Information processing device and information processing method

Abstract

A calculation device (102) identifies the type of a second anomaly. The calculation device determines a maintenance schedule for the second anomaly on the basis of the type of the second anomaly. The communication interface (106) outputs the maintenance schedule.

Description

Information processing device and information processing method

[0001] The present disclosure relates to an information processing device and an information processing method.

[0002] For example, Japanese Patent Laid-Open Publication No. 2013-185507 (Patent Document 1) discloses a condition monitoring system for a wind turbine generator. This condition monitoring system includes a sensor that detects a physical quantity (e.g., vibration value) at a target position of the wind turbine generator. The condition monitoring system diagnoses whether or not there is an abnormality in the wind turbine generator based on the physical quantity detected by the sensor. The condition monitoring system then displays the diagnosis result on a display unit of a monitoring terminal. The manager of the wind turbine generator or the like can then visually confirm the diagnosis result.

[0003] JP 2013-185507 A

[0004] In the above-mentioned condition monitoring system, the diagnosis result may indicate that a serious abnormality has been detected in the power generation equipment. In this case, if the manager who has been notified of the diagnosis result has little maintenance experience, the manager may not be able to determine whether maintenance is necessary or when to schedule the maintenance.

[0005] The present disclosure has been made to solve the above-mentioned problem, and its purpose is to quickly determine a maintenance schedule for a power generation device when a highly abnormal condition is detected in the device.

[0006] The information processing device disclosed herein is a device related to a power generation device. The power generation device includes a sensor that detects a physical quantity related to the operation of the power generation device. The information processing device includes an interface and a calculation device. The calculation device identifies a first abnormality in the power generation device when the physical quantity satisfies a first condition. The calculation device identifies a second abnormality in the power generation device that is more abnormal than the first abnormality when the physical quantity satisfies a second condition. The calculation device identifies a type of the second abnormality. The calculation device determines a maintenance schedule for the second abnormality based on the type of the second abnormality. The interface outputs the maintenance schedule.

[0007] The information processing method disclosed herein includes identifying a first abnormality of the power generation device when a physical quantity related to operation of the power generation device satisfies a first condition. The information processing method includes identifying a second abnormality of the power generation device, the second abnormality being more abnormal than the first abnormality, when the physical quantity satisfies a second condition. The information processing method includes identifying a type of the second abnormality. The information processing method includes determining a maintenance schedule for the power generation device based on the type of the second abnormality. The information processing method includes outputting the maintenance schedule.

[0008] According to the present disclosure, when a highly abnormal condition is detected in a power generation device, a maintenance schedule for the abnormal condition can be determined quickly.

[0009] FIG. 1 is a diagram illustrating an example of a configuration of a management system of the present disclosure. FIG. 2 is a diagram illustrating an abnormality in a wind power generation device. FIG. 3 is a functional block diagram of a monitoring device. FIG. 4 is a diagram illustrating an example of a first DB. FIG. 5 is a diagram illustrating an example of a second DB. FIG. 6 is a diagram illustrating an example of a third DB. FIG. 7 is a diagram illustrating an example of a first report. FIG. 8 is a diagram illustrating an example of a second report. FIG. 9 is a diagram illustrating an example of a screen displayed on an operator terminal. FIG. 10 is a diagram illustrating change control of a second threshold. FIG. 11 is a flowchart illustrating main processing of the monitoring device. FIG. 12 is a flowchart illustrating main processing of an operator terminal and the monitoring device. FIG. 13 is a functional block diagram of a monitoring device of another embodiment.

[0010] 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 description thereof will not be repeated.

[0011] First Embodiment Fig. 1 is a diagram illustrating an example configuration of a management system 10 according to the present disclosure. The management system 10 according to the present disclosure includes M (M is an integer equal to or greater than 1) power generation units 45, a monitoring device 100, a user terminal 50, a worker terminal 60, a maintenance terminal 70, a weather server 80, and a network NW. In the example of Fig. 1, the power generation unit 45 and the power generation unit 45A are illustrated as examples of the M power generation units. The control devices 40 and 40A, which will be described later, the monitoring device 100, the user terminal 50, the worker terminal 60, the maintenance terminal 70, and the weather server 80 can communicate with each other via the network NW.

[0012] The M power generation units 45 are related to one another. More specifically, the wind power generation devices of the M power generation units 45 are related to one another. Here, "related" mainly means that the M wind power generation devices 20 have the same configuration. As a variant, "related" may mean at least one of "the M wind power generation devices 20 start operation at the same time" and "they are installed at the same site (for example, the same wind farm)."

[0013] The power generation unit 45 includes a wind power generation device 20, a collecting device 30, a control device 40, and N (N is an integer equal to or greater than 1) vibration sensors Sn (n=1, . . . , N, N is an integer equal to or greater than 1). The power generation unit 45A includes a wind power generation device 20A, a collecting device, a control device 40A, and multiple vibration sensors. Note that the collecting device and multiple sensors of the power generation unit 45A are not shown in FIG. 1 .

[0014] The wind turbine generator 20 corresponds to the "power generation device" in the present disclosure. The wind turbine generator 20A corresponds to the "other power generation device" in the present disclosure. The operator terminal 60 corresponds to the "predetermined terminal" in the present disclosure.

[0015] The wind power generation device 20 is a device that receives wind power and generates electricity. The wind power generation device 20 includes a bearing unit, a generator, and the like. Each of the vibration sensors Sn detects vibration values ​​at a predetermined monitoring target location (e.g., a bearing unit) of the wind power generation device 20. The vibration values ​​correspond to the "physical quantity" in the present disclosure. The vibration values ​​are expressed, for example, by any of the displacement, speed, and acceleration of the monitoring target location. The vibration values ​​detected by the N vibration sensors Sn are output to the collection device 30. The collection device 30 collects the vibration values ​​detected by the vibration sensors Sn. The "vibration values ​​detected by the vibration sensors Sn" correspond to the "physical quantity related to the operation of the power generation device" in the present disclosure.

[0016] The vibration values ​​collected by the collection device 30 are output to the control device 40. The control device 40 detects the presence or absence of an abnormality in the wind turbine generator 20 and the location of the abnormality based on the vibration values ​​(time-series data) from the collection device 30. The control device 40 may also generate a frequency spectrum by performing a fast Fourier transform (FFT) on the vibration values ​​(time-series data) accumulated over a predetermined period (e.g., one month). The control device 40 may then detect the presence or absence of an abnormality in the wind turbine generator 20 and the location of the abnormality based on the frequency spectrum.

[0017] In this way, the physical quantity (vibration value) is used to identify the presence or absence of an abnormality in the wind turbine generator 20. In this embodiment, the control device 40 executes an abnormality detection process to detect the presence or absence of an abnormality in the wind turbine generator 20. However, as a modified example, the monitoring device 100 may execute the abnormality detection process.

[0018] In this embodiment, "abnormality" refers to, for example, damage to the wind turbine generator 20. In addition, in this embodiment, "abnormal location" includes not only a location where an abnormality has actually occurred, but also a location where an abnormality is estimated and a location where an abnormality is predicted. An abnormality prediction location is a location where no abnormality has occurred at the present time, but where an abnormality is predicted to occur in the future.

[0019] Each of the M wind power generation devices 20 is assigned a wind power generation device ID (identification) for identifying the wind power generation device 20. Each vibration sensor Sn is assigned a vibration sensor ID for identifying the vibration sensor.

[0020] When the control device 40 detects an abnormality in the wind turbine generator 20, it transmits abnormality information to the monitoring device 100. The abnormality information includes the wind turbine generator ID of the wind turbine generator 20 in which the abnormality has occurred, abnormality level information, and abnormality type information.

