Wind turbine monitoring device, wind turbine monitoring system, wind turbine monitoring method, and program

Abstract

To provide a wind turbine monitoring device that allows for appropriate inspection according to the condition of the wind turbine. [Solution] One embodiment of the wind turbine monitoring device is a wind turbine monitoring device having a plurality of devices and a nacelle housing the plurality of devices. This wind turbine monitoring device includes a wind condition prediction processing unit that predicts future wind conditions at the wind turbine installation site, a power output prediction processing unit that predicts future power generation conditions of the wind turbine, and a determination processing unit that uses sensing data obtained by sensing the plurality of devices, the wind condition prediction results, and the operating condition prediction results to identify the future operating state of the plurality of devices and select the device to be inspected from among the plurality of devices according to the identified operating state.

Description

Technical Field

[0001] Embodiments of the present invention relate to a wind turbine monitoring device, a wind turbine monitoring method, and a program.

Background Art

[0002] When an operator visits a site to inspect a wind turbine installed in a wind farm, the cost required for the site visit increases. Therefore, it is desirable to reduce the number of visits. Thus, when an inspection device such as a drone installed in the nacelle of the wind turbine performs an inspection at a preset time and transmits inspection data to the monitoring system, it becomes possible to reduce the number of visits by the operator.

[0003] However, since the operating state of wind power generation depends on the wind conditions, even if an inspection is performed at a preset time, the inspection target device may be stopped. In this case, useful inspection data for grasping the abnormality of the device cannot be measured.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] Embodiments of the present invention provide a wind turbine monitoring device, a wind turbine monitoring system, a wind turbine monitoring method, and a program capable of appropriately inspecting according to the state of a wind turbine.

Means for Solving the Problems

[0006] One embodiment of the wind turbine monitoring device is a wind turbine monitoring device having a plurality of devices and a nacelle housing the plurality of devices. This wind turbine monitoring device includes a wind condition prediction processing unit that predicts future wind conditions at the wind turbine installation site, a power output prediction processing unit that predicts future power generation conditions of the wind turbine, and a determination processing unit that uses sensing data obtained by sensing the plurality of devices, the wind condition prediction results, and the operating condition prediction results to identify the future operating status of the plurality of devices and select the device to be inspected from among the plurality of devices according to the identified operating status. [Effects of the Invention]

[0007] According to this embodiment, it becomes possible to inspect the wind turbine appropriately according to its condition. [Brief explanation of the drawing]

[0008] [Figure 1] (A) is a schematic diagram showing an example of a fixed-bottom offshore wind turbine, and (B) is a schematic diagram showing an example of a floating offshore wind turbine. [Figure 2] This is a schematic diagram illustrating the interior of a wind turbine nacelle. [Figure 3] This block diagram shows the configuration of a wind turbine monitoring system according to one embodiment. [Figure 4] This is a block diagram showing an example configuration of inspection equipment. [Figure 5] A flowchart illustrating the method for monitoring wind turbines is shown. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. The embodiments described below are not intended to limit the present invention.

[0010] First, we will describe the wind turbines that are monitored by the wind turbine monitoring system according to this embodiment.

[0011] Figure 1(A) is a schematic diagram showing an example of a fixed-bottom offshore wind turbine. Figure 1(B) is a schematic diagram showing an example of a floating offshore wind turbine. Figure 2 is a schematic diagram showing the interior of the nacelle of the wind turbine 20 shown in Figures 1(A) and 1(B).

[0012] The wind turbine 20 shown in Figures 1(A) and 1(B) comprises multiple blades 21, a hub 22, a nacelle 23, and a tower 24. Each blade 21 is arranged radially so as to be connected to the rotor shaft 25 (see Figure 2) by the hub 22. The pitch angle of each blade 21 is adjusted with respect to the wind inflow direction so as to efficiently convert the flowing energy of the wind into rotational energy. A drive mechanism (not shown) such as a motor, brake, and emergency power supply is provided inside the hub 22 to adjust this pitch angle. The tower 24 is constructed vertically on the upper surface of a foundation 26 built on the seabed and exposed above the sea surface.

[0013] In this embodiment, the wind turbine to be inspected is an offshore-mounted wind turbine 20. However, the wind turbine to be inspected is not limited to offshore-mounted types, and the method can also be applied to ground-mounted wind turbines.

