Condition Monitoring System

Abstract

To provide a state monitoring system for presenting a suppression amount according to a damage state of a generator.SOLUTION: A state monitoring system 500 includes a monitoring terminal 202, acceleration sensors 71 to 73, and a data processor 80. The data processor 80 calculates a diagnosis parameter R from data measured by the acceleration sensors 71 to 73, judges the degree of damage on a bearing or a gear included in a wind power generator 10 based on the diagnosis parameter R, and causes the monitoring terminal 202 to display information indicating the suppression amount of power generated by the wind power generator 10 according to the degree of damage on the bearing or the gear.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a condition monitoring system, and more particularly to a condition monitoring system for a power generating device. [Background technology]

[0002] Wind power generation equipment has been attracting attention as an environmentally friendly power generation device. In a wind power generation device, a nacelle that houses blades that convert wind power into rotational force and a conversion device that converts the rotational force into electric power is disposed at a high position (e.g., several tens of meters above the ground) on a support. In each wind power generation device, the status of the wind power generation device is monitored using data collected from various sensors. Such status monitoring is often performed from a remote location via a communication line or the like.

[0003] Examples of such state monitoring devices for wind power generation equipment are disclosed in Japanese Patent Application Publication No. 2009-287564 (Patent Document 1), Japanese Patent Application Publication No. 2013-185507 (Patent Document 2), and Japanese Patent Application Publication No. 2018-060387 (Patent Document 3). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2009-287564 A [Patent Document 2] JP 2013-185507 A [Patent Document 3] JP 2018-060387 A [Patent Document 4] Patent No. 3882328 Summary of the Invention [Problem to be solved by the invention]

[0005] In the technology described in the above-mentioned JP 2009-287564 A (Patent Document 1), the output of the wind power generator is controlled according to the environmental conditions around the wind power generator. However, damage to the rotating machinery (such as a gearbox) that constitutes the wind power generator is not taken into consideration as a factor in the output control.

[0006] If damage is suspected to the rotating machinery (speed-up gears, etc.) that constitutes the wind power generation equipment, it is necessary to replace the machinery or carry out maintenance, etc. During this work, the power generation equipment is stopped and power cannot be generated, which means a loss of profits for the power generation company.

[0007] Furthermore, if operation continues with damaged rotating machinery, the damage will progress and a sudden failure will occur, forcing the power generation equipment to be shut down. In that case, a maintenance plan will need to be drawn up and replacement machinery will need to be arranged after the equipment is shut down, which may result in prolonged downtime.

[0008] To avoid the above problems, power generation companies may decide to continue operation at a lower output than the rated output. When the output is reduced, the rotation speed becomes slower than when operating at rated output, and the progression of damage is also slower than when operating at rated output. This makes it possible to generate electricity while suppressing the progression of damage.

[0009] When operating with reduced output as described above, the timing and extent of output reduction is determined by a human being, for example, based on abnormal machine noises or metal wear particles contained in the grease or lubricant. Since control is performed based on human judgment, there is a possibility that the control will not be optimal. For example, the machine may be operated at a higher output than optimal, or conversely, at a lower output. , etc. are possible possibilities.

[0010] In some cases, the wind power output is controlled by a supervisory control and data acquisition (SCADA) system installed in the wind power generation equipment. The data collected by DA is related to operating conditions such as wind direction, wind volume, power generation, and rotation speed, but does not collect data on vibrations of rotating machinery. Since symptoms of damage to bearings or gears appear in vibrations in the high-frequency band, it is difficult for SCADA to control output according to the degree of damage to the rotating machinery.

[0011] The present invention has been made to solve the above problems, and an object of the present invention is to provide a condition monitoring system that presents a suppression amount according to the damage state of a power generation device. [Means for solving the problem]

[0012] The present disclosure relates to a condition monitoring system for monitoring the condition of a wind turbine generator. The condition monitoring system includes a monitoring terminal, an acceleration sensor, and a data processing device. The data processing device calculates diagnostic parameters from data measured by the acceleration sensor, determines the degree of damage to bearings or gears included in the wind turbine generator based on the diagnostic parameters, and causes the monitoring terminal to display information indicating the degree of suppression of power generation by the wind turbine generator according to the degree of damage to the bearings or gears.

[0013] Preferably, the data processing device includes a memory and a calculation unit for storing in the memory the number of times that the magnitude of the diagnostic parameter exceeds a first threshold value, the calculation unit not causing the monitoring terminal to display information indicating the suppression degree until the number of times reaches a predetermined first number, and causing the monitoring terminal to display information indicating the suppression degree when the number of times reaches or exceeds the predetermined first number.

[0014] More preferably, when the diagnostic parameter exceeds a second threshold value that is greater than the first threshold value, the calculation unit outputs a signal to a control device that controls the operation of the wind turbine generator to instruct the control device to stop the operation of the wind turbine generator.

[0015] Preferably, the data processing device determines an interval for calculating a time rate of change of the diagnostic parameter based on a product of a rotation speed of a rotating element of the wind turbine generator and a power output of the wind turbine generator. When the rate of change of the diagnostic parameter in the interval increases compared to the rate of change of the diagnostic parameter in the previous interval, the data processing device calculates a suppression degree and causes the monitoring terminal to display information reflecting the calculated suppression degree.

[0016] Preferably, the data processing device increases the frequency of measurements by the acceleration sensor when the magnitude of the diagnostic parameter exceeds a threshold value.

