequency spectrum level of at least one of the inner ring 111, the outer ring 112, the rolling element 113, and the cage of the rolling bearing 11 is greater than a threshold value, it is determined that there is an abnormality in the corresponding part. (Step S112).

  Through such a procedure, it is possible to diagnose whether there is an abnormality in the rolling bearing 11 that is a rotating part and to identify an abnormal part.

  The result of the diagnosis performed in this way is output to the control device 22 that controls the operation of the machine facility 10 and a control signal corresponding to the diagnosis result is fed back. Further, the data is transmitted to the output device 30 by the data transmission means 31 using the wireless considering the wired or network. (Step S113).

Next, in order to confirm the accuracy of the diagnosis result when the abnormality diagnosis apparatus 1 according to the embodiment of the present invention was used, the following two tests were performed.
(Example 1)
First, with respect to the abnormality diagnosis apparatus 1 according to the embodiment of the present invention, a first test was performed in order to confirm the effect of individually setting a threshold value for each frequency of a fundamental wave and a harmonic wave of an abnormal frequency. . In this test, in order to evaluate this effect more objectively, a threshold value was not set for each part, and the threshold value was made constant between parts.
In this test, when the outer ring (O) of the tapered roller bearing has an artificial defect on the raceway surface and peripheral noise enters during rotation at a rotational speed of 200 min ⁻¹ in the inner ring of the tapered roller bearing, Frequency analysis was performed by applying envelope treatment to vibration. The test results at this time are shown in FIG.

Here, the solid line is a frequency spectrum subjected to envelope processing based on actually measured vibration data, the dotted line is the threshold value Co _i , and the one-dot chain line is the fourth wave from the fundamental wave caused by the outer ring damage based on the rotational speed 200 min ⁻¹ . It is the abnormal vibration generation frequency (f _{1 to} f ₄ ) up to the harmonic. Here, the threshold value Co ₁ for the fundamental wave is as follows: Co ₁ = reference value = effective value + 6 dB, threshold value for the second harmonic Co ₂ = Cx ₁ × 0.7, threshold value Co for the nth harmonic. _n = Con _n-1 × 0.7.
In consideration of practicality, the threshold value Co _i is set up to the fourth harmonic. The subscript “o” of C means an outer ring.

As a result, since the peak exceeding the threshold value C o _i coincides with the frequency component resulting from the outer ring damage, it can be diagnosed that the outer ring of the tapered roller bearing is damaged.

  On the other hand, FIG. 6B shows a case where a conventional abnormality diagnosis method is used in which the threshold value is not set for each frequency of the fundamental wave and the harmonic wave but is set to be constant. In this case, for harmonics other than the fundamental wave, the frequency component resulting from damage to the outer ring does not exceed the threshold value. It can be said that it is not a diagnosis.

  Therefore, by this test, the threshold value is individually set for each of the fundamental frequency and the harmonic frequency of the abnormal frequency, thereby making it less susceptible to the influence of ambient noise, diagnosing whether there is an abnormality, It can be seen that the specific accuracy can be improved.

(Example 2)
Next, with respect to the abnormality diagnosis apparatus 1 according to the embodiment of the present invention, a second test was performed in order to confirm the effect of setting a threshold value for each part. In this test, in order to evaluate this effect more objectively, no threshold is set for each of the fundamental and harmonic frequencies of the abnormal frequency, and the threshold between the fundamental and harmonics is not set. The value was kept constant.
FIG. 7 shows the frequency analysis by applying envelope processing to the vibration of the housing when the inner ring of the ball bearing with an artificial defect on the raceway surface of the outer ring of the rolling bearing is rotated at a rotational speed of 1500 min ^−1. FIG.

As shown in FIG. 7, the solid line is a frequency spectrum subjected to envelope processing based on actually measured data, the dotted line is a threshold value (= effective value + 6 dB), and the alternate long and short dash line is caused by outer ring damage based on a rotational speed of 1500 min ^−1. Frequency components f _{1 to} f ₃ to be performed are shown.

  As a result, since the peak exceeding the threshold value coincides with the frequency component resulting from the damage of the outer ring, it can be diagnosed that the outer ring of the ball bearing is damaged.

On the other hand, FIG. 8 shows an envelope process for the vibration of the bearing box when the inner ring of a rolling bearing having an artificial defect on the surface of the rolling element (ball) is rotated at a rotational speed of 1500 min ^−1. It is a figure which shows the data which analyzed.