[0014] The nacelle 23 is located at the top of the tower 24 via a yaw control device 411 that automatically adjusts the rotor shaft 25 to follow the wind direction.

[0015] The nacelle 23 houses the main engine 30 and auxiliary engines 40. The main engine 30 is located around the rotor shaft 25 and is directly involved in wind power generation. The main engine 30 includes, for example, a main bearing 311, a speed increaser 312, a generator 313, and a PCS 314 (Power Conditioning System). The main bearing 311 supports the rotor shaft 25. The speed increaser 312 is connected to the end of the rotor shaft 25 and increases the rotational speed of the rotor shaft 25. The generator 313 converts the rotational energy of the rotor shaft 25 into electrical energy. The PCS 314 modulates and transforms the output of the generator 313 to output power matched to the grid frequency and grid voltage.

[0016] On the one hand, the auxiliary machine 40 is a device that assists the main machine 30. The auxiliary machine 40 includes, for example, a yaw control device 411, a hydraulic device 412, and a cooling device 413. The yaw control device 411 has a yaw motor for changing the yaw angle of the wind turbine 20 and a yaw brake for fixing the yaw angle of the wind turbine 20. The hydraulic device 412 has a hydraulic pump connected to the generator 313 and the like. The cooling device 413 has a radiator, a cooling water pump motor for circulating cooling water between the radiator and the generator 313 and the like.

[0017] Note that the main machine 30 and the auxiliary machine 40 are not limited to the above-described devices, and other devices may be included.

[0018] In this embodiment, sensors 50 are installed on the main machine 30 and the auxiliary machine 40. Examples of the sensors 50 include a gyro sensor, an acceleration sensor, a vibration sensor, an AE (Acoustic Emission) sensor, a pressure sensor, a temperature sensor, an odor sensor, a sound wave sensor, a noise sensor, a distance sensor, and the like. For example, vibration sensors are installed as the sensors 50 on the main bearing 311 and the speed increaser 312. Also, for example, temperature sensors are installed as the sensors 50 on the generator 313 and the PCS 314. Further, in this embodiment, a wind condition sensor 51 for measuring the wind condition indicating the wind speed and the wind direction is provided outside the nacelle 23.

[0019] The sensing data measured by each sensor 50 is acquired by the wind turbine monitoring device 10 as SCADA (Supervisory Control And Data Acquisition) data or CMS (Condition Monitoring System) data. Also, the wind condition measured data measured by the wind condition sensor 51 is acquired by the wind turbine monitoring device 10 as part of the operation data.

[0020] In this embodiment, the wind turbine monitoring device 10 is housed inside the nacelle 23. The wind turbine monitoring device 10 causes the inspection device 60 to inspect the main machine 30 and the auxiliary machine 40 based on the results of analyzing the sensing data, the operation data, and the weather prediction data. Here, referring to FIG. 3, the configuration of the wind turbine monitoring system according to this embodiment will be described.

[0021] FIG. 3 is a block diagram showing the configuration of a wind turbine monitoring system according to an embodiment. The wind turbine monitoring system 1 shown in FIG. 3 includes a wind turbine monitoring device 10 and an inspection device 60.

[0022] First, the configuration of the wind turbine monitoring device 10 will be described. The wind turbine monitoring device 10 has hardware resources such as a CPU, ROM, RAM, HDD, GPU, etc., and can be configured by a computer in which information processing by software is realized using the hardware resources by the CPU executing various programs. Furthermore, the wind turbine monitoring method using the wind turbine monitoring device 10 can be realized by causing a computer to execute various programs. The wind turbine monitoring device 10 shown in FIG. 3 includes a communication unit 11, a storage unit 12, a display unit 13, a data processing unit 14, and a device control unit 15.

