State monitoring apparatus and state monitoring method
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- NTN CORP
- Filing Date
- 2025-12-24
- Publication Date
- 2026-07-30
Smart Images
Figure JP2025045328_30072026_PF_FP_ABST
Abstract
Description
Condition Monitoring Device and Condition Monitoring Method
[0001] The present disclosure relates to a condition monitoring device and a condition monitoring method.
[0002] For the fault diagnosis of various rotating equipment, etc., a monitoring device that acquires data indicating the condition of the equipment, such as vibration data and temperature data, is known. In this case, in order to estimate the cause of an abnormality, a method of performing frequency analysis of the vibration data is used.
[0003] Since the rotational speed of a rotating shaft such as a windmill or a wheel fluctuates, the frequency of the vibration to be analyzed also changes in the condition monitoring device, and the frequency spectrum fluctuates. For this reason, various countermeasures have been studied against fluctuations in the rotational speed.
[0004] For example, Japanese Patent Application Laid-Open No. 2015-34776 (Patent Document 1) discloses a method of fitting the acquired data with a basis function having the rotational position of the rotating shaft as a variable. Thereby, frequency components related to the rotation of the rotating shaft can be extracted without being affected by changes in the rotational speed.
[0005] Also, for example, Japanese Patent No. 6665062 (Patent Document 2) discloses a method that does not use a rotation sensor. In this method, the acquired data is divided, and the rotational speed is estimated for each divided data. The divided data is corrected based on the estimated rotational speed, and the corrected data is combined and analyzed. Thereby, the influence of rotational fluctuations can be reduced and accurate analysis can be performed.
[0006] Japanese Patent Application Laid-Open No. 2015-34776, Japanese Patent No. 6665062
[0007] Japanese Patent Application Laid-Open No. 2015-34776 (Patent Document 1), etc. show an example of a signal processing method for removing the influence of rotational speed fluctuations. Applying this technique can improve the diagnostic accuracy, but for this purpose, it is necessary to acquire data with a certain degree of rotational fluctuations. However, there is a problem that a method for acquiring data aiming at rotational fluctuations has not been disclosed, and it is not certain whether the effect of improving the diagnostic accuracy can be enjoyed depending on the content of the acquired data.
[0008] The purpose of this disclosure is to provide a monitoring device that can identify data during periods when a rotating part is experiencing rotational fluctuations and use that identified data to improve diagnostic accuracy.
[0009] This disclosure relates to a condition monitoring device for monitoring the state of a device having a rotating part. The condition monitoring device includes a receiving unit that receives sensor signals from a sensor that monitors the state of the device and a speed signal indicating the rotational speed of the rotating part, a storage device that stores measurement data including sensor information and speed information corresponding to the sensor signal and speed signal received by the receiving unit, respectively, and a computing device that analyzes the measurement data. The computing device is configured to extract data from the measurement data that includes a section in which the fluctuation of the rotational speed exceeds a standard, and to perform tracking processing that analyzes the sensor information in the extracted data in accordance with the change in rotational speed.
[0010] According to the condition monitoring device disclosed herein, data from the period during which the rotational fluctuation of the rotating part exceeds a standard is identified and used for diagnosis, thereby improving diagnostic accuracy.
[0011] This is a block diagram showing the configuration of the state monitoring device according to this embodiment. This is a flowchart for explaining the data processing performed by the state monitoring device 20. This is a waveform diagram for explaining the first method of determining rotational fluctuations. This is a waveform diagram showing the determination result according to the first method of determining rotational fluctuations. This is a waveform diagram for explaining the second method of determining rotational fluctuations. This is a waveform diagram showing the determination result according to the second method of determining rotational fluctuations. This is a waveform diagram for explaining the third method of determining rotational fluctuations. This is a waveform diagram showing the determination result according to the third method of determining rotational fluctuations. This is a waveform diagram for explaining the fourth method of determining rotational fluctuations. This is a waveform diagram showing the determination result according to the fourth method of determining rotational fluctuations. This is a waveform diagram for explaining the fifth method of determining rotational fluctuations. This is a waveform diagram showing the determination result according to the fifth method of determining rotational fluctuations. This is a waveform diagram for explaining the sixth method of determining rotational fluctuations. This is a waveform diagram showing the determination result according to the sixth method of determining rotational fluctuations. This is a graph showing the spectrum when frequency analysis is performed without partial data selection. This is a graph showing the spectrum when frequency analysis is performed by selecting data for the rotational fluctuation period.
[0012] Embodiments of the present invention will be described in detail below with reference to the drawings. In the drawings, identical or corresponding parts are denoted by the same reference numerals, and their descriptions will not be repeated.
