Equipment status monitoring device, wind power generation system, and equipment status monitoring method

Abstract

To provide a device condition monitoring device capable of properly monitoring device condition.SOLUTION: A device condition monitoring device 100 includes: a frequency analysis unit 31 that outputs a vibration frequency spectrum SP1 generated by a device 10 to be monitored; a strength extraction unit 32 that extracts the strength of feature frequency, which is the frequency associated with the states of the device 10 to be monitored and the strength of the sideband frequencies of the feature frequency; and a signal calculation unit 33 that performs predetermined calculations using the strength correspondence value corresponding to the strength of the feature frequency fc and the strength correspondence value corresponding to the strength of the sideband frequencies.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an equipment status monitoring device, a wind power generation system, and an equipment status monitoring method. [Background technology]

[0002] As background technology in this technical field, the abstract of Patent Document 1 listed below states that "the abnormality diagnosis method sets a main monitoring band for each of the fundamental frequency and harmonic frequencies caused by bearing damage calculated based on the rotational speed signal and the bearing design specifications (S3), performs frequency analysis on the measurement data, and judges an abnormality in the bearing to be diagnosed using a first value Σm indicating the sum of the power of frequency components in the main monitoring band for each of the fundamental frequency and harmonic frequency, and a second value Σo indicating the sum of the power of frequency components in a secondary monitoring band other than the main monitoring band (S5 to S9)." [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-86349 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, with respect to the above-mentioned technology, there is a demand for more appropriate monitoring of the device state. The present invention has been made in consideration of the above-mentioned circumstances, and an object of the present invention is to provide an equipment state monitoring device, a wind power generation system, and an equipment state monitoring method that are capable of appropriately monitoring the equipment state. [Means for solving the problem]

[0005] In order to solve the above problems, an equipment status monitoring device of the present invention includes a frequency analysis unit that outputs a frequency spectrum of vibrations generated by a monitored equipment, an intensity extraction unit that extracts the intensity of a feature frequency, which is a frequency related to the status of the monitored equipment, and the intensity of a sideband frequency of the feature frequency, and a signal calculation unit that performs a predetermined calculation using an intensity correspondence value corresponding to the intensity of the feature frequency and an intensity correspondence value corresponding to the intensity of the sideband frequency. and 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, wherein the monitored device has a plurality of rotating shafts, and the sideband frequency is a frequency obtained by increasing or decreasing the characteristic frequency by an integer multiple of the rotation frequency of each of the plurality of rotating shafts. It is characterized by: Effect of the Invention

[0006] According to the present invention, the device status can be appropriately monitored. [Brief description of the drawings]

[0007] [Figure 1] 1 is a block diagram of a main part of a wind power generation system according to a first embodiment. [Diagram 2] FIG. 3 is a diagram showing an example of a frequency spectrum obtained in the first embodiment. [Diagram 3] FIG. 11 is a block diagram of a main part of a wind power generation system according to a second embodiment. [Figure 4] FIG. 11 is a diagram showing an example of a frequency spectrum obtained in the second embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] [Prerequisites for the embodiment] Among plant equipment that is automatically controlled, there are systems that are operated almost unmanned. In such cases, there is a high need for measuring devices that can diagnose the health of the equipment in place of equipment inspectors. For example, in a typical wind power generation system, since the power generation operation is automatically controlled, it is rare for an equipment inspector who also serves as an operator to stay in the machine room to check the operating status of the equipment. In such cases, a measuring device that evaluates the soundness of the equipment is pre-installed in the system, the status of the equipment during operation is measured, and the measurement results are transmitted to a monitoring station away from the system to evaluate whether the operating status is normal or not.

[0009] With such measuring devices, for example, the vibration of a rolling bearing supporting a rotating shaft is measured, and the characteristic frequency components of the vibration generated by the bearing are separated and extracted, and the time change of the frequency components is monitored to evaluate the soundness of the bearing. However, when the magnitude of the vibration signal is insufficient, for example, when the rotation speed of the shaft is low, the signal magnitude becomes close to the environmental noise level, and it may be difficult to obtain the time change of the signal with good sensitivity.

[0010] It is believed that this type of problem can be solved to some extent by applying the technology of the above-mentioned Patent Document 1. In other words, it is believed that by calculating the sum of the power of the fundamental frequency and harmonic frequency components, it becomes easier to detect abnormalities in the bearings or other components that are the subject of diagnosis.

