JP2023007250A - Device condition monitoring device, wind power generation system, and device status monitoring method - Google Patents

Abstract

Kind Code: A1 A device status monitoring device capable of appropriately monitoring device status is provided. A frequency analysis unit (31) for outputting a frequency spectrum (SP1) of vibration generated by a monitoring target device (10), an intensity of a characteristic frequency which is a frequency related to the state of the monitoring target device (10), and a sideband frequency of the characteristic frequency. an intensity extraction unit 32 for extracting the intensity, an intensity corresponding value corresponding to the intensity of the characteristic frequency fc, and an intensity corresponding value corresponding to the intensity of the sideband frequency, and a signal operation for performing a predetermined operation. and a unit 33 are provided in the device state monitoring device 100 . [Selection drawing] Fig. 1

Description

TECHNICAL FIELD The present invention relates to an equipment condition monitoring device, a wind power generation system, and an equipment condition monitoring method.

As a background art of this technical field, the abstract of Patent Document 1 below states, "The abnormality diagnosis method is based on the rotational speed signal and the bearing design specifications, and each of the fundamental frequency and the harmonic frequency caused by the damage of the bearing is calculated. (S3), perform frequency analysis on the measured data, and obtain a first value Σm indicating the sum of the power of the frequency components in the main monitoring band at each of the fundamental frequency and the harmonic frequency; , and a second value Σo indicating the sum of the powers of the frequency components in the sub-monitoring band other than the main monitoring band, to determine the abnormality of the bearing to be diagnosed (S5 to S9).” .

JP 2019-86349 A

By the way, with respect to the above-described technology, there is a demand for more appropriate monitoring of device states.
SUMMARY OF THE INVENTION It is an object of the present invention to provide a device state monitoring device, a wind power generation system, and a device state monitoring method that can appropriately monitor device states.

In order to solve the above-mentioned problems, the device state monitoring apparatus of the present invention comprises: a frequency analysis unit that outputs a frequency spectrum of vibration generated by a monitored device; an intensity of a characteristic frequency that is a frequency related to the state of the monitored device; Using an intensity extraction unit that extracts the intensity of the sideband frequency of the characteristic frequency, an intensity corresponding value corresponding to the intensity of the characteristic frequency, and an intensity corresponding value corresponding to the intensity of the sideband frequency, and a signal calculation unit that performs calculation.

ADVANTAGE OF THE INVENTION According to this invention, an apparatus state can be monitored appropriately.

1 is a block diagram of main parts of a wind power generation system according to a first embodiment; FIG. It is a figure which shows an example of the frequency spectrum obtained in 1st Embodiment. FIG. 10 is a block diagram of the essential parts of a wind power generation system according to a second embodiment; It is a figure which shows an example of the frequency spectrum obtained in 2nd Embodiment.

[Premise of the embodiment]
Among the plant equipment that is automatically operated and controlled, there are systems that operate almost unmanned. is high.
For example, in a typical wind power generation system, since the power generation operation is automatically controlled, it is rare for a facility inspector who also serves as an operator to stay in the machine room to check the operating state of the equipment. In such a case, a measuring device that evaluates the soundness of the equipment is installed in advance in the system, measures the status of the equipment during operation, and transmits the measurement results to a monitoring station remote from the system to confirm that the operating status is normal. It may be evaluated whether or not

Such a measuring device, for example, measures the vibration of a rolling bearing that supports a rotating shaft, separates and extracts the frequency component of the characteristic vibration generated by the bearing, and monitors its change over time to determine the soundness of the bearing. is often used. However, if the magnitude of the vibration signal is not sufficient, such as when the rotation speed of the shaft is low, the magnitude of the signal and the level of the environmental noise will be close, making it difficult to acquire the time change of the signal with good sensitivity. may become

It is considered that this type of problem can be solved to some extent by applying the technique of Patent Literature 1 described above. That is, it is considered that the sum of the powers of the frequency components of the fundamental frequency and the harmonic frequency makes it easier to detect an abnormality in the bearing or the like that is the object of diagnosis.

However, the measurement device configured as described above requires signal collection over a high frequency range, which necessitates the provision of a high-speed signal collection device, which may increase the cost of the measurement device. be. If the system to be evaluated has been introduced for a long time and does not have this kind of high-precision measuring equipment, the increase in cost may be a hindrance to the introduction of the measuring equipment. In general, the higher the frequency of an oscillating wave or sound wave, the higher the attenuation rate. Therefore, the amount of information obtained from the frequency components of high-order harmonics is relatively small.
As described above, the embodiments described later provide a device status monitoring device and method that are low in installation cost and can be applied regardless of the equipment configuration of the target system.