[0013] [Basic Configuration of the Status Monitoring Device] Figure 1 is a block diagram showing the configuration of the status monitoring device according to this embodiment. The status monitoring device and its surroundings used in this embodiment will be explained using Figure 1.
[0014] The monitored device 10 is a piece of equipment monitored by the condition monitoring device and has a rotating part. For example, the monitored device 10 may be a wind power generation system, a machine tool, a robot, or a vehicle. A wind power generation system may include, for example, the rotating shaft of a wind turbine as a rotating part. A machine tool may include, for example, the rotating shaft to which a tool such as a drill is attached as a rotating part. A vehicle may include, for example, the rotating shaft of a wheel as a rotating part. The monitored device 10 may be any device other than those described above. Any device that includes a rotating shaft and bearings (regardless of type, such as ball bearings or roller bearings) may qualify as the monitored device 10.
[0015] The control device 11 is a device that controls the operation of the monitored device 10. For example, SCADA (Supervisory Control And Data Acquisition), a remote monitoring and control system for wind power generation equipment, PLC (Programmable Logic Controller) for controlling machine tools, and ECU (Electronic Control Unit) in vehicles may all be considered control devices 11.
[0016] Sensor 12 is a sensor for monitoring the state of the device 10 to be monitored. For example, vibration sensors, acoustic sensors, AE sensors, displacement sensors, proximity sensors, temperature sensors, current sensors, torque sensors, etc., may be considered as sensors 12.
[0017] The status monitoring device 20 is a system that acquires or measures signals from the sensor 12 and the control device 11, and processes and analyzes them to estimate, diagnose, and detect the status of the monitored device 10. Furthermore, the monitored device 10 may be controlled based on the results of this processing, analysis, estimation, diagnosis, and detection.
[0018] The display / server 30 stores and displays data acquired or measured by the status monitoring device 20, as well as the results of processing, analyzing, estimating, diagnosing, and detecting the data.
[0019] The status monitoring device 20 includes a receiving unit 21, an interface (I / F) unit 22, a CPU (Central Processing Unit) 23, a storage device 24, and a transmitting unit 25. The storage device 24 includes ROM (Read Only Memory), RAM (Random Access Memory), a hard disk, etc.
[0020] The CPU 23 is an arithmetic unit that implements a state monitoring method, which will be described in detail later, by executing various programs stored in the ROM of the storage device 24. The RAM of the storage device 24 is used as a work area by the CPU 23. The ROM of the storage device 24 records a program that includes each step of the flowchart (described later) showing the procedure of the state monitoring method. The receiving unit 21 is a device for reading data from the control device 11. The transmitting unit 25 is a device for outputting the calculation results from the CPU 23.
[0021] Figure 2 is a flowchart illustrating the data processing performed by the status monitoring device 20.
[0022] First, in step S1, the status monitoring device 20 performs data measurement processing. In the data measurement processing, the CPU 23 acquires data from the sensor 12 and the control device 11 via the receiving unit 21, which includes signals indicating operating information and information detected by the sensor. The CPU 23 may continuously send the acquired data to step S2, or it may temporarily store the acquired data in a sufficiently large buffer memory (ring buffer) included in the storage device 24 and send it to step S2 as needed or requested. Alternatively, the CPU 23 may temporarily store the acquired data in the storage device 24 or server 30, and read it from the storage device 24 or server 30 and send it to step S2 as needed or requested.
[0023] Next, in step S2, the state monitoring device 20 performs data selection processing. The CPU 23 determines whether the acquired data is from a period in which the rotational speed fluctuation exceeds a standard (hereinafter referred to as the rotational speed fluctuation period), and selects or extracts the data from the acquired data for the rotational speed fluctuation period and sends it to step S3. The rotational speed included in the data may be the rotational speed directly measured by a speed sensor, proximity sensor, etc., or it may be the rotational speed acquired or estimated from the control signal of the monitored device 10, or it may be the rotational speed estimated from an acceleration signal, current signal, etc.
[0024] Next, in step S3, the status monitoring device 20 performs rotational speed tracking processing. Rotational speed tracking processing is a process that removes the effects of fluctuations in rotational speed, and is a process that resamples data acquired at normal fixed time intervals to time intervals corresponding to the rotational speed (or rotational angle). For example, as rotational speed tracking processing, the resampling processing described in Japanese Patent Publication No. 6665062 (Patent Document 2) can be used. However, this method is not limited to this method, and other resampling processing may be applied to rotational speed tracking processing.
[0025] Finally, in step S4, the condition monitoring device 20 performs analysis and diagnosis processing. In the analysis and diagnosis processing, the CPU 23 analyzes, diagnoses, and detects the state of the monitored device based on data from which the effects of rotational speed fluctuations have been reduced by the rotational speed tracking processing.