[0011] However, the measurement device configured as described above needs to collect signals over a high frequency range, which requires a high-speed signal collection device, and this may increase the cost of the measurement device. If the system to be evaluated was introduced a long time ago and does not have this type of high-precision measurement equipment, the increase in cost may be an obstacle to the introduction of the measurement device. In addition, since vibration waves and sound waves generally have a higher attenuation rate as their frequency increases, the information obtained from the frequency components of higher harmonics is relatively small. As described above, the embodiments described below provide an equipment status monitoring apparatus and method that can be installed at low cost and that can be applied regardless of the equipment configuration of a target system.

[0012] [First embodiment] FIG. 1 is a block diagram of a main part of a wind power generation system 1 according to the first embodiment. The wind power generation system 1 includes a bearing mechanism 10 (monitored equipment) and an equipment state monitoring device 100. Here, the bearing mechanism 10 supports, for example, a wind turbine (not shown) provided in the wind power generation system 1. The equipment state monitoring device 100 monitors the state of the bearing mechanism 10.

[0013] The 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 not shown in the drawings, the rolling bearing 12 includes a substantially annular inner ring, a substantially annular outer ring provided on the outer periphery of the inner ring, a plurality of spherical or cylindrical rolling elements sandwiched between the inner ring and the outer ring, and a cage that maintains the distance between the rolling elements. The inner ring of the rolling bearing 12 is fixed to the rotating shaft 11. 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.

[0014] The equipment status 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 unit 22, and a collection control unit 23. The signal analysis device 30 includes general computer hardware (all not shown) such as a CPU (Central Processing Unit), RAM (Random Access Memory), and ROM (Read Only Memory), and the ROM stores a control program executed by the CPU, various data, and the like.

[0015] 1, the inside of the signal analysis device 30 is shown as blocks representing functions realized by a control program, etc. 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 conversion unit 34, and a frequency storage unit 35.

[0016] The collection control unit 23 in the signal recording device 20 supplies a signal acquisition command to the signal collection unit 22 at each predetermined timing. In synchronization with the signal acquisition command, the signal collection unit 22 acquires the vibration signal S1 generated by the rolling bearing 12 from the signal sensor 21 based on a predetermined collection condition, and stores the result as waveform information. Note that the predetermined collection condition is, for example, a condition such as "the rotation speed of the rotating shaft 11 reaches a predetermined speed."

[0017] The frequency analysis unit 31 in the signal analysis device 30 reads out the waveform information stored in the signal collection unit 22, performs frequency analysis, and acquires 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 the vibration acceleration.

[0018] FIG. 2 is a diagram showing an example of spectrum data SP1 obtained in the first embodiment. In Fig. 2, the horizontal axis is vibration frequency, and the vertical axis is the amplitude (strength) of vibration acceleration of each frequency component. In this way, Fig. 2 shows the frequency and amplitude at which the rolling bearing 12 to be monitored vibrates. 2, the rotation frequency fr is the rotation frequency of the rotating shaft 11. This rotation frequency fr occurs due to eccentricity of the rotating shaft 11. Furthermore, the characteristic frequency fc is a frequency component of vibration occurring in the rolling bearing 12, and is, for example, any 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 the cage

[0019] The rotational frequency fr and the characteristic frequency fc appear as peaks in the spectrum data SP1. By analyzing the time-series changes in the frequency components of the characteristic frequency fc, the soundness of the rolling bearing 12 to be monitored can be evaluated. In the illustrated example, peaks occur in the frequencies of the sideband components around the characteristic frequency fc. In the illustrated example, the frequencies of the negative and positive primary sideband components are fm1=fc-fr and fp1=fc+fr.

[0020] Moreover, the frequencies of the negative and positive secondary sideband components are fm2=fc-2fr and fp2=fc+2fr. Although not shown, third and fourth order sideband components may also occur. These sideband components are vibration components originating from the component of the characteristic frequency fc of the rolling bearing 12, and it is believed that by extracting the sideband components, the vibration of the component of the characteristic frequency fc can be evaluated with higher accuracy.

