Condition Monitoring System

Abstract

The state monitoring system (500) includes a monitoring terminal (202), acceleration sensors (71-73) and a data processing device (80). The data processing device (80) calculates a diagnostic parameter (R) based on data measured by the acceleration sensors (71-73), determines the degree of damage of a bearing or a gear included in a wind power generation device (10) based on the diagnostic parameter (R), and controls the monitoring terminal (202) to display information indicating the degree of suppression of the generated power of the wind power generation device (10) corresponding to the degree of damage to the bearing or the gear.

Description

Technical Field

[0001] The present invention relates to a state monitoring system, in particular to a state monitoring system for a power generation device. Background Art

[0002] As an environmentally friendly power generation device, wind power generation devices have attracted attention. In a wind power generation device, blades that convert wind energy into rotational force and a nacelle that stores a conversion device that converts the rotational force into electrical energy are arranged at a high position (e.g., several tens of meters above the ground) on a support column. In each wind power generation device, the status of the wind power generation device is monitored using data collected from various sensors. The status is often monitored from a remote location through a communication line or the like.

[0003] Japanese Patent Laid-Open No. 2009-287564 (Patent Document 1), Japanese Patent Laid-Open No. 2013-185507 (Patent Document 2), and Japanese Patent Laid-Open No. 2018-060387 (Patent Document 3) each discloses an example of a state monitoring system for a wind turbine generator.

[0004] Prior art

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Laid-Open No. 2009-287564

[0007] Patent Document 2: Japanese Patent Laid-Open No. 2013-185507

[0008] Patent Document 3: Japanese Patent Laid-Open No. 2018-060387

[0009] Patent Document 4: Japanese Patent No. 3882328 Summary of the invention

[0010] Technical problem to be solved by the invention

[0011] According to the technology described in Japanese Patent Laid-Open No. 2009-287564 (Patent Document 1), the output of a wind turbine generator is controlled according to the environmental conditions around the wind turbine generator. However, damage to the rotating machinery (gearbox, etc.) included in the wind turbine generator is not considered as a factor in output control.

[0012] When there is a question of damage to the rotating machinery (gearbox, etc.) included in the wind power generation device, the machinery needs to be replaced or repaired. During the work to do so, the operation of the generator is stopped and power generation cannot be achieved. As a result, the profits of the power generation company will be damaged.

[0013] When the operation continues with damaged rotating machinery, the damage will progress and a sudden failure will occur, and the generator will have to be stopped. In this case, the maintenance plan will be made and the replacement equipment will be arranged after the generator is stopped, so the downtime will be longer.

[0014] In order to solve the above problem, power generation companies sometimes decide to continue operating the generator with the output lower than the rated value. If the output is suppressed, the speed is lower than when running at the rated value, and the progress of damage becomes slower than when running at the rated value. Therefore, it is possible to generate electricity while suppressing the progress of damage.

[0015] When the machine is operated with the output suppressed as described above, the time and degree to suppress the output are determined manually based on abnormal sounds from the equipment or metal wear debris contained in the grease or lubricating oil. Since the control is determined manually, it may be inappropriate. For example, the machine may be operated at an output higher than the optimal output, or conversely, at a lower output.

[0016] Output is sometimes controlled by a monitoring system (SCADA) installed in a wind turbine. However, the data collected by SCADA is related to operating conditions such as wind direction, wind volume, power generation, and rotation speed, but the vibration of the rotating machinery is not collected. Since the signs of damage to bearings or gears appear as high-frequency vibrations, it is difficult to use SCADA to achieve output control corresponding to the degree of damage to the rotating machinery.

[0017] The present invention has been made to solve the above-mentioned problems, and an object of the present invention is to provide a state monitoring system that provides a suppression amount according to the damage status of a power generation device.

[0018] Technical solutions adopted to solve technical problems

[0019] The present disclosure relates to a state monitoring system that monitors the state of a wind power generation device. The state monitoring system includes a monitoring terminal, an acceleration sensor, and a data processing device. The data processing device calculates diagnostic parameters based on data measured by the acceleration sensor, determines the degree of damage of a bearing or a gear included in the wind power generation device based on the diagnostic parameters, and controls the monitoring terminal to display information indicating the degree of suppression of the generated power of the wind power generation device corresponding to the degree of damage to the bearing or the gear.

[0020] Preferably, the data processing device includes a memory and a computing unit, the computing unit causing the memory to store the number of times the magnitude of the diagnostic parameter exceeds a first threshold value. Before the number of times reaches a preset first number, the computing unit does not cause the monitoring terminal to display information indicating the degree of suppression, and when the number of times is greater than or equal to the preset first number, the computing unit causes the monitoring terminal to display information indicating the degree of suppression.

[0021] More preferably, when the diagnosis parameter exceeds a second threshold value that is greater than the first threshold value, the calculation unit outputs a signal instructing the wind turbine generator to stop operating to a control device that controls the operation of the wind turbine generator.

[0022] Preferably, the data processing device determines an interval for calculating the rate of change of the diagnostic parameter over time based on the product of the rotation speed of the rotating element of the wind turbine generator and the power generation output. When the rate of change of the diagnostic parameter in the interval is higher than the rate of change of the diagnostic parameter in the previous interval, the data processing device calculates the suppression degree and controls the monitoring terminal to display the information reflecting the calculated suppression degree.

[0023] Preferably, when the magnitude of the diagnostic parameter exceeds a threshold value, the data processing device increases the measurement frequency of the acceleration sensor.