[First embodiment]
FIG. 1 is a block diagram of main parts of a wind power generation system 1 according to the first embodiment.
The wind power generation system 1 includes a bearing mechanism 10 (device to be monitored) and a device state monitoring device 100 . Here, the bearing mechanism 10 supports, for example, a windmill (not shown) provided in the wind power generation system 1 . Also, the device state monitoring device 100 monitors the state of the bearing mechanism 10 .

A bearing mechanism 10 for a wind turbine includes a rotating shaft 11 , a rolling bearing 12 , a bearing casing 13 and a bearing cover 14 . The rotating shaft 11 is formed in a substantially cylindrical shape. Although the details of the rolling bearing 12 are omitted, the rolling bearing 12 has a generally annular inner ring, a generally annular outer ring provided on the outer peripheral side of the inner ring, and a spherical or spherical ring sandwiched between the inner ring and the outer ring. It has a plurality of cylindrical rolling elements and a retainer that maintains a distance between the rolling elements. The inner ring of rolling bearing 12 is fixed to rotating shaft 11 . Moreover, the bearing casing 13 fixes the outer ring of the rolling bearing 12 . The bearing cover 14 is formed to cover the exposed portion of the rolling bearing 12 .

The device state monitoring device 100 includes a signal recording device 20 and a signal analysis device 30 . Here, the signal recording device 20 includes a signal sensor 21 , a signal collection section 22 and a collection control section 23 . The signal analysis device 30 includes hardware such as a CPU (Central Processing Unit), RAM (Random Access Memory), ROM (Read Only Memory) and the like (none of which are shown) as a general computer. , control programs executed by the CPU, various data, and the like are stored.

In FIG. 1, the inside of the signal analysis device 30 shows functions implemented by a control program or the like as blocks. That is, the signal analysis device 30 includes a frequency analysis unit 31 , an intensity extraction unit 32 , a signal calculation unit 33 , a signal time series unit 34 and a frequency storage unit 35 .

The collection control unit 23 in the signal recording device 20 supplies a signal acquisition command to the signal collection unit 22 at predetermined timings. The signal collector 22 acquires the vibration signal S1 generated by the rolling bearing 12 from the signal sensor 21 based on a predetermined collection condition in synchronization with the signal acquisition command, and stores the result as waveform information. The predetermined collection condition is, for example, a condition such as "the rotational speed of the rotating shaft 11 has reached a predetermined speed".

The frequency analysis unit 31 in the signal analysis device 30 reads the waveform information stored in the signal acquisition unit 22 and performs frequency analysis to obtain spectrum data SP1 (frequency spectrum) of the vibration signal S1. The spectrum data SP1 includes the frequency of each frequency of the vibration signal S1 and the amplitude (intensity) of vibration acceleration.

FIG. 2 is a diagram showing an example of spectrum data SP1 obtained in the first embodiment.
In FIG. 2, the horizontal axis is the vibration frequency, and the vertical axis is the amplitude (strength) of the vibration acceleration of each frequency component. Thus, FIG. 2 shows at what frequency and amplitude the monitored rolling bearing 12 is vibrating.
In FIG. 2 , the rotation frequency fr is the rotation frequency of the rotating shaft 11 . This rotational frequency fr is generated due to the eccentricity of the rotating shaft 11 or the like. Also, the characteristic frequency fc is a frequency component of vibration generated in the rolling bearing 12, and is, for example, one of the frequencies listed below.
・Inner ring passing frequency of rolling elements ・Outer ring passing frequency of rolling elements ・Rotational frequency of rolling elements ・Rotational frequency of cage

The rotation frequency fr and the characteristic frequency fc appear as peaks in the spectrum data SP1. By analyzing the time series change of the frequency component of the characteristic frequency fc, the soundness of the rolling bearing 12 to be monitored can be evaluated. Also, in the illustrated example, a peak occurs in the frequency of the sideband component around the characteristic frequency fc. In the example shown, the frequencies of the negative and positive primary sideband components are fm1=fc-fr and fp1=fc+fr.

The frequencies of the negative and positive secondary sideband components are fm2=fc-2fr and fp2=fc+2fr. Although not shown, third-order and fourth-order sideband components may also occur. These sideband wave components are vibration components derived from the component of the characteristic frequency fc of the rolling bearing 12. Extracting the sideband wave component is considered to enable more accurate evaluation of the vibration of the component of the characteristic frequency fc.

