JP5218614B2 - Abnormality diagnosis device, rotating device, railway vehicle, automobile and abnormality diagnosis method - Google Patents

Description

  The present invention relates to an abnormality diagnosing device and an abnormality diagnosing method for diagnosing the presence or absence of abnormality in a rotating device used in a railway vehicle, an automobile, a machine facility, or the like.

  Conventionally, in a rotating device such as a rolling bearing used in a rotating part of a railway vehicle or an automobile, for example, the presence or absence of an abnormality is diagnosed using an abnormality diagnosis device having a configuration shown in FIG. reference). This rotating device includes a tapered roller bearing 33 disposed between a rotating shaft 31 such as an axle and a housing 32.

  A sensor module 34 is fixed to the outer surface of the housing 32 through a mounting hole communicating with the inside. The sensor module 34 includes a rotation speed sensor that detects the rotation speed of the rotating shaft 31, a vibration sensor that detects vibration and temperature of the tapered roller bearing 33, and a temperature sensor.

  The sensor module 34 faces the gear 35 attached to the rotating shaft 31, and the rotating speed sensor outputs a pulse signal having a frequency proportional to the rotating speed of the rotating shaft 31, and measures the period of the pulse signal. Thus, the rotational speed of the rotating shaft 31 is detected. Each sensor monitors the operating state of the plurality of tapered roller bearings 33 for each detected speed, temperature, and vibration.

  On the other hand, it is known to diagnose the presence / absence of an abnormality such as a scratch or peeling of the bearing based on the vibration signal obtained from the vibration sensor and the rotation speed obtained from the rotation speed sensor (for example, Patent Document 2). reference). In the abnormality diagnosis device described in Patent Document 2, an abnormality is detected earlier than that described in Patent Document 1 because an abnormality is determined by analyzing a specific frequency component of vibration such as a scratch or peeling of the bearing. It is possible.

Special table 2001-500707 gazette JP 2002-295464 A

  However, when the rotating device is used in a poor environment, noise is superimposed on the output signal of the rotation speed sensor. For this reason, the rotational speed cannot be detected accurately, and there is a problem that the accuracy of abnormality diagnosis is low.

  The present invention has been made in view of the above circumstances, and its purpose is to accurately detect the rotational speed by eliminating the influence of noise even when the noise is superimposed on the output signal of the rotational speed sensor. It is possible to provide an abnormality diagnosing device and an abnormality diagnosing method capable of diagnosing a rotating device abnormality with high accuracy.

  In order to achieve the above-described object, an abnormality diagnosis apparatus and abnormality diagnosis method according to the present invention have the following configuration.

(1) An abnormality diagnosing device for diagnosing an abnormality of the rotating device based on the detected vibration and rotational speed
The rotation signal from the rotation speed sensor is A / D converted, and the rotation is obtained by obtaining the period of the rotation signal from the frequency component indicating the maximum peak intensity of the frequency spectrum obtained by frequency analysis by Fourier transform for the converted digital signal. An abnormality diagnosis apparatus comprising a rotation analysis unit that calculates a speed.

( 2 ) An abnormality diagnosis method for diagnosing an abnormality of the rotating device based on the detected vibration and rotational speed,
A / D conversion of the rotation signal from the rotation speed sensor;
Performing a frequency analysis by Fourier transform on the converted digital signal, calculating the rotation speed by obtaining a period of the rotation signal from a frequency component indicating a maximum peak intensity of the frequency spectrum obtained by the Fourier transform ;
An abnormality diagnosis method characterized by comprising:

( 3 ) The abnormality diagnosis method according to ( 2 ), wherein the rotating device is a rotating device for a railway vehicle or an automobile.

( 4 ) A rotating device comprising the abnormality diagnosis device according to (1 ) .
(5) A railway vehicle comprising the rotating device according to (4).
(6) An automobile comprising the rotating device according to (4).

  According to the present invention, even when noise is superimposed on the output signal of the rotational speed sensor, it is possible to accurately detect the rotational speed by eliminating the influence of the noise, and to accurately detect the abnormality of the rotating device. An abnormality diagnosis device and an abnormality diagnosis method that can be diagnosed can be provided.