[0026] In the data processing described above, data for the rotational fluctuation period is selected in step S2. For example, there are six methods for determining whether the "rotational speed fluctuation exceeds the standard."
[0027] The first method is a determination method based on the difference between the minimum and maximum values of the rotational speed. The second method is a determination based on an evaluation value (such as the standard deviation) that indicates the variation in rotational speed. The third method is a determination based on the minimum and maximum values of the rotational speed. The fourth method is a determination based on the cumulative value of the derivative of the rotational speed. The fifth method is a determination based on the number of regions that the rotational speed has passed through, etc. The sixth method is a determination based on the value of the rotational speed after filtering. These determinations will be explained in order below.
[0028] [1. Judgment based on the difference between the minimum and maximum values of rotational speed] Figure 3 is a waveform diagram illustrating the first method for determining rotational fluctuations. Figure 4 is a waveform diagram showing the judgment result based on the first method for determining rotational fluctuations.
[0029] In Figure 3, waveform W1 shows the change in rotational speed (rpm) of the rotating part observed by the sensor. Waveform W2 shows the speed change range (rpm), which is the difference between the maximum and minimum values of the rotational speed over a certain period. For example, if the time from time t2 to t3 is a certain period Δt, the maximum value of the rotational speed during this period is 1970 rpm and the minimum value is 1811 rpm. Therefore, the speed change range (rpm) at time t2 is the difference between 1970 - 1811 = 159. In other words, if the value of the speed change range (rpm) at time t is W2(t), then W2(t) is the maximum - minimum value of the rotational speed from time t until a certain period Δt has elapsed. Waveform W2 shows the results of performing the above calculation continuously for times t1 to t5.
[0030] Figure 4 shows how a threshold is set for waveform W2, and when the threshold is exceeded, it is determined that the rotational speed fluctuation exceeds a standard during the period Δt from the time when the threshold is exceeded. If waveform W2(t1s) exceeds the threshold at time t1s, data is selected as the rotational fluctuation period for a certain period Δt from time t1s, and the selected data is used for subsequent processing. Similarly, if waveform W2(t4s) exceeds the threshold at time t4s, data is selected as the rotational fluctuation period for a certain period Δt from time t4s, and the selected data is used for subsequent processing.
[0031] Furthermore, to simplify post-processing, data may be selected only up to Δt from the point when waveform W2 exceeds the threshold, thereby reducing overlap in selected time periods. However, if overlap in selected time periods is acceptable, data may be selected from the point when waveform W2 exceeds the threshold, up to Δt.
[0032] Furthermore, while a fixed time interval Δt was used as the unit of the judgment interval, a fixed rotational speed ΔN may be used instead of a fixed time interval Δt. Also, while the difference between the maximum and minimum values of the rotational speed in the judgment interval was used as the judgment target, the difference between the maximum and minimum values obtained by performing calculations such as squaring on the rotational speed may also be used as the judgment target. Alternatively, instead of the difference between these maximum and minimum values, the value obtained by performing calculations such as squaring on the difference may be used as the judgment target. When any of the above judgment targets exceed a predetermined threshold, it can be determined that the fluctuation in rotational speed exceeds the standard.
[0033] [2. Judgment based on evaluation values (standard deviation, etc.) indicating rotational speed variation] Figure 5 is a waveform diagram for explaining the second method of determining rotational fluctuations. Figure 6 is a waveform diagram showing the judgment result using the second method of determining rotational fluctuations.
[0034] In Figure 5, waveform W11 shows the change in rotational speed (rpm) of the rotating part observed by the sensor. Waveform W12 shows the standard deviation value, which indicates the variation in rotational speed over a certain period. The standard deviation s is given by s = √(Σ(xi - xm)) ２ This is expressed as follows: Here, if n is the number of data points included in a certain period, then xi = x1, ..., xn, and xm represents the average value. For example, if the time from time t12 to t13 is a certain period Δt, then the standard deviation s, which indicates the variation in rotational speed within this period, is 44.2. In other words, if the value of the velocity standard deviation s at time t is W12(t), then W12(t) is the standard deviation s of the rotational speed from time t until a certain period Δt has elapsed. Waveform W2 shows the results of performing the above calculation continuously from time t11 to t15.
[0035] Figure 6 shows how a threshold is set for waveform W12, and it is determined that the rotational speed fluctuation exceeds a standard during the period Δt from the time when the threshold is exceeded. At time t12s, if waveform W12(t12s) exceeds the threshold, data is selected as the rotational fluctuation period for a certain period Δt from time t12s, and the selected data is used for subsequent processing. Similarly, at time t14s, if waveform W12(t14s) exceeds the threshold, data is selected as the rotational fluctuation period for a certain period Δt from time t14s, and the selected data is used for subsequent processing.