[0017] More preferably, the acceleration sensor includes a plurality of acceleration sensor elements, and the data processing device calculates a diagnostic parameter for each of the data measured by each of the plurality of acceleration sensor elements, and the data processing device increases a measurement frequency for an acceleration sensor element having a corresponding diagnostic parameter exceeding a threshold value, while not changing the measurement frequency for an acceleration sensor element having a corresponding diagnostic parameter not exceeding a threshold value.

[0018] More preferably, the acceleration sensor includes a plurality of acceleration sensor elements, the data processing device calculates a diagnostic parameter for each of the data measured by each of the plurality of acceleration sensor elements, and when an acceleration sensor element having a corresponding diagnostic parameter exceeding a threshold value is present among the plurality of acceleration sensor elements, the data processing device increases the measurement frequency of the plurality of acceleration sensor elements. Effect of the Invention

[0019] According to the present invention, the suppression amount is presented according to the damage state of the power generation equipment. Therefore, without relying on the intuition of the power generation company's workers, the suppression amount can be set to a level that will allow the power generation business to continue until the maintenance period while suppressing the progression of damage to the power generation equipment, thereby avoiding sudden breakdowns. [Brief description of the drawings]

[0020] [Figure 1] 1 is a diagram illustrating roughly the configuration of a wind turbine generator to which a state monitoring device according to an embodiment of the present invention is applied. [Diagram 2] FIG. 1 is a functional block diagram showing a configuration of a status monitoring system. [Diagram 3] 13 is a diagram for explaining a threshold value that is set when the effective value RMS is adopted as the diagnostic parameter R. FIG. [Figure 4] 4 is a flowchart for explaining a process executed immediately after the state monitoring system starts operating in the first embodiment. [Diagram 5] FIG. 13 shows the first half of a flowchart of the output suppression determination process executed in step S9. [Figure 6] 13 shows the second half of the flowchart of the output suppression determination process executed in step S9. FIG. [Figure 7] FIG. 13 is a diagram for explaining the integration of a load parameter P. [Figure 8] 11 is a diagram for explaining calculation of the rate of change of a diagnostic parameter R. FIG. [Figure 9] 11 is a flowchart for explaining a process executed immediately after the state monitoring system starts operating in the second embodiment. [Figure 10] 10 is a flowchart for explaining a process of setting additional measurement timing executed in step S104 of FIG. 9. [Figure 11] FIG. 13 is a diagram for explaining threshold values ​​when setting additional measurement timing. [Figure 12] 13 is a flowchart illustrating a process of setting additional measurement timing to be performed in a modification of the second embodiment. [Figure 13] FIG. 13 is a diagram for explaining an example of how additional measurement timing is set. [Figure 14] 11 is a flowchart for explaining a process executed immediately after the state monitoring system starts operating in the third embodiment. [Figure 15]15 is a flowchart for explaining a process of setting additional measurement timing executed in step S131 of FIG. 14. [Figure 16] 13 is a flowchart illustrating a process of setting additional measurement timing to be performed in a modification of the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following drawings, the same or corresponding parts are designated by the same reference numerals, and the description thereof will not be repeated.

[0022] [Embodiment 1] Fig. 1 is a diagram showing a schematic configuration of a wind turbine generator to which a condition monitoring device according to an embodiment of the present invention is applied. Referring to Fig. 1, a wind turbine generator 10 includes a main shaft 20, blades 30, a gearbox 40, a generator 50, a control panel 52, a power transmission line 54, and a main shaft bearing (hereinafter simply referred to as "bearing") 60.

[0023] The gearbox 40 , the generator 50 , the control panel 52 , and the bearings 60 are housed in a nacelle 90 , which is supported by a tower 100 .

[0024] The main shaft 20 enters the nacelle 90 and is connected to the input shaft of the gearbox 40, and is rotatably supported by bearings 60. The main shaft 20 transmits rotational torque generated by the blades 30 receiving wind force to the input shaft of the gearbox 40. The blades 30 are provided at the tip of the main shaft 20, and convert the wind force into rotational torque and transmit it to the main shaft 20.

[0025] Bearing 60 is fixedly installed within nacelle 90 and rotatably supports main shaft 20. Bearing 60 is a rolling bearing, such as a self-aligning roller bearing, a tapered roller bearing, a cylindrical roller bearing, a ball bearing, etc. These bearings may be single-row or double-row.

[0026] The speed-up gear 40 is provided between the main shaft 20 and the generator 50, and increases the rotation speed of the main shaft 20 and outputs the increased rotation speed to the generator 50. As an example, the speed-up gear 40 is configured by a gear speed-up mechanism including a planetary gear, an intermediate shaft, a high-speed shaft, etc. The generator 50 is connected to the output shaft of the speed-up gear 40, and generates electricity by the rotation torque received from the speed-up gear 40. The generator 50 is configured by, for example, an induction generator.

[0027] The control panel 52 includes an inverter (not shown) etc. The inverter converts the power generated by the generator 50 into a system voltage and frequency, and outputs the converted power to a power transmission line 54 connected to the system.

[0028] In order to monitor the wind turbine generator 10, a condition monitoring system is installed in the wind turbine generator 10.