[0021] The abnormality level information indicates whether the abnormality that has occurred is a first abnormality or a second abnormality, which will be described later. The abnormality type information indicates the abnormal location and the type of abnormality (damage, etc.). The abnormality type information is, for example, an abnormality type ID, which will be described later.

[0022] The user terminal 50 is a terminal device owned by a user A. "User A" is typically a person who owns a wind power generation device 20, such as a power generation company. The user terminal 50 is typically a mobile terminal that can be carried by the user A. The user terminal 50 may also be a dedicated computer terminal.

[0023] The maintenance terminal 70 is a terminal owned by a maintenance company of the wind power generation device 20 and is operated by a maintenance manager D of the maintenance company. The maintenance terminal 70 is a terminal related to the maintenance of the wind power generation device 20. "Maintenance" in the present disclosure includes inspection of abnormal parts of the wind power generation device 20 and repair of the abnormal parts. The maintenance terminal 70 corresponds to the "terminal of the worker performing maintenance" in the present disclosure.

[0024] The maintenance terminal 70 is, for example, a terminal that receives the maintenance request. Specifically, when the monitoring device 100 identifies a second abnormality, which will be described later, it transmits maintenance information for requesting maintenance to the maintenance terminal 70. The maintenance information includes the address of the wind power generation device 20 that is the maintenance target, the date and time of maintenance, etc. The monitoring device 100 transmits the maintenance information to the maintenance terminal 70 to request a maintenance company to perform maintenance on the wind power generation device 20.

[0025] The display unit of the maintenance terminal 70 displays a request image based on the maintenance information. Manager D, who has viewed the request image, arranges for worker B to arrive at the address and on the date and time displayed in the request image. "Worker B" typically refers to a person who will perform maintenance on the abnormality of the wind turbine generator 20.

[0026] The worker terminal 60 is a terminal device held by a worker B who is dispatched to the wind power generation device 20. The worker terminal 60 is typically a mobile terminal that can be carried by the worker B. The worker B inputs maintenance result information (described later) into the worker terminal 60.

[0027] The weather server 80 outputs meteorological information for the location where the wind turbine generator 20 is installed to the monitoring device 100. The meteorological information is information that indicates the weather from the present to the future at the location where the wind turbine generator 20 is installed, and includes, for example, wind speed and probability of precipitation.

[0028] The monitoring device 100 is a terminal held by the manager of the M wind power generation devices 20. The monitoring device 100 corresponds to the "information processing device related to power generation devices" of the present disclosure. The monitoring device 100 determines maintenance schedules, as will be described later. The monitoring device 100 has a calculation device 102, a memory 104, and a communication interface 106. The communication interface is denoted as "communication I / F" in FIG. 1. The calculation device 102 executes various processes and calculations. The components are interconnected by a data bus. The memory 104 includes a ROM (Read Only Memory), a RAM (Random Access Memory), and the like.

[0029] The arithmetic device 102 is configured with a central processing unit (CPU), a field-programmable gate array (FPGA), a graphics processing unit (GPU), etc. The arithmetic device 102 may be configured with at least one of a CPU, an FPGA, and a GPU. The arithmetic device 102 may also be configured with processing circuitry. The arithmetic device 102 is also referred to as "at least one processor" or "arithmetic circuitry."

[0030] The memory 104 includes a volatile storage area (e.g., a working area) that temporarily stores program code, work memory, etc. when the arithmetic unit 102 executes any program. For example, the memory 104 includes a random access memory (RAM) and a read-only memory (ROM).

[0031] The ROM stores programs executed by the arithmetic device 102. The RAM temporarily stores data generated by the execution of the programs in the arithmetic device 102. The RAM can function as a temporary data memory used as a working area.

[0032] The communication interface 106 is configured to communicate with devices external to the monitoring device 100 (such as the control device 40).

[0033] [Regarding Abnormalities] Next, an abnormality in the wind turbine generator 20 will be described. Fig. 2 is a diagram for explaining an abnormality in the wind turbine generator 20. The vertical axis of Fig. 2 represents a vibration value V detected by an arbitrary vibration sensor among the vibration sensors Sn, and the horizontal axis represents time t.

[0034] In this embodiment, two thresholds Th1 and Th2 are defined for the physical quantity (vibration value), where Th1<Th2. In this embodiment, the smaller the vibration value V, the better, and the larger the vibration value V, the greater the degree of abnormality.

[0035] In the example of Fig. 2, 0 <= vibration value V < Th1 is set as the normal range. Furthermore, Th1 <= vibration value V < Th2 is set as the first abnormal range. Furthermore, Th2 <= vibration value V is set as the second abnormal range. Note that the first abnormal range may be further divided into multiple ranges.

[0036] When the vibration value V falls within the normal range (less than the threshold value Th1), the control device 40 determines that the location corresponding to the vibration sensor that detected the vibration value V is normal. When the vibration value V falls within the first abnormal range (Th1≦vibration value V<Th2), the control device 40 determines that the location corresponding to the vibration sensor that detected the vibration value V has a first abnormality. When the vibration value V falls within the second abnormal range (Th2≦vibration value V), the control device 40 determines that the location corresponding to the vibration sensor that detected the vibration value V has a second abnormality.

[0037] The vibration value V belonging to the first abnormal range corresponds to an example of "the physical quantity satisfies the first condition" in the present disclosure, and the vibration value V belonging to the second abnormal range corresponds to an example of "the physical quantity satisfies the second condition" in the present disclosure.

[0038] Here, the second abnormality is of a greater degree than the first abnormality. A greater degree of abnormality means, for example, greater damage. If the operation of the wind turbine generator 20 continues while the second abnormality of the wind turbine generator 20 remains, an event such as the wind turbine generator 20 becoming inoperable may occur.

[0039] Therefore, if a second abnormality occurs in the wind turbine generator 20, it is preferable to perform maintenance (emergency maintenance) for the second abnormality as soon as possible. However, even if the monitoring device 100 notifies a manager C or a user A, etc. (hereinafter simply referred to as "manager C, etc.") of the wind turbine generator 20 that a second abnormality has occurred in the wind turbine generator 20, if the manager C, etc. does not have maintenance knowledge, the manager C, etc. will not be able to determine whether or not to perform emergency maintenance. Furthermore, even if the manager C, etc. considers whether or not to perform emergency maintenance and then decides to perform emergency maintenance, the emergency maintenance may be delayed for the period of time the manager C, etc. is considering it, which may result in an increase in the number of second abnormalities.

[0040] Therefore, in this embodiment, when a second abnormality is detected in the wind power generation device 20, the monitoring device 100 determines a maintenance schedule for the second abnormality and outputs the maintenance schedule. In this way, the monitoring device 100 can determine the maintenance schedule by itself without relying on the judgment of the manager C or the like, and therefore the maintenance schedule can be determined quickly.

[0041] [Functional Block Diagram of Monitoring Device 100] Fig. 3 is a functional block diagram of the monitoring device 100. The monitoring device 100 has a receiving unit 112, a processing unit 114, a transmitting unit 116, and a storage unit 118. The receiving unit 112 and the transmitting unit 116 correspond to the communication interface 106 in Fig. 1. The processing unit 114 corresponds to the arithmetic unit 102 in Fig. 1. The storage unit 118 corresponds to the memory 104, and at least a portion of the storage area of ​​the memory 104 is used.

[0042] The receiving unit 112 acquires the above-mentioned abnormality information from the control device 40. Furthermore, the receiving unit 112 receives maintenance result information (described later) from the worker terminal 60. The monitoring device 100 is capable of transmitting a weather request signal to the weather server 80. Upon receiving the weather request signal, the weather server 80 transmits weather information to the monitoring device 100. The receiving unit 112 acquires the weather information transmitted from the weather server 80. The information received by the receiving unit 112 is output to the processing unit 114.