[0024] It is further preferred that the acceleration sensor includes a plurality of acceleration sensor elements. The data processing device calculates the diagnostic parameter for each data measured by each of the plurality of acceleration sensor elements. The data processing device increases the measurement frequency for the acceleration sensor element whose corresponding diagnostic parameter among the plurality of acceleration sensor elements exceeds the threshold value, and does not change the measurement frequency for the acceleration sensor element whose corresponding diagnostic parameter among the plurality of acceleration sensor elements does not exceed the threshold value.

[0025] It is further preferred that the acceleration sensor includes a plurality of acceleration sensor elements. The data processing device calculates the diagnostic parameter for each data measured by each of the plurality of acceleration sensor elements. When there is an acceleration sensor element among the plurality of acceleration sensor elements whose corresponding diagnostic parameter exceeds the threshold value, the data processing device increases the measurement frequency of the plurality of acceleration sensor elements.

[0026] Effects of the Invention

[0027] According to the present invention, a suppression amount corresponding to the damage condition of the power generation device is provided. Therefore, the suppression amount that suppresses the progress of the damage of the power generation device and allows the power generation company to continue operating until the maintenance time can be set without relying on the intuition of the operator of the power generation company, etc., and sudden failures can be avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a diagram schematically showing the structure of a wind turbine generator to which a state monitoring device according to an embodiment of the present invention is applied.

[0029] Figure 2 This is a functional block diagram showing the structure of the condition monitoring system.

[0030] Figure 3 This is a diagram for explaining a threshold value that is set when a root mean square value RMS is used as a diagnosis parameter R.

[0031] Figure 4 This is a flowchart for explaining the processing executed immediately after the state monitoring system is started in the first embodiment.

[0032] Figure 5 1 is a diagram showing the first half of a flowchart of the output suppression determination process executed in step S9.

[0033] Figure 6 1 is a diagram showing the second half of the flowchart of the output suppression determination process executed in step S9.

[0034] Figure 7 This is a diagram for explaining the integration of the load parameter P.

[0035] Figure 8 This is a diagram for explaining the calculation of the change rate of the diagnosis parameter R.

[0036] Fig. 9 This is a flowchart for explaining the processing executed immediately after the state monitoring system is started in the second embodiment.

[0037] Fig.10 It is used for Fig. 9 Flowchart for explaining the setting process of the additional measurement timing executed in step S104 in FIG.

[0038] Fig.11 This is a diagram for explaining the threshold value for setting the additional measurement timing.

[0039] Fig.12 This is a flowchart for explaining the setting process of the additional measurement timing executed in the modification of the second embodiment.

[0040] Fig.13This is a diagram for explaining an example of how to set the additional measurement timing.

[0041] Fig.14 This is a flowchart for explaining the processing executed immediately after the state monitoring system is started in the third embodiment.

[0042] Fig.15 It is used for Fig.14 Flowchart for explaining the setting process of the additional measurement timing executed in step S131 in FIG.

[0043] Fig.16 This is a flowchart for explaining the setting process of the additional measurement timing executed in the modification of the third embodiment. DETAILED DESCRIPTION

[0044] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. The same or corresponding elements in the following drawings have the same reference numerals and will not be described repeatedly.

[0045] [Implementation Method 1]

[0046] Figure 1 1 is a diagram schematically showing the structure of a wind turbine generator to which a state monitoring device according to an embodiment of the present invention is applied. Figure 1 As shown, the wind turbine generator 10 includes a main shaft 20, blades 30, a gear box 40, a generator 50, a control panel 52, a transmission line 54, and a main shaft bearing 60 (hereinafter referred to as "bearing").

[0047] The gearbox 40 , the generator 50 , the control panel 52 , and the bearing 60 are stored in a nacelle 90 , and the nacelle 90 is supported by a tower 100 .

[0048] The main shaft 20 is inserted into the nacelle 90, connected to the input shaft of the gear box 40, and rotatably supported by the bearing 60. The main shaft 20 transmits the rotation torque generated by the blades 30 receiving the wind force to the input shaft of the gear box 40. The blades 30 are arranged at the front end of the main shaft 20, convert the wind force into the rotation torque, and transmit the rotation torque to the main shaft 20.

[0049] The bearing 60 is fixed to the nacelle 90 and rotatably supports the main shaft 20. The bearing 60 is composed of a roller, such as a self-aligning rolling bearing, a tapered rolling bearing, a cylindrical rolling bearing, or a spherical bearing. These bearings can be single-row bearings or multi-row bearings.

[0050] The gearbox 40 is provided between the main shaft 20 and the generator 50, increases the rotation speed of the main shaft 20, and outputs the increased rotation speed to the generator 50. As an example, the gearbox 40 is composed of a gear speed-increasing structure including a planetary gear, an intermediate shaft, and a high-speed shaft. The generator 50 is connected to the output of the gearbox 40, and generates electricity using the rotation torque received from the gearbox 40. The generator 50 is composed of an induction generator, for example.

[0051] The control panel 52 includes an inverter (not shown) that converts the power generated by the generator 50 into a system voltage and frequency, and outputs the power to a transmission line 54 connected to the system.

[0052] In order to monitor the wind turbine generator 10 , a state monitoring system is provided in the wind turbine generator 10 .

[0053] Figure 2 This is a functional block diagram showing the structure of the condition monitoring system. Figure 1 and Figure 2 The state monitoring system 500 includes acceleration sensors 71-73, proximity sensors 74, current sensors 75, a data processing device 80 and a monitoring terminal 202. The acceleration sensors 71-73, proximity sensors 74, current sensors 75 and the data processing device 80 are stored in the cabin 90. These components can be connected to each other by wire or wirelessly.