[0029] Fig. 2 is a functional block diagram showing the configuration of the condition monitoring system. With reference to Fig. 1 and Fig. 2, the condition monitoring system 500 includes acceleration sensors 71-73, a proximity sensor 74, a current sensor 75, a data processing device 80, and a monitoring terminal 202. The acceleration sensors 71-73, the proximity sensor 74, the current sensor 75, and the data processing device 80 are housed in a nacelle 90. The connections between these elements may be wired or wireless.

[0030] The acceleration sensors 71-73 are installed in rotating machines such as the gearbox 40, generator 50, and bearing 60 inside the nacelle 90 of the wind turbine generator 10, respectively, to detect vibrations of these machines and output each detected value of vibration to the data processing device 80. The acceleration sensors 71-73 are preferably installed in positions where they can detect vibrations of the bearings and gears that make up each rotating machine.

[0031] The acceleration sensors 71 to 73 are used to detect damage to bearings or gears in rotating machinery, and therefore are preferably sensors that can measure vibrations in the high frequency range (2 kHz to 10 kHz) where signs of damage appear.

[0032] The proximity sensor 74 is used to detect the rotation speed of the wind turbine generator 10. It is desirable to install it in a position where it can detect the rotation of the shaft of the generator 50. The proximity sensor 74 detects the rotation speed of the wind turbine generator 10 by detecting the period in which protrusions or holes such as the heads of bolts on the shaft of the generator 50 approach each other due to the rotation of the shaft.

[0033] The current sensor 75 is installed in the nacelle 90 for the purpose of detecting the power generation output of the wind turbine generator 10 .

[0034] The data processing device 80 includes filters 81-85 which receive the outputs of the acceleration sensors 71-73, the proximity sensor 74, and the current sensor 75, respectively, and remove noise, A / D converters 91-95 which convert the noise-removed signals into digital values, a calculation unit (processor) 200, and a memory 201 which is a storage unit.

[0035] The calculation unit 200 periodically (for example, every two hours) performs measurements with each sensor. For data collected by the acceleration sensors 71-73, the calculation unit 200 calculates a plurality of diagnostic parameters R corresponding to each sensor. The diagnostic parameters R are highly sensitive in detecting damage to bearings or gears. In order to standardize the measurement conditions, the diagnostic parameters R are calculated only when the rotation speed and power generation output exceed the set values.

[0036] As the diagnostic parameter R, for example, feature quantities such as the effective 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.

[0037]

number

[0038] Equation (1) represents the effective value RMS, t represents time, T represents the calculation interval t2-t1, and v(t) represents the time waveform.

[0039]

number

[0040] Equation (2) shows the modulation value MOF, v AM (t) shows the envelope of the time waveform.

[0041]

number

[0042] Equation (3) represents the peak value Peak.

[0043]

number

[0044] Equation (4) shows the envelope spectrum peak value. f is the frequency, and V AM (2πf) represents the envelope spectrum. The envelope spectrum is expressed by the following formula (5).

[0045]

number

[0046] The calculation unit 200 is also configured to be capable of cooperating with a power generation control device 300 that controls power generation of the wind power generation device 10. For example, when damage to the wind power generation device 10 progresses, the calculation unit 200 transmits a stop signal to the power generation control device 300 to stop power generation. The power generation control device 300 is a type of SCADA (Supervisory Control And Data Acquisition).

[0047] Fig. 3 is a diagram for explaining threshold values ​​that are set when the effective value RMS is adopted as the diagnostic parameter R. As shown in Fig. 3, two types of threshold values ​​are set for the diagnostic parameter R. The two types of threshold values ​​may be set arbitrarily, or may be generated based on measurement data for a certain period of time. For example, a threshold value Rth1 (initial damage detection threshold value) and a threshold value Rth2 (use limit threshold value) are set.

[0048] The threshold value Rth1 is a threshold value for detecting early-stage damage. The threshold value Rth1 makes it possible to determine whether the degree of damage to a bearing or gear is normal (no damage) or minor damage.

[0049] The threshold value Rth2 is a threshold value for detecting when the damage has progressed to the point where replacement of a bearing or a gear is necessary. The threshold value Rth2 is a value larger than the threshold value Rth1 for detecting early stage damage.

[0050] Fig. 4 is a flow chart for explaining a process executed immediately after the state monitoring system in the first embodiment starts operating. With reference to Figs. 2 and 4, in step S1, the calculation unit 200 initializes the count value m of the threshold excess counter to m=0. Then, in step S2, the calculation unit 200 waits until a preset measurement period (e.g., two hours) has elapsed, and in step S3, the calculation unit 200 performs measurement using the acceleration sensors 71-73. Then, in step S4, the diagnosis parameter R (illustrated in Fig. 3) is calculated from the data obtained by the measurement.

[0051] Next, in step S5, the calculation unit 200 judges whether the number X1 of diagnostic parameters R that exceed the threshold value Rth1 is n1 or more. In the example of FIG. 1, since there are three vibration sensors, the number of diagnostic parameters R is also three, but there may be more vibration sensors. The judgment value n1 is an integer of 1 or more and can be appropriately determined according to the number of vibration sensors. If X1≧n1 is not satisfied (NO in S5), the processing returns to step S1. If X1≧n1 is satisfied (YES in S5), the calculation unit 200 judges in step S6 whether the count value m of the threshold value excess counter is equal to or more than a set value.

[0052] If m is less than the set value (NO in S6), 1 is added to the count value m in step S7, and the processes in steps S2 and after are executed again. By doing so, even if the threshold value is temporarily exceeded due to noise or the like mixed in the measurement data, the output suppression determination process in step S9 is not executed.