[0021] Returning to FIG. 1, the frequency storage unit 35 stores frequency data D1. The frequency data D1 includes a characteristic frequency fc (see FIG. 2) of the rolling bearing 12 and sideband frequencies fm1, fm2, fp1, and fp2. The intensity extraction unit 32 extracts the intensities of a plurality of frequency components specified by the frequency data D1 from the spectrum data SP1. Note that, if the spectrum data SP1 is acquired when the rotation speed of the rotating shaft 11 is a predetermined value, the characteristic frequency fc and the sideband frequencies are often constant. Therefore, in such a case, the frequency data D1 stored in the frequency storage unit 35 may also be constant.

[0022] The signal integration calculation unit 33 adds the intensities of the characteristic frequency fc and each sideband wave component. That is, the signal calculation unit 33 adds 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 wave frequency as a predetermined calculation. The "intensity corresponding value" is a "value corresponding to the intensity" and may be "intensity" itself. In the above example, the signal integration calculation unit 33 adds the intensities of the characteristic frequency fc and each sideband wave frequency fm1, fm2, fp1, and fp2. As a result, the state of the rolling bearing 12 appears with higher accuracy in the addition result (calculation result). Note that the signal integration calculation unit 33 may calculate an arithmetic sum of the intensity of the characteristic frequency fc and the intensity of each sideband wave component, but it is more preferable to calculate a sum of squares because it is more quantitative. Note that the predetermined calculation may be addition or multiplication, or may be another calculation that can solve the problem.

[0023] The intensity of the feature frequency fc and its squared value can both be considered to be values ​​corresponding to the intensity of the feature frequency fc, i.e., "intensity corresponding values." Similarly, the intensity of each sideband wave component and its squared value can be considered to be "intensity corresponding values" corresponding to the intensity of each sideband wave component. There are various other possible "intensity corresponding values" besides those mentioned above. Therefore, the signal calculation unit 33 may perform a predetermined calculation on various intensity corresponding values ​​of the feature frequency fc and each sideband wave component other than those mentioned above.

[0024] The signal calculation unit 33 adds the intensities of the extracted frequency components. The signal time series conversion unit 34 arranges the addition results in the signal calculation unit 33 in a time series and outputs the result as a diagnostic signal S2. The time series values ​​of the diagnostic signal S2 represent the situation in which the vibration components generated by the monitored object (the rolling bearing 12 in the above example) change over time, and can be used as an index for evaluating the soundness of the monitored object. In other words, an operator can find an abnormality or the like of the rolling bearing 12 by visually checking the graph of the diagnostic signal S2. Also, the presence or absence of an abnormality or the like of 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.

[0025] [Second embodiment] 3 is a block diagram of the main parts of a wind power generation system 2 according to the second embodiment. In the following description, parts corresponding to those in the first embodiment described above are given the same reference numerals, and the description thereof may be omitted. The wind power generation system 2 includes a gear mechanism 50 and an equipment state monitoring device 102. The gear mechanism 50 is, for example, a mechanism for reducing the rotational speed of a wind turbine (not shown) provided in the wind power generation system 1.

[0026] In Fig. 3, a gear mechanism 50 for a wind turbine includes gears 51 and 52. The gears 51 and 52 mesh with each other and rotate around rotation shafts 51a and 52a, respectively. Also in Fig. 3, an equipment status monitoring device 102 includes a signal recording device 20 and a signal analyzing device 130.

[0027] Here, the configuration of the signal recording device 20 is the same as that of the first embodiment (see FIG. 1). Also, 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 the function thereof includes a peak detection unit 137 in addition to those of the first embodiment. Also, in this embodiment, the spectrum data output by the frequency analysis unit 31 is called SP2.

[0028] 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 gears 51 and 52, respectively. The characteristic frequency fc is, for example, the meshing frequency of gears 51 and 52. In the illustrated example, sideband components based on both rotational frequencies fr1 and fr2 are generated around the characteristic frequency fc. That is, the frequencies of the negative and positive primary sideband components of gear 51 are fn1=fc-fr1 and fq1=fc+fr1. The frequencies of the negative and positive secondary sideband components of gear 51 are fn2=fc-2fr1 and fq2=fc+2fr1. The frequencies of the negative and positive primary sideband components of gear 52 are fm1=fc-fr2 and fp1=fc+fr2. The frequencies of the negative and positive secondary sideband components of gear 52 are fm2=fc-2fr2 and fp2=fc+2fr2.