[0054] The acceleration sensors 71 to 73 are respectively provided in rotating mechanisms such as the gear box 40, the generator 50 and the bearing 60 located in the nacelle 90 of the wind turbine generator 10, detect their vibrations and output the detected vibration values ​​to the data processing device 80. The acceleration sensors 71 to 73 are preferably provided at positions where the vibrations of the bearings or gears constituting each rotating mechanism can be detected.

[0055] The acceleration sensors 71 to 73 are used to detect damage to bearings or gears in a rotating mechanism, and therefore, are preferably sensors that can measure vibrations in a high frequency band (2 kHz to 10 kHz) that indicate signs of damage.

[0056] The proximity sensor 74 is used to measure the rotation speed of the wind turbine generator 10. It is desirable to provide the proximity sensor at a position where the rotation of the rotating shaft of the generator 50 can be measured. The proximity sensor 74 detects the period at which a protrusion or a hole such as a head of a bolt of the rotating shaft of the generator 50 approaches due to the rotation of the rotating shaft, thereby measuring the rotation speed of the wind turbine generator.

[0057] The current sensor 75 is provided in the nacelle 90 to detect the power generation output from the wind turbine generator 10 .

[0058] The data processing device 80 includes: filters 81~85, which receive outputs from acceleration sensors 71~73, proximity sensors 74 and current sensors 75 and remove noise therein; A / D converters 91~95, which convert the noise-removed signals into digital values; an operation unit (processor) 200; and a memory 201 as a storage unit.

[0059] The operation unit 200 performs measurements using each sensor periodically (for example, every 2 hours). For the data collected by the acceleration sensors 71 to 73, the operation unit 200 calculates a plurality of diagnostic parameters R corresponding to the sensors. The diagnostic parameter R is highly sensitive to the detection of damage to the bearing or gear. In order to set the same measurement conditions, the diagnostic parameter R is calculated only when the rotation speed and the power output exceed the set value.

[0060] For example, feature quantities such as the root mean square value RMS, the modulation value MOF, the peak value Peak, and the envelope spectrum peak value EnvPeak given by the following formula can be used as the diagnosis parameter R.

[0061]

[0062] Formula (1) represents the root mean square value RMS, where t represents time, T represents the calculation area of ​​t2-t1, and v(t) represents the time waveform.

[0063]

[0064] Formula (2) represents the modulation value MOF, where v AM (t) represents the envelope of the time waveform.

[0065] Peak=|v(t)|max···(3)

[0066] Formula (3) represents the peak value Peak.

[0067] EnvPeak=V AM (2πf)|max···(3)

[0068] Formula (4) represents the envelope spectrum peak value. In the formula, f represents the frequency, and VAM (2πf) represents the envelope spectrum. The envelope spectrum is represented by the following formula (5).

[0069]

[0070] The operation unit 200 is configured to cooperate with the power generation control device 300 that performs power generation control of the wind turbine generator 10. For example, when damage to the wind turbine generator 10 progresses, the operation unit 200 sends a stop signal to stop power generation to the power generation control device 300. The power generation control device 300 is a type of supervisory control and data acquisition system (SCADA).

[0071] Figure 3 is a diagram for explaining the threshold value set when the root mean square value RMS is used as the diagnostic parameter R. Figure 3 As shown, two thresholds are set for the diagnostic parameter R. The two thresholds may be set arbitrarily or may be generated based on measurement data of a certain period. For example, a threshold Rth1 (initial damage detection threshold) and a threshold Rth2 (usage limit threshold) are set.

[0072] The threshold value Rth1 is a threshold value for detecting initial damage. The threshold value Rth1 can be used to determine whether the damage degree of the bearing or gear is normal (no damage) or slight damage.

[0073] The threshold value Rth2 is a threshold value for detecting that the damage has progressed to such an extent that the bearing or gear needs to be replaced. The threshold value Rth2 is greater than the threshold value Rth1 for detecting the initial damage.

[0074] Figure 4 This is a flowchart for explaining the processing performed immediately after the state monitoring system is started in the first embodiment. Figure 2 and Figure 4 In step S1, the operation unit 200 initializes the count value m of the threshold exceeding counter to m=0. Next, in step S2, the operation unit 200 waits until a preset measurement period (e.g., 2 hours) has passed. In step S3, the operation unit 200 uses the acceleration sensors 71 to 73 to perform measurements. Then, in step S4, the operation unit calculates the diagnostic parameter R( Figure 3 Calculate the example).

[0075] Next, in step S5, the calculation unit 200 determines whether the number X1 of the diagnostic parameters R exceeding the threshold value Rth1 is equal to or greater than n1. Figure 1 In the example, 3 vibration sensors are provided, and therefore, the number of diagnostic parameters R is also 3. However, a greater number of vibration sensors may be provided. n1, which is a determination value, is an integer greater than 1, and n1 can be appropriately set according to the number of vibration sensors. When the relationship X1 ≥ n1 does not hold ("No" in step S5), the process returns to step S1. When the relationship X1 ≥ n1 holds ("Yes" in step S5), in step S6, the operation unit 200 determines whether the count value m of the threshold exceeding counter is greater than the set value.

[0076] If m is smaller than the set value (No in step S6), in step S7, the count value m is incremented by 1, and the processing after step S2 is executed again. Thus, even if the noise mixed in the measurement data exceeds the threshold temporarily, the output suppression determination processing in step S9 is not performed.

[0077] When at least a set number (n1) of diagnostic parameters R exceed the threshold value Rth1 for the number of consecutive set values ​​("Yes" in step S5 and "Yes" in step S6), in step S8, the operation unit 200 determines whether the use limit of the bearing or gear is exceeded. Specifically, the operation unit 200 determines whether the number of diagnostic parameters R exceeding the threshold value Rth2 is n2 or more.