[0053] If a set number (n1) or more of the diagnostic parameters R exceed the threshold value Rth1 consecutively the set number of times (YES in S5 and YES in S6), the calculation unit 200 judges in step S8 whether the bearing or gear has exceeded its usage limit. Specifically, the calculation unit 200 judges whether the number of diagnostic parameters R that exceed the threshold value Rth2 is n2 or more.

[0054] If the number of diagnostic parameters R exceeding the threshold value Rth2 is less than n2 (NO in S8), the calculation unit 200 executes an output suppression determination process in step S9 and displays the recommended output suppression amount on the monitoring terminal 202. The operator refers to the suppression amount displayed on the monitoring terminal 202, determines the output of the generator, and continues operation of the generator. If operation of the generator continues, If so, the processes from step S2 onwards are executed again.

[0055] On the other hand, if the number X2 of diagnostic parameters exceeding the threshold value Rth2 is n2 or more in step S8, the calculation unit 200 determines in step S10 that it is time to replace the bearings or gears, outputs an operation stop signal to the SCADA, and ends control in step S11. This makes it possible to automatically stop operation of the wind turbine generator even if the damage to the bearings or gears progresses to a level that exceeds the limit value when the operator is absent, for example, at night. This makes it possible to prevent damage from occurring that requires large-scale maintenance.

[0056] Fig. 5 is a diagram showing the first half of a flowchart of the output suppression determination process executed in step S9. Fig. 6 is a diagram showing the second half of a flowchart of the output suppression determination process executed in step S9. In the output suppression determination process, the recommended output is displayed according to the flowcharts of Figs. 5 and 6.

[0057] In step S51, the calculation unit 200 determines whether the output suppression determination process has been performed for the first time. If the output suppression determination process has been performed for the first time (YES in S51), in step S52, the calculation unit 200 sets the most recent measurement date and time as the start point of the integration interval. Then, in step S53, the calculation unit 200 sets the recommended output to be presented to the operator to 100%, and the process proceeds to step S54. On the other hand, if there is a history of the output suppression determination process having already been performed (NO in S51), the calculation unit 200 proceeds to step S54 without performing the processes of steps S52 and S53.

[0058] In step S54, the calculation unit 200 calculates the product (load parameter) of the rotation speed and the power generation output, and then in step S55, the load parameter P is integrated with respect to time.

[0059] Fig. 7 is a diagram for explaining the integration of the load parameter P. In Fig. 7, the diagnostic parameter R and the load parameter P are shown on the vertical axis, and the date and time are shown on the horizontal axis. For example, each time an integral value S obtained by integrating from time t1 at which the initial damage threshold value Rth1 is exceeded for the first time as the starting point exceeds a preset value S0, the rate of change dR / dt of the diagnostic parameter R (interval: integral interval of the load parameter) is calculated.

[0060] For example, if the integral value S=S1 at time t2 exceeds a preset value S0, the rate of change dR / dt is calculated at this time. Also, with time t2 as the next starting point, if the integral value S=S2 at time t3 exceeds the preset value S0, the rate of change dR / dt is calculated again at this time.

[0061] Fig. 8 is a diagram for explaining the calculation of the rate of change of the diagnostic parameter R. With reference to Figs. 7 and 8, the rate of change dR1 / dT1 is calculated at time t2, and the rate of change dR2 / dT2 is calculated at time t3. In this manner, each time the integral value S of the load parameter P exceeds the preset value S0 (YES in step S56), the calculation unit 200 sets the latest measurement time as the end point of the integral interval (step S57), draws an approximation line between the start point and the end point, and obtains the rate of change dR / dt of the diagnostic parameter R (interval: integral interval of the load parameter) (step S58).

[0062] Next, in step S59, the calculation unit 200 determines whether or not 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), the calculation unit 200 determines in step S60 whether or not the rate of change of the diagnostic parameter R is greater than the rate of change in the previous interval.

[0063] If there is no data on the previous rate of change of diagnostic parameter R in step S59, and if the rate of change of diagnostic parameter R is equal to or less than the rate of change of the previous section in step S60, the calculation unit 200 stores the calculated rate of change of diagnostic parameter R in memory 201 in step S61, and displays the same recommended output as the previous time on the monitoring terminal 202 in step S63 as information to the effect that the operating output will be maintained in the previous state.

[0064] If the rate of change of diagnostic parameter R is greater than the rate of change in the previous interval (YES in S60), calculation unit 200 determines that damage is progressing, corrects the recommended output to 0.9 times the current setting value in step S62, and causes monitoring terminal 202 to display the corrected recommended output as information to the effect that the operating output will be suppressed in step S63. 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 to subtract a predetermined power.

[0065] 7 and 8 show an example in which a load parameter P, which is the product of the rotation speed and the amount of power generated, is calculated, and the power generation is suppressed depending on the magnitude of the rate of change. In FIG. 7, the measurement date and time t1 at which the output suppression determination process was first performed is set as the "start point." After that, each time the output suppression determination process is performed, the integral value S of the load parameter P is calculated in the section from the "start point" to the latest measurement date and time.

[0066] 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. In Fig. 7, the latest measurement date and time t2 at which the integral value S1 exceeds the set value S0 is set as the new "starting point" and calculation of the integral value S2 begins. The latest measurement date and time t3 at which the integral value S2 exceeds the set value S0 is set as the new "starting point".

