JP6714806B2 - Status monitoring device and status monitoring method - Google Patents

Description

The present invention relates to a state monitoring device and a state monitoring method for monitoring the state of a rotating component that rotates relative to a stationary member, and in particular, diagnosis of presence/absence of abnormality and disassembly of this abnormality without disassembling mechanical equipment. The present invention relates to a state monitoring device and a state monitoring method for identifying a corresponding part and determining the degree of damage or the progress of damage.

BACKGROUND ART Mechanical equipment such as railway vehicles, machine tools, wind turbine generators, and elevator devices are often equipped with rotating parts such as rolling bearings and sliding parts such as ball screws and linear guides. If wear and damage occur due to long-term use of these rotating and sliding parts, smooth rotation and sliding of these rotating and sliding parts are obstructed, abnormal noise is generated, and the life There is a risk that it will fall and become damaged, leading to failure of machinery and equipment and accidents. For this reason, conventionally, after the mechanical equipment has been used for a certain period, the presence or absence of abnormality such as wear or damage is inspected.

This inspection is performed by disassembling the parts where the rotating and sliding parts of the mechanical equipment are installed, or the entire mechanical equipment, and the damage and wear generated on the rotating and sliding parts are visually inspected by the operator. Discovered by inspection. The main defects (abnormalities) found in the inspection are, in the case of bearings, indentations caused by the entrapment of foreign matter, peeling due to rolling fatigue, other wear, etc. In the case of a wheel, such as wear, there is flat wear and the like, and in any case, if unevenness or wear that is not found in a new product is found, the wheel is replaced with a new one. That is, when abnormalities such as wear and damage are found as a result of the inspection, the parts are replaced with new ones to prevent mechanical equipment failures and accidents.

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

In addition, when reassembling, a dent that was not present before the inspection is attached to the rotating component or the sliding component, and the inspection itself has a possibility of causing defects in the rotating component or the sliding component. Further, since a large number of bearings are visually inspected within a limited time, there is a problem that defects may be overlooked. Further, there is individual difference in the determination of the degree of this defect, and even if there is substantially no defect, the parts are replaced, which results in wasteful cost.

In order to solve such a problem, conventionally, without disassembling a mechanical device in which a rolling bearing is incorporated, a condition monitoring device for monitoring the condition of rotating parts or sliding parts in an actual operating condition of mechanical equipment, or a condition Various monitoring methods have been proposed (see, for example, Patent Documents 1 and 2).

Japanese Patent No. 4117500 JP, 2013-185507, A

However, in the device described in Patent Document 1, although it is described that the degree of damage is diagnosed, only the bearing outer ring abnormality is targeted.
Further, the device described in Patent Document 2 is intended to detect the presence or absence of an abnormality in the bearing and the detection of that portion, and the degree of damage cannot be determined.
Further, in any of the state monitoring devices, it has been required to improve the processing efficiency by reducing the calculation amount.

The present invention has been made in view of the above circumstances, and an object thereof is to determine whether or not there is an abnormality in a rotating component incorporated in mechanical equipment, specify the abnormal portion, and the degree of damage or the progress of damage. It is an object of the present invention to provide a state monitoring device and a state monitoring method capable of making accurate and efficient determination.