[0078] When the number of diagnostic parameters R exceeding the threshold value Rth2 is less than n2 (No in S8), in step S9, the operation unit 200 performs output suppression determination processing and displays the recommended output suppression amount on the monitoring terminal 202. The operator determines the output of the generator with reference to the suppression amount displayed on the monitoring terminal 202 so that the operation of the generator continues. When the operation of the generator continues, the processing after step S2 is performed again.

[0079] When the number X2 of diagnostic parameters exceeding the threshold value Rth2 in step S8 is n2 or more, in step S10, the operation unit 200 determines that the time to replace the bearing or gear has arrived, and outputs an operation stop signal to the SCADA. Then, the control is terminated in step S11. Thus, when the degree of damage to the bearing or gear progresses to a degree exceeding the limit value when the operator is not present, for example, at night, the operation of the wind turbine generator can be automatically stopped. Damage requiring large-scale repairs can be avoided.

[0080] Figure 5 1 is a diagram showing the first half of a flowchart of the output suppression determination process executed in step S9. Figure 6 FIG. 1 is a diagram showing the second half of a flowchart of the output suppression determination process executed in step S9. Figure 5 , Figure 6 A flowchart is shown to show the recommended output.

[0081] In step S51, the operation unit 200 determines whether the output suppression judgment process is executed for the first time. When the output suppression judgment process is executed for the first time ("Yes" in S51), in step S52, the operation unit 200 sets the latest measurement date and time as the starting point of the integration interval. Then, in step S53, the operation unit 200 sets the recommended output presented to the operator to 100%, and proceeds to step S54. When there is a record that the output suppression judgment process has been executed ("No" in S51), the operation unit 200 does not execute the processing of steps S52 and S53, and the processing proceeds to step S54.

[0082] In step S54, the calculation unit 200 calculates the product of the rotation speed and the power generation output (load parameter). In step S55, the load parameter P is integrated with respect to time.

[0083] Figure 7 is a diagram for explaining the integration of the load parameter P. Figure 7 In the figure, the vertical axis represents the diagnostic parameter R and the load parameter P, and the horizontal axis represents the date and time. For example, each time the integral value S integrated starting from the time t1 when the initial damage threshold Rth1 is first exceeded exceeds the preset value S0, the change rate dR / dt (interval: the integral interval of the load parameter) of the diagnostic parameter R is calculated.

[0084] For example, when the integral value S=S1 at time t2, if the integral value exceeds the preset value S0, the change rate dR / dt is calculated at that time. When the integral value S=S2 at time t3 with time t2 as the next starting point, if the integral value exceeds the preset value S0, the change rate dR / dt is calculated again at that time.

[0085] Figure 8 1 is a diagram for explaining the calculation of the rate of change of the diagnostic parameter R. Figure 7 and Figure 8 , the rate of change dR1 / dT1 is calculated at time t2, and the rate of change dR2 / dT2 is calculated at time t3. Thus, each time the integral value S of the load parameter P exceeds the preset setting value S0 ("Yes" in step S56), the operation unit 200 sets the latest measurement time as the end point of the integral interval (step S57), draws an approximate straight line between the starting point and the end point, and calculates the rate of change dR / dt (interval: integral interval of the load parameter) of the diagnostic parameter R (step S58).

[0086] Next, in step S59, the operation unit 200 determines whether there is data on the rate of change of the previous diagnostic parameter R. If there is data on the rate of change of the previous diagnostic parameter R ("Yes" in S59), in step S60, the operation unit 200 determines whether the rate of change of the diagnostic parameter R is greater than the rate of change of the previous interval.

[0087] When there is no data on the last rate of change of the diagnostic parameter R in step S59, and when the rate of change of the diagnostic parameter R in step S60 is lower than the rate of change of the previous interval, in step S61, the operation unit 200 stores the calculated rate of change of the diagnostic parameter R in the memory 201, and in step S63, the operation unit 200 controls the monitoring terminal 202 to display the same recommended output as the last time as information indicating that the operating output will maintain the last state.

[0088] When the rate of change of the diagnostic parameter R is greater than the rate of change of the previous interval ("Yes" in S60), the operation unit 200 determines that the damage is progressing. In step S62, the operation unit 200 corrects the recommended output to 0.9 times the current setting value. In step S63, the operation unit 200 controls the monitoring terminal 202 to display the corrected recommended output as information that the operating output is suppressed. Note that 0.9 times is an example of suppression. In step S62, it is also possible to multiply by a number smaller than 1 other than 0.9, or divide by a specified power.

[0089] Figure 7 and Figure 8 An example is shown in which the load parameter P, which is the product of the rotation speed and the power generation amount, is calculated and the generated power is suppressed by using the magnitude of the rate of change. Figure 7 In the example, the measurement date and time t1 after the first implementation of the output suppression determination process is set as the “starting point”. Then, each time the output suppression determination process is executed, the integral value S of the load parameter P is calculated in the interval from the “starting point” to the latest measurement date and time.

[0090] When the integral value S1 of the load parameter P exceeds the set value S0 at time t2, the "starting point" of the integral interval is updated. Figure 7 In the calculation, the latest measurement date and time t2 when the integral value S1 exceeds the set value S0 is set as the new "starting point", and the calculation of the integral value S2 is started. The latest measurement date and time t3 when the integral value S2 exceeds the set value S0 is set as the new "starting point".

[0091] Then, the change rate dR / dt of the diagnostic parameter R in each integral interval is calculated. Figure 8 As shown, the rate of change of the diagnostic parameter R can be considered as the slope of the approximate straight line.