[0043] The storage unit 118 stores a threshold value 121 , a past operating record 131 , a first database (DB) 141 , a second database (DB) 142 , and a third database (DB) 143 .

[0044] The threshold value 121 is a first threshold value Th1 and a second threshold value Th2 (see FIG. 2 ) for a plurality of monitoring target locations of each of the M wind power generation devices 20. The past operating results are information indicating the operating results of each of the M wind power generation devices 20 over a predetermined period of time in the past (for example, one year). The operating results include, for example, the amount of power generated by the wind power generation device 20 and the rotation speed of the wind turbine of the wind power generation device 20. The first DB 141, the second DB 142, and the third DB 143 will be described later.

[0045] The processing unit 114 determines that a first abnormality has occurred when the abnormality level information in the abnormality information acquired from the control device 40 indicates a first abnormality. That is, the processing unit 114 determines that a first abnormality has occurred in the wind turbine generator 20 when the vibration value falls within a first range. Then, the processing unit 114 generates a first report, which will be described later.

[0046] Furthermore, when the abnormality level information of the abnormality information acquired from the control device 40 indicates a second abnormality, the processing unit 114 determines that a second abnormality has occurred. That is, the processing unit 114 determines a second abnormality in the wind turbine generator 20 when the vibration value falls within a second range. Then, the processing unit 114 determines a maintenance schedule using predetermined information described below. Furthermore, the processing unit 114 generates a second report including the determined maintenance schedule.

[0047] Note that maintenance in response to the first abnormality is typically a simple procedure such as an endoscopic inspection or greasing, whereas maintenance in response to the second abnormality (emergency maintenance) is a large-scale procedure such as replacing parts such as bearings.

[0048] The transmission unit 116 displays the reports (first report and second report) generated by the processing unit 114 on a display (not shown) of the monitoring device 100. This allows the monitoring device 100 to allow the administrator C to recognize the contents of the reports.

[0049] Furthermore, the transmission unit 116 transmits the report generated by the processing unit 114 to the user terminal 50 corresponding to the wind turbine generator ID for which it has been determined that an abnormality has been detected based on the anomaly information (see FIG. 8 described later). This allows the monitoring device 100 to make the user A aware of the report.

[0050] 4 is a diagram illustrating an example of the first DB 141. Wind turbine generator IDs and user terminal IDs are associated with each other in the first DB 141. For example, a wind turbine generator ID: W1 is associated with a user terminal ID: U1.

[0051] The processing unit 114 identifies the user terminal ID corresponding to the wind turbine generator ID included in the anomaly information by referring to the first DB, and then transmits the generated report to the user terminal 50 with the identified user terminal ID.

[0052] 5 is a diagram illustrating an example of the second DB 142. The second DB 142 is a database related to maintenance. In the second DB 142, for each abnormality type ID, the type of maintenance, the period required for the maintenance, the number of workers required for the maintenance, the estimated cost, and the parts used are associated with each other.

[0053] The abnormality type ID is information for identifying the location and type of abnormality. The maintenance content is the content of the maintenance to repair the abnormality indicated by the abnormality type ID. The maintenance content includes, for example, repairing bearing parts and changing lubricating oil. The "period required for maintenance" is, for example, the period from the start to the end of the maintenance. The "number of workers required for maintenance" is, for example, the number of workers required for the maintenance. The "estimated cost" is, for example, the estimated cost of the maintenance. The "parts used" is the type and number of parts (for example, consumables) required for the maintenance.

[0054] 5, for example, A1 is associated with the abnormality type ID: X1 as the "contents required for maintenance," and B1 days is associated with the "period required for maintenance." Also, C1 person is associated with the abnormality type ID: X1 as the "number of workers required for maintenance," D1 yen is associated with the "estimated cost," and M1 is associated with the "parts used."

[0055] 6 is a diagram showing an example of the third DB 143. The third DB 143 is a database for checking the availability (schedule) of workers. In the third DB 143, availability is associated with each worker ID. The worker ID is identification information assigned in association with each of all workers who perform maintenance on the wind turbine generator 20. All of the workers belong to the maintenance company described above.

[0056] The processing unit 114 determines a schedule for maintenance (maintenance schedule) for repairing the second abnormality using the type of the second abnormality (abnormality type ID) and predetermined information. This predetermined information includes at least one of (a) the period required for maintenance, (b) the number of workers required for maintenance, (c) the schedule of the workers required for maintenance, (d) future weather information for the installation location of the wind turbine generator 20, (e) the past operating record of the wind turbine generator 20, and (f) whether or not there is inventory of parts to be used. In this embodiment, the predetermined information is made up of all of the information (a) to (f).

[0057] When the processing unit 114 determines that a second abnormality has occurred by analyzing the abnormality information, it identifies the abnormality type ID included in the abnormality information.The processing unit 114 then refers to the second DB to identify the type of maintenance corresponding to the abnormality type ID, the period required for the maintenance, the number of workers required for the maintenance, the estimated cost, and the parts used.After identifying the period and number of workers required for the maintenance, the processing unit 114 refers to the third DB 143 to identify the number of workers who are able to perform the maintenance over that period.

[0058] The processing unit 114 also checks whether the identified used parts are in stock, and identifies a period during which the used parts are in stock as a maintenance period.

[0059] The processing unit 114 also transmits the weather request signal to the weather server 80 to obtain and refer to weather information for the location where the wind turbine generator 20 is installed. As described above, the weather information is information indicating the current and future weather conditions at the location where the wind turbine generator 20 is installed, such as wind speed and precipitation probability. Generally, operation of the wind turbine generator 20 is stopped during maintenance periods. Therefore, for example, on days when the wind speed is greater than a predetermined wind volume reference value, the wind turbine generator 20 can generate a large amount of power. Therefore, the processing unit 114 excludes days with high wind speeds from the maintenance schedule. Furthermore, the maintenance burden on worker B is generally greater on rainy days than on sunny days. Furthermore, if the wind turbine generator 20 has an openable roof, the work performed by worker B may include specific tasks that require the roof to be open. In this case, the roof cannot be opened on rainy days, making it difficult for worker B to perform the specific tasks. Therefore, the processing unit 114 excludes from the maintenance schedule any day on which the probability of precipitation is higher than a predetermined probability reference value.

[0060] The processing unit 114 also refers to the past operation record 131 of the wind power generation device 20. For example, assume that the past operation record 131 of the wind power generation device 20 shows that the amount of power generated was high during the period from C to D of month B of year A. It is expected that the amount of power generated will also be high one year from now, from C to D of month B of year A+1 (a period later than the present). Therefore, the processing unit 114 excludes this period from the maintenance schedule.

[0061] As described above, the processing unit 114 determines the maintenance schedule using all of the information (a) to (f). Note that, although the above description mainly describes a configuration in which the processing unit 114 determines the maintenance schedule based on DB information, for example, the processing unit 114 may determine the maintenance schedule using AI (artificial intelligence). For example, the processing unit 114 may output the maintenance schedule by applying anomaly information from the control device 40 to the trained model.

[0062] Returning to Fig. 3 for the explanation, if the processing unit 114 determines that the anomaly information acquired from the control device 40 includes information indicating that a second anomaly has occurred, and if the user A permits emergency maintenance (see step S14 in Fig. 12 described below), the transmission unit 116 transmits the maintenance information to the maintenance terminal 70. The maintenance information includes the address of the wind turbine generator 20 to be maintained, information indicating that emergency maintenance will be performed, the maintenance schedule, and the above-mentioned predetermined information used to determine the maintenance schedule.