  As shown in FIG. 8, the solid line is a frequency spectrum that has been subjected to envelope processing based on the actually measured vibration data. Since the frequency component to be processed does not exceed the threshold value, there is a possibility that it is determined that there is no abnormality. However, if it is determined using a threshold value (= effective value + 4 dB) set for each part in order to determine damage of the ball, it can be determined that the ball is damaged.

  From this result, it can be seen that since the threshold value is individually set for each part of the rolling bearing, the presence / absence of abnormality and the identification of the part of abnormality can be accurately performed.

  As described above, according to the abnormality diagnosis apparatus and the abnormality diagnosis method according to the embodiment of the present invention, vibration generated during operation from the rolling bearing 11 of the mechanical equipment 10 is detected and converted into an electric signal. The frequency spectrum corresponding to the calculated abnormal frequency is calculated by calculating the level of the frequency spectrum by performing envelope analysis and frequency analysis, and calculating the frequency of vibration caused by the abnormal part of the rolling bearing 11 based on a predetermined relational expression. Are extracted and compared with a predetermined threshold value. Thereby, the presence or absence of abnormality can be diagnosed without disassembling the mechanical equipment 10, and it becomes possible to reduce the effort concerning disassembly and assembly of the mechanical equipment 10.

  In addition, the threshold value used for comparison and verification is set individually for each fundamental frequency and harmonic frequency of the abnormal frequency to diagnose the presence or absence of an abnormality and identify the part of the abnormality, making it less susceptible to ambient noise. Thus, it is possible to improve the accuracy of diagnosis of the presence / absence of an abnormality and identification of an abnormal part.

  Furthermore, since the threshold value used for comparison and collation is individually set for each part of the rolling bearing 11 to diagnose the presence / absence of abnormality and to identify the abnormal part, diagnosis of presence / absence of abnormality and identification of the abnormal part are performed. It can be performed with high accuracy.

  Moreover, it is good to set the threshold value of the predetermined part of the rolling bearing 11 on the basis of the threshold value of another part. Thereby, diagnosis of the presence or absence of abnormality and specification of the site | part of abnormality can be performed more accurately.

  Moreover, according to this embodiment, since the data transmission means 13 which transmits a diagnosis and a specific result is provided, the result can be transmitted to the signal processor 21, and data processing can be performed. Alternatively, it is possible to diagnose the presence / absence of abnormality of the plurality of rolling bearings 11 of the mechanical equipment 10 and the identification of the abnormal part with high accuracy and at the same time in the actual operation state.

  The abnormality diagnosis apparatus of the present invention is not limited to the above-described embodiment, and appropriate modifications and improvements can be made. For example, in the above-described embodiment, the example in which the abnormality diagnosis device 1 is applied to the rolling bearing 11 for a railway vehicle, which is one of the mechanical facilities 10, has been described. Needless to say, the present invention can be similarly applied to a bearing device.

  In the above-described embodiment, the rolling bearing 11 is exemplified as the rotating or sliding component. However, the abnormality diagnosis device and abnormality diagnosis method of the present invention generate periodic vibration due to damage, for example, a gear, an axle. The present invention can be similarly applied to rotating parts such as ball screws and sliding parts such as linear guides and linear ball bearings.

  Also, as shown in FIG. 9, by using a microcomputer or the like for the controller 20, a signal processor 21 can be built in the mechanical equipment 10, and the unit can be made compact and downsized. The controller 20 may be incorporated in the bearing device, for example, or may be installed in the machine facility 10. In addition, a plurality of sensors 12 and the like can be provided in the mechanical facility 10.

  Furthermore, in the above-described embodiment, the threshold value is described as (effective value + α) dB. However, the threshold value is not limited to this, and can be calculated based on an equation such as effective value + β dB. Here, α and β are arbitrary real numbers. Further, instead of the effective value, an average value or a peak value of actually measured spectrum data at an arbitrary time may be used.