It is a block diagram which shows schematic structure of the abnormality diagnosis apparatus which concerns on 1st and 2nd embodiment of this invention. It is a block diagram which shows the structure of the rotation analysis part of the abnormality diagnosis apparatus which concerns on 1st Embodiment of this invention. (A) is a figure which shows the waveform of the rotation signal of the rotation speed sensor in the abnormality diagnosis apparatus of 1st Embodiment, (b) is a figure which shows the waveform after shaping the rotation signal of a rotation speed sensor. . (A) is a figure which shows the waveform of the rotation signal which noise superimposed on the rotation speed sensor in the abnormality diagnosis apparatus of 1st Embodiment, (b) shaped the rotation signal which superimposed the noise of the rotation speed sensor. It is a figure which shows a later waveform. It is a time chart for demonstrating the process sequence of the rotation analysis part of the abnormality diagnosis apparatus which concerns on 1st Embodiment of this invention. 6 is a time chart illustrating the processing procedure of the rotation analysis unit in FIG. 5 in a more general manner. It is a block diagram which shows the structure of the rotation analysis part of the abnormality diagnosis apparatus which concerns on 2nd Embodiment of this invention. It is a time chart for demonstrating the process sequence of the rotation analysis part of the abnormality diagnosis apparatus which concerns on 2nd Embodiment of this invention. It is a figure which shows the frequency spectrum of the rotation pulse signal of the rotation speed sensor in the abnormality diagnosis apparatus of 2nd Embodiment. It is a figure which shows the rotation signal which consists of a sine wave of the rotation speed sensor in the abnormality diagnosis apparatus of 2nd Embodiment. It is a figure which shows the structure of the conventional abnormality diagnostic apparatus.

  Hereinafter, an abnormality diagnosis apparatus and an abnormality diagnosis method according to each embodiment of the present invention will be described in detail with reference to the drawings.

(First embodiment)
First, the overall configuration of the abnormality diagnosis apparatus according to the first embodiment of the present invention will be described. FIG. 1 is a block diagram illustrating a schematic configuration of the abnormality diagnosis apparatus according to the first embodiment.

  As shown in FIG. 1, the abnormality diagnosis device according to the present embodiment includes a vibration sensor 11, a filter unit 12, a vibration analysis unit 13, an abnormality determination unit 14, a rotation speed sensor 15, and a rotation analysis unit 16.

  The vibration sensor 11 is composed of a vibration measuring element such as a piezoelectric element or an acceleration sensor. The vibration sensor 11 detects vibration generated by damage to the rotating device such as a scratch or peeling of a bearing, a gear loss, or flat wear of a wheel, and outputs a vibration signal. Output. The vibration sensor 11 may be an acceleration, speed, displacement type, or the like that can convert vibration into an electrical signal. When the vibration sensor 11 is attached to a mechanical device having a lot of noise, the use of an insulation type is more affected by noise. It is preferable because it does not receive. Further, the vibration sensor 11 may be configured to be housed in a single casing together with a rotation speed sensor 15 and a temperature sensor which will be described later.

  The filter unit 12 removes unnecessary high-frequency components such as noise included in the vibration signal output from the vibration sensor 11.

  The vibration analysis unit 13 performs frequency analysis of vibration generated in the rotating device based on the vibration signal output from the filter unit 12. Specifically, the vibration signal output from the filter unit 12 is converted into a digital signal by an A / D converter, and a frequency spectrum of vibration is calculated based on an FFT (Fast Fourier Transform) algorithm. The A / D conversion may be performed before the processing by the filter unit 12 is performed.

  The abnormality determination unit 14 compares the frequency spectrum of vibration by the vibration analysis unit 13 with a reference value calculated based on rotation speed information calculated by the rotation analysis unit 16 to be described later, and determines whether there is an abnormality in the rotating device. Determine. Specifically, a peak having a spectral intensity greater than a predetermined reference value is extracted from the frequency spectrum, and the frequency between the peaks and the frequency component resulting from damage to the member at the calculated rotational speed are compared and collated. Presence and absence and abnormal site are determined.

  For example, as shown in FIG. 11, the rotation speed sensor 15 is arranged in the vicinity of an encoder such as a gear or a multipolar magnet that is a detection target attached to the rotation shaft of the rotation device, and rotates the rotation shaft. A voltage signal generated therewith, for example, a rotation signal composed of a sine wave as shown in FIG.

  The rotation analysis unit 16 calculates the rotation speed of the rotation device from the rotation signal output from the rotation speed sensor 15. As shown in FIG. 2, the rotation analysis unit 16 includes a waveform shaping unit 161, a pulse period measurement unit 162, a pulse period determination unit 163, and a rotation speed calculation unit 164.