[0063] The maintenance terminal 70 displays a request image based on the maintenance information on the display unit of the maintenance terminal 70. This allows the manager D to recognize the address of the wind power generation device 20 to be maintained, information indicating that emergency maintenance will be performed, the maintenance schedule, and the predetermined information used to determine the maintenance schedule.

[0064] [Report] Next, a description will be given of a report generated by the processing unit 114. Fig. 7 is a diagram showing an example of the first report 301. As described above, the processing unit 114 generates the first report 301 when a first abnormality is identified.

[0065] The first report 301 has the title "Normal Report" and includes recommendation information 351. The recommendation information 351 is information indicating that maintenance is recommended in response to the first abnormality. In the example of FIG. 7, the image contains the words "We recommend that you perform maintenance on the bearings during your next inspection."

[0066] FIG. 8 is a diagram showing an example of the second report 302. As described above, the processing unit 114 generates the second report 302 when a second abnormality is identified. The second report 302 has the title "Urgent Report" and includes abnormality type information 361, maintenance content information 362, arrangement information 363, maintenance schedule information 364, and estimate information 365. The abnormality type information 361 is information indicating the type of serious abnormality (second abnormality). In the example of FIG. 8, the abnormality type information 361 is an image of the words "A serious abnormality has been found in the bearing." User A can recognize the type of the second abnormality from the abnormality type information 361.

[0067] The maintenance content information 362 is information indicating the content of the emergency maintenance. In the example of Fig. 8, the maintenance content information 362 is an image of the words "Emergency maintenance must be performed on the bearing." The maintenance content information 362 allows user A to recognize the content of the emergency maintenance.

[0068] The arrangement information 363 is information indicating that emergency maintenance has been arranged. In the example of Fig. 8, the arrangement information 363 is an image of the words "Emergency maintenance has been arranged." The arrangement information 363 allows user A to recognize that emergency maintenance has been arranged.

[0069] The maintenance schedule information 364 is information indicating the maintenance schedule determined by the processing unit 114. In the example of Fig. 8, the maintenance schedule information 364 is an image of the words "A month, B day." The maintenance schedule information 364 allows user A to recognize the maintenance schedule for emergency maintenance.

[0070] The estimate information 365 is information that indicates the estimated cost of emergency maintenance. In the example of Fig. 8, the estimate information 365 is an image of the words "The estimated cost is D1 yen." The estimate information 365 allows user A to recognize the estimated cost of emergency maintenance.

[0071] The user terminal 50 displays the second report and receives from the user A whether or not the emergency maintenance is permitted. If the user A inputs that the emergency maintenance is permitted, the monitoring device 100 transmits the maintenance information to the maintenance terminal 70. On the other hand, if the user A inputs that the emergency maintenance is not permitted, the monitoring device 100 does not transmit the maintenance information to the maintenance terminal 70.

[0072] [Maintenance Result Information] Next, information input to the worker terminal 60 will be described. FIG. 9 shows examples of screens displayed on the worker terminal 60. FIG. 9(A) shows an example of an input screen 401, and FIG. 9(B) shows an example of a transmitted screen 402. For example, worker B or the like performs a predetermined operation on the worker terminal 60, causing the worker terminal 60 to display the input screen 401. In this embodiment, the display control of the input screen 401 is executed under the control of the monitoring device 100. However, as a modified example, the worker terminal 60 may execute the display control of the input screen 401 under the control of the worker terminal 60 itself.

[0073] The input screen 401 displays an image 411 without abnormality, an image 412 with abnormality, an input area 414, and a send button 415. The image 411 without abnormality, the image 412 with abnormality, and the input area 414 are images for inputting maintenance result information by the operator B. In the example of Fig. 9, the operator B can specify either the image 411 without abnormality or the image 412 with abnormality using the radio buttons.

[0074] For example, worker B is dispatched to the wind power generation device 20 that is the target of emergency maintenance, and inspects the location determined to have the second abnormality in the wind power generation device 20. However, when worker B inspects the location determined to have the second abnormality, there may be cases where no abnormality actually occurs in that location. In this case, worker B designates the no-abnormality image 411 and operates the send button 415.

[0075] Furthermore, if worker B determines that an abnormality has occurred as a result of inspecting the location of the wind turbine generator 20 that has been determined to have a second abnormality, worker B designates an abnormality image 412. Furthermore, worker B inputs the details of the emergency maintenance (such as replacing a bearing) in input area 414. Then, worker B operates send button 415.

[0076] When the send button 415 is operated, the worker terminal 60 sends the ID of the wind power generation device to be maintained and the maintenance result information entered on the input screen 401 to the monitoring device 100. At the same time, the worker terminal 60 displays the sent screen of FIG. 9(B). By displaying this sent screen, the worker terminal 60 can recognize that the maintenance result information has been sent to the monitoring device 100. Note that the worker terminal 60 or the monitoring device 100 may also send the maintenance result information entered by worker B to the user terminal 50.

[0077] 9, the monitoring device 100 causes the worker terminal 60 to maintain the display of the input screen 401 until the maintenance result information is input on the input screen 401. In other words, the worker terminal 60 displays the transmitted screen 402 only when the maintenance result information is input on the input screen 401.

[0078] [Changing the Second Threshold Th2] The processing unit 114 ( FIG. 3 ) of the monitoring device 100 executes change control to change the second threshold Th2 based on the maintenance result information transmitted from the operator terminal 60. FIGS. 10 and 11 are diagrams for explaining change control of the second threshold Th2. In this embodiment, either the range greater than the second threshold Th2 or the range smaller than the second threshold Th2 is a detection range in which the second abnormality is detected, and the other is an undetected range in which the second abnormality is not detected. In the example of FIG. 10 , as described in FIG. 2 , the range greater than the second threshold Th2 is a detection range (second abnormal range) in which the second abnormality is detected, and the range smaller than the second threshold Th2 is an undetected range (first abnormal range and normal range) in which the second abnormality is not detected.

[0079] 10A is a diagram showing the second threshold value Th2 before variation control is executed, and FIG. 10B is a diagram showing the second threshold value Th2 after variation control is executed. There is a case where worker B inspects a location determined to have a second abnormality and finds that no abnormality has occurred at that location. In this case, if the second threshold value Th2 is not changed, even if a second abnormality is identified again at that location, there is a high possibility that the result of maintenance (inspection) for the second abnormality will actually be that no abnormality has occurred.

[0080] Therefore, when the maintenance result information indicates that no abnormality has occurred in the wind turbine generator 20 (when the no-abnormality image 411 is specified), the monitoring device 100 increases the second threshold value Th2 as shown in FIG. 10 . In other words, the processing unit 114 executes change control to change the second threshold value Th2 so that it falls within the detection range before the change control. Therefore, the monitoring device 100 can prevent the detection of a second abnormality that indicates that no abnormality has occurred as a result of maintenance (i.e., a false detection). In other words, the monitoring device 100 can prevent excessive maintenance suggestions.

[0081] FIG. 11A shows the second threshold value Th2 before another change control is executed, and FIG. 11B shows the second threshold value Th2 after another change control is executed. When worker B inspects a location determined to have a second abnormality, an abnormality may occur at that location. Generally, maintenance (inspection) of a location where a second abnormality has been identified reveals an abnormality (second abnormality). Even if the abnormality is repaired by maintenance (repair), there is a high possibility that a second abnormality will occur at that location. Therefore, when the maintenance (inspection) reveals an abnormality in the wind power generation device 20 (when an abnormality image 412 is specified), the monitoring device 100 decreases the second threshold value Th2 (changes the second threshold value Th2 so that it falls within the undetectable range) as shown in FIG. 11 . Therefore, the monitoring device 100 can quickly identify a second abnormality (a highly likely abnormality) at a location where a second abnormality has been identified.