[0029] Returning to Fig. 3, the peak detection unit 137 performs peak detection on the spectrum data SP2 generated by the frequency analysis unit 31. Then, based on the distribution shape of the detected peak, the peak detection unit 137 identifies the characteristic frequency fc and the frequencies of its sideband components, and stores the identified frequencies in the frequency storage unit 35. That is, in the example shown in Fig. 4, the peak detection unit 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 unit 35. Then, the signal calculation unit 33 adds up the intensities of the characteristic frequency fc and each sideband frequency.

[0030] 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 wave component is generated, its frequency and intensity are detected, and a value corresponding to the intensity of the characteristic frequency fc (intensity corresponding value) and a value corresponding to the intensity of each sideband wave component (intensity corresponding value) are added together. This makes it possible to detect the state of the gear mechanism 50 with high accuracy, as in the first embodiment.

[0031] [Effects of the embodiment] As described above, according to the embodiment, the equipment status monitoring device 100, 102 includes a frequency analysis unit (31) that outputs a frequency spectrum (SP1, SP2) of vibrations generated by the monitored equipment (10, 50), an intensity extraction unit (32) that extracts the intensity of a feature frequency (fc), which is a frequency related to the state of the monitored equipment (10, 50), and the intensities of sideband frequencies (fm1, fp1, fn1, fq1, ...) of the feature frequency (fc), and a signal calculation unit (33) that performs a predetermined calculation using an intensity correspondence value corresponding to the intensity of the feature frequency (fc) and an intensity correspondence value corresponding to the intensities of the sideband frequencies (fm1, fp1, fn1, fq1, ...).

[0032] Also, from another perspective, the above-described embodiment is an equipment status monitoring method characterized by having a frequency analysis process (31) that outputs a frequency spectrum (SP1, SP2) of vibrations generated by the monitored equipment (10, 50), an intensity extraction process (32) that extracts the intensity of a feature frequency (fc), which is a frequency related to the state of the monitored equipment (10, 50), and the intensities of sideband frequencies (fm1, fp1, fn1, fq1, ...) of the feature frequency (fc), and a signal calculation process (33) that performs a predetermined calculation using an intensity correspondence value corresponding to the intensity of the feature frequency (fc) and an intensity correspondence value corresponding to the intensities of the sideband frequencies (fm1, fp1, fn1, fq1, ...).

[0033] As a result, according to the above-described embodiment, the state of the equipment can be monitored accurately and appropriately based on the intensity of the feature frequency fc and the intensity of the sideband frequencies (fm1, fp1, fn1, fq1, ...). More specifically, since the state of the monitored equipment (10, 50) is determined based on the feature frequency fc and the sideband frequencies that belong to a relatively low frequency band, it is not necessary to collect signals over a high frequency range. Furthermore, vibration waves and sound waves that belong to a relatively low frequency band have a low attenuation rate in a medium such as air or metal, a relatively high intensity signal can be obtained. As a result, the monitored equipment (10, 50) can be monitored accurately at low cost.

[0034] It is more preferable to further include a peak detection unit 137 that detects frequencies at which intensity peaks occur in the frequency spectrum SP2 and determines the feature frequency fc and sideband frequencies (fm1, fp1, fn1, fq1, ...) based on the detection results, like the equipment status monitoring device 102. This makes it possible to monitor the equipment status more accurately and appropriately based on the state of the frequency spectrum SP2.

[0035] Moreover, it is more preferable that the monitored device (10, 50) has one or more rotation shafts 11, 51a, 52a, and the sideband frequencies (fm1, fp1, fn1, fq1, ...) are frequencies obtained by increasing or decreasing the characteristic frequency fc by an integer multiple of the rotation frequencies fr, fr1, fr2 of the rotation shafts 11, 51a, 52a. This makes it possible to more accurately and appropriately monitor the device status using the sideband components generated based on the rotation frequencies fr, fr1, fr2.

[0036] Moreover, it is more preferable that the equipment status monitoring devices 100, 102 further include a signal collecting unit 22 that collects vibrations generated by the monitored equipment (10, 50) based on predetermined collection conditions. This makes it possible to collect frequency spectra (SP1, SP2) according to the collection conditions, and to monitor the equipment status more accurately and appropriately.