The above-mentioned object of the present invention is achieved by the following configurations.
(1) A state monitoring device for monitoring the state of a rotating component that rotates relative to a stationary member,
A vibration sensor fixed to the rotating component or the stationary member,
A simple diagnosis unit that calculates at least one simple diagnosis value obtained from the waveform of the signal detected by the vibration sensor and compares it with a threshold value, and diagnoses whether there is an abnormality in the rotating component,
A filter processing unit that divides and extracts the waveform of the signal detected by the vibration sensor into a plurality of damage filter frequency bands,
An arithmetic processing unit that performs envelope processing and frequency analysis on the filtered waveform transferred from the filter processing unit to obtain spectrum data,
In the extracted damage filter frequency band, a bearing damage frequency caused by damage to the rotating component calculated based on a rotation speed signal of the rotating component, and a frequency component included in the spectrum data obtained by the arithmetic processing unit. And a precise diagnosis unit that identifies the abnormal part of the rotating component,
Based on the diagnostic value for each frequency band calculated for each damage filter frequency band, a damage level diagnostic unit for diagnosing the degree of damage or the progress of damage of the site,
A condition monitoring device comprising:
(2) The diagnostic value for each frequency band is a vibration effective value,
The damage level diagnosis unit diagnoses the degree of damage or the progress of damage of the rotary component by comparing the vibration effective value calculated for each damage filter frequency band with a value of a normal product or a normal time. The state monitoring device according to (1), characterized in that.
(3) The diagnostic value for each frequency band is an envelope vibration effective value calculated from the spectrum data obtained by the arithmetic processing unit,
The damage level diagnosis unit diagnoses the degree of damage or the progress of damage of the rotary component by comparing the envelope vibration effective value calculated for each damage filter frequency band with a value of a normal product or a normal time. The condition monitoring device according to (1), characterized in that
(4) The diagnostic value for each frequency band is the presence/absence of a damage component or the number of peaks of the damage component in the spectrum data for each damage filter frequency band obtained by the arithmetic processing unit,
The damage level diagnosis unit diagnoses the degree of damage or the progress of damage of the rotary component based on the presence or absence of the damage component or the number of peaks of the damage component for each damage filter frequency band ( The condition monitoring device according to 1).
(5) The diagnostic value for each frequency band is a diagnostic value that digitizes the presence or absence of a damage component in the spectrum data for each damage filter frequency band obtained by the arithmetic processing unit,
The damage level diagnosis unit diagnoses the degree of damage or the progress of damage of the rotary component based on a diagnostic value that is a numerical value indicating the presence or absence of the damage component for each damage filter frequency band (1). ) State monitoring device described in.
(6) The condition monitoring device according to (1), wherein the simple diagnosis value is at least one of an effective value, an average value, a peak value, and a crest factor.
(7) The rotating component is a rolling bearing, the stationary member is a housing supporting the rolling bearing,
A rolling bearing device comprising the condition monitoring device according to any one of (1) to (6).
(8) A state monitoring method for monitoring the state of a rotating component that rotates relative to a stationary member,
A detection step of detecting a signal from a vibration sensor fixed to the rotating component or the stationary member,
A simple diagnosis step of diagnosing the presence or absence of abnormality of the rotating component by calculating at least one simple diagnosis value obtained from the waveform of the signal detected by the vibration sensor and comparing it with a threshold value,
A filtering step of dividing the waveform of the signal detected by the vibration sensor into a plurality of damage filter frequency bands and extracting the waveform.
An arithmetic processing step of obtaining spectral data by performing envelope processing and frequency analysis on the filtered waveform transferred from the filtering step,
In the extracted damage filter frequency band, a bearing damage frequency caused by damage to the rotating component calculated based on a rotation speed signal of the rotating component, and a frequency component included in the spectrum data obtained in the arithmetic processing step. And a precise diagnosis step of identifying the abnormal portion of the rotating component,
Based on the diagnostic value for each frequency band calculated for each damage filter frequency band, a damage level diagnosis step of diagnosing the degree of damage of the site or the progress of damage,
Equipped with
The condition monitoring method, wherein the precise diagnosis step and the damage level diagnosis step are performed when the rotary component is diagnosed as having an abnormality in the simple diagnosis step.
(9) The diagnostic value for each frequency band is a vibration effective value,
The damage level diagnosis step diagnoses the degree of damage or the progress of damage of the rotary component by comparing the vibration effective value calculated for each damage filter frequency band with a value of a normal product or a normal time. The state monitoring method according to (8), characterized in that
(10) The diagnostic value for each frequency band is an envelope vibration effective value calculated from the spectrum data obtained in the arithmetic processing step,
In the damage level diagnosis step, the envelope vibration effective value calculated for each damage filter frequency band is compared with a value of a normal product or a normal time to diagnose the degree of damage of the rotary component or the progress of the damage. The condition monitoring method according to (8), characterized by:
(11) The diagnostic value for each frequency band is the presence or absence of a damage component or the number of peaks of the damage component in the spectrum data for each damage filter frequency band obtained in the arithmetic processing step,
The damage level diagnosing step is characterized by diagnosing the degree of damage or the progress of damage of the rotary component based on the presence or absence of the damage component or the number of peaks of the damage component for each damage filter frequency band ( The condition monitoring method described in 8).
(12) The diagnostic value for each frequency band is a diagnostic value that digitizes the presence or absence of a damage component in the spectrum data for each damage filter frequency band obtained in the arithmetic processing step,
The damage level diagnosing step is characterized by diagnosing a degree of damage or a progress of damage of the rotary component based on a diagnostic value that is a numerical value indicating the presence or absence of the damage component for each damage filter frequency band (8). ) State monitoring method described in.
(13) The condition monitoring method according to (8), wherein the simple diagnostic value is at least one of an effective value, an average value, a peak value, and a crest factor.