[0082] The processing unit 114 may also change the second threshold value Th2 based on other information. For example, worker B performs maintenance on another wind turbine generator 20A and inputs maintenance result information from the input screen 401 in Fig. 9. For example, if the maintenance result information for the other wind turbine generator 20A shows no abnormalities (the no-abnormality image 411 is specified), the processing unit 114 increases the second threshold value Th2 for the wind turbine generator 20 corresponding to this location (see Fig. 10).

[0083] On the other hand, if the maintenance result information for another wind turbine generator 20A indicates an abnormality (the image 412 indicating an abnormality is specified), it is highly likely that an abnormality will occur in the wind turbine generator 20 at the location determined to have the abnormality, and it is preferable that the monitoring device 100 be on guard for an abnormality occurring in the wind turbine generator 20 at that location. Therefore, the processing unit 114 decreases the second threshold value Th2 of the wind turbine generator 20 corresponding to that location (see FIG. 11 ). Therefore, the monitoring device 100 can detect an abnormality in the wind turbine generator 20 that is likely to occur at an early stage. The processing unit 114 transmits the changed second threshold value Th2 to the control device 40 corresponding to the changed second threshold value Th2. The control device 40 updates the second threshold value Th2 to the changed second threshold value Th2.

[0084] 12 is a flowchart showing the main processing of the monitoring device 100. In step S2, the monitoring device 100 determines whether or not abnormality information has been acquired from the control device 40. The monitoring device 100 repeats the processing of step S2 until abnormality information is acquired (NO in step S2).

[0085] When the monitoring device 100 acquires anomaly information (YES in step S2), in step S4, the monitoring device 100 identifies the anomaly type (anomaly type ID) included in the anomaly information. Then, in step S6, the monitoring device 100 references the anomaly level information to identify whether the anomaly that has occurred is a first anomaly or a second anomaly. If in step S6 the anomaly that has occurred is a second anomaly (YES in step S6), the process proceeds to step S8. On the other hand, if in step S6 the anomaly that has occurred is a first anomaly (NO in step S6), the process proceeds to step S18.

[0086] In step S8, the monitoring device 100 determines a schedule for emergency maintenance using the above-mentioned predetermined information, etc. Next, in step S10, the monitoring device 100 generates a second report 302 (see FIG. 8 ). Then, in step S12, the monitoring device 100 transmits the second report 302 to the user terminal 50, etc.

[0087] Furthermore, in step S14, the monitoring device 100 determines whether or not permission for emergency maintenance has been received from the user terminal 50. If permission for emergency maintenance has been received from the user terminal 50 in step S14 (YES in step S14), the monitoring device 100 transmits maintenance information to the maintenance terminal 70 in step S16. On the other hand, if permission for emergency maintenance has not been received from the user terminal 50 (NO in step S14), the processing in FIG. 12 ends.

[0088] In step S18, the monitoring device 100 generates the first report 301 (see FIG. 7). Then, in step S20, the monitoring device 100 transmits the first report 301 to the user terminal 50 or the like. Thereafter, the processing in FIG. 12 ends.

[0089] 13 is a flowchart showing the main processing of the worker terminal 60 and the monitoring device 100. In step S102, the worker terminal 60 determines whether or not the maintenance result information has been input by worker B on the input screen 401 (see FIG. 9A) of the worker terminal 60. The worker terminal 60 repeats the processing of step S102 until the maintenance result information is input (NO in step S102).

[0090] When the maintenance result information is input to the worker terminal 60, in step S104, the worker terminal 60 transmits the maintenance result information to the monitoring device 100. In step S106, the monitoring device 100 determines whether or not the maintenance result information has been received. The monitoring device 100 repeats the process of step S106 until the maintenance result information is received (NO in step S106). Then, in step S108, when the monitoring device 100 receives the maintenance result information, the monitoring device 100 executes change control to change the second threshold value Th2 (see FIGS. 10 and 11 ).

[0091] [Summary] (1) As shown in FIG. 2 and other figures, the monitoring device 100 identifies a first abnormality corresponding to a physical quantity (vibration value) of the wind turbine generator 20 when the physical quantity satisfies a first condition (belongs to a first abnormality range). Furthermore, the monitoring device 100 identifies a second abnormality corresponding to the physical quantity of the wind turbine generator 20 when the physical quantity (vibration value) satisfies a second condition (belongs to a second abnormality range). The second abnormality is more abnormal than the first abnormality. In this embodiment, the monitoring device 100 identifies the first abnormality and the second abnormality based on the abnormality information from the control device 40. Furthermore, the monitoring device 100 identifies the type of the second abnormality (step S4 in FIG. 12 ) and determines a maintenance schedule based on the type of the second abnormality (step S8 in FIG. 12 ). Therefore, when a second abnormality with a higher degree of abnormality than the first abnormality is detected, the monitoring device 100 determines a maintenance schedule for the second abnormality. This allows the monitoring device 100 to quickly determine a maintenance schedule for the second abnormality. Furthermore, the monitoring device 100 can quickly determine a maintenance schedule for the second abnormality without requiring the user A or the administrator C who has been notified of the second abnormality to determine whether maintenance for the second abnormality is necessary, etc. Therefore, the monitoring device 100 can reduce the burden on the user A or the administrator C who has been notified of the second abnormality.

[0092] (2) The monitoring device 100 executes change control (see FIGS. 10 and 11 ) for changing the second threshold value Th2 (second condition) based on the maintenance result information input from the input screen 401 in Fig. 9. Therefore, the monitoring device 100 can reflect the maintenance results in the second threshold value Th2, thereby improving the accuracy of determining the second abnormality.

[0093] (3) As shown in Fig. 9, the monitoring device 100 maintains the display of the input screen 401 until maintenance result information is input on the input screen 401. Therefore, the monitoring device 100 can encourage the input of maintenance result information.

[0094] (4) When the monitoring device 100 identifies a first abnormality, as shown in Fig. 7 , the monitoring device 100 generates a first report 301 including recommendation information 351 indicating that maintenance in response to the first abnormality is recommended, and transmits the first report 301 to the user terminal 50. Thus, the monitoring device 100 can make the user A aware that maintenance in response to the first abnormality is recommended.

[0095] 8, when the monitoring device 100 identifies a second abnormality, it generates a second report 302 and transmits it to the user terminal 50. The second report 302 includes maintenance content information 362 indicating that maintenance will be performed in response to the second abnormality, and maintenance schedule information 364. Therefore, the monitoring device 100 can make user A aware that maintenance will be performed in response to the second abnormality and the maintenance schedule for this maintenance.

[0096] (5) Furthermore, the monitoring device 100 determines the maintenance schedule using the type of the second abnormality and all of the information (a) to (f) above. Therefore, the monitoring device 100 can appropriately determine the maintenance schedule.

[0097] (6) Furthermore, the monitoring device 100 acquires information about abnormalities in the other wind turbine generators 20A and changes the second threshold value Th2 based on the information. Therefore, the monitoring device 100 can improve the accuracy of determining the second abnormality by using the abnormalities in the other wind turbine generators 20A.

[0098] (7) Furthermore, the monitoring device 100 outputs maintenance information indicating that the maintenance will be performed to the maintenance terminal 70 (step S16 in FIG. 12). Therefore, the monitoring device 100 can automatically request the maintenance from the worker B who will perform the maintenance. Therefore, the monitoring device 100 can reduce the burden on the user A of requesting maintenance and can realize emergency maintenance for the second abnormality at an early stage.