[0036] Furthermore, to simplify post-processing, data may be selected only up to Δt from the point when waveform W12 exceeds the threshold, thereby reducing the overlap of selected time periods. However, if overlapping of selected time periods is acceptable, data may be selected from the point when waveform W12 exceeds the threshold, up to Δt.
[0037] Furthermore, while a fixed time interval Δt was used as the unit of the judgment interval, a fixed rotational speed ΔN may be used instead of a fixed time interval Δt. Also, while the standard deviation s of the rotational speed in the judgment interval was used as the judgment target, other evaluation values that indicate the variation in rotational speed in the relevant interval, such as a value obtained by performing calculations such as squaring the rotational speed, may also be used as the judgment target. When any of the above judgment targets exceed a predetermined threshold, it can be determined that the variation in rotational speed exceeds the standard.
[0038] [3. Judgment based on minimum and maximum rotational speed] Figure 7 is a waveform diagram illustrating the third method for determining rotational fluctuations. Figure 8 is a waveform diagram showing the judgment result based on the third method for determining rotational fluctuations.
[0039] In Figure 7, waveform W21 shows the change in rotational speed (rpm) of the rotating part observed by the sensor. Waveform W22 shows the result of determining whether there was a portion of the period in which the rotational speed exceeded the upper limit (True) or whether there was no portion in which the rotational speed exceeded the upper limit (False). Waveform W23 shows the result of determining whether there was a portion of the period in which the rotational speed fell below the lower limit (True) or whether there was no portion in which the rotational speed fell below the lower limit (False). Waveform W24 shows the result of AND processing of waveforms W22 and W23.
[0040] For example, if we define the period Δt as a fixed time interval from time t22 to t23, then during this period, the waveform W21 falls between the upper and lower limits, and the upper limit determination result is False, as is the lower limit determination result. Therefore, both the upper and lower limit determination results at t22 are False, and the result of their AND operation is also False.
[0041] Figure 8 shows how the system determines that the rotational speed fluctuation exceeds a certain threshold based on the waveform W24 determination result. When the waveform W24 changes from False to True at time t22s, data is selected as the rotational fluctuation period for a certain period Δt from time t22s, and this selected data is used in subsequent processing. Similarly, when the waveform W24 changes from False to True at time t24s, data is selected as the rotational fluctuation period for a certain period Δt from time t24s, and this selected data is used in subsequent processing.
[0042] In the above waveforms, at the time when the waveform W22 indicating the upper limit value determination result switches from False to True (rising point), the rotational speed after a certain period Δt exceeds the upper limit value. Among the changing points of the waveform W23 indicating the lower limit value determination result, at the rising point, the rotational speed after a certain period Δt is below the lower limit value. On the other hand, among the changing points of the waveform W23, at the falling point, the rotational speed at the left end (simultaneous with the falling) of a certain period Δt exceeds the lower limit value, and there is no part that falls below the lower limit value during the certain period Δt. In other words, when the value of the rotational speed is observed to be 2 or more during a certain period Δt starting from a certain time, the observed rotational speed values include the first rotational speed value and the second rotational speed value, the first rotational speed value exceeds the upper limit value, and the second rotational speed value is below the lower limit value, the certain period Δt is selected as the rotational fluctuation period.
[0043] For the ease of post-processing, data may be selected for Δt starting from the time when the waveform W24 changes from False to True so that the overlap of the selected time zones is reduced. However, if the selected time zones may overlap, when the waveform W24 is True, Δt may be selected starting from that time.
[0044] Also, although a certain time Δt is used as the unit of the determination section, a certain number of rotations ΔN may be used as the unit of the determination section instead of a certain time Δt. Also, although the determination target is whether the rotational speed in the determination section exceeds the upper limit value or is below the lower limit value, the same determination may be made with the value obtained by performing arithmetic processing such as squaring on the rotational speed as the determination target. When any of the above determination targets exceeds a preset threshold value, it can be determined that the fluctuation of the rotational speed exceeds the standard.
[0045] [4. Determination Based on the Integrated Value of the Differential Value of the Rotational Speed] Fig. 9 is a waveform diagram for explaining the fourth determination method of rotational fluctuation. Fig. 10 is a waveform diagram showing the determination result by the fourth determination method of rotational fluctuation.
[0046] In FIG. 9, waveform W31 shows the change in the rotational speed (rpm) of the rotating part observed by the sensor. Waveform W32 shows the value obtained by squaring the differential value of the rotational speed over a certain period Δt. Waveform W33 shows the value obtained by integrating the value of waveform W32 over a certain period Δt. For example, the value of waveform W33 at t32 is the value obtained by integrating the value of waveform W32 during a certain period Δt from time t32 to t33. Waveform W33 shows the result of continuously performing the above calculation for times t31 to t35.