[0092] The calculated rate of change is compared to the rate of change calculated in the previous interval. Figure 8 The following shows a comparison between dR1 / dT1 calculated in the interval dT1 = t1 to t2 and dR2 / dT2 calculated in the interval dT2 = t2 to t3 .

[0093] When the change rate of the current interval is greater than the change rate of the previous interval, the operation unit 200 determines that the damage degree is progressing, and controls the monitoring terminal 202 to display information that suppresses output (recommended output). For example, the initial value of the recommended output is defined as 100%, and each time it is determined that the damage is progressing, the recommended output decreases by 10%. Figure 8 In the case where the relationship dR1 / dT1<dR2 / dT2 is satisfied, it is determined that the damage is progressing. At this time, the recommended output is set to 90% (=100%×0.9). Figure 7 At time t3, the operator suppresses the output to 90%, the power generation decreases, and the load parameter P also decreases by one level.

[0094] When the diagnostic parameter R of the set number (n2) or more exceeds the use limit threshold Rth2, it is determined that it is time to replace the bearing or gear, and the operation unit 200 outputs an operation stop signal to the SCADA 300. Therefore, even if the damage progresses without the operator monitoring, the wind turbine generator can be stopped before it is significantly damaged.

[0095] Refer again Figures 1 to 8 Implementation method 1 will be summarized.

[0096] The present disclosure relates to a state monitoring system that monitors the state of a wind turbine generator 10. The state monitoring system 500 includes a monitoring terminal 202, acceleration sensors 71 to 73, and a data processing device 80. The data processing device 80 calculates a diagnostic parameter R based on data measured by the acceleration sensors 71 to 73, determines the degree of damage of a bearing or a gear included in the wind turbine generator 10 based on the diagnostic parameter R, and controls the monitoring terminal 202 to display information indicating the degree of suppression of the power generated by the wind turbine generator 10 corresponding to the degree of damage to the bearing or the gear.

[0097] The degree of damage to the bearing or gear is determined based on the number of times m that the diagnostic parameter exceeds the threshold Rth1 and the rate of change of the diagnostic parameter. Figure 4 As shown in FIG. 1 , when the number m of times exceeding the threshold value Rth1 is greater than the set value, the data processing device 80 performs output suppression judgment processing. Figure 6When the change rate of the diagnostic parameter shown in step S60 increases compared with the previous change rate, it is determined that the degree of damage has progressed, and the recommended output is made lower than the current output.

[0098] According to the state monitoring system 500 of this embodiment, damage to the rotating machine can be suppressed and the wind turbine generator 10 can generate electricity. This can reduce the risk of a sudden major accident and shorten downtime compared to the case of continuous operation at rated output.

[0099] In Japan, the wind is strong in winter, and it is desirable to operate the wind turbines as much as possible. If the state monitoring system 500 of this embodiment is used, even for a wind turbine with suspected damage to the rotating machinery, the output can be suppressed to a level where the damage does not progress significantly. Therefore, the wind turbine can be operated at an appropriate time, which can benefit the power generation company.

[0100] Preferably, the data processing device 80 includes a memory 201 and a computing unit 200, and the computing unit 200 causes the memory to store the number of times m that the magnitude of the diagnostic parameter R exceeds the first threshold Rth1. Before the number of times m reaches a preset first number, the computing unit 200 does not cause the monitoring terminal to display information indicating the degree of suppression ("No" in S6), and when the number of times m is greater than or equal to the preset first number ("Yes" in S6), the computing unit 200 causes the monitoring terminal to display information indicating the degree of suppression.

[0101] This eliminates the influence of increased vibration due to temporary strong winds, and when damage occurs, information indicating the degree of suppression can be accurately displayed.

[0102] More preferably, when the diagnostic parameter R exceeds a second threshold Rth2 greater than the first threshold Rth1 (Yes in S8 ), the operation unit 200 outputs a signal to the control device (SCADA 300 ) that controls the operation of the wind turbine generator 10 , instructing the wind turbine generator 10 to stop operating.

[0103] When it is determined that the damage to the rotating machine is further progressing, the state monitoring system of this embodiment can automatically stop the operation of the wind turbine generator by cooperating with SCADA. This can reduce downtime caused by sudden failures.

[0104] Preferably, the data processing device 80 determines the interval for calculating the rate of change of the diagnostic parameter R over time based on the product of the rotation speed of the rotating element of the wind turbine generator and the power generation output. When the rate of change dR / dt of the diagnostic parameter in the interval is higher than the rate of change dR / dt of the diagnostic parameter in the previous interval ("Yes" in S60), the data processing device 80 calculates the suppression degree and controls the monitoring terminal 202 to display information reflecting the calculated suppression degree.

[0105] This makes it possible to determine whether the damage has progressed.

[0106] [Implementation Method 2]

[0107] In the first embodiment, an example is described in which the state of the rotating machine is monitored, and when damage progresses during rotation, the power generation is suppressed or the operation is stopped. However, when the damage progresses rapidly, it may not be possible to grasp the situation only through regular monitoring. Therefore, in the second embodiment, when it is suspected that damage has occurred, the monitoring frequency of the corresponding part is increased, so that even when the damage progresses rapidly, its progress can be monitored. In addition to the processing performed by the state monitoring system of the first embodiment, the state monitoring system of the second embodiment also performs the following processing.

[0108] Fig. 9 This is a flowchart for explaining the processing performed immediately after the state monitoring system is started in the second embodiment. Fig. 9 In the flowchart, except Figure 4 In addition to the processing in the flowchart, the processing of steps S101 to S104 is also executed.