[0023] The communication unit 11 receives weather forecast data D1, operation data D2, and sensing data D3 via the network 100. Weather forecast data D1 is forecast data for the weather at the installation site of the wind turbine 20. Weather forecast data D1 includes, for example, at least one of the following: Japan Meteorological Agency forecast data, weather forecast GPV (Grid Point Value) data, weather forecast SCW site (Super C Weather) data, weather reanalysis data such as ERA-5, and data from WRF (Weather Research and Forecasting) analysis results such as numerical weather models. Japan Meteorological Agency forecast data is data predicted by the Japan Meteorological Agency. Weather forecast GPV data is past and future weather forecast data calculated by a supercomputer at grid points pre-set on a map. ERA-5 data is data used by the European Centre for Medium-Range Weather Forecasts for weather forecasting. WRF is a forecasting model for predicting wind conditions such as wind speed and wind direction.

[0024] The operating data D2 is data related to the operation of the wind turbine 20. The operating data D2 includes, for example, data showing the power output of the wind turbine 20, in other words, the output power of the generator 313, and actual wind condition measurement data measured by the wind condition sensor 51.

[0025] Sensing data D3 is data measured by the main unit 30 and auxiliary unit 40 by the sensor 50. Sensing data D3 includes, for example, vibration data and temperature data.

[0026] The communication unit 11 receives weather forecast data D1, operation data D2, and sensing data D3 at predetermined intervals. However, the reception intervals for each data do not need to be the same and may be different. In addition, the communication unit 11 may receive the operation data D2 and sensing data D3 directly from the sensor 50 and wind condition sensor 51 without going through the network 100.

[0027] The storage unit 12 stores weather forecast data D1, operation data D2, and sensing data D3 received by the communication unit 11. The storage unit 12 has a weather forecast database 121, an operation database 122, and a sensing database 123. The weather forecast database 121 stores the weather forecast data D1 in chronological order. The operation database 122 stores the operation data D2 in chronological order. The sensing database 123 stores the sensing data D3 in chronological order.

[0028] The display unit 13 outputs inspection data, for example, showing the inspection results of the inspection equipment 60. The display unit 13 is composed of a device that displays images, such as a display. This display may be separate from or integrated with the main body of the wind turbine monitoring device 10 (computer).

[0029] The data processing unit 14 processes the weather forecast data D1, operation data D2, and sensing data D3 read from the storage unit 12 to determine the inspection contents for the main unit 30 and auxiliary unit 40. As shown in Figure 3, the data processing unit 14 according to this embodiment includes a wind condition forecast processing unit 141, a power generation output forecast processing unit 142, a determination processing unit 143, and an inspection planning processing unit 144.

[0030] The wind condition prediction processing unit 141 performs wind condition prediction processing to predict future wind speed and wind direction at the installation site of the wind turbine 20, using the weather forecast data D1 stored in the weather forecast database 121 of the storage unit 12. The wind condition prediction processing unit 141 may also perform wind condition prediction processing using actual wind condition data measured by the wind condition sensor 51, in addition to the weather forecast data D1. Furthermore, if the wind turbine 20 is an offshore wind turbine, the wind condition prediction processing unit 141 may also perform wind condition prediction processing using ocean condition data of the installation site of the wind turbine 20, in addition to the weather forecast data D1 and actual wind condition data. Ocean condition data may include, for example, wave height, period, tides, and tidal level.

[0031] The power output prediction processing unit 142 uses the operation data D2 stored in the operation database 122 of the memory unit 12 to perform power output prediction processing to predict the future operating status of the wind turbine 20, such as the amount of power generated. The power output prediction processing unit 142 may also perform power output prediction processing using weather forecast data D1 instead of operation data D2. In this case, the power output prediction processing unit 142 may perform power output prediction processing based on the results of machine learning to determine the correlation between past weather forecast data D1 and past operation data D2.

[0032] The determination processing unit 143 uses the sensing data D3 stored in the sensing database 123, the results of the wind condition prediction processing by the wind condition prediction processing unit 141, and the results of the power output prediction processing by the power output prediction processing unit 142 to determine which equipment is to be inspected.

[0033] The inspection planning processing unit 144 uses the results of the wind condition forecasting process performed by the wind condition forecasting processing unit 141 and the results of the power output forecasting process performed by the power output forecasting processing unit 142 to formulate an inspection plan for the equipment to be inspected by the inspection equipment 60. The inspection plan includes the date and time of the inspection, the inspection route, and so on.