[0067] Then, the rate of change dR / dt of the diagnostic parameter R in each integral interval is calculated. The rate of change of the diagnostic parameter R can be expressed as the gradient of an approximation line, as shown in FIG.

[0068] The calculated rate of change is compared with the rate of change calculated in the previous interval. In FIG. 8, it is shown that dR1 / dT1 calculated in the interval dT1 = t1 to t2 is compared with dR2 / dT2 calculated in the interval dT2 = t2 to t3.

[0069] When the rate of change in the current interval is compared with the rate of change in the previous interval and the rate of change in the current interval is large, the calculation unit 200 determines that the degree of damage is progressing, and causes the monitoring terminal 202 to display information (recommended output) indicating that the output is to be suppressed. For example, the recommended output has an initial value of 100% and is decreased by 10% each time it is determined that the damage is progressing. In FIG. 8, since dR1 / dT1 < dR2 / dT2, it is determined that the damage is progressing. The recommended output at this time is 90% (= 100% × 0.9). As a result, in FIG. 7, since the operator suppresses the output to 90% at time t3, the power generation amount decreases, so the load parameter P also decreases by one step.

[0070] When the number of set diagnosis parameters (n2) or more of the diagnosis parameter R exceeds the use limit threshold value Rth2, it is determined that the bearing or gear has reached the replacement time, and the calculation unit 200 outputs an operation stop signal to the SCADA 300. Therefore, even when the damage progresses when the operator is not monitoring, it is possible to stop the operation before the wind power generation device suffers significant damage.

[0071] Regarding Embodiment 1, referring to FIGS. 1 to 8 again, a summary will be given.

[0072] The present disclosure relates to a condition monitoring system for monitoring the condition of the wind power generation device 10. The condition 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 diagnosis parameter R from the data measured by the acceleration sensors 71 to 73, determines the degree of damage to the bearing or gear included in the wind power generation device 10 based on the diagnosis parameter R, and displays information indicating the degree of suppression of the generated power of the wind power generation device 10 according to the degree of damage to the bearing or gear on the monitoring terminal 202.

[0073] The degree of damage to the bearing or gear is determined by the number of times m that the diagnostic parameter exceeds a threshold value Rth1 and the rate of change of the diagnostic parameter. As shown in Fig. 4, the data processing device 80 performs an output suppression determination process when the number of times m that the threshold value Rth1 is exceeded is equal to or greater than a set value. When the rate of change of the diagnostic parameter increases compared to the previous rate of change as shown in step S60 of Fig. 6, the data processing device 80 determines that the degree of damage has progressed and reduces the recommended output from the current level.

[0074] According to the condition monitoring system 500 of this embodiment, it is possible to generate power in the wind turbine generator 10 while suppressing damage to the rotating machinery. This reduces the risk of sudden major failures and reduces downtime compared to when operation is continued at rated output.

[0075] In addition, there are many windy days during the winter in Japan, and there is a demand to operate wind power generation equipment as long as possible. By using the condition monitoring system 500 of this embodiment, even if the rotating machinery of a wind power generation equipment is suspected to be damaged, the output can be suppressed to a level that does not significantly progress the damage, so that the equipment can be operated at a time suitable for power generation, which leads to profits for the power generation company.

[0076] Preferably, the data processing device 80 includes a memory 201 and a calculation unit 200 that stores in the memory the number m of times that the magnitude of the diagnostic parameter R exceeds a first threshold value Rth1. The calculation unit 200 does not cause the monitoring terminal to display information indicating the suppression degree until the number m reaches a predetermined first number (NO in S6), and when the number m reaches or exceeds the predetermined first number (YES in S6), causes the monitoring terminal to display information indicating the suppression degree (S9).

[0077] In this way, the influence of increased vibrations due to temporary strong winds and the like can be eliminated, and if damage occurs, information showing the correct degree of suppression can be displayed.

[0078] More preferably, when the diagnostic parameter R exceeds a second threshold value Rth2 that is greater than the first threshold value Rth1 (YES in S8), the calculation unit 200 outputs a signal to the control device (SCADA 300) that controls the operation of the wind power generation plant 10 to instruct the operation of the wind power generation plant 10 to stop.

[0079] If it is determined that the damage to the rotating machinery has progressed further, the condition monitoring system of this embodiment can automatically stop the operation of the wind turbine generator by linking with the SCADA, thereby reducing the downtime caused by sudden failures.

[0080] Preferably, the data processing device 80 determines an interval for calculating the time rate of change of the diagnostic parameter R 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 an interval has increased compared to the rate of change dR / dt of the diagnostic parameter in the previous interval (YES in S60), the data processing device 80 calculates the degree of suppression and causes the monitoring terminal 202 to display information reflecting the calculated degree of suppression.

[0081] By doing so, it is possible to determine whether the damage has progressed.

[0082] [Embodiment 2] In the first embodiment, the condition of the rotating machine is monitored, and when damage during rotation progresses, As explained above, the system reduces the amount of power consumed and stops operation. However, regular monitoring alone may not be enough to grasp the situation when damage progresses rapidly. Therefore, in the second embodiment, when damage is suspected, the frequency of monitoring the relevant part is increased, making it possible to monitor the progress of damage even when the damage progresses rapidly. The status monitoring system of the second embodiment executes the following processes in addition to the processes executed by the status monitoring system of the first embodiment.