[0047] In FIG. 10, a threshold is set for waveform W33, and it shows the state where it is determined that the fluctuation of the rotational speed exceeds the standard during the period of Δt from the time when the threshold is exceeded. At time t32s, when waveform W33(t32s) exceeds the threshold, data for a certain period Δt from time t32s is selected as the rotation fluctuation period, and the selected data is used for subsequent processing. Similarly, at time t34s, when waveform W33(t34s) exceeds the threshold, data for a certain period Δt from time t34s is selected as the rotation fluctuation period, and the selected data is used for subsequent processing.
[0048] For the ease of post-processing, data may be selected only for Δt from the time when waveform W33 exceeds the threshold so that the overlap of the selected time zones is reduced. However, if the selected time zones may overlap, data for Δt may be selected from the time when waveform W33 exceeds the threshold.
[0049] Also, although a certain time Δt is used as the unit of the determination section, a certain number of rotations ΔN may be used as the unit of the determination section instead of a certain time Δt. Also, although the square of the differential value of the rotational speed in the determination section is the determination target, the differential value of the rotational speed itself or the value obtained by integrating a value obtained by an arithmetic operation other than squaring may be used as the determination target. When any of the above determination targets exceeds a preset threshold, it can be determined that the fluctuation of the rotational speed exceeds the standard.
[0050] [5. Determination based on the number of regions through which the rotational speed has passed, etc.] Figure 11 is a waveform diagram illustrating the fifth method for determining rotational fluctuations. Figure 12 is a waveform diagram showing the determination result according to the fifth method for determining rotational fluctuations.
[0051] In Figure 11, waveform W41 shows the change in rotational speed (rpm) of the rotating part observed by the sensor. The rotational speed range is divided into 100 rpm intervals by the boundaries shown Lv. 0 to Lv. 5. Points P1 to P14 that pass through the boundaries are shown on waveform W41.
[0052] Waveform W42 shows the number of times the rotation speed transitions from one divided region to an adjacent region during a certain period Δt. This number indicates how many points P1 to P14 are included during that period Δt. For example, as shown in Figure 11, if the period Δt is t42 to t43, then the period Δt includes two points, P4 and P5. Therefore, at time t42, the waveform W42 shows a level change count N=2. If the period Δt is shifted slightly backward, the period Δt will include three points, P4, P5, and P6. Therefore, the waveform W42 changes from a level change count N=2 to N=3 a little after time t42. Waveform W42 shows the results of continuously performing the above counting process from time t41 to t45.
[0053] Figure 12 shows how a threshold is set for waveform W42, and it is determined that the rotational speed fluctuation exceeds a standard during the period Δt from the time when the threshold is exceeded. At time t42s, if waveform W42(t42s) exceeds the threshold, data is selected as the rotational fluctuation period for a certain period Δt from time t42s, and the selected data is used for subsequent processing. Similarly, at time t44s, if waveform W42(t44s) exceeds the threshold, data is selected as the rotational fluctuation period for a certain period Δt from time t44s, and the selected data is used for subsequent processing.
[0054] Furthermore, to simplify post-processing, data may be selected only up to Δt from the point when waveform W42 exceeds the threshold, thereby reducing the overlap of selected time periods. However, if overlapping of selected time periods is acceptable, data may be selected from the point when waveform W42 exceeds the threshold, up to Δt.
[0055] Furthermore, while the number of transitions from one region to another within a certain period of time was used as the unit for determination, the number of regions traversed may also be used as the unit for determination. Also, while a certain period of time Δt was used as the unit for the determination interval, a certain number of rotations ΔN may be used instead of a certain period of time Δt as the unit for the determination interval. When counting the number of times moving between regions, an unconventional counting method may be adopted, such as not counting movement to adjacent regions. When any of the above determination targets exceed a predetermined threshold, it can be determined that the change in rotational speed exceeds the standard.
[0056] [6. Judgment based on filtered values of rotational speed] Figure 13 is a waveform diagram illustrating the sixth method for determining rotational fluctuations. Figure 14 is a waveform diagram showing the judgment result according to the sixth method for determining rotational fluctuations.
[0057] In Figure 13, waveform W51 shows the change in rotational speed (rpm) of the rotating part observed by the sensor. Waveform W52 shows the result of applying a high-pass filter to the rotational speed signal.
[0058] Waveform W53 shows the value obtained by calculating the root mean square (RMS) of the value of waveform W52 over a certain period Δt. For example, the value of waveform W53 at t52 is the RMS of the value of waveform W52 over a certain period Δt from time t52 to t53. Waveform W53 shows the results of performing the above calculation continuously from time t51 to t55.