[0099] (8) The monitoring device 100 does not need to immediately determine a schedule for maintenance for the first abnormality (maintenance with low urgency). Therefore, if the first abnormality is identified (NO in step S6), the monitoring device 100 does not determine a maintenance schedule in step S8. Therefore, the monitoring device 100 can reduce the processing burden of determining a maintenance schedule.

[0100] Second Embodiment In the following description, it is assumed that the M wind turbine generators include “one power generation unit 45 (first wind power generation unit)” and “another power generation unit 45 (second wind power generation unit).” The “one power generation unit 45” and the “another power generation unit 45” are related to each other.

[0101] In this embodiment, it is assumed that an abnormality is detected in one power generating unit 45. Here, "one power generating unit 45" and "other power generating units 45" are related to each other. Therefore, the same abnormality as that which occurred in one power generating unit 45 tends to occur in the other power generating units 45. Furthermore, even if the abnormality in one power generating unit 45 in which an abnormality was detected is resolved, the same abnormality tends to occur again in the first power generating unit 45.

[0102] In view of this tendency, the monitoring device 100 of this embodiment executes change control to change the monitoring parameters 530 based on abnormality information related to an abnormality in one power generating unit 45. The monitoring parameters 530 are parameters used for monitoring the power generating units 45. The change control is control for improving the accuracy of detecting abnormalities or signs of abnormality in M ​​wind power generating devices including "one power generating unit 45" and "other power generating units 45." The abnormality information is information indicating the location of an abnormality or the location of a sign of abnormality in the power generating unit 45. The abnormality information may also be information used by the monitoring device 100 to identify the location of an abnormality or the location of a sign of abnormality in the power generating unit 45 (for example, the vibration value or supply voltage value described above).

[0103] The first power generating unit 45 and the other power generating units 45 have the following configuration. At least one first sensor (vibration sensor Sn) is disposed in the first power generating unit 45, and the first sensor detects a physical quantity related to the operation of the first power generating unit 45. The other power generating units 45 are also disposed in the second power generating units 45, and the type of physical quantity detected by the at least one first sensor is the same as the type of physical quantity detected by the at least one second sensor. The location of the at least one first sensor in the first power generating unit 45 is the same as the location of the at least one second sensor in the other power generating units 45. The monitoring device 100 detects an abnormality or a sign of an abnormality in the other power generating units 45 based on the physical quantity detected by the at least one second sensor and the monitoring parameters 530 changed by variation control.

[0104] In the second embodiment, an example will be described in which AI is used to control the change of the monitoring parameters 530. The monitoring parameters 530 include, for example, thresholds related to the operation of the power generation unit 45. The thresholds include, for example, thresholds Th1, Th2, and the like.

[0105] FIG. 14 is a functional block diagram of a monitoring device 100 according to this embodiment. As shown in FIG. 14 , the monitoring device 100 includes an estimating unit 1102 in addition to an acquiring unit 522 and a changing unit 526. The memory unit 528 stores a trained model 123 in addition to monitoring parameters 530. The trained model 123 includes a neural network 1211 and parameters 1212. The parameters 1212 are configured by weighting coefficients and judgment values. The trained model 123 is trained by supervised learning, unsupervised learning, or the like. In supervised learning, for example, a combination of anomaly information and monitoring parameters, or a combination of maintenance information (described below) and monitoring parameters, is used as training data.

[0106] The acquisition unit 522 acquires the abnormality information and the maintenance result information from a predetermined terminal. For example, the abnormality information is acquired from the control device 40. The maintenance result information is acquired from the worker terminal 60.

[0107] The estimation unit 1102 estimates the monitoring parameters 530 based on the input data input from the acquisition unit 522 and the trained model 123 including the neural network 1211. The change control is control for changing the monitoring parameters 530 stored in the storage unit 528 to the estimated monitoring parameters 530.

[0108] As shown below, the estimation unit 1102 estimates the monitoring parameters 530 to improve the accuracy of detecting abnormalities or signs of abnormalities in the "other power generating units 45" and the "first power generating unit 45 from which the abnormality has been resolved." A specific description will be given below. The monitoring device 100 starts monitoring the first power generating unit 45 when the amount of power generated by the first power generating unit 45 during a first predetermined period (e.g., one week) is greater than a first threshold. The monitoring device 100 also starts monitoring the other power generating units 45 when the amount of power generated by the other power generating units 45 during the first predetermined period is greater than a second threshold. The monitoring parameters 530 also include a second threshold. The estimation unit 1102 estimates the second threshold (monitoring parameters 530) so that the second threshold is smaller than the first threshold. This configuration can accelerate the timing for starting monitoring the other power generating units 45, thereby enabling earlier detection of abnormalities in the other power generating units 45. This improves the accuracy of detecting abnormalities in the other power generating units 45.

[0109] Furthermore, the monitoring device 100 monitors one power generating unit 45 for each first period. The monitoring device 100 monitors the other power generating units 45 for each second period. The monitoring parameters 530 include the second period. The estimation unit 1102 estimates the second period (monitoring parameters 530) so that the second period is shorter than the first period. With this configuration, the frequency of monitoring the other power generating units 45 is increased, allowing for early detection of abnormalities in the other power generating units 45.

[0110] The monitoring device 100 monitors one power generating unit 45 using the intensity of each first frequency band in the first frequency spectrum of the one power generating unit 45, which is generated based on a physical quantity (e.g., a vibration value) detected by at least one first sensor. The monitoring device 100 monitors the other power generating units 45 using the intensity of each second frequency band in the second frequency spectrum of the other power generating units 45, which is generated based on a physical quantity detected by at least one second sensor. The abnormality information includes an abnormal frequency band in the first frequency spectrum that is a cause of an abnormal location or an abnormality precursor location. The monitoring parameters 530 include a second frequency band. The estimation unit 1102 estimates the second frequency band (monitoring parameters 530) so that the second frequency band, which includes the abnormal frequency band, is narrower than the first frequency band. This configuration improves the resolution of the intensity in the frequency spectrum used to monitor the other power generating units 45, thereby enabling early detection of abnormalities in the other power generating units. Therefore, abnormalities in other power generating units 45 can be detected early.

[0111] The monitoring device 100 also monitors one power generating unit 45 based on a physical quantity detected by at least one first sensor and a third threshold (at least one of thresholds Th1 and Th2). The monitoring device 100 also monitors the other power generating units 45 based on a physical quantity detected by at least one second sensor and a fourth threshold (at least one of thresholds Th1 and Th2). Either a range greater than the third threshold or a range smaller than the third threshold is an undetected range in which no abnormality in one power generating unit 45 is detected. The monitoring parameters 530 include a fourth threshold. The estimation unit 1102 then estimates the fourth threshold (monitoring parameters 530) corresponding to an abnormal location or an abnormality precursor location so that the fourth threshold falls within the undetected range.

[0112] According to this configuration, the threshold value (fourth threshold value) used to monitor the other power generating units 45 is changed to the undetectable range of the third threshold value, so that abnormalities in the other power generating units 45 can be detected early.

[0113] In the above example, the estimation unit 1102 is mainly described as controlling the estimation of the monitoring parameters 530 used for monitoring the other power generating units 45. However, the estimation unit 1102 may be configured to estimate the monitoring parameters 530 used for monitoring one power generating unit 45. With such a configuration, it is possible to improve the accuracy of detecting an abnormality or a sign of an abnormality that may occur again in one power generating unit 45.