[0083] Fig. 9 is a flowchart for explaining the processing executed immediately after the state monitoring system starts operation in embodiment 2. In the flowchart of Fig. 9, in addition to the processing in the flowchart of Fig. 4, processing in steps S101 to S104 is executed.

[0084] In the second embodiment, when any diagnostic parameter exceeds a specific value (threshold value Rth1) after the first output suppression judgment (initial damage is detected), the measurement timing of the corresponding acceleration sensor is additionally set. This measurement timing is the timing at which measurements are performed in steps S102 and S103, separate from the regular measurements in steps S3 and S4 performed in all channels of the acceleration sensor. The timing of the additional measurement is set in step S104 of FIG. 9.

[0085] Then, in step S101, it is determined whether or not it is time for additional measurement. If it is time for additional measurement (YES in S101), in step S102, measurement is performed only for the channel of the acceleration sensor for which the additional measurement timing is set, and in step S103, diagnostic parameters are calculated.

[0086] In this embodiment, the output suppression judgment shown in Fig. 5 and Fig. 6 is performed only at the time of regular measurement. Measurement data at the additional measurement timing is not used for output suppression judgment.

[0087] The additional measurement timing is set for each sensor. Fig. 10 is a flowchart for explaining the additional measurement timing setting process executed in step S104 of Fig. 9.

[0088] 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 is set to 1. Furthermore, in step S113, the counter c for the additional measurement timing is initialized. As a result, c is set to 0.

[0089] In step S114, the data processing device 80 judges whether or not there is a diagnostic parameter that exceeds the threshold value Rth1 for the j-th measurement channel ch(j). If there is a diagnostic parameter that exceeds the threshold value Rth1 (YES in S114), in step S115, the counter c for additional measurement timing is incremented and additional measurement timing is set for the j-th channel ch(j). The additional measurement timing is set between the regular measurement timings by the value of c. Then, the process proceeds to step S117.

[0090] On the other hand, if there is no diagnostic parameter that exceeds the threshold value Rth1 (NO in S114), the processes in steps S115 and S116 are not executed, and the process proceeds to step S117.

[0091] In step S117, it is determined whether or not the next channel ch(j+1) exists. If the next channel ch(j+1) exists, the process proceeds to step S118, where j is The counter is incremented, and the processes from step S113 onward are executed again.

[0092] For example, if there is no diagnostic parameter in sensor ch(1) that exceeds threshold value Rth1 but there is one in sensor ch(2), then only the regular measurement will be performed in sensor ch(1), but in addition to the regular measurement, measurement in sensor ch(2) will be performed separately after a certain time has elapsed (before the start of the next regular measurement).

[0093] As described above, when the abnormality diagnosis system shown in the second embodiment detects the occurrence or progression of damage in a certain part, it increases the number of measurements of that part compared to normal parts. This reduces the number of measurements during normal times to suppress the amount of data and contributes to reducing storage capacity, while increasing the number of measurements when necessary to perform a detailed analysis.

[0094] Preferably, in the second embodiment, the data processing device 80 increases the frequency of measurements by the acceleration sensor 71 when the magnitude of the diagnostic parameter exceeds the threshold value Rth1.

[0095] 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 of the data measured by each of the plurality of acceleration sensor elements 71-73. The data processing device 80 increases the measurement frequency for acceleration sensor elements among the plurality of acceleration sensor elements 71-73 whose corresponding diagnostic parameters exceed a threshold value Rth1, while not changing the measurement frequency for acceleration sensor elements among the plurality of acceleration sensor elements 71-73 whose corresponding diagnostic parameters do not exceed the threshold value Rth1.

[0096] In this way, in the second embodiment, the number of measurements is increased only for areas suspected of damage compared to normal areas, allowing for intensive measurements of areas requiring attention. This makes it easier to detect signs of damage progression, and provides information that is useful for determining whether to suppress output.

[0097] [Modification of the second embodiment] In the flowchart of Fig. 10 of the second embodiment, there is one threshold value Rth1 for determining whether or not to set additional measurement timing. In the modified example of the second embodiment, an example is shown in which multiple threshold values ​​are provided for determining whether or not to set additional measurement timing. In this case, the number of additional measurement timings is increased according to the number of exceeded threshold values.

[0098] FIG. 11 is a diagram for explaining thresholds when setting additional measurement timing. In FIG. 11, an example is explained in which two thresholds are provided for determining whether or not to set additional measurement timing. For example, as shown in FIG. 11, a threshold Rth3 is provided between a threshold Rth1 for detecting initial damage and a threshold Rth2 for detecting a usage limit. As shown in FIG. 11, the effective value detected by the acceleration sensor exceeds the threshold Rth1 at time t11, exceeds the threshold Rth3 at time t12, and further exceeds the threshold Rth2 at time t13 as damage progresses. In the example of FIG. 11, there are two thresholds for determining whether or not to set additional measurement timing: the threshold Rth1 and the threshold Rth3. The number of additional measurement timings is one when the threshold Rth1 is exceeded, and two when the threshold Rth3 is exceeded. The number of thresholds may be further increased, and the number of additional measurement timings may also be further increased.

[0099] In FIG. 11, one of the judgment thresholds for setting the timing for additional measurement is common to the initial damage detection threshold Rth1 in FIG. 3, but the judgment threshold for setting the timing for additional measurement may be determined separately from the initial damage detection threshold Rth1.