[0034] The equipment control unit 15 controls the operation of the inspection equipment 60 in accordance with the inspection plan formulated by the inspection plan processing unit 144. The equipment control unit 15 may also acquire sensing data D3 via the communication unit 11 during the inspection period. In this case, if the acquired sensing data D3 value is an abnormal value outside the preset normal range, the equipment control unit 15 may send an emergency stop signal to the inspection equipment 60. Upon receiving the emergency stop signal, the inspection equipment 60 interrupts the inspection and returns to the standby position.

[0035] Next, we will explain the configuration of the inspection equipment 60.

[0036] Figure 4 is a block diagram showing an example configuration of the inspection equipment 60. The inspection equipment 60 shown in Figure 3 is, for example, a multi-rotor drone and includes a positioning unit 61, a distance measuring unit 62, a camera 63, a microphone 64, a drive unit 65, a processing unit 66, a flight controller 67, and a communication unit 68. Note that the inspection equipment 60 is not limited to drones or other unmanned aerial vehicles, but may also be, for example, a mobile robot.

[0037] The positioning unit 61 receives position data transmitted from, for example, GPS (Global Positioning System) or GNSS (Satellite positioning, navigation and timing system). The positioning unit 61 also periodically transmits the received position data to the flight controller 67.

[0038] The distance measuring unit 62 measures, for example, the distance to the main engine 30 and auxiliary engine 40 that are being inspected. The distance measuring unit 62 is composed of, for example, a 3D LiDAR (Light Detection And Ranging). The 3D LiDAR measures the time from when a laser beam is emitted from a light source until the laser beam reflected by an object is received by a light receiving unit, and calculates the distance to the main engine 30 and auxiliary engine 40 based on the measured time. The distance measuring unit 62 periodically transmits data indicating the calculation result to the processing unit 66. The distance measuring unit 62 is used to ensure that the inspection equipment 60 avoids collisions with the main engine 30 and auxiliary engine 40 and maintains a constant distance. However, in this embodiment, as will be described later, the flight path of the inspection equipment 60 is set so as not to collide with the wind turbine, so the distance measuring unit 62 does not need to be provided on the inspection equipment 60.

[0039] Camera 63 can photograph the main unit 30 and the auxiliary unit 40. Camera 63 periodically transmits image data showing the captured image to the processing unit 66.

[0040] The microphone 64 can measure the sounds generated by the main unit 30 and the auxiliary unit 40. The microphone 64 periodically transmits acoustic data indicating the measured sounds to the processing unit 66.

[0041] The drive unit 65 consists of several components necessary for driving the inspection equipment 60. These components include, for example, a storage battery, a motor that rotates using power supplied from the storage battery, an ESC (Electric Speed ​​Controller) that controls the motor's rotation speed, and a propeller connected to the motor.

[0042] The processing unit 66 processes various data acquired from the distance measuring unit 62, the camera 63, and the microphone 64. The processing unit 66 is composed of, for example, a computer that processes data according to a predetermined program.

[0043] The flight controller 67 determines the current position of the inspection equipment 60 based on position data from the positioning unit 61. The flight controller 67 also controls the drive unit 65 to make the inspection equipment 60 fly based on instructions from the processing unit 66.

[0044] The communication unit 68 communicates data with the equipment control unit 15 of the wind turbine monitoring device 10. The communication unit 68 receives inspection control data from the equipment control unit 15, which indicates the inspection route of the inspection equipment 60. The communication unit 68 also transmits inspection data, including image data and acoustic data of the equipment to be inspected, to the equipment control unit 15. The transmitted inspection data is displayed on the display unit 13.

[0045] Next, we will explain how the wind turbine 20 is monitored by the wind turbine monitoring device 10.

[0046] Figure 5 shows a flowchart of the monitoring method for the wind turbine 20. In this flowchart, first, the communication unit 11 receives weather forecast data D1, operation data D2, and sensing data D3 (step S11). The received weather forecast data D1, operation data D2, and sensing data D3 are stored in the weather forecast database 121, operation database 122, and sensing database 123 of the storage unit 12, respectively.

[0047] Next, the data processing unit 14 uses the weather forecast data D1, the operation data D2, and the sensing data D3 to determine whether or not the operating state of the wind turbine 20 is maintained (step S102).

[0048] In step S102, first, the wind condition forecasting processing unit 141 performs the wind condition forecasting process described above. Subsequently, the power output forecasting processing unit 142 performs the power output forecasting process described above.