[0059] Figure 14 shows how a threshold is set for waveform W53, and it is determined that the rotational speed fluctuation exceeds a standard during the period Δt from the time when the threshold is exceeded. At time t52s, if waveform W53 (t52s) exceeds the threshold, data for a certain period Δt from time t52s is selected as the rotational fluctuation period, and this data is used in subsequent processing. Similarly, at time t54s, if waveform W53 (t54s) exceeds the threshold, data for a certain period Δt from time t54s is selected as the rotational fluctuation period, and this data is used in subsequent processing.
[0060] Furthermore, to simplify post-processing, data may be selected only up to Δt from the point when waveform W53 exceeds the threshold, thereby reducing overlap in selected time periods. However, if overlap in selected time periods is acceptable, data may be selected from the point when waveform W53 exceeds the threshold, up to Δt.
[0061] Furthermore, while a fixed time interval Δt was used as the unit of the judgment interval, a fixed rotational speed ΔN may be used instead of a fixed time interval Δt. Also, while the RMS value was calculated from the value after high-pass filtering, it may be calculated from the value after other filtering processes such as band-pass filtering. Filtering may be performed using digital filters such as FIR or IIR, or analog filters such as switched-capacitor or RC filters. In addition, while the RMS value of the rotational speed after filtering in the judgment interval was used as the judgment target, a value that evaluates the magnitude of the fluctuating value, such as the sum of squares, may be used as the judgment target instead of the RMS value. When any of the above judgment targets exceed a preset threshold, it can be determined that the fluctuation in rotational speed exceeds the standard.
[0062] Furthermore, if we define the data length (such as frequency analysis) used in step S4 of Figure 2 as the "window length," then in the filtering process, it is desirable to attenuate frequency components below eight times the window length, or at least avoid emphasizing them. This is because extremely low-frequency components interfere with this judgment method. For example, if RMS is used as the evaluation value, a large amount of low-frequency components will cause the RMS to constantly exceed the threshold, making judgment impossible.
[0063] [Method for selecting data during the rotational speed fluctuation period] The above explains how to determine whether the rotational speed fluctuation exceeds the standard. Now, we will explain how to select the data determined by this method.
[0064] [Selection Method 1] When continuous or sufficiently long measurement data is available, the following describes a method of processing the data in short data intervals relative to the length of the data to be analyzed. Note that Selection Method 1 includes so-called real-time measurement. Also, Selection Method 1 includes cases where the data is separated but there is no dead time between the data.
[0065] A portion of the measurement data is extracted, and it is determined whether the data in that extracted portion is exhibiting rotational fluctuations. For the determination method, any one of the six methods described in Figures 3 to 14 can be used. The data extraction interval is sequentially slid in the time direction, and the measurement data from the interval determined to exhibit rotational fluctuations is extracted as data for analysis (data selection in S2).
[0066] Furthermore, an upper limit, lower limit, or both of the data length to be extracted may be determined based on time or rotation speed. If an upper limit is set, data exceeding the upper limit will be discarded or separated into other data. If a lower limit is set, data below the lower limit will be discarded.
[0067] Furthermore, some of the extracted data may include data in which the rotational speed fluctuation is determined not to exceed a certain threshold. For example, a section in which the rotational speed fluctuation is determined not to exceed a certain threshold may be included in the section in which the rotational speed fluctuation is determined to exceed a certain threshold. Also, sections in which the rotational speed fluctuation is determined not to exceed a certain threshold may be included before and after the section in which the rotational speed fluctuation is determined to exceed a certain threshold.
[0068] [Selection Method 2] For all or part of one of the pre-divided measurement data, one of the six methods described in Figures 3 to 14 is used to determine whether the rotational speed fluctuation exceeds the standard. If it is determined that the rotational speed fluctuation exceeds the standard, all or part of that divided data is extracted as data for analysis (data selection in S2).
[0069] [Derivations of the above two selection methods] Alternatively, the data extracted for analysis using selection method 1 or selection method 2 may be ranked according to the values used for evaluation, and data within a certain range of ranks may be ultimately extracted (selected). Furthermore, weighting may be applied to the ranking based on data length or data volume. Furthermore, weighting may be applied to the ranking based on the evaluation values of data that are close in time.
[0070] Once data has been extracted that has been determined to exceed a certain threshold for rotational speed fluctuation, it is acceptable to refrain from extracting further data for a certain period of time. For example, in selection method 1, if the period is set to be the same as or longer than Δt as shown in Figure 3, it is possible to avoid selecting data at overlapping time points.