[0100] FIG. 12 is a flowchart showing a process of setting the additional measurement timing to be executed in a modification of the second embodiment. 12 is a flowchart for explaining the process of the modification of the second embodiment. In the modification of the second embodiment, the process of step S104A shown in FIG.

[0101] 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 is set to 1. Furthermore, in step S113, the counter c for the additional measurement timing is initialized. As a result, c is set to 0.

[0102] In the next step S121, the data processing device 80 judges whether or not there is a diagnostic parameter that exceeds the threshold value Rth1 for the j-th measurement channel ch(j). If there is a diagnostic parameter that exceeds the threshold value Rth1 (YES in S121), in step S122, the counter c for additional measurement timing is incremented.

[0103] Furthermore, in step S123, the data processing device 80 judges whether or not there is a diagnostic parameter that exceeds the threshold value Rth3 for the j-th measurement channel ch(j). If there is a diagnostic parameter that exceeds 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. If there is no diagnostic parameter that exceeds the threshold value Rth3 (NO in S123), the process of step S124 is not executed, and the process proceeds to step S116.

[0104] In step S116, an additional measurement timing is set for the j-th channel ch(j). The additional measurement timing is set between the regular measurement timings by the value of c. That is, if the threshold value Rth3 is exceeded, c=2 so two additional measurement timings are set, and if the threshold value Rth1 is exceeded but not Rth3, c=1 so one additional measurement timing is set. Then, the process proceeds to step S117.

[0105] On the other hand, if there is no diagnostic parameter that exceeds the threshold value Rth1 (NO in S121), the processes in steps S122 to S124 and S116 are not executed, and the process proceeds to step S117.

[0106] In step S117, it is determined whether or not a next channel ch(j+1) exists. If a next channel ch(j+1) exists, the process proceeds to step S118, j is incremented, and the processes from step S113 onwards are executed again.

[0107] Fig. 13 is a diagram for explaining an example of how the additional measurement timing is set. As shown in Fig. 13, in a normal state where no damage is observed, only the regular measurement timing is set. The regular measurement timing is time t21 and time t25, and is set every two hours.

[0108] When the observed value exceeds the threshold value Rth1 but does not exceed the threshold value Rth3, c=1 in Fig. 12, so one additional measurement timing is set between the scheduled measurement timings. In the example of Fig. 13, the additional measurement timing is set at time t23. In this case, the measurement interval is every hour.

[0109] When the observed value exceeds the threshold value Rth3, since c=2 in Fig. 12, two additional measurement timings are set between the scheduled measurement timings. In the example of Fig. 13, the additional measurement timings are set at times t22 and t24. In this case, the measurement interval is 2 / 3 hours.

[0110] In the second embodiment, either the normal state or the additional timing setting 1 shown in Fig. 13 is set for each measurement channel by the process shown in Fig. 10. In the modified example of the second embodiment, either the normal state, the additional timing setting 1, or the additional timing setting 2 as described above is set for each measurement channel by the process shown in Fig. 12.

[0111] In the modified example of the second embodiment, the frequency of increasing the number of measurements for each part can be determined according to the degree of suspected damage, and the parts that require attention can be measured more intensively. This makes it easier to detect signs of damage progression, and provides information that is useful for determining whether to suppress the output.

[0112] [Embodiment 3] In the second embodiment and the modified example of the second embodiment, the timing of the additional measurement is monitored but not used to determine whether to suppress the output. In the third embodiment, the output suppression is determined even at the timing of the additional measurement, thereby reliably protecting the generator.

[0113] Fig. 14 is a flowchart for explaining the processing executed immediately after the operation of the status monitoring system in embodiment 3. In the flowchart of Fig. 14, the processing of step S130 is executed instead of step S2 in the processing of the flowchart of Fig. 4, and further, the processing of step S131 is added.

[0114] In step S131, the additional measurement timing is set. Then, in step S130, both the regular measurement timing and the additional measurement timing are detected, and the measurements and diagnoses in steps S3 and S4 are performed in all the measurement channels.

[0115] The other steps having the same step numbers have been described with reference to FIG. 4 and will not be described again.

[0116] The additional measurement timing is set commonly to all measurement channels when a diagnostic parameter exceeds a threshold value in any measurement channel. Fig. 15 is a flowchart for explaining the setting process of the additional measurement timing executed in step S131 in Fig. 14.

[0117] In the flowchart of Fig. 15, the flow returns to step S114 after step S118 in which the channel number j is incremented by 1 in the process of the flowchart of Fig. 10. As a result, the counter c is not initialized for each channel, and the additional measurement timing counter c is incremented for all channels. The additional measurement timing that was set for each channel in step S116 is now set commonly for all channels in steps S141 and S142.

[0118] That is, by repeating the processing of steps S114, S115, S117, and S118 in FIG. 15, if at least one of the measurement channels has a diagnostic parameter that exceeds the threshold value Rth1, c≧1 is satisfied, and one additional measurement timing is set in step S142.

[0119] Conversely, only when there is no diagnostic parameter exceeding the threshold value Rth1 in any of the measurement channels, c=0, and therefore the additional measurement timing is not set in step S142.

[0120] [Modification of the third embodiment] In the flowchart of FIG. 15 of the third embodiment, the timing of additional measurement is determined. There was one threshold value Rth1. In the modified example of the third embodiment, an example is shown in which multiple threshold values ​​are set for determining whether or not to set additional measurement timing, as in the modified example of the second embodiment. In this case, the number of additional measurement timings is increased according to the number of exceeded threshold values. An example of setting multiple threshold values ​​is the same as in FIG. 11.