[0037] Moreover, it is more preferable that the monitored devices (10, 50) are part of the wind power generation systems 1, 2. This allows the states of the wind power generation systems 1, 2 to be monitored more accurately and appropriately.

[0038] [Variations] The present invention is not limited to the above-mentioned embodiment, and various modifications are possible. The above-mentioned embodiment is exemplified to explain the present invention in an easy-to-understand manner, and is not necessarily limited to those having all the configurations described. In addition, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. In addition, it is possible to delete a part of the configuration of each embodiment, or to add or replace other configurations. In addition, the control lines and information lines shown in the figure show those that are considered necessary for explanation, and do not necessarily show all the control lines and information lines necessary on the product. In reality, it may be considered that almost all the configurations are connected to each other. Possible modifications of the above-mentioned embodiment are, for example, as follows.

[0039] (1) Although the above embodiments are directed to monitoring the bearing mechanism 10 or the gear mechanism 50, which are components of the wind power generation systems 1 and 2, the application of the present invention is not limited to this. That is, the present invention can be applied to condition monitoring of machine elements such as bearings and gears associated with rotating shaft systems in various plant machines.

[0040] (2) The hardware of the signal analysis device 30 in the above embodiment can be realized by a general computer. Therefore, the programs for executing the various processes described above may be stored on a storage medium or distributed via a transmission line.

[0041] (3) In the above embodiment, each process of the signal analysis device 30 has been described as a software process using a program. However, some or all of the process may be replaced with hardware process using an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array), etc.

[0042] (4) The various processes executed by the signal analysis device 30 may be executed by a server computer via a network (not shown), and the various data stored in the above embodiment may also be stored in the server computer. [Explanation of symbols]

[0043] 1,2 Wind power generation system 10 Bearing mechanism (monitored equipment) 11, 51a, 52a Rotation axis 22 Signal Acquisition Unit 31 Frequency analysis section (frequency analysis process) 32 Intensity extraction part (intensity extraction process) 33 Signal calculation section (signal calculation process) 50 Gear mechanism (monitored equipment) 100,102 Equipment status monitoring device 137 Peak detector D1 Frequency Data fc Characteristic frequency SP1, SP2 spectrum data (frequency spectrum) fr,fr1,fr2 rotation frequency fm1, fm2, fp1, fp2, fn1, fn2, fq1, fq2 Sideband frequencies

Claims

1. a frequency analysis unit that outputs a frequency spectrum of vibrations generated by the monitored equipment; an intensity extraction unit that extracts an intensity of a characteristic frequency, which is a frequency related to a state of the monitored device, and an intensity of a sideband frequency of the characteristic frequency; 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 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, The monitored device has a plurality of rotation axes, The sideband frequency is a frequency obtained by increasing or decreasing the characteristic frequency by an integer multiple of the rotation frequency of each of the plurality of rotation shafts. An equipment status monitoring device comprising:

2. The apparatus further includes a signal collecting unit that collects vibrations generated by the monitored device based on a predetermined collection condition.

2. The equipment status monitoring device according to claim 1.

3. The monitored device is part of a wind power generation system.

3. The equipment status monitoring device according to claim 1 or 2.

4. The monitored device; a frequency analysis unit that outputs a frequency spectrum of the vibration generated by the monitored device; an intensity extraction unit that extracts an intensity of a characteristic frequency, which is a frequency related to a state of the monitored device, and an intensity of a sideband frequency of the characteristic frequency; 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 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, The monitored device has a plurality of rotation axes, The sideband frequency is a frequency obtained by increasing or decreasing the characteristic frequency by an integer multiple of the rotation frequency of each of the plurality of rotation shafts. A wind power generation system comprising:

5. a frequency analysis process for outputting a frequency spectrum of vibrations generated by the monitored equipment; an intensity extraction step of extracting an intensity of a characteristic frequency, which is a frequency related to the state of the monitored device, and an intensity of a sideband frequency of the characteristic frequency; a signal calculation step of performing 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 peak detection process for detecting a frequency at which an intensity peak occurs in the frequency spectrum and determining the characteristic frequency and the sideband frequency based on the detection result; The monitored device has a plurality of rotation axes, The sideband frequency is a frequency obtained by increasing or decreasing the characteristic frequency by an integer multiple of the rotation frequency of each of the plurality of rotation shafts.

2. A method for monitoring an equipment status comprising:

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