[0114] Next, the maintenance result information will be described. The maintenance result information is information that is input by worker C to worker terminal 60. Worker C is the person who performed maintenance on the wind power generation equipment (here, one power generation unit 45) in which an abnormality occurred. The maintenance includes inspection of the wind power generation equipment and repair of the wind power generation equipment. The worker terminal 60 is a terminal (for example, a mobile terminal) held by worker C.

[0115] Next, an example will be described in which the estimation unit 1102 uses the maintenance result information transmitted from the operator terminal 60. When the maintenance result information indicates that no abnormality has occurred in one power generating unit 45 (when the abnormality-free image 411 is specified) or when the maintenance is minor, the estimation unit 1102 estimates monitoring parameters 530 that reduce the accuracy of abnormality detection. The change unit 526 then changes the monitoring parameters 530 to the estimated monitoring parameters 530 (monitoring parameters 530 with reduced accuracy of abnormality detection). Examples of the process of changing the monitoring parameters 530 to the estimated monitoring parameters 530 (the process of estimating the monitoring parameters 530 so as to reduce the accuracy of abnormality detection) include, for example, increasing the second threshold value, lengthening the second period, placing the fourth threshold value within the abnormality range, and widening the second frequency band. This control reduces the amount of calculation required for abnormality detection.

[0116] Furthermore, even if maintenance (inspection) of a location where an abnormality is identified in one power generating unit 45 generally indicates an abnormality, and the abnormality is repaired through maintenance (repair), there is a high possibility that an abnormality will occur in the same location in another power generating unit 45. Therefore, when the maintenance result information indicates that an abnormality has occurred in one power generating unit 45 (when the image 412 indicating an abnormality is specified) or when the maintenance is large-scale maintenance, the estimation unit 1102 estimates monitoring parameters 530 that improve the accuracy of abnormality detection. The change unit 526 then changes the monitoring parameters 530 to the estimated monitoring parameters 530 (monitoring parameters 530 with improved accuracy of abnormality detection). Examples of the process of changing the monitoring parameters 530 to the estimated monitoring parameters 530 include, for example, decreasing the second threshold, shortening the second period, setting the fourth threshold to fall within the normal range, and narrowing the second frequency band. This control enables early detection of abnormalities in other power generating units 45.

[0117] [Modifications] (1) In the above embodiment, the power generation device is a wind power generation device. However, the power generation device may be another type of power generation device. Examples of the other power generation device include a hydroelectric power generation device and a solar power generation device.

[0118] (2) The control for changing the second threshold value Th2 may be other control than the control for directly changing the second threshold value Th2. For example, the control for changing the second threshold value Th2 may include a control for recommending to the administrator C that the second threshold value Th2 be changed.

[0119] The monitoring device 100 may also be configured to change the second threshold value Th2 using maintenance result information and AI. Specifically, the monitoring device 100 applies the maintenance result information to the trained model to output the changed second threshold value Th2. When such a configuration is employed, the change control may be control to update (the parameters of) the trained model. For example, if the maintenance result information indicates that no abnormality is present, the monitoring device 100 executes change control to update the trained model so that the second threshold value Th2 is increased and output. If the maintenance result information indicates that an abnormality is present, the monitoring device 100 executes change control to update the trained model so that the second threshold value Th2 is decreased and output.

[0120] (3) In the above embodiment, as illustrated in FIG. 2 , the first condition is that the physical quantity falls within the first abnormal range, and the second condition is that the physical quantity falls within the second abnormal range. However, at least one of the first condition and the second condition may be other conditions. For example, the first condition may be that the detected physical quantity contains noise of a first peak value, and the second condition may be that the detected physical quantity contains noise of a second peak value greater than the first peak value.

[0121] (4) In the above embodiment, the sensor used to detect the presence or absence of an abnormality in the wind turbine generator 20 is a vibration sensor. However, the sensor may be another sensor. The other sensor may be, for example, a temperature sensor or a sound sensor.

[0122] [Notes] (Note 1) An information processing device relating to a power generation unit, the power generation unit including a sensor for detecting a physical quantity related to the operation of the power generation unit, the information processing device including an interface and a calculation device, the calculation device identifying a first abnormality of the power generation unit when the physical quantity satisfies a first condition, identifying a second abnormality of the power generation unit that is more abnormal than the first abnormality when the physical quantity satisfies a second condition, identifying a type of the second abnormality, and determining a maintenance schedule for the second abnormality based on the type of the second abnormality, and the interface outputting the maintenance schedule.

[0123] With this configuration, when a second abnormality that is more severe than the first abnormality is identified, the information processing device determines a maintenance schedule for the second abnormality, thereby enabling the information processing device to quickly determine a maintenance schedule for the second abnormality.

[0124] (Supplementary Note 2) The information processing device according to Supplementary Note 1, wherein the interface acquires a result of the maintenance from a predetermined terminal, and the arithmetic device executes change control to change the second condition based on the result of the maintenance.

[0125] According to this configuration, the results of maintenance can be reflected in the second condition, thereby improving the accuracy of determining the second abnormality.

[0126] (Supplementary Note 3) An information processing device as described in Supplementary Note 2, wherein a threshold value is defined for the physical quantity, and either a range greater than the threshold value or a range smaller than the threshold value is a detection range in which the second abnormality is detected, and the other is an undetected range in which the second abnormality is not detected, and when the physical quantity falls within the detection range, the physical quantity satisfies the second condition, and when the result of the maintenance is that no abnormality has occurred in the power generation unit, the calculation device executes control to change the threshold value so that it falls within the detection range as the change control.

[0127] Generally, the results of maintenance for a location where a second abnormality was identified may result in no abnormality occurring. In this case, even if a second abnormality is identified again for that location, the results of maintenance for the second abnormality are likely to result in no abnormality occurring. Therefore, with this configuration, when the results of maintenance show that no abnormality has occurred in the power generation unit, control is performed to change the threshold so that the threshold falls within the detection range. Therefore, the information processing device can prevent the detection of a second abnormality for which the results of maintenance show that no abnormality has occurred.

[0128] (Supplementary Note 4) The information processing device described in Supplementary Note 2, wherein a threshold value is defined for the physical quantity, and either a range greater than the threshold value or a range smaller than the threshold value is a detection range in which the second abnormality is detected, and the other is an undetected range in which the second abnormality is not detected, and when the physical quantity falls within the detection range, the physical quantity satisfies the second condition, and when the result of the maintenance shows that an abnormality has occurred in the power generation unit, the calculation device executes at least one of the following as the change control: control to change the threshold value so that it falls within the undetected range.

[0129] Generally, if maintenance of a location where a second abnormality has been identified results in an abnormality (second abnormality), and even if the abnormality is repaired, there is a high possibility that a recurrence of an abnormality will occur in that location. Therefore, with this configuration, if the maintenance results in an abnormality occurring in the power generation unit, control is performed to change the threshold value so that the threshold value falls within the undetectable range. Therefore, the information processing device can quickly identify a recurrence of an abnormality in the location where a second abnormality has been identified.

[0130] (Supplementary Note 5) The information processing device according to any one of Supplementary Notes 2 to 4, wherein the arithmetic device displays an input screen on the specified terminal for accepting input of the results of the maintenance, and maintains display of the input screen until the results of the maintenance are input on the input screen.

[0131] According to this configuration, it is possible to encourage input of maintenance results. (Supplementary Note 6) The information processing device according to any one of Supplementary Notes 1 to 5, wherein the arithmetic device generates a first report when the first abnormality is identified and transmits the first report to a user terminal of a user of the power generating unit, generates a second report when the second abnormality is identified and transmits the second report to the user terminal, the first report including information indicating that the maintenance corresponding to the first abnormality is recommended, and the second report including information to perform the maintenance corresponding to the second abnormality and the maintenance schedule.