[0121] Fig. 16 is a flowchart for explaining a setting process of additional measurement timing executed in a modification of embodiment 3. In the modification of embodiment 3, the process of step S131A shown in Fig. 16 is executed instead of step S131 explained in Fig. 15.

[0122] In the flowchart of Fig. 16, the flow returns to step S121 after step S118 in which the channel number j is incremented by 1 in the process of the flowchart of Fig. 12. As a result, the counter c is not initialized for each channel, and the additional measurement timing counter c is incremented for all channels. The additional measurement timing that was set for each channel in step S116 is now set commonly for all channels in steps S151 to S154.

[0123] That is, by repeating the processes of steps S121 to S124, S117, and S118 in Fig. 16, the value of the counter c is accumulated according to the number of measurement channels in which diagnostic parameters exceed the threshold value Rth1 exist. Then, after all measurement channels are reflected in the counter c, if c is 2 or more (YES in S151), two additional measurement timings are set in step S152. If c is 1 (NO in S151 and YES in S153), one additional measurement timing is set in step S154. Note that if c is 0 (NO in S151 and NO in S153), no additional measurement timing is set. In the additional measurement timing set in the third embodiment, the output suppression judgment shown in Figs. 5 and 6 is performed in the same manner as in the regular measurement timing.

[0124] As described above, in the abnormality diagnosis system of the third embodiment, the acceleration sensor includes a plurality of acceleration sensor elements 71-73. The data processing device 80 calculates a diagnostic parameter for each of the data measured by each of the plurality of acceleration sensor elements 71-73. When there is an acceleration sensor element among the plurality of acceleration sensor elements for which the magnitude of the corresponding diagnostic parameter exceeds a threshold value, the data processing device increases the measurement frequency for all of the plurality of acceleration sensor elements 71-73.

[0125] This allows the number of measurements to be increased when damage is suspected, and the decision on whether to suppress output is made more frequently than normal, allowing for careful operation of damaged wind power generation equipment.

[0126] The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims, not by the description of the embodiments described above, and is intended to include all modifications within the meaning and scope of the claims. [Explanation of symbols]

[0127] 10 wind power generation device, 20 main shaft, 30 blade, 40 gearbox, 50 generator, 52 control panel, 54 power transmission line, 60 bearing, 71-73 acceleration sensor, 74 proximity sensor, 75 current sensor, 80 data processing device, 81-85 filter, 90 nacelle, 91-95 A / D converter, 100 tower, 200 calculation unit, 201 memory, 202 monitoring terminal, 300 power generation control device, 500 status monitoring system.

Claims

1. A status monitoring system for monitoring a status of a wind turbine generator, A monitoring terminal; An acceleration sensor; a data processing device, the data processing device includes a calculation unit configured to be able to cooperate with a power generation control device, The calculation unit a process of calculating diagnostic parameters from the data measured by the acceleration sensor, determining the degree of damage to bearings or gears included in the wind power generation device based on the diagnostic parameters, and outputting information indicating the degree of suppression of power generation by the wind power generation device according to the degree of damage to the bearings or gears; and executing processing in cooperation with the power generation control device to suppress the progression of damage to the bearing or the gear based on information indicating the degree of suppression.

2. The data processing device includes: Memory and a calculation unit that stores in the memory the number of times the magnitude of the diagnostic parameter exceeds a first threshold value; 2. The status monitoring system according to claim 1, wherein the calculation unit does not cause the information to be displayed on the monitoring terminal until the number of times reaches a predetermined first number, and causes the information to be displayed on the monitoring terminal when the number of times reaches or exceeds the predetermined first number.

3. 3. The status monitoring system according to claim 2, wherein the calculation unit outputs a signal to the power generation control device to instruct the power generation control device to stop operation of the wind turbine power generation device when the diagnostic parameter exceeds a second threshold value that is greater than the first threshold value.

4. the data processing device determines an interval for calculating a time rate of change of the diagnostic parameter based on a product of a rotation speed of a rotating element of the wind turbine generator and a power generation output; 2. The condition monitoring system according to claim 1, wherein the data processing device calculates the suppression degree when the rate of change of the diagnostic parameter in the section increases compared to the rate of change of the diagnostic parameter in the previous section, and causes the monitoring terminal to display the information reflecting the calculated suppression degree.

5. 2. The condition monitoring system according to claim 1, wherein the data processing device increases the frequency of measurements by the acceleration sensor when the magnitude of the diagnostic parameter exceeds a threshold value.

6. the acceleration sensor includes a plurality of acceleration sensor elements; the data processing device calculates the diagnostic parameters for each of the data measured by each of the plurality of acceleration sensor elements; 6. The condition monitoring system according to claim 5, wherein the data processing device increases the measurement frequency for acceleration sensor elements among the plurality of acceleration sensor elements whose corresponding diagnostic parameter exceeds the threshold value, while not changing the measurement frequency for acceleration sensor elements among the plurality of acceleration sensor elements whose corresponding diagnostic parameter does not exceed the threshold value.

7. the acceleration sensor includes a plurality of acceleration sensor elements; the data processing device calculates the diagnostic parameters for each of the data measured by each of the plurality of acceleration sensor elements; 6. The condition monitoring system according to claim 5, wherein the data processing device increases the measurement frequency 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.

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