Returning to FIG. 1, the frequency storage unit 35 stores frequency data D1. The frequency data D1 includes the characteristic frequency fc (see FIG. 2) of the rolling bearing 12 and the sideband frequencies fm1, fm2, fp1 and fp2. The intensity extractor 32 extracts the intensity of a plurality of frequency components specified by the frequency data D1 from the spectrum data SP1. If the spectrum data SP1 is obtained when the rotational speed of the rotating shaft 11 is a predetermined value, the characteristic frequency fc and the sideband frequency are often constant. Therefore, in such a case, the frequency data D1 stored in the frequency storage unit 35 may also be constant.

The signal accumulator 33 adds the characteristic frequency fc and the intensity of each sideband component. That is, the signal calculator 33 adds an intensity correspondence value corresponding to the intensity of the characteristic frequency fc and an intensity correspondence value corresponding to the intensity of the sideband frequency as a predetermined calculation. The "intensity corresponding value" is a "value corresponding to intensity", and may be "intensity" itself. In the above example, the signal accumulator 33 adds the intensity of the characteristic frequency fc and the sideband frequencies fm1, fm2, fp1, and fp2. As a result, the state of the rolling bearing 12 appears in the addition result (calculation result) with higher accuracy. The signal accumulator 33 may calculate the arithmetic sum of the intensity of the characteristic frequency fc and the intensity of each sideband component, but it is more desirable to obtain the sum of squares because it is more quantitative. Note that the predetermined operation may be addition, multiplication, or other operations that can solve the problem.

Both the intensity of the characteristic frequency fc and its square value can be considered to be values corresponding to the intensity of the characteristic frequency fc, that is, "intensity corresponding values". Similarly, the intensity of each sideband component and their squared values can be considered to be "intensity correspondence values" corresponding to the intensity of each sideband component. Various values other than those described above are conceivable for the “intensity corresponding value”. Therefore, the signal calculator 33 may perform predetermined calculations on various intensity corresponding values other than those described above for the characteristic frequency fc and each sideband component.

The signal calculator 33 adds the intensity of the extracted frequency components. The signal time-serialization unit 34 arranges the addition result in the signal calculation unit 33 in time series, and outputs the result as a diagnostic signal S2. The time-series value of the diagnostic signal S2 represents a situation in which the vibration component generated by the monitored object (the rolling bearing 12 in the above example) changes in time series, and can be used as an index for evaluating the soundness of the monitored object. can. In other words, the operator can detect an abnormality or the like of the rolling bearing 12 by visually observing the graph of the diagnostic signal S2. Moreover, the presence or absence of an abnormality in the rolling bearing 12 may be automatically determined based on whether or not the value of the diagnostic signal S2 exceeds a predetermined threshold value.

[Second embodiment]
FIG. 3 is a block diagram of main parts of the wind power generation system 2 according to the second embodiment. In addition, in the following description, the same code|symbol may be attached|subjected to the part corresponding to each part of 1st Embodiment mentioned above, and the description may be abbreviate|omitted.
The wind power generation system 2 includes a gear mechanism 50 and a device state monitoring device 102 . The gear mechanism 50 is, for example, a mechanism that reduces the rotational speed of a windmill (not shown) provided in the wind power generation system 1 .

In FIG. 3, a wind turbine gear mechanism 50 includes gears 51 and 52 . The gears 51 and 52 mesh with each other and rotate about the rotation shafts 51a and 52a, respectively. Further, in FIG. 3, the device status monitoring device 102 includes a signal recording device 20 and a signal analysis device 130 .

Here, the configuration of the signal recording device 20 is the same as that of the first embodiment (see FIG. 1). The hardware configuration of the signal analysis device 130 is the same as that of the signal analysis device 30 of the first embodiment, but its functions are provided with a peak detector 137 in addition to those of the first embodiment. Further, in this embodiment, the spectrum data output by the frequency analysis unit 31 is called SP2.

FIG. 4 is a diagram showing an example of spectrum data SP2 obtained in the second embodiment.
In FIG. 4, rotational frequencies fr1 and fr2 are the rotational frequencies of the gears 51 and 52, respectively. The characteristic frequency fc is the meshing frequency of the gears 51 and 52, for example. In the illustrated example, sideband wave components based on both rotation frequencies fr1 and fr2 are generated around the characteristic frequency fc. That is, the frequencies of the negative and positive primary sideband components by gear 51 are fn1=fc-fr1 and fq1=fc+fr1. Further, the frequencies of the secondary sideband components on the negative and positive sides by the gear 51 are fn2=fc-2fr1 and fq2=fc+2fr1. The frequencies of the negative and positive primary sideband components by gear 52 are fm1=fc-fr2 and fp1=fc+fr2. The frequencies of the negative and positive secondary sideband components by gear 52 are fm2=fc-2fr2 and fp2=fc+2fr2.