[0109] In the second embodiment, when there is a diagnostic parameter exceeding a specific value (threshold Rth1) after the output suppression judgment is first implemented (initial damage is detected), the corresponding acceleration sensor measurement timing is additionally set. This measurement timing is different from the periodic measurement of steps S3 and S4 implemented in all channels of the acceleration sensor, and is the timing of performing the measurement in steps S102 and S103. Fig. 9 In step S104, the timing of the additional measurement is set.

[0110] Then, in step S101, it is determined whether the additional measurement timing has arrived. If the additional measurement timing has arrived (Yes in S101), in step S102, measurement is performed only on the channel of the acceleration sensor for which the additional measurement timing has been set, and in step S103, the diagnostic parameter is calculated.

[0111] In this embodiment, only the periodic measurement is performed Figure 5 and Figure 6 The output suppression judgment shown. The measurement data at the additional measurement timing is not used for output suppression judgment.

[0112] Set the additional measurement timing for each sensor. Fig.10 It is used for Fig. 9 Flowchart for explaining the setting process of the additional measurement timing executed in step S104 in FIG.

[0113] First, in step S111, the data processing device 80 resets the additional measurement timing for all measurement channels. Then, in step S112, the channel counter j is initialized. As a result, j=1 is set. In step S113, the additional measurement timing counter c is initialized. As a result, c=0 is set.

[0114] In step S114, the data processing device 80 determines whether there is a diagnostic parameter exceeding the threshold value Rth1 for the j-th measurement channel ch(j). If there is a diagnostic parameter exceeding the threshold value Rth1 ("Yes" in S114), in step S115, the counter c for additional measurement timing is incremented, and an additional measurement timing is set for the j-th channel ch(j). An additional measurement timing of size c is set between the regular measurement timings. Then, the process proceeds to step S117.

[0115] When there is no diagnosis parameter exceeding the threshold value Rth1 (NO in S114), the processing of steps S115 and S116 is not performed, and the processing proceeds to step S117.

[0116] In step S117, it is determined whether the next channel ch(j+1) exists. If the next channel ch(j+1) exists, the process proceeds to step S118, j is incremented, and the process after step S113 is executed again.

[0117] For example, when there are no diagnostic parameters exceeding the threshold value Rth1 in sensor ch(1), but there are diagnostic parameters exceeding the threshold value Rth1 in sensor ch(2), sensor ch(1) only performs periodic measurement, and the measurement of sensor ch(2) is performed after a certain period of time (before the next periodic measurement starts) in addition to the periodic measurement.

[0118] As described above, the abnormality diagnosis system shown in Embodiment 2 increases the number of measurements of a certain part when damage occurs or the progress of damage is detected. Thus, the number of measurements is reduced to suppress the amount of data under normal conditions, which helps to reduce the capacity of the memory. On the other hand, when necessary, the number of measurements can be increased to perform detailed analysis.

[0119] Preferably, in the second embodiment, when the magnitude of the diagnostic parameter exceeds the threshold value Rth1, the data processing device 80 increases the measurement frequency of the acceleration sensor 71.

[0120] More preferably, the acceleration sensor (71-73) includes a plurality of acceleration sensor elements 71-73. The data processing device 80 calculates a diagnostic parameter for each data measured by each of the plurality of acceleration sensor elements 71-73. The data processing device 80 increases the measurement frequency for the acceleration sensor element whose corresponding diagnostic parameter among the plurality of acceleration sensor elements 71-73 exceeds the threshold value Rth1, and does not change the measurement frequency for the acceleration sensor element whose corresponding diagnostic parameter among the plurality of acceleration sensor elements 71-73 does not exceed the threshold value Rth1.

[0121] Thus, in Embodiment 2, the number of measurements of only suspected damaged parts is increased more than that of normal parts, so that the parts requiring attention can be measured intensively. This makes it easier to detect signs of damage progression and obtain information that is effective for determining output suppression.

[0122] [Variation of Embodiment 2]

[0123] In implementation mode 2 Fig.10 In the flowchart, the threshold Rth1 for whether to set the additional measurement timing is 1. The modification of the second embodiment shows an example in which a plurality of thresholds for whether to set the additional measurement timing are set. In this case, the number of additional measurement timings is increased according to the number of thresholds exceeded.

[0124] Fig.11 This is a diagram for explaining the threshold value for setting the additional measurement timing. Fig.11 An example of setting two thresholds for determining whether to set additional measurement timing is described below. Fig.11 As shown, the threshold Rth3 is set between the threshold Rth1 for detecting initial damage and the threshold Rth2 for detecting usage limit. Fig.11 As shown in the above, the RMS value detected by the acceleration sensor exceeds the threshold value Rth1 at time t11, exceeds the threshold value Rth3 at time t12, and exceeds the threshold value Rth2 at time t13. Fig.11 In the example of , the thresholds for setting additional measurement timing are threshold Rth1 and threshold Rth3. When the threshold Rth1 is exceeded, the number of additional measurement timings is set to 1, and when the threshold Rth3 is exceeded, the number of additional measurement timings is set to 2. The number of thresholds can be further increased, and the number of additional measurement timings can also be further increased.

[0125] exist Fig.11 In the example, one of the thresholds for determining the timing of additional measurement is set to be equal to Figure 3 The initial damage detection threshold Rth1 is common to the above, but the threshold for determining the additional measurement timing may be set separately from the initial damage detection threshold Rth1.

[0126] Fig.12 FIG. 2 is a flowchart for explaining the setting process of the additional measurement timing executed in the modification of the second embodiment. Fig.12 Step S104A shown is replaced by Fig.10 Step S104 described in .