[0132] With this configuration, the information processing device can make the user of the power generating unit aware, via the first report, that maintenance in response to the first abnormality is recommended, and can also make the user aware, via the second report, that maintenance in response to the second abnormality will be performed and the schedule for the second maintenance.

[0133] (Appendix 7) The information processing device described in any one of Appendices 1 to 6, wherein the calculation device determines the maintenance schedule based on the type of the second abnormality and specified information, and the specified information includes at least one of the period required for the maintenance, the number of workers required for the maintenance, the schedule of the workers required for the maintenance, and the past operating history of the power generation unit.

[0134] With this configuration, the maintenance schedule can be appropriately determined based on this information.

[0135] (Appendix 8) An information processing device described in any one of Appendices 1 to 7, wherein the interface acquires information regarding abnormalities in other power generation units associated with the power generation unit, and the calculation device changes the second condition based on the information regarding the abnormalities in the other power generation units.

[0136] According to this configuration, it is possible to improve the accuracy of determining the second abnormality by using abnormalities in other power generation units related to the power generation unit.

[0137] (Supplementary Note 9) The information processing device according to any one of Supplementary Notes 1 to 8, wherein the arithmetic device outputs maintenance information indicating that the maintenance will be performed to a terminal of a worker who will perform the maintenance.

[0138] With this configuration, maintenance can be automatically requested from a maintenance worker.

[0139] (Appendix 10) The information processing device according to any one of Appendices 1 to 9, wherein the calculation device determines a maintenance schedule for the second abnormality based on the type of the second abnormality, but does not determine the maintenance schedule if the first abnormality is identified.

[0140] According to this configuration, a maintenance schedule for the first abnormality is not determined, and therefore it is possible to avoid determining a maintenance schedule that is less necessary.

[0141] (Supplementary Note 11) The information processing device according to Supplementary Note 1 to Supplementary Note 10, wherein the information processing device includes a memory that stores a trained model that has been machine-learned, the interface acquires maintenance results of the power generation unit or abnormality information of the power generation unit from a predetermined terminal, and the calculation device executes change control to change monitoring parameters used to monitor the power generation unit by applying the abnormality information or the maintenance results to the trained model.

[0142] With this configuration, there is no need for an administrator or the like to change the monitoring parameters; the monitoring parameters are changed using a machine-learned model, allowing change control to be performed appropriately.

[0143] (Supplementary Note 12) An information processing method comprising: identifying a first abnormality of a power generation unit when a physical quantity related to the operation of the power generation unit satisfies a first condition; identifying a second abnormality of the power generation unit that is more abnormal than the first abnormality when the physical quantity satisfies a second condition; identifying a type of the second abnormality; determining a maintenance schedule for the power generation unit based on the type of the second abnormality; and outputting the maintenance schedule.

[0144] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the description of the above embodiments, and is intended to include all modifications within the meaning and scope of the claims.

[0145] 10 Management system, 20, 20A Wind power generation device, 30 Collection device, 40, 40A Control device, 45, 45A Power generation unit, 50 User terminal, 60 Worker terminal, 70 Maintenance terminal, 80 Weather server, 100 Monitoring device, 102 Arithmetic unit, 104 Memory, 106 Communication interface, 112 Receiving unit, 114 Processing unit, 116 Transmitting unit, 118 Storage unit, 121, Th1, Th2 Threshold value, 131 Past operating record, 301 First report, 302 Second report, 351 Recommended information, 361 Abnormality type information, 362 Maintenance content information, 363 Arrangement information, 364 Maintenance schedule information, 365 Estimated amount information, 401 Input screen, 402 Sent screen, 411 Image without abnormality, 412 Image with abnormality, 414 Input area.

Claims

1. An information processing device relating to a power generation unit, the power generation unit including a sensor for detecting a physical quantity related to the operation of the power generation unit, the information processing device comprising: an interface; and a calculation device, the calculation device identifying a first abnormality of the power generation unit when the physical quantity satisfies a first condition, identifying a second abnormality of the power generation unit which is more abnormal than the first abnormality when the physical quantity satisfies a second condition, identifying a type of the second abnormality, and determining a maintenance schedule for the second abnormality based on the type of the second abnormality, and the interface outputting the maintenance schedule.

2. The information processing device according to claim 1, wherein the interface acquires the results of the maintenance from a specified terminal, and the computing device executes change control for changing the second condition based on the results of the maintenance.

3. The information processing device of claim 2, wherein a threshold is defined for the physical quantity, one of a range greater than the threshold and a range smaller than the threshold is a detection range in which the second abnormality is detected, and the other is an undetected range in which the second abnormality is not detected, the physical quantity satisfies the second condition when it falls within the detection range, and the calculation device executes control to change the threshold so that it falls within the detection range as the change control when the result of the maintenance is that no abnormality has occurred in the power generation unit.

4. The information processing device of claim 2, wherein a threshold is defined for the physical quantity, one of a range greater than the threshold and a range smaller than the threshold is a detection range in which the second abnormality is detected, and the other is an undetectable range in which the second abnormality is not detected, the physical quantity satisfies the second condition when it falls within the detection range, and the computing device executes at least one of the following as the change control: control to change the threshold so that it falls within the undetectable range when the result of the maintenance indicates that an abnormality has occurred in the power generation unit.

5. An information processing device according to any one of claims 2 to 4, wherein the arithmetic device displays an input screen on the specified terminal for accepting input of the results of the maintenance, and maintains display of the input screen until the results of the maintenance are input on the input screen.

6. The information processing device according to any one of claims 1 to 4, wherein the calculation device generates a first report when the first abnormality is identified and transmits the first report to a user terminal of a user of the power generation unit, generates a second report when the second abnormality is identified and transmits the second report to the user terminal, the first report including information indicating that the maintenance corresponding to the first abnormality is recommended, and the second report including information indicating that the maintenance corresponding to the second abnormality is to be performed and a maintenance schedule.

7. An information processing device as described in any one of claims 1 to 4, wherein the calculation device determines the maintenance schedule based on the type of the second abnormality and specified information, and the specified information includes at least one of: the period required for the maintenance; the number of workers required for the maintenance; the schedules of the workers required for the maintenance; and the past operating history of the power generation unit.

8. An information processing device according to any one of claims 1 to 4, wherein the interface acquires information regarding abnormalities in other power generation units associated with the power generation unit, and the calculation device changes the second condition based on the information regarding the abnormalities in the other power generation units.

9. The information processing device according to any one of claims 1 to 4, wherein the arithmetic device outputs maintenance information, indicating that the maintenance will be performed, to a terminal of a worker who will perform the maintenance.

10. An information processing device according to any one of claims 1 to 4, wherein the calculation device determines a maintenance schedule for the second abnormality based on the type of the second abnormality, but does not determine the maintenance schedule when the first abnormality is identified.

11. The information processing device according to any one of claims 1 to 4, wherein the information processing device includes a memory for storing a trained model based on machine learning, the interface acquires maintenance results of the power generation unit or abnormality information of the power generation unit from a specified terminal, and the computing device executes change control for changing monitoring parameters used to monitor the power generation unit by applying the abnormality information or the maintenance results to the trained model.

12. An information processing method comprising: identifying a first abnormality of the power generation equipment when a physical quantity related to the operation of the power generation equipment satisfies a first condition; identifying a second abnormality of the power generation equipment, the second abnormality being more abnormal than the first abnormality, when the physical quantity satisfies a second condition; identifying a type of the second abnormality; determining a maintenance schedule for the power generation equipment based on the type of the second abnormality; and outputting the maintenance schedule.

Images