According to the present invention, it is possible to accurately and efficiently determine the presence/absence of an abnormality, the location of an abnormality, and the degree of damage or the progress of damage of a rotating component incorporated in mechanical equipment.

It is a block diagram which shows schematic structure of the state monitoring apparatus which concerns on embodiment of this invention. It is a block diagram which shows the functional structure of the arithmetic processing unit which concerns on embodiment of this invention. It is a flow chart for explaining the operation procedure of the state monitoring device concerning an embodiment of the present invention. 5 is a table showing a relationship between a scratched portion of the rolling bearing according to the embodiment of the present invention and a vibration frequency generated due to the scratched portion. (A)-(c) is a graph which shows the envelope frequency spectrum based on the vibration data of the bearing in Example 1 which differs in the degree of damage. (A) And (b) is a graph which shows the envelope frequency spectrum based on the vibration data of the bearing from which the degree of damage differs in 5th Example.

Preferred embodiments of a status monitoring device and a status monitoring method according to the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a schematic configuration of a state monitoring device according to an embodiment of the present invention.

As shown in FIG. 1, the state monitoring device 1 of the present embodiment is for diagnosing an abnormality of a rolling bearing 11 which is a rotary component incorporated in a mechanical equipment 10, and a vibration (signal) generated from the rolling bearing 11 is detected. A vibration sensor 12 for detecting the rotation speed, a rotation sensor (not shown) for detecting the rotation speed of the rolling bearing 11, and a signal detected by the vibration sensor 12 or the rotation sensor are received via a data transmission means (transmission means) 13. Then, the arithmetic processing unit 21 (arithmetic processing unit) that performs signal processing to diagnose whether there is an abnormality in the rolling bearing 11, identifies the abnormal portion, and diagnoses the degree of damage or the progress of damage in real time, and a machine. A controller 20 including a control device 22 that drives and controls the equipment 10 and an output device 30 including a monitor, an alarm device, and the like are provided.
The control device 22 drives and controls the mechanical equipment 10 so as to feed back the diagnosis result obtained by the arithmetic processing unit 21 to the operating condition (such as lowering the rotation speed).
Note that examples of the mechanical equipment 10 to which the state monitoring device 1 of the present embodiment is applied include rail cars, machine tools, wind power generators, elevator devices, and the like.
The controller 20 is composed of a microcomputer (IC chip, CPU, MPU, DSP, etc.). Therefore, each processing described later can be executed by the program of this microcomputer, so that the apparatus can be simplified, downsized, and inexpensive.

The rolling bearing 11 includes an inner ring 111 externally fitted to a rotary shaft of the mechanical equipment 10, an outer ring 112 internally fitted to a housing or the like, and a plurality of rolling elements arranged so as to be rollable between the inner ring 111 and the outer ring 112. It has a moving body 113 and a retainer (not shown) that holds the rolling body 113 in a rollable manner.

The vibration sensor 12 is fixed to the housing load zone of the outer ring 112, which is the fixed ring of the rolling bearing 11. The method of fixing the vibration 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 fixing with bolts, a rotation stop function may be provided. Further, by molding the vibration sensor 12 with a resin material, it is possible to prevent the intrusion of water and further improve the vibration-proof property against external vibration, so that the reliability of the sensor itself is dramatically improved. be able to.

As the vibration sensor 12, in addition to the acceleration sensor applied in the present embodiment, for example, an AE (Acoustic Emission) sensor, an ultrasonic sensor, a shock pulse sensor, or the like can be used. It is also possible to appropriately use a device capable of equivalently detecting vibration and converting it into an electric signal by detecting stress, displacement, and the like.

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

FIG. 2 is a block diagram showing the main functional configuration of the arithmetic processor 21 according to the present embodiment.
As illustrated in FIG. 2, the arithmetic processing unit 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 arithmetic processing unit 21 is composed of a microcomputer as described above, that is, by executing a program recorded and held in the microcomputer, each processing unit such as the data collection/distribution unit 211 or the like. Will execute the following processes.