  The waveform shaping unit 161 shapes a rotation signal composed of a sine wave output from the rotation speed sensor 15 into a pulse signal using a comparator or the like. FIG. 3B shows the waveform of the pulse signal after the output of the rotational speed sensor 15 shown in FIG.

  The pulse period measurement unit 162 measures a pulse period that is arbitrary N pieces of period data for the pulse train of the rotation signal shaped by the waveform shaping unit 161. N is an arbitrary integer of 3 or more. FIG. 3B shows an example in which every other three pulse periods T1, T2, and T3 are measured. The pulse period can be easily measured by a timer / counter incorporated in the microcomputer.

  By the way, noise may be superimposed on the output signal of the rotation speed sensor 15 when the use environment of the rotating device is poor. FIG. 4A shows an example in which noise is superimposed on a part of a rotation signal composed of a sine wave output from the rotation speed sensor 15. As described above, when the waveform shaping unit 161 shapes the rotation signal on which the noise is superimposed, the noise is also shaped into a pulse together, and thus an incorrect pulse period is measured. FIG. 4B shows an example in which the extremely short pulse period T2 is included in the measured three pulse periods T1 to T3 due to the influence of noise.

  The pulse period determination unit 163 determines that an arbitrary M number of pulse periods (period data) out of N pulse periods measured by the pulse period measurement unit 162 is within a predetermined range as a correct pulse period. Then, a predetermined calculation is performed based on the M pulse periods to calculate a correct pulse period T.

  The rotation speed calculation unit 164 calculates the rotation speed from the pulse period T calculated by the pulse period determination unit 163 by calculation of a microcomputer. The rotational speed information calculated in this way is sent to the abnormality determination unit 14 in FIG. 1 and used for abnormality determination of the rotating device as described above.

  Next, the operation of the rotation analysis unit 16 configured as described above will be described based on the rotation signals shown in FIGS. FIG. 5 is a time chart for explaining the processing procedure of the rotation analysis unit 16.

  First, a rotation signal composed of, for example, a sine wave as shown in FIG. 3A output from the rotation speed sensor 15 along with the rotation of the rotation shaft in the rotation device is input (step S101), and the waveform shaping unit 161 is input. Is amplified and shaped to obtain a pulse train as shown in FIG. 3B (step S102). Note that steps S101 and S102 are performed by hardware processing by an electronic circuit.

  Next, the pulse period measurement unit 162 measures arbitrary pulse periods T1, T2, and T3 from the pulse train (step S103) and sorts them in ascending order (step S104). Here, the measured pulse periods T1, T2, and T3 are Ti, Tj, and Tk in ascending order of the pulse period.

  The pulse period determining unit 163 determines whether or not the difference between Tj and Ti with respect to Ti is a predetermined reference value, for example, 5% or less (step S105). In addition, this reference value is appropriately set according to a difference in rotating parts in a railway vehicle, an automobile, or the like to which the rotating device is applied, an operating environment and operating conditions of the rotation speed sensor 15, and is usually 1 to 10%. Set the range.

  When it is determined in the processing procedure of step S105 that the difference between Tj and Ti with respect to Ti is equal to or smaller than a predetermined reference value, the correct period T is calculated by taking the average value of the periods Ti and Tj (step S106). .

  In step S107, the rotation speed is calculated from the correct cycle T by a microcomputer, and the process is terminated. The rotational speed information calculated in this way is sent to the abnormality determination unit 14 of FIG. 1 and used as a determination condition for abnormality determination.

  On the other hand, if it is determined in the processing procedure of step S105 that the difference between Tj and Ti with respect to Ti exceeds a predetermined reference value, the process proceeds to the procedure of step S108, and the pulse period determination unit 163 determines the difference between Tk and Tj with respect to Tj. It is determined whether or not the difference is equal to or less than a predetermined reference value.

  If it is determined in the processing procedure of step S108 that the difference between Tk and Tj with respect to Tj is equal to or smaller than a predetermined reference value, the correct period T is calculated by taking the average value of the periods Tj and Tk (step S109). In step S107, the rotation speed is calculated.

  On the other hand, if it is determined in the processing procedure of step S108 that the difference between Tk and Tj with respect to Tj exceeds a predetermined reference value, it means that the pulse period within the predetermined variation range has not been measured. Returning to the procedure of S103, N new pulse periods are measured for the pulse train output from the waveform shaping unit 161.