[0071] This embodiment explains the effects of selecting data for the rotational fluctuation period using the condition monitoring device.
[0072] Figure 15 is a graph showing the spectrum when frequency analysis is performed without partial data selection. Figure 16 is a graph showing the spectrum when frequency analysis is performed by selecting data from the rotational fluctuation period.
[0073] In Figure 15, six peaks are observed in the vibration of the rotating part: X1-X3 and Y1-Y3. Here, X1-X3 are rotation-synchronous components and represent peaks that may be characteristic frequency peaks indicating damage. On the other hand, Y1-Y3 are non-rotation-synchronous components and represent peaks that do not have the potential to be characteristic frequency peaks indicating damage.
[0074] In Figure 16, as a result of resampling that takes rotational speed into account, the rotational synchronous components, peaks X1 to X3, become sharper, while the non-rotational synchronous components, Y1 to Y3, become less sharp. Therefore, it becomes easier to separate the rotational synchronous components from other components (such as power supply noise), facilitating early detection of damage to rotating parts.
[0075] As described above, in this embodiment, data during the rotational fluctuation period is selectively acquired. When rotational tracking processing is applied to the measurement data during the rotational fluctuation period, in frequency analysis, peaks originating from parts other than the rotating part are dulled, while peaks originating from the rotating part are emphasized. This makes it possible to distinguish between vibrations from the rotating part and other vibrations, thereby improving diagnostic accuracy. By specifically measuring data during the rotational fluctuation period, the effect of improving diagnostic accuracy through rotational tracking processing can be maximized.
[0076] [Note] The exemplary embodiments described above will be understood by those skilled in the art to be specific examples of the following embodiments.
[0077] (1) This disclosure relates to a condition monitoring device 20 for monitoring the state of a device 10 having a rotating part. The condition monitoring device 20 shown in Figure 1 includes a receiving unit 21 that receives sensor signals from a sensor 12 that monitors the state of the device 10 and speed signals indicating the rotational speed of the rotating part, a storage device 24 that stores measurement data including sensor information and speed information corresponding to the sensor signals and speed signals received by the receiving unit 21, respectively, and a computing device (CPU) 23 that analyzes the measurement data. The computing device 23 is configured to extract data from the measurement data that includes a section in which the fluctuation of the rotational speed exceeds a standard, and to perform tracking processing that analyzes the sensor information in the extracted data in accordance with the change in rotational speed.
[0078] (2) In the state monitoring device 20 described in (1), the calculation device 23 determines whether the fluctuation in rotational speed exceeds a standard over a certain period of time or over an elapsed period of time, as shown in Figures 3 and 4, by using the difference between the maximum and minimum values obtained from the rotational speed over a certain period of time or over an elapsed period of time while the rotating part rotates for a certain number of rotations.
[0079] (3) In the condition monitoring device 20 described in (1), the calculation device 23 determines whether the fluctuation in rotational speed exceeds a standard over a certain period of time or over an elapsed period of time, as shown in Figures 5 and 6, by using an evaluation value (such as a standard deviation) that shows the variation in the value obtained from the rotational speed over a certain period of time or over an elapsed period of time while the rotating part rotates for a certain number of rotations.
[0080] (4) In the state monitoring device 20 described in (1), the calculation device 23 determines whether the fluctuation of the rotation speed exceeds a standard over a certain period of time or over an elapsed period of time, as shown in Figures 7 and 8, by determining whether the value obtained from the rotation speed over a certain period of time or over an elapsed period of time while the rotating part rotates for a certain number of rotations includes a value that is below a predetermined lower limit and also includes a value that is above a predetermined upper limit.
[0081] (5) In the state monitoring device 20 described in (1), the calculation device 23 determines whether the fluctuation in rotational speed exceeds a standard over a certain period of time or over an elapsed period of time, using the integral value obtained from the differential value of the rotational speed over a certain period of time or over an elapsed period of time while the rotating part rotates for a certain number of rotations, as shown in Figures 9 and 10.
[0082] (6) In the state monitoring device 20 described in (1), the range of rotational speeds that the speed information can indicate is divided in advance into a plurality of rotational speed regions, and the calculation device 23 is configured to determine which of the plurality of rotational speed regions the rotational speed of the rotating part belongs to, as shown in Figures 11 and 12, and the calculation device 23 determines whether the fluctuation of the rotational speed exceeds a standard during a certain period of time or during the elapsed time while the rotating part rotates for a certain number of rotations, using the number of times the rotational speed has transitioned between the plurality of rotational speed regions or the number of regions that the rotational speed has passed through among the plurality of rotational speed regions.