The data collection/distribution unit 211 converts the signal sent from the vibration sensor 12 into a digital signal by an A/D converter, and also collects and temporarily accumulates a signal related to the rotation speed, depending on the type of the signal. It is assigned to either the rotation analysis unit 212 or the filter processing unit 213.
The A/D converter may be integrated with the vibration sensor 12 so that the digital signal is received via the data transmission means 13 described above.

The rotation analysis unit 212 calculates the rotation speed of the inner ring 111 based on the signal output from the rotation sensor, and outputs the calculated rotation speed to the comparison determination unit 215.
When the rotation 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 of the encoder and the rotation speed. Become a signal. Therefore, the rotation analysis unit 212 has a predetermined conversion function or conversion table according 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 band pass filter, divides the output signal of the vibration sensor 12 into a plurality of damage filter frequency bands, and extracts them, and removes other unnecessary frequency bands. The damage filter frequency band is set according to the natural frequency band of each bearing device. This natural frequency can be easily obtained by exciting the DUT by a striking method using an impulse hammer or the like, and by performing a frequency analysis on the vibration detector attached to the DUT or the sound generated by the striking. it can.
When the object to be measured is the rolling bearing 11, the natural frequency due to any of the inner ring 111, the outer ring 112, the rolling elements 113, the housing, etc. is given. Generally, there are a plurality of natural frequencies of mechanical parts, and the amplitude level at the natural frequency is high, so that the measurement sensitivity is good.

The vibration analysis unit 214 analyzes the frequency of the vibration signal generated from the rolling bearing 11 based on the output signal (measured data) from the vibration 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.
The vibration analysis unit 214 may perform absolute value conversion processing or envelope processing as preprocessing for performing FFT, and may convert only frequency components necessary for abnormality diagnosis. Further, if necessary, the spectrum data after the envelope processing (envelope frequency spectrum) is also output to the comparison/determination unit 215.

The comparison determination unit 215 periodically monitors the state of the rolling bearing 11 based on the measured vibration and rotation speed of the rolling bearing 11. Specifically, the comparison/determination unit 215 constitutes a simple diagnosis unit, a precise diagnosis unit, and a damage level diagnosis unit described below.

The simple diagnosis unit calculates at least one simple diagnosis value of the effective value, the peak value, and the crest factor obtained from the waveform of the signal detected by the vibration sensor 12, and compares it with each threshold value. Then, when “effective value, peak value, crest factor>each threshold value”, the rolling bearing 11 is simply diagnosed as having an abnormality.

When the simple diagnosis unit diagnoses that there is an abnormality, the precise diagnosis unit uses a predetermined relational expression shown in FIG. 4 to calculate in advance a bearing damage frequency caused by damage to each part of the rolling bearing 11, With the spectrum data output by the vibration analysis unit 214 as a target, the presence or absence of an abnormality such as a bearing scratch and the portion thereof are identified by collating each bearing damage frequency (whether or not “peak frequency=bearing damage frequency”).
The bearing damage frequency may be calculated by using the past data stored in the internal memory 216 when the same diagnosis is performed before.

The damage level diagnosis unit determines the degree of damage to the site (degree of damage: early/progress phase/end phase) based on the diagnostic value for each frequency band calculated for each damage filter frequency band when or after the damaged site is identified. Or, diagnose the progress of damage. Note that the following four methods can be given as examples of methods for diagnosing the degree of damage.

(1) In the first method, the diagnosis value for each frequency band is set as the vibration effective value, and the damage level diagnosis unit compares the vibration effective value calculated for each damage filter frequency band with a normal product or a normal value. To do. Then, the value of the ratio of the effective vibration value to the normal value or the value at the normal time is determined for each damage filter frequency band, thereby diagnosing the degree of damage or the progress of damage of the rotating component.
(2) The diagnosis value for each frequency band is set as the envelope vibration effective value calculated from the spectrum data obtained by the vibration analysis unit 214, and the damage level diagnosis unit sets the envelope vibration effective value calculated for each damage filter frequency band as The degree of damage to the rotating parts or the progress of damage is diagnosed by comparing the values with normal or normal values.
(3) The diagnostic value for each frequency band is used as the presence or absence of a damage component or the number of peaks of the damage component in the spectrum data for each damage filter frequency band obtained by the vibration analysis unit 214, and the damage level diagnostic unit determines each damage filter frequency band. Based on the presence or absence of the damage component or the number of peaks of the damage component, the degree of damage of the rotating component or the progress of damage is diagnosed.
(4) The diagnostic value for each frequency band is used as a diagnostic value that digitizes the presence or absence of a damage component in the spectrum data for each damage filter frequency band obtained by the vibration analysis unit 214, and the damage level diagnostic unit determines for each damage filter frequency band. The degree of damage to the rotating parts or the progress of damage is diagnosed based on the diagnostic value that numerically indicates the presence or absence of the damage component.