It is a block diagram which shows schematic structure of the abnormality diagnosis apparatus which concerns on embodiment of this invention. It is sectional drawing which shows the principal part structure of the bearing apparatus for rail vehicles which concerns on embodiment of this invention. It is a block diagram which shows the function structure of the signal processor which concerns on 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 embodiment of this invention, and the vibration frequency which arises resulting from a damage | wound. It is a flowchart for demonstrating the operation | movement procedure of the abnormality diagnosis apparatus which concerns on embodiment of this invention. (A) The graph which shows Example 1 to which the abnormality diagnosis apparatus and abnormality diagnosis method concerning this invention are applied, (B) is a graph which shows the conventional abnormality diagnosis method. It is a figure which shows the data of Example 2 which applied the abnormality diagnosis apparatus and abnormality diagnosis method which concern on embodiment of this invention. It is a figure which shows another data of Example 2 which applied the abnormality diagnostic apparatus and abnormality diagnostic method which concern on embodiment of this invention. It is a block diagram which shows schematic structure of the modification of the abnormality diagnosis apparatus which concerns on this invention.

Explanation of symbols

1 Abnormality diagnosis device 10 Mechanical equipment 11 Rolling bearing (rotating part)
12 Acceleration sensor (detection means)
DESCRIPTION OF SYMBOLS 20 Controller 21 Signal processor 212 Rotation analysis part 213 Filter processing part 214 Vibration analysis part 215 Comparison determination part 22 Control apparatus 31 Data transmission means (transmission means)

Claims (14)

The signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detection means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the measured data, and the rotation part or sliding part An abnormal frequency of vibration caused by an abnormality is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and comparison and verification between the extracted frequency component and a threshold value are performed. An abnormality diagnosis device that performs diagnosis of presence / absence of an abnormality and identification of a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis apparatus, wherein the threshold value is set individually for each frequency of a fundamental wave and a harmonic wave of the abnormal frequency. The abnormality diagnosis apparatus according to claim 1, wherein the threshold value is set based on a rotation speed of the rotating part or a moving speed of the sliding part. The signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detection means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the measured data, and the rotation part or sliding part An abnormal frequency of vibration caused by an abnormality is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and comparison and verification between the extracted frequency component and a threshold value are performed. An abnormality diagnosis device that performs diagnosis of presence / absence of abnormality and identification of a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis apparatus, wherein the threshold value is set individually for each part. The abnormality diagnosis apparatus according to claim 3, wherein the threshold is individually set based on a transmission distance or a transmission path of the signal between the part and the detection unit. The threshold value is set such that a threshold value of a predetermined part of the rotating part or the sliding part is set based on a threshold value of another predetermined part. 5. The abnormality diagnosis device according to any one of 4 above. 6. The abnormality diagnosis apparatus according to claim 1, further comprising a transmission unit for transmitting the diagnosis and the specific result. The abnormality diagnosis apparatus according to claim 1, wherein at least one of the envelope analysis, the frequency analysis, and the comparison and collation is executed by a program of a microcomputer. .   A bearing device for a railway vehicle to which the abnormality diagnosis device according to any one of claims 1 to 7 is applied.   A bearing device for a wind turbine to which the abnormality diagnosis device according to any one of claims 1 to 7 is applied.   A bearing device for a machine tool main spindle to which the abnormality diagnosis device according to any one of claims 1 to 7 is applied. The signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detection means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the measured data, and the rotation part or sliding part An abnormal frequency of vibration caused by an abnormality is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and comparison and verification between the extracted frequency component and a threshold value are performed. An abnormality diagnosis method for performing diagnosis of presence / absence of abnormality and identification of a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis method, wherein the threshold value is individually set for each frequency of a fundamental wave and a harmonic wave of the abnormal frequency. The abnormality diagnosis method according to claim 11, wherein the threshold is set based on a rotational speed of the rotating part or a moving speed of the sliding part. The signal generated from the rotating part or sliding part of the mechanical equipment is detected by the detection means, and the detection result is subjected to envelope analysis and frequency analysis to obtain the frequency component of the measured data, and the rotation part or sliding part An abnormal frequency of vibration caused by an abnormality is calculated based on a predetermined relational expression, a frequency component of the actual measurement data corresponding to the abnormal frequency is extracted, and comparison and verification between the extracted frequency component and a threshold value are performed. An abnormality diagnosis method for performing diagnosis of presence / absence of abnormality and identification of a part of the rotating part or the sliding part corresponding to the abnormality,
The abnormality diagnosis method, wherein the threshold is individually set for each part. The abnormality diagnosis method according to claim 13, wherein the threshold is individually set based on a transmission distance or a transmission path of the signal between the part and the detection unit.

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