[0083] (7) In the state monitoring device 20 described in (1), the calculation device 23 determines whether the fluctuation in rotational speed exceeds a standard over a certain period of time or over an elapsed period of time, as shown in Figures 13 and 14, by using an evaluation value which is obtained by evaluating the magnitude of the value after filtering the rotational speed over a certain period of time or over an elapsed period of time during which the rotating part rotates for a certain number of rotations. The filtering process includes a process that emphasizes or attenuates some frequency components.
[0084] (8) In other aspects, the present disclosure relates to a state monitoring method for monitoring the state of a device to be monitored 10 having a rotating part. The state monitoring method comprises the steps of: receiving a sensor signal from a sensor 12 that monitors the state of the device to be monitored 10 and a speed signal indicating the rotational speed of the rotating part; storing measurement data including sensor information and speed information corresponding to the received sensor signal and speed signal, respectively (S1); extracting data from the measurement data that includes a section in which the fluctuation of the rotational speed exceeds a standard (S2); and performing a tracking process (S3) that analyzes the sensor information in the extracted data in accordance with the change in rotational speed.
[0085] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of the present invention is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope of the claims are intended to be included.
[0086] 10. Device to be monitored, 11. Control device, 12. Sensor, 20. Status monitoring device, 21. Receiving unit, 22. I / F unit, 23. Processing unit, 24. Storage device, 25. Transmitter, 30. Display / server.
Claims
1. A condition monitoring device for monitoring the state of a device having a rotating part, comprising: a receiving unit that receives a sensor signal from a sensor that monitors the state of the device and a speed signal indicating the rotational speed of the rotating part; a storage device that stores measurement data including sensor information and speed information corresponding to the sensor signal and speed signal received by the receiving unit, respectively; and a computing device that analyzes the measurement data, wherein the computing device is configured to extract data from the measurement data that includes a section in which the fluctuation of the rotational speed exceeds a standard, and to perform tracking processing that analyzes the sensor information in the extracted data in accordance with the change in rotational speed.
2. The state monitoring device according to claim 1, wherein the calculation device determines whether the fluctuation in rotational speed exceeds a standard during the elapsed time while the rotating part rotates for a certain period of time or a certain number of rotations, by using the difference between the maximum and minimum values obtained from the rotational speed during the elapsed time or while the rotating part rotates for a certain number of rotations.
3. The state monitoring device according to claim 1, wherein the calculation device determines whether the fluctuation in rotational speed exceeds a standard during the elapsed time while the rotating part rotates for a certain period of time or a certain number of rotations, using an evaluation value that shows the variation in the value obtained from the rotational speed during the elapsed time while the rotating part rotates for a certain period of time or a certain number of rotations.
4. The state monitoring device according to claim 1, wherein the calculation device determines whether the fluctuation in rotational speed during the certain period of time or the elapsed time during which the rotating part rotates for a certain number of rotations exceeds a standard, based on whether the value obtained from the rotational speed during the elapsed time includes a value below a predetermined lower limit and a value above a predetermined upper limit.
5. The state monitoring device according to claim 1, wherein the calculation device determines whether the fluctuation in rotational speed exceeds a standard during the elapsed time while the rotating part rotates for a certain period of time or a certain number of rotations, by using the integrated value of the derivative of the rotational speed during the elapsed time while the rotating part rotates for a certain period of time or a certain number of rotations.
6. The state monitoring device according to claim 1, wherein the range of rotational speeds that the speed information can indicate is divided in advance into a plurality of rotational speed regions, the calculation device is configured to determine which of the plurality of rotational speed regions the rotational speed of the rotating part belongs to, and the calculation device determines whether the fluctuation of the rotational speed exceeds a standard during a certain period of time or during the elapsed time while the rotating part rotates for a certain number of rotations, using the number of times the rotational speed transitions between the plurality of rotational speed regions or the number of regions the rotational speed passes through during the plurality of rotational speed regions.
7. The state monitoring device according to claim 1, wherein the calculation device determines whether the fluctuation in rotational speed exceeds a standard during the elapsed time, which is the time during which the rotating part rotates for a certain period of time or a certain number of rotations, by using an evaluation value which is obtained by evaluating the magnitude of the value after filtering the rotational speed during the elapsed time, and the filtering includes a process that emphasizes or attenuates some frequency components.
8. A condition monitoring method for monitoring the state of a device having a rotating part, comprising: receiving a sensor signal from a sensor that monitors the state of the device and a speed signal indicating the rotational speed of the rotating part; storing measurement data including sensor information and speed information corresponding to the received sensor signal and speed signal, respectively; extracting data from the measurement data that includes a section in which the fluctuation of the rotational speed exceeds a standard; and performing a tracking process that analyzes the sensor information in the extracted data in accordance with the change in rotational speed.