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

The internal memory 216 is composed of, for example, a memory or a HDD, and is designed to determine whether there is an abnormality in the rolling bearing 11 determined by the comparison determination unit 215 and the design specification data of each rotating component used for calculating the abnormal frequency. Each data regarding the part 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. Further, 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.
Further, the signal data transmission means 13 may be wired as long as it can accurately transmit and receive signals, or may be wireless in consideration of a network.

Next, the operation of the state monitoring device 1 thus configured will be described. FIG. 3 is a flowchart for explaining the operation procedure of the state monitoring device 1.

First, in step S1, the vibration sensor 12 detects the vibration generated from the rolling bearing 11 and the rotation sensor detects the rotation speed of the rolling bearing 11, and the detected vibration signal and rotation speed signal are transmitted via the data transmission means 13. It is input to the data collection/distribution unit 211 of the arithmetic processing unit 21.

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.

Next, in step S2, diagnostic parameters used for subsequent diagnostics are calculated based on the data stored in the data collection/distribution unit 211 and the internal memory 216. Specifically, as a diagnostic parameter, the threshold value of at least one of the effective value (RMS), the peak value (PEAK), and the crest factor (CF) used for simple diagnosis, the bearing damage frequency, and the damage filter frequency band are calculated. To be done.

Next, in step S3, a simple diagnosis is performed in which the effective value (RMS), peak value (PEAK), and crest factor (CF) obtained from the waveform of the signal detected by the vibration sensor 12 are compared with the respective threshold values. When "effective value (RMS), peak value (PEAK), crest factor (CF)>each threshold value", it is determined that there is an abnormality in the rolling bearing 11, the process proceeds to step S4, and when each value is less than or equal to the threshold value, If there is no abnormality, the process returns to step S1 and step S1 is executed at the next timing.

In step S4, the arithmetic processing unit 21 divides and extracts the waveform of the signal detected by the vibration sensor 12 for each damage filter frequency band calculated in step S2.

Further, in step S5, the arithmetic processing unit 21 performs envelope processing and frequency analysis on the filtered waveform transferred from the filter processing unit to obtain spectrum data.

Then, in step S6, in the comparison determination unit 215, in the extracted damage filter frequency band, the bearing damage frequency resulting from the damage of the rolling bearing 11 calculated based on the rotation speed signal of the rolling bearing 11, and the calculation processing unit. The frequency component included in the spectrum data obtained in step S7 is compared, and in step S7, the abnormal portion of the rolling bearing 11 is specified.
That is, the bearing damage frequency component of the rolling bearing 11 includes the bearing damage component Sx, that is, the inner ring damage component Si, the outer ring damage component So, the rolling element damage component Sb, and the cage component Sc. It will be extracted. Then, it identifies whether the abnormal part is the inner ring, the outer ring, the rolling element, or the cage.

Next, in step S8, the degree of damage to the site or the progress of damage is diagnosed by any method using the above-described diagnostic value for each frequency band, which is calculated for each damage filter frequency band.

Through such a procedure, it is possible to diagnose whether or not there is an abnormality in the rolling bearing 11, which is a rotating component, specify the abnormal portion, and diagnose the extent of damage to the portion or the progress of damage.

The result of the diagnosis performed in this manner is output to the control device 22 that controls the operation of the mechanical equipment 10, and the control signal according to the diagnosis result is fed back. Further, the data is transmitted to the output device 30 by the data transmission means 31 using wire or wireless considering the network.

Next, the following five tests were performed in order to confirm the accuracy of the diagnostic result when the state monitoring device 1 of this embodiment was used.