  For this reason, when measuring three pulse periods as shown in FIG. 3, the normal period T is obtained from the average value of the two pulse periods T1 and T2, and the correct rotational speed can be obtained. In the case of measuring three pulse periods as shown in FIG. 4, a normal period T is obtained from the average value of the two pulse periods T1 and T3, and a correct rotational speed can be obtained. Further, when noise is superimposed on two pulse periods of T1, T2, and T3, three pulse periods are measured again, so that a correct rotation speed can be obtained.

  As described above, according to the abnormality diagnosis apparatus of the first embodiment of the present invention, the waveform of the rotation signal detected by the rotation speed sensor 15 when diagnosing the abnormality of the rotation apparatus based on the vibration and the rotation speed. When N (3) pulse periods are measured from a pulse train that is shaped, and there are M (2) pulse periods whose difference between the two pulse periods is equal to or less than a predetermined reference value, the arithmetic average value thereof From this, the correct pulse period is obtained and the rotation speed is calculated.

  As a result, even when noise is superimposed on the rotation signal output from the rotation speed sensor 15, it is possible to accurately eliminate the influence and accurately detect the rotation speed, and to prevent abnormalities in the rotation device. Diagnosis can be made with high accuracy. Such an abnormality diagnosing device is difficult to apply in the case of a bearing device or the like in which the rotational speed changes abruptly, but it may change abruptly such as the rotational speed of the axle of a railway vehicle or the axle of an automobile. It is very effective for bearing devices for axles that do not.

  The N pulse periods may be measured every other period as shown in FIGS. 3 and 4, and a continuous period may be used depending on the measurement object or purpose of use of the rotational speed sensor. It is also possible to use discrete periods.

  In the above embodiment, the rotation speed is calculated with the average value of the two pulse periods as the correct period in steps S106 and S109, but either of the two pulse periods may be calculated as the correct period.

  In the present embodiment, the description has been made with three pulse periods in order to make the explanation easy to understand. However, the number of periods may be longer than that, and even when N periods are measured, rotation is performed from M average values. The speed may be calculated. That is, as shown in FIG. 6, after measuring N pulse periods Tl (l = 1,..., N) in step S103, whether the M pulse periods Tl are within a predetermined range. (Step S110), and if the M pulse periods are within a predetermined range, the correct period T is calculated (Step S111), and the rotation speed is calculated from the period T in Step S107. That's fine. Therefore, as a calculation method in step S111, an average value is obtained for the M pulse periods in which the difference between the two pulse periods is equal to or less than a predetermined reference value to obtain a correct pulse period. However, the present invention is not limited to this. The median value of the individual pulse period distributions or the one with the highest appearance frequency may be used, or may be calculated by another calculation method. Further, the determination method in step S110 is not limited to that in the above embodiment.

(Second Embodiment)
The overall configuration of the abnormality diagnosis apparatus according to the second embodiment of the present invention is the same as that of the abnormality diagnosis apparatus according to the first embodiment shown in FIG. 1, and only the internal configuration of the rotation analysis unit 16 is different. For this reason, about the equivalent part to 1st Embodiment, the same code | symbol is attached | subjected and description is abbreviate | omitted or simplified.

  The rotation analysis unit 26 of the present embodiment shown in FIG. 1 calculates the rotation speed of the rotation shaft from the rotation signal output from the rotation speed sensor 15, similarly to the rotation analysis unit 16 of the first embodiment. Hereinafter, the configuration and operation of the rotation analysis unit 26 will be described in detail with reference to the drawings. FIG. 7 is a block diagram illustrating a schematic configuration of the rotation analysis unit 26.

  As illustrated in FIG. 7, the rotation analysis unit 26 includes an A / D converter 262, a frequency analysis unit 263, and a rotation speed calculation unit 264.

  The A / D converter 262 performs A / D conversion on the analog rotation signal and converts it into a digital signal.

  The frequency analysis unit 263 calculates the frequency spectrum by calculating the digitized rotation signal based on the FFT algorithm, and obtains the fundamental frequency of the rotation signal from the frequency component indicating the maximum peak of the frequency spectrum intensity.

  The rotation speed calculation unit 264 calculates the rotation speed of the rotation device by calculation of a microcomputer based on the basic frequency of the pulse train obtained by the frequency analysis unit 263.