[0049] Next, the determination processing unit 143 determines, based on the value of the sensing data D3, whether the wind turbine 20 is currently operating, i.e., generating power. For example, the determination processing unit 143 determines that the wind turbine 20 is generating power if the value of the sensing data D3 of the main unit 30 is within a predetermined range, and determines that power generation is stopped if it is outside the predetermined range.

[0050] If the wind turbine 20 is generating power, the determination processing unit 143 calculates the amount of power generated under the wind speed conditions from the present to the future, as shown in the wind condition forecast result of the wind condition forecast processing unit 141. At this time, the determination processing unit 143 calculates the amount of power generated using, for example, a pre-set conversion formula between wind speed and power generation. Subsequently, the determination processing unit 143 compares the calculated amount of power generated with the amount of power generated shown in the operation data D2. If the difference between these two amounts of power generated is within a predetermined allowable range, the determination processing unit 143 determines that the power output of the wind turbine 20 is maintained above a certain level and selects the main unit 30 as the equipment to be inspected (step S103).

[0051] If the wind turbine 20 is not generating power, inspecting the main unit 30 will not provide useful inspection data for identifying equipment abnormalities. Furthermore, for example, if the wind condition forecast by the wind condition forecasting processing unit 141 predicts a significant decrease in wind speed from the current point in time, the calculated power generation may be significantly lower than the power generation shown in the operating data D2. In this case, there is a high probability that the operating state of the wind turbine 20 will change from a power generation state to a power generation stop state at the start of the inspection. Therefore, in this case as well, it will not be possible to obtain useful inspection data for inspecting the main unit 30.

[0052] Therefore, if the determination processing unit 143 determines that the current state of the wind turbine 20 is in a power generation stop state, or if it determines that the power generation output of the wind turbine 20 is not maintained above a certain level, it determines whether or not the auxiliary equipment 40 is in operation (step S104).

[0053] Even when the wind turbine 20 is in a power generation-stopped state, the yaw motor of the yaw control equipment 411, the hydraulic pump of the hydraulic equipment 412, and the cooling water pump motor of the cooling equipment 413 may still be operating. Therefore, the determination processing unit 143 determines that the auxiliary equipment 40 is operating if the value of the sensing data D3 of the auxiliary equipment 40 exceeds a standard value, and determines that the auxiliary equipment 40 is in a stopped state if it is not.

[0054] If the determination processing unit 143 determines that the auxiliary equipment 40 is in operation, it selects the auxiliary equipment 40 as the equipment to be inspected (step S105).

[0055] Next, the inspection planning processing unit 144 formulates an inspection plan for the equipment selected in step S103 or step S105 (step S106). If the equipment to be inspected is the main unit 30, the inspection planning processing unit 144 sets the inspection route for the main unit 30 and outputs the set inspection route to the equipment control unit 15. On the other hand, if the equipment to be inspected is the auxiliary unit 40, the inspection planning processing unit 144 sets the inspection route for the auxiliary unit 40 and outputs the set inspection route to the equipment control unit 15.

[0056] When setting up an inspection route, the inspection planning processing unit 144 calculates the probability of operation for multiple inspection target equipment using, for example, past sensing data D3 stored in the sensing database 123. The probability of operation is the percentage of correct answers for determining whether each point-verified equipment is operating or stopped, calculated from all the sensing data D3 stored in the sensing database 123 and past power output prediction results.

[0057] Next, the inspection planning processing unit 144 sets an inspection route to inspect equipment with a high probability of operation. For example, if the equipment to be inspected is the main engine 30, and the probability of operation decreases in the order of main bearing 311, speed increaser 312, generator 313, and PCS 314, the inspection planning processing unit 144 sets an inspection route that inspects in this order, or sets a route that does not inspect equipment with a low probability of operation. On the other hand, if the equipment to be inspected is the auxiliary equipment 40, and the probability of operation decreases in the order of yaw control equipment 411, hydraulic equipment 412, and cooling equipment 413, the inspection planning processing unit 144 sets an inspection route that inspects in this order, or sets a route that does not inspect equipment with a low probability of operation.

[0058] As described above, by prioritizing the inspection order for equipment with a high probability of malfunction, useful inspection data can be efficiently acquired, and equipment failures can be detected.