(Example 1)
First, a cylindrical roller bearing with three kinds of flaw defects (defect size ratio: large: medium: small = 100:10:1) with different degrees of damage on the inner ring raceway surface is used, and the radial load is applied to the cylindrical roller bearing. The vibration of the housing is measured by rotating the inner ring at 1500 min ⁻¹ while applying 127 kN and an axial load of 50 kN. As a result, as shown in Table 1, in the simple diagnosis with the threshold value (=the ratio of the effective vibration value of the normal product to 2), since “actual measurement value>threshold value”, it is diagnosed that there is an abnormality.

Next, the vibration data was filtered in the frequency band (4000 to 10000 Hz), and FFT was performed after envelope processing. In FIG. 5, the solid line indicates the envelope frequency spectrum based on the actually measured vibration data, and the alternate long and short dash line indicates the frequency component caused by the inner ring damage based on the rotation speed of 1500 min ⁻¹ . As a result, since the peak coincides with the frequency component caused by the inner ring damage, it can be diagnosed by the precise diagnosis that the inner ring of the bearing is damaged.

Next, in the damage level diagnosis, the vibration effective values in the frequency bands f ₁ (0 to 1000 Hz), f ₂ (1000 to 4000 Hz), f ₃ (4000 to 10000 Hz) are calculated, and the vibration effective value ratio with the normal product is calculated. It shows in Table 2. From this result, it can be seen that the vibration effective value ratio only in the high frequency band is large when the degree of damage is small, and the vibration effective value ratio is large in the lower frequency band as the degree of damage is larger. That is, the degree of damage can be determined from the effective vibration value ratio in each frequency band.

Although the scratch defect is illustrated in Example 1, the same applies to peeling damage. Further, although the threshold value of the simple diagnosis is the effective value ratio of the normal product, the average value or the peak value of the measured spectrum data at any time may be used instead of the effective value.
In the detailed diagnosis, the threshold for each part may be set according to the vibration transmission distance difference or the path difference, or each part may be set in advance according to the vibration response level difference measured by the impact test such as impulse hammer. You may set it.
Further, it is preferable to select a band including the natural frequency of the bearing or the housing as the filter frequency band because a damage signal is excited.

(Example 2)
In the second embodiment, the test target, the basic configuration of the condition monitoring device 1, the simple diagnosis and the precise diagnosis are the same as those of the first embodiment, and the test is performed with different damage level diagnosis.

In the damage level diagnosis of the present embodiment, FFT is performed after envelope processing in each of frequency bands f ₁ (0 to 1000 Hz), f ₂ (1000 to 4000 Hz), and f ₃ (4000 to 10000 Hz), and an effective envelope frequency spectrum is obtained. The value was calculated. Table 3 shows the ratio between the effective value of the envelope frequency spectrum and the normal product.

From this result, it can be seen that when the degree of damage is small, the envelope vibration effective value ratio is large only in the high frequency band, and as the degree of damage is large, the envelope vibration effective value ratio is large even in the lower frequency band. That is, the degree of damage can be determined from the envelope vibration effective value ratio in each frequency band.
In this way, by using the envelope frequency spectrum, it is less likely to be affected by noise or the like other than defects, so that the accuracy of determining the degree of damage is improved.

(Example 3)
Also in Example 3, the test target, the basic configuration of the condition monitoring device 1, the simple diagnosis and the precise diagnosis were the same as those in Example 1, and the test was performed with different damage level diagnosis.

In the damage level diagnosis of the present embodiment, envelope processing is performed on waveforms of frequency bands f ₁ (0 to 1000 Hz), f ₂ (1000 to 4000 Hz), and f ₃ (4000 to 10000 Hz) extracted by filter processing during precise diagnosis. , And FFT are performed, and as shown in Table 4, the presence or absence of a damage component is displayed for each band. From this result, it can be seen that when the degree of damage is small, the damage component peak exists in the high frequency band, but as the degree of damage increases, the damage component peak also exists in the lower frequency band. That is, the degree of damage can be determined based on the presence or absence of the damage component peak in each frequency band.