Returning to FIG. 3, the peak detector 137 performs peak detection on the spectrum data SP2 generated by the frequency analyzer 31. FIG. Then, based on the detected peak distribution shape and the like, the characteristic frequency fc and the frequency of the sideband wave component thereof are specified, and the specified frequencies are stored in the frequency storage unit 35 . That is, in the example shown in FIG. 4, the peak detector 137 identifies the characteristic frequency fc and the sideband frequencies fm1, fm2, fp1, fp2, fn1, fn2, fq1, and fq2, and stores the identified frequencies in the frequency storage. stored in the unit 35; Then, the signal calculator 33 adds the characteristic frequency fc and the intensity of each sideband frequency.

The configuration and operation of this embodiment other than those described above are the same as those of the first embodiment. According to this embodiment, when a sideband component is generated, its frequency and intensity are detected, and the value corresponding to the intensity of the characteristic frequency fc (intensity corresponding value) and the intensity of each sideband component are corresponding values (intensity corresponding values) can be added. As a result, the state of the gear mechanism 50 can be detected with high accuracy as in the first embodiment.

[Effects of Embodiment]
As described above, according to the above-described embodiments, the device state monitoring devices 100 and 102 include the frequency analysis section (31) that outputs the frequency spectrum (SP1, SP2) of the vibration generated by the monitoring target device (10, 50). , the intensity of the characteristic frequency (fc), which is the frequency related to the state of the monitored device (10, 50), and the intensity of the sideband frequencies (fm1, fp1, fn1, fq1, . . . ) of the characteristic frequency (fc). An intensity extraction unit (32) for extraction, an intensity corresponding value corresponding to the intensity of the characteristic frequency (fc), and an intensity corresponding value corresponding to the intensity of the sideband frequencies (fm1, fp1, fn1, fq1, . . . ) and a signal calculation unit (33) for performing a predetermined calculation using the signal.

In addition, according to another aspect of the above-described embodiment, a frequency analysis process (31) that outputs the frequency spectrum (SP1, SP2) of the vibration generated by the monitoring target equipment (10, 50), and the monitoring target equipment ( 10, 50) and the intensity of the sideband frequencies (fm1, fp1, fn1, fq1, . 32), an intensity corresponding value corresponding to the intensity of the characteristic frequency (fc), and an intensity corresponding value corresponding to the intensity of the sideband frequencies (fm1, fp1, fn1, fq1, . and a signal calculation step (33).

Thus, according to the above-described embodiment, it is possible to accurately and appropriately monitor the device state based on the intensity of the characteristic frequency fc and the intensity of the sideband frequencies (fm1, fp1, fn1, fq1, . . . ). More specifically, since the state of the monitored device (10, 50) is determined based on the characteristic frequency fc and the sideband frequency belonging to a relatively low frequency band, it becomes unnecessary to collect signals over a high frequency region. . Furthermore, since vibration waves and sound waves belonging to a relatively low frequency band have a low attenuation factor in media such as air and metals, relatively high-intensity signals can be obtained. As a result, the monitored device (10, 50) can be monitored at low cost and with high accuracy.

Also, like the device status monitoring device 102, it detects the frequency at which the intensity peak occurs in the frequency spectrum SP2, and determines the characteristic frequency fc and the sideband frequencies (fm1, fp1, fn1, fq1, . . . ) based on the detection result. It is more preferable to further include a peak detector 137 that As a result, the equipment status can be monitored more accurately and appropriately based on the status of the frequency spectrum SP2.

In addition, the equipment to be monitored (10, 50) has one or more rotating shafts 11, 51a, 52a, and the sideband frequencies (fm1, fp1, fn1, fq1, . . . ) are , frequencies obtained by increasing or decreasing integral multiples of the rotational frequencies fr, fr1, and fr2 of the rotating shafts 11, 51a, and 52a. As a result, the sideband wave components generated based on the rotational frequencies fr, fr1, and fr2 enable more accurate and appropriate monitoring of the device state.

Further, it is more preferable that the device state monitoring devices 100 and 102 further include a signal collection unit 22 that collects vibrations generated by the monitoring target device (10, 50) based on predetermined collection conditions. As a result, the frequency spectrum (SP1, SP2) can be collected according to the collection conditions, and the device status can be monitored more accurately and appropriately.