[0059] According to the embodiment described above, the data processing unit 14 identifies the future operating state of the wind turbine 20 and selects the equipment to be inspected from the main unit 30 and auxiliary equipment 40 according to the identified operating state. As a result, the equipment to be inspected that is most suitable for inspection according to the operating state of the wind turbine 20 is selected, making it possible to properly inspect the wind turbine 20.

[0060] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of Symbols]

[0061] 1: Wind turbine monitoring system 10: Wind turbine monitoring device 20: Windmill 23: Nasser 30: Main engine 40: Auxiliary equipment 60: Inspection equipment 141: Wind Condition Prediction Processing Unit 142: Power output prediction processing unit 143: Determination Processing Unit 144: Inspection Planning Processing Unit

Claims

1. A wind turbine monitoring device having multiple devices and a nacelle housing the multiple devices, A wind condition prediction processing unit that predicts future wind conditions at the wind turbine installation site, A power output prediction processing unit that predicts the future power generation status of the wind turbine, A determination processing unit that uses sensing data obtained from sensing the multiple devices, the wind condition prediction results, and the operating condition prediction results to identify the future operating state of the multiple devices, and selects a device to be inspected from among the multiple devices according to the identified operating state, A wind turbine monitoring device equipped with the following features.

2. The aforementioned plurality of devices consist of a main engine and auxiliary engines that assist the main engine, which are arranged around a rotor shaft that transmits rotational energy converted from wind flow energy. The wind turbine monitoring device according to claim 1, wherein the determination processing unit selects the equipment to be inspected as the main unit or the auxiliary unit according to the identified operating state.

3. The wind turbine monitoring device according to claim 2, wherein the determination processing unit selects the main unit as the equipment to be inspected when the power output of the wind turbine is maintained above a certain level.

4. The wind turbine monitoring device according to claim 2, wherein the determination processing unit determines whether or not to select the equipment to be inspected as the auxiliary equipment based on the value of the sensing data of the auxiliary equipment when the wind turbine is not generating power or when the power output of the wind turbine is not maintained at a constant level.

5. The wind turbine monitoring device according to claim 1, further comprising an inspection planning processing unit that sets an inspection route for the equipment to be inspected selected by the determination processing unit.

6. The wind turbine monitoring device according to claim 5, wherein the inspection planning processing unit calculates the probability of operation of each of the multiple inspection target devices using the sensing data and sets an inspection route for inspecting the inspection target devices with a high probability of operation.

7. A wind turbine monitoring system having multiple devices and a nacelle housing the multiple devices, The system comprises a wind turbine monitoring device and an inspection device that inspects the plurality of devices based on the control of the wind turbine monitoring device, The wind turbine monitoring device, A wind condition prediction processing unit that predicts future wind conditions at the wind turbine installation site, A power output prediction processing unit that predicts the future power generation status of the wind turbine, A determination processing unit that uses sensing data obtained from sensing the multiple devices, the wind condition prediction results, and the operating condition prediction results to identify the future operating state of the multiple devices, and selects a device to be inspected from among the multiple devices according to the identified operating state, A wind turbine monitoring system.

8. The wind turbine monitoring system according to claim 7, wherein the inspection equipment includes a microphone for measuring the sound generated by the plurality of devices.

9. A method for monitoring a wind turbine having multiple devices and a nacelle housing the multiple devices, Predicting future wind conditions at the aforementioned wind turbine installation site, We predict the future power generation status of the aforementioned wind turbines, Using the sensing data obtained from sensing the multiple devices, the wind condition prediction results, and the operating condition prediction results, the future operating state of the multiple devices is identified. In accordance with the identified operating conditions, the equipment to be inspected is selected from among the aforementioned multiple devices. Wind turbine monitoring method.

10. A process for predicting future wind conditions at the installation site of a wind turbine having multiple devices and a nacelle housing the multiple devices, A process for predicting the future power generation status of the aforementioned wind turbine, A process to identify the future operating state of the multiple devices using sensing data obtained from sensing the multiple devices, the wind condition prediction results, and the operating condition prediction results. A process to select the equipment to be inspected from among the multiple equipment according to the identified operating conditions, A program that causes a computer to execute something.

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