Further, in the third embodiment, the damage level diagnosis is performed by using the frequency bands f ₁ (0 to 1000 Hz), f ₂ (1000 to 4000 Hz), and f ₃ (4000 to 10000 Hz) divided by the filter processing during the precise diagnosis. , Envelope processing and FFT are performed on the waveform of each frequency band. Therefore, by performing the damage level diagnosis of the third embodiment at the same time as the precise diagnosis, the calculation amount in the diagnosis can be reduced.
If the accuracy of the damage level diagnosis is improved by making each frequency band used in the damage level diagnosis different from the frequency band used in the precision diagnosis, use a different frequency band and perform the separate diagnosis separately. It

(Example 4)
Also in Example 4, the test target, the basic configuration of the state monitoring device 1, the simple diagnosis and the precise diagnosis were the same as those in Example 1, and the test was performed with different damage level diagnosis.

In the damage level diagnosis of the present embodiment, at the time of precise diagnosis, the frequency band f ₁ (0 to 1000 Hz), f ₂ (1000 to 4000 Hz), and f ₃ (4000 to 10000 Hz) are subjected to envelope processing of the waveform for each band and FFT. It is carried out and the presence or absence of a damage component is digitized from the envelope frequency spectrum. Table 5 shows the digitized diagnostic values. From this result, it is understood that the diagnostic value in the high frequency band is large when the degree of damage is small, and the loss diagnostic value is large in the low frequency band as the degree of damage is large. That is, the degree of damage can be determined from the diagnostic value in each frequency band.
Various known methods can be applied to the method of digitizing the diagnostic value.

(Example 5)
Example 5 shows a specific example of abnormality diagnosis of damage due to electrolytic corrosion. The basic configuration of the status monitoring device 1 is the same as that of the first embodiment.

In Example 5, two types of deep groove ball bearings with different degrees of corrosion on the outer ring raceway (small: effective vibration ratio to normal product=4.4 times/large: same=21 times) were used. While rotating the deep groove ball bearing at a radial load of 20 kN and an axial load of 3.5 kN at 1800 min ⁻¹ , the vibration of the housing was measured. As shown in Table 6, in the simple diagnosis using the threshold value (=the ratio of the effective vibration value of the normal product is 2), since “measured value>threshold value”, it can be diagnosed that there is an abnormality.

Next, the vibration data was filtered in the frequency band (0 to 20000 Hz), and FFT was performed after envelope processing. In FIG. 6, the solid line indicates the envelope frequency spectrum based on the actually measured vibration data, the dotted line indicates the threshold value (=effective value+6 dB), and the alternate long and short dash line indicates the frequency components (fo _{1 to} fo ₃ ) caused by the outer ring damage based on the rotation speed of 1800 min ^−1. Is shown. From this result, in the precise diagnosis, since the peak exceeding the threshold value coincides with the frequency component caused by the outer ring damage, it is diagnosed that the outer ring of the bearing is damaged.

Next, in the damage level diagnosis, the effective vibration values in the frequency bands f ₁ (500 to 2000 Hz), f ₂ (2000 to 6000 Hz) and f ₃ (6000 to 20000 Hz) were calculated, and as shown in Table 7, the vibration effective values were calculated. The ratio between the effective value and the normal product was calculated.

From this result, when the degree of damage is small, the vibration effective value ratio in the low frequency band (f _{1 to} f ₂ ) is large, and when the degree of damage is large, the vibration effective value up to the high frequency band (f _{1 to} f ₃ ) is obtained. You can see that the ratio is large. That is, the degree of damage can be determined from the effective vibration value ratio in each frequency band.

As described above, according to the state monitoring device 1 and the state monitoring method according to the embodiment of the present invention, the vibration sensor 12 fixed to the rolling bearing 11 or the housing, and the signal detected by the vibration sensor 12. Of at least one simple diagnostic value obtained from the waveform of the rolling bearing 11 and comparing it with a threshold to diagnose whether there is an abnormality in the rolling bearing 11, and a waveform of a signal detected by the vibration sensor 12 for plural damage filters. A filter processing unit that divides and extracts the frequency band, an envelope processing and frequency analysis of the filtered waveform transferred from the filter processing unit to obtain spectrum data, and an extracted damaged filter frequency band In the above, the bearing damage frequency resulting from the damage of the rolling bearing 11 calculated based on the rotation speed signal of the rolling bearing 11 and the frequency component included in the spectrum data obtained by the arithmetic processing unit are compared, and A precision diagnostic unit that identifies an abnormal site, and a damage level diagnostic unit that diagnoses the extent of damage or the progress of damage of the site based on the diagnostic value for each frequency band calculated for each damage filter frequency band .. As a result, it is possible to accurately and efficiently determine the presence/absence of an abnormality, the location of the abnormality, and the degree of damage or the progress of damage of the rolling bearing 11 incorporated in the mechanical equipment.