[0127] First, in step S111, the data processing device 80 resets the additional measurement timing for all measurement channels. Then, in step S112, the channel counter j is initialized. As a result, j=1 is set. In step S113, the additional measurement timing counter c is initialized. As a result, c=0 is set.

[0128] In the next step S121, the data processing device 80 determines whether there is a diagnostic parameter exceeding the threshold Rth1 for the jth measurement channel ch(j). If there is a diagnostic parameter exceeding the threshold Rth1 (Yes in S121), in step S122, the additional measurement timing counter c is incremented.

[0129] In step S123, the data processing device 80 determines whether there is a diagnostic parameter exceeding the threshold value Rth3 for the j-th measurement channel ch(j). When there is a diagnostic parameter exceeding the threshold value Rth3 ("Yes" in S123), in step S124, the counter c for additional measurement timing is incremented again, and the process proceeds to step S116. When there is no diagnostic parameter exceeding the threshold value Rth3 ("No" in S123), the process of step S124 is not performed, and the process proceeds to step S116.

[0130] In step S116, additional measurement timing is set for the j-th channel ch(j). Additional measurement timing of size c is set between the regular measurement timings. Specifically, when the threshold Rth3 is exceeded, since c=2, two additional measurement timings are set, and when the threshold Rth1 is exceeded but the threshold Rth3 is not exceeded, since c=1, one additional measurement timing is set. Then, the process proceeds to step S117.

[0131] When there is no diagnostic parameter exceeding the threshold value Rth1 (NO in S121 ), the processing of steps S122 to S124 and S116 is not performed, and the processing proceeds to step S117 .

[0132] In step S117, it is determined whether the next channel ch(j+1) exists. If the next channel ch(j+1) exists, the process proceeds to step S118, j is incremented, and the process after step S113 is executed again.

[0133] Fig.13 FIG. 1 is a diagram for explaining an example of how to set the additional measurement timing. Fig.13 As shown, in normal times when no damage is observed, only the periodic measurement timing is set. The periodic measurement timing is set at time t21 and time t25, and the periodic measurement timing is set once every 2 hours.

[0134] When the observed value exceeds the threshold Rth1 but does not exceed the threshold Rth3, Fig.12 In , c=1, therefore, one additional measurement timing is set between regular measurement timings. Fig.13 In the example of , additional measurement timing is set at time t23. In this case, measurement is performed once every hour.

[0135] When the observed value exceeds the threshold Rth3, Fig.12 In , c=2, therefore, two additional measurement timings are set between the regular measurement timings. Fig.13 In the example of , additional measurement timing is set at time t22 and t24. In this case, measurement is performed once every 2 / 3 hours.

[0136] In implementation mode 2, using Fig.10 The processing shown in Fig.13 In the normal operation shown in FIG. 1 , an arbitrary additional timing setting 1 is set for each measurement channel. In a variation of the second embodiment, using Fig.12 In the processing shown, in the above-mentioned normal operation, the arbitrary additional timing setting 1 and the additional timing setting 2 are set for each measurement channel.

[0137] In the variation of the second embodiment, the frequency of increasing the number of measurements at each site can be determined according to the degree of suspected damage, and the site requiring attention can be measured more intensively. This makes it easier to detect signs of damage progression and obtain information that is effective for determining output suppression.

[0138] [Implementation method 3]

[0139] In the second embodiment and its modification, monitoring is performed at the timing of additional measurement, and the timing of additional measurement is not used for output suppression determination. In the third embodiment, output suppression determination is also performed at the timing of additional measurement, thereby reliably protecting the generator.

[0140] Fig.14 This is a flowchart for explaining the processing performed immediately after the status monitoring system is started in the third embodiment. Fig.14 In the flowchart of Figure 4 In the process of the flowchart, the process of step S130 is executed instead of step S2, and the process of step S131 is added.

[0141] In step S131, the additional measurement timing is set. In step S130, both the regular measurement timing and the additional measurement timing are detected, and the measurement and diagnosis of steps S3 and S4 are performed in all measurement channels.

[0142] The same step numbers in other parts have been processed in Figure 4 The description has been given in , so it will not be repeated here.

[0143] When a diagnostic parameter exceeding a threshold value exists in any measurement channel, the additional measurement timing is set to be common to all measurement channels. Fig.15 It is used for Fig.14 Flowchart for explaining the setting process of the additional measurement timing executed in step S131 in FIG.

[0144] exist Fig.15 In the flowchart of Fig.10 In the process of the flowchart of , the step after returning from step S118 where the channel number j is incremented by 1 is changed to step S114. Since the counter c is not initialized for each channel, the counter c of the additional measurement timing is incremented for all channels. The additional measurement timing set for each channel in step S116 is set to be common for all channels in steps S141 and S142.

[0145] That is, repeat Fig.15 The processing of steps S114, S115, S117 and S118 is performed, so that there is a diagnostic parameter exceeding the threshold value Rth1 in at least one of the measurement channels. In this case, c≥1 holds, and one additional measurement timing is set in step S142.

[0146] On the contrary, only when there are no diagnostic parameters exceeding the threshold value Rth1 in all the measurement channels, c=0 holds, and therefore, the additional measurement timing is not set in step S142.

[0147] [Variation of Implementation Example 3]

[0148] In implementation mode 3 Fig.15 In the flowchart of , the threshold Rth1 for whether to set the additional measurement timing is set to 1. In the modified example of the third embodiment, as in the modified example of the second embodiment, an example is shown in which the threshold for whether to set the additional measurement timing is set to multiple. In this case, the number of additional measurement timings is increased according to the number of thresholds exceeded. The example of setting multiple thresholds is the same as Fig.11 same.