  Next, operation | movement of the rotation analysis part 26 of this embodiment comprised in this way is demonstrated using FIGS. 8-10. FIG. 8 is a time chart for explaining the processing procedure of the rotation analysis unit 26.

  First, a rotation signal that is an analog signal output from the rotation speed sensor 15 along with the rotation of the rotation shaft in the rotating device is input (step S201), and converted into a digital signal by the A / D converter 262 (step S202). .

  Next, the frequency analysis unit 263 performs frequency analysis based on the FFT algorithm (step S203), and calculates a frequency spectrum as shown in FIG. Several peaks appear in this frequency spectrum, and the fundamental frequency showing the maximum peak intensity among them corresponds to the frequency of the rotation pulse signal. Accordingly, this is extracted to calculate the correct period T of the rotation signal (step S204).

  In step S205, the rotational speed is calculated by the operation of the microcomputer from the calculated period. The rotation speed signal obtained in this way is sent to the abnormality determination unit 14 shown in FIG. 1 and used for abnormality determination of the rotating device.

  As described above, the rotation analysis unit 26 of the present embodiment performs A / D conversion on the rotation signal output from the rotation speed sensor 15 and performs FFT processing to calculate a frequency spectrum. Since the period of the rotation signal is calculated from the frequency component indicating the maximum peak intensity of the frequency spectrum, noise such as chattering superimposed on the rotation signal output from the rotation speed sensor 15 is increased to a high frequency range by performing FFT. The transition can be made, and there is no influence when calculating the period of the rotation signal.

  The rotation signal input to the A / D converter 262 is not necessarily a sine wave but may be a waveform having a frequency component proportional to the rotation speed, such as a rectangular wave. Direct A / D conversion of the sine wave eliminates the need for the waveform shaping unit 161 as compared with the first embodiment, so that the circuit configuration can be simplified.

  Further, the execution of the FFT algorithm in the rotation analysis unit 26 is performed by software processing by the CPU. Further, A / D conversion can be realized by using a vacant AD input port of the microcomputer.

  As described above, according to the abnormality diagnosis apparatus according to the second embodiment of the present invention, the rotation detected by the rotation speed sensor 15 when diagnosing the abnormality of the rotation apparatus based on the vibration and the rotation speed. The signal is A / D converted and FFT processed, the period of the rotation signal is obtained from the frequency indicating the maximum peak intensity of the calculated frequency spectrum, and the rotation speed is calculated. As a result, the influence of noise included in the rotation signal of the rotation speed sensor 15 can be eliminated, and the rotation speed of the rotation device can be accurately detected, and abnormality of the rotation device can be diagnosed with high accuracy.

  In addition, this invention is not limited to each embodiment mentioned above, A deformation | transformation, improvement, etc. are possible suitably.

DESCRIPTION OF SYMBOLS 11 Vibration sensor 12 Filter part 13 Vibration analysis part 14 Abnormality determination part 15 Rotation speed sensor 16, 26 Rotation analysis part 161 Waveform shaping part 162 Pulse period measurement part 163 Pulse period determination part 164, 264 Rotation speed calculation part 262 A / D conversion 263 Frequency Analyzer

Claims (6)

An abnormality diagnosing device for diagnosing an abnormality of the rotating device based on the detected vibration and rotational speed,
The rotation signal from the rotation speed sensor is A / D converted, and the rotation is obtained by obtaining the period of the rotation signal from the frequency component indicating the maximum peak intensity of the frequency spectrum obtained by frequency analysis by Fourier transform for the converted digital signal. An abnormality diagnosis apparatus comprising a rotation analysis unit that calculates a speed. An abnormality diagnosis method for diagnosing an abnormality of the rotating device based on the detected vibration and rotation speed,
A / D conversion of the rotation signal from the rotation speed sensor;
Performing a frequency analysis by Fourier transform on the converted digital signal, calculating the rotation speed by obtaining a period of the rotation signal from a frequency component indicating a maximum peak intensity of the frequency spectrum obtained by the Fourier transform ;
An abnormality diagnosis method characterized by comprising: The abnormality diagnosis method according to claim 2 , wherein the rotating device is a rotating device for a railway vehicle or an automobile. A rotating device comprising the abnormality diagnosis device according to claim 1 .   A railway vehicle comprising the rotating device according to claim 4.   An automobile comprising the rotating device according to claim 4.

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