The condition monitoring device of the present invention is not limited to the above-described embodiment, and can be appropriately modified and improved.
For example, the condition monitoring device and the condition monitoring method of the present invention can be applied to mechanical equipment such as railway vehicles, machine tools, wind power generators, and elevator devices. Further, the state monitoring device and the state monitoring method of the present invention can be applied to the rolling bearing device including the rolling bearing 11 as a rotating component, as in the above-described embodiment.

Further, the state monitoring apparatus and the state monitoring method of the present embodiment may determine the diagnostic result at the time when the diagnostic result is repeated a plurality of times for the purpose of preventing erroneous diagnosis due to the influence of noise or the like.
Further, in the present embodiment, the case of monitoring the state of the rolling bearing in the case of the inner ring rotation has been described, but the state monitoring device and the state monitoring method of the present invention can also be used for monitoring the state of the rolling bearing in the outer ring rotation. Applicable.

1 Condition Monitoring Device 10 Mechanical Equipment 11 Rolling Bearing (Rotating Parts)
12 vibration sensor 20 controller 21 arithmetic processor 212 rotation analysis unit 213 filter processing unit 214 vibration analysis unit 215 comparison determination unit 22 control device 31 data transmission means

Claims (2)

A state monitoring device for monitoring the state of a rotating component that rotates relative to a stationary member,
A vibration sensor fixed to the rotating component or the stationary member,
A simple diagnosis unit that calculates at least one simple diagnosis value obtained from the waveform of the signal detected by the vibration sensor and compares it with a threshold value, and diagnoses whether there is an abnormality in the rotating component,
A filter processing unit that divides and extracts the waveform of the signal detected by the vibration sensor into a plurality of damage filter frequency bands,
An arithmetic processing unit that performs envelope processing and frequency analysis on the filtered waveform transferred from the filter processing unit to obtain spectrum data,
In the extracted damage filter frequency band, a bearing damage frequency caused by damage to the rotating component calculated based on a rotation speed signal of the rotating component, and a frequency component included in the spectrum data obtained by the arithmetic processing unit. And a precise diagnosis unit that identifies the abnormal part of the rotating component,
Based on the diagnostic value for each frequency band calculated for each damage filter frequency band, a damage level diagnostic unit for diagnosing the degree of damage or the progress of damage of the site,
Equipped with
The frequency band-based diagnostic value is the presence or absence of a peak in the spectrum data for each damage filter frequency band obtained in the arithmetic processing unit,
The state monitoring device, wherein the damage level diagnosis unit diagnoses the degree of damage or the progress of damage of the rotary component based on the presence or absence of the peak for each damage filter frequency band. A state monitoring method for monitoring the state of a rotating component that rotates relative to a stationary member,
A detection step of detecting a signal from a vibration sensor fixed to the rotating component or the stationary member,
A simple diagnosis step of diagnosing the presence or absence of abnormality of the rotating component by calculating at least one simple diagnosis value obtained from the waveform of the signal detected by the vibration sensor and comparing it with a threshold value,
A filtering step of dividing the waveform of the signal detected by the vibration sensor into a plurality of damage filter frequency bands and extracting the waveform.
An arithmetic processing step of obtaining spectral data by performing envelope processing and frequency analysis on the filtered waveform transferred from the filtering step,
In the extracted damage filter frequency band, a bearing damage frequency caused by damage to the rotating component calculated based on a rotation speed signal of the rotating component, and a frequency component included in the spectrum data obtained in the arithmetic processing step. And a precise diagnosis step of identifying the abnormal portion of the rotating component,
Based on the diagnostic value for each frequency band calculated for each damage filter frequency band, a damage level diagnosis step of diagnosing the degree of damage of the site or the progress of damage,
Equipped with
The precision diagnosis step and the damage level diagnosis step are performed when the rotary component is diagnosed as abnormal in the simple diagnosis step,
The frequency band-specific diagnostic value is the presence or absence of a peak in the spectrum data for each damage filter frequency band obtained in the arithmetic processing step ,
The state monitoring method, wherein the damage level diagnosis step diagnoses the degree of damage or the progress of damage of the rotary component based on the presence or absence of the peak for each damage filter frequency band.

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