Moreover, it is more preferable that the monitored equipment (10, 50) is a part of the wind power generation system 1, 2. As a result, the states of the wind power generation systems 1 and 2 can be monitored more accurately and appropriately.

[Modification]
The present invention is not limited to the embodiments described above, and various modifications are possible. The above-described embodiments are illustrated for easy understanding of the present invention, and are not necessarily limited to those having all the described configurations. Also, part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Also, it is possible to delete part of the configuration of each embodiment, or to add or replace other configurations. Also, the control lines and information lines shown in the drawings are those considered to be necessary for explanation, and do not necessarily show all the control lines and information lines necessary on the product. In practice, it may be considered that almost all configurations are interconnected. Possible modifications to the above embodiment are, for example, the following.

(1) Each of the above embodiments monitors the bearing mechanism 10 or the gear mechanism 50, which are components of the wind power generation systems 1 and 2, but the application of the present invention is not limited to this. That is, the present invention can be applied to condition monitoring of mechanical elements such as bearings and gears attached to a rotating shaft system in various plant machines.

(2) Since the hardware of the signal analysis device 30 in the above embodiment can be realized by a general computer, the programs and the like for executing the various processes described above can be stored in a storage medium or distributed via a transmission line. good.

(3) Each process of the signal analysis device 30 described above was described as a software process using a program in the above embodiment, but part or all of it is an ASIC (Application Specific Integrated Circuit) Alternatively, hardware processing using an FPGA (Field Programmable Gate Array) or the like may be substituted.

(4) Various processes executed in the signal analysis device 30 may be executed by a server computer via a network (not shown), and various data stored in the above embodiment may also be stored in the server computer. good.

1, 2 Wind power generation system 10 Bearing mechanism (device to be monitored)
11, 51a, 52a rotating shaft 22 signal collecting unit 31 frequency analysis unit (frequency analysis process)
32 intensity extraction unit (strength extraction process)
33 Signal calculation unit (signal calculation process)
50 gear mechanism (device to be monitored)
100, 102 Equipment state monitoring device 137 Peak detector D1 Frequency data fc Characteristic frequencies SP1, SP2 Spectrum data (frequency spectrum)
fr, fr1, fr2 rotation frequencies fm1, fm2, fp1, fp2, fn1, fn2, fq1, fq2 sideband frequencies

Claims (7)

a frequency analysis unit that outputs a frequency spectrum of vibration generated by the monitored device;
an intensity extraction unit that extracts the intensity of a characteristic frequency, which is a frequency related to the state of the monitored device, and the intensity of a sideband frequency of the characteristic frequency;
a signal calculation unit that performs a predetermined calculation using an intensity corresponding value corresponding to the intensity of the characteristic frequency and an intensity corresponding value corresponding to the intensity of the sideband frequency. Device. 2. The device status monitor according to claim 1, further comprising a peak detection unit that detects a frequency at which an intensity peak occurs in the frequency spectrum and determines the characteristic frequency and the sideband frequency based on the detection result. Device. the monitored device comprises one or more rotating shafts,
3. The device state monitoring apparatus according to claim 1, wherein the sideband frequency is a frequency obtained by increasing or decreasing an integral multiple of the rotational frequency of the rotating shaft with respect to the characteristic frequency. The equipment status monitoring apparatus according to any one of claims 1 to 3, further comprising a signal collection unit that collects the vibration generated by the monitoring target equipment based on a predetermined collection condition. The equipment status monitoring device according to any one of claims 1 to 4, wherein the equipment to be monitored is part of a wind power generation system. a monitored device;
a frequency analysis unit that outputs a frequency spectrum of vibration generated by the monitored device;
an intensity extraction unit that extracts the intensity of a characteristic frequency, which is a frequency related to the state of the monitored device, and the intensity of a sideband frequency of the characteristic frequency;
A wind power generation system comprising: a signal calculation unit that performs a predetermined calculation using an intensity correspondence value corresponding to the intensity of the characteristic frequency and an intensity correspondence value corresponding to the intensity of the sideband frequency. . a frequency analysis process for outputting a frequency spectrum of vibrations generated by the monitored device;
an intensity extraction step of extracting the intensity of a characteristic frequency, which is a frequency related to the state of the monitored device, and the intensity of a sideband frequency of the characteristic frequency;
a signal calculation process for performing a predetermined calculation using the intensity corresponding value corresponding to the intensity of the characteristic frequency and the intensity corresponding value corresponding to the intensity of the sideband frequency. Method.

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