[0149] Fig.16FIG. 4 is a flowchart for explaining the setting process of the additional measurement timing executed in the modification of the third embodiment. Fig.16 Step S131A shown is replaced by Fig.15 Step S131 described in .

[0150] exist Fig.16 In the flowchart of Fig.12 In the process of the flowchart of , the step after returning from step S118 where the channel number j is incremented by 1 is changed to step S121. Since the counter c is not initialized for each channel, the counter c of the additional measurement timing is incremented for all channels. The additional measurement timing set for each channel in step S116 is set to be common for all channels in steps S151 and S154.

[0151] Specifically, repeat Fig.16 Steps S121 to S124, S117, and S118 are processed in the process, thereby accumulating the value of counter c according to the number of measurement channels in which there are diagnostic parameters exceeding the threshold Rth1. Then, after all the measurement channels are reflected in counter c, if c is greater than 2 ("Yes" in S151), two additional measurement timings are set in step S152. When the value of c is 1 ("No" in S151 and "Yes" in S153), one additional measurement timing is set in step S154. When the value of c is 0 ("No" in S151 and "No" in S153), no additional measurement timing is set. In the additional measurement timing set in Implementation Example 3, as in the case of regular measurement timing, implementation Example 3 is implemented as follows: Figure 5 and Figure 6 Output suppression judgment shown.

[0152] As described above, in the abnormality diagnosis system of the third embodiment, the acceleration sensor includes a plurality of acceleration sensor elements 71 to 73. The data processing device 80 calculates a diagnostic parameter for each data measured by each of the plurality of acceleration sensor elements 71 to 73. When there is an acceleration sensor element among the plurality of acceleration sensor elements whose corresponding diagnostic parameter exceeds a threshold value, the data processing device increases the measurement frequency of all the plurality of acceleration sensor elements 71 to 73.

[0153] When damage is suspected, the number of measurements can be increased compared to normal times. In this case, the decision on whether to suppress output is performed more frequently than normal times, and even a damaged wind turbine can be used with caution.

[0154] It should be understood that the embodiments disclosed herein are illustrative rather than restrictive in all aspects. The scope of the present invention is indicated by the claims rather than the description of the above embodiments, and is intended to include all changes within the meaning and scope equivalent to the claims.

[0155] Description of symbols

[0156] 10 Wind power generation device

[0157] 20 Spindle

[0158] 30 blades

[0159] 40 Gear Box

[0160] 50 Generator

[0161] 52 Control Panel

[0162] 54 Power lines

[0163] 60 Bearings

[0164] 71~73 Acceleration sensor

[0165] 74 Proximity Sensor

[0166] 75 Current sensor

[0167] 80 Data processing device

[0168] 81~85 Filter

[0169] 90 Cabin

[0170] 91~95 A / D converter

[0171] 100 Tower

[0172] 200 Operation unit

[0173] 201 Memory

[0174] 202 Monitoring Terminal

[0175] 300 Power generation control device

[0176] 500 Condition Monitoring System.

Claims

1. A state monitoring system for monitoring the state of a wind power generation device, characterized in that: include: Monitoring terminal; Accelerometer; as well as data processing device, The data processing device calculates diagnostic parameters based on the data measured by the acceleration sensor, determines the degree of damage of the bearings or gears included in the wind turbine generator based on the diagnostic parameters, and controls the monitoring terminal to display information indicating the degree of suppression of the generated power of the wind turbine generator corresponding to the degree of damage to the bearings or gears. The data processing device determines an interval for calculating the rate of change of the diagnostic parameters over time based on the product of the rotational speed of the rotating elements of the wind turbine generator and the power generation output. When the rate of change of the diagnostic parameters within the interval is higher than the rate of change of the diagnostic parameters within the previous interval, the data processing device calculates the suppression degree and controls the monitoring terminal to display the information reflecting the calculated suppression degree.

2. The state monitoring system according to claim 1, characterized in that: The data processing device comprises: Memory; and a calculation unit configured to cause the memory to store the number of times the magnitude of the diagnostic parameter exceeds a first threshold value, Before the number of times reaches a preset first number, the computing unit does not cause the monitoring terminal to display the information. When the number of times is greater than or equal to the first preset number, the calculation unit causes the monitoring terminal to display the information.

3. The state monitoring system according to claim 2, characterized in that: When the diagnosis parameter exceeds a second threshold value that is greater than the first threshold value, the calculation unit outputs a signal instructing the wind turbine generator to stop operating, to a control device that controls the operation of the wind turbine generator.

4. The state monitoring system according to claim 1, characterized in that: When the magnitude of the diagnostic parameter exceeds a threshold value, the data processing device increases the measurement frequency of the acceleration sensor.

5. The state monitoring system according to claim 4, characterized in that: The acceleration sensor includes a plurality of acceleration sensor elements. The data processing device calculates the diagnostic parameter for each data measured by each of the acceleration sensor elements. The data processing device increases the measurement frequency for the acceleration sensor elements whose corresponding diagnostic parameters among the multiple acceleration sensor elements exceed the threshold value, and does not change the measurement frequency for the acceleration sensor elements whose corresponding diagnostic parameters do not exceed the threshold value.

6. The state monitoring system according to claim 4, characterized in that: The acceleration sensor includes a plurality of acceleration sensor elements. The data processing device calculates the diagnostic parameter for each data measured by each of the acceleration sensor elements. When there is an acceleration sensor element among the plurality of acceleration sensor elements whose corresponding diagnostic parameter has a magnitude exceeding the threshold, the data processing device increases the measurement frequency of the plurality of acceleration sensor elements.

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