Diagnosis device and method for diagnosis

Abstract

To realize a proposal of at least one of an accurate diagnosis and a precise maintenance type.SOLUTION: A diagnosis device 100 stores a first database 141 storing the combination of features of waveform data of a wind power generator 20 and attribute information of the wind power generator 20 and correspondence information in which diagnosis results of abnormalities of the wind power generator 20 and maintenance type diagnosis information of the wind power generator 20 are related to each other. The diagnosis device 100 specifies diagnosis information on the basis of an acquisition parameter and acquisition attribute information by using the first database 141, and outputs the diagnosis information to a user terminal 50.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to a diagnostic apparatus and a diagnostic method.

Background Art

[0002] For example, Japanese Patent Application Laid-Open No. 2013-185507 (Patent Document 1) discloses a condition monitoring system for a wind power generation device. This condition monitoring system includes a vibration sensor that detects a vibration value at a target position of the wind power generation device. The condition monitoring system diagnoses the presence or absence of an abnormality based on the vibration value detected by the vibration sensor. Then, the condition monitoring system displays the diagnosis result on the display unit of the monitoring terminal.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional condition monitoring device for a wind power generation device, only an abnormality diagnosis is performed for each measurement data, and there may be a problem that a highly accurate diagnosis cannot be performed. Further, in a conventional condition monitoring device for a wind power generation device, only a simple diagnosis result is displayed on the display unit. Therefore, separately, there may be a problem that engineers or the like need to devise maintenance of the wind power generation device, which takes a lot of time.

[0005] The present disclosure has been made to solve the above problems, and an object thereof is to achieve at least one of a highly accurate diagnosis and a proposal of a highly accurate maintenance type in the diagnosis of a wind power generation device.

Means for Solving the Problems

[0006] The diagnostic device of the present disclosure includes an interface, a memory, and a processing device. The interface acquires, as acquisition parameters, parameters used for diagnosing a wind power generation device, and also acquires, as acquisition attribute information, the attribute information of the wind power generation device. The memory stores correspondence information in which a combination of the diagnostic parameters of the wind power generation device and the attribute information of the wind power generation device is associated with diagnostic information including at least one of a diagnostic result regarding an abnormality of the wind power generation device and a maintenance type of the wind power generation device. The processing device uses the correspondence information to specify the diagnostic information based on the acquisition parameters and the acquisition attribute information, and outputs the diagnostic information to an external device.

[0007] The diagnostic method of the present disclosure includes acquiring, as acquisition parameters, parameters used for diagnosing a wind power generation device, and also acquiring, as acquisition attribute information, the attribute information of the wind power generation device. Further, the diagnostic method uses correspondence information in which a combination of the diagnostic parameters of the wind power generation device and the attribute information of the wind power generation device is associated with diagnostic information including at least one of a diagnostic result regarding an abnormality of the wind power generation device and a maintenance type of the wind power generation device, to specify the diagnostic information based on the acquisition parameters and the acquisition attribute information, and outputs the diagnostic information to an external device.

Advantages of the Invention

[0008] According to the present disclosure, in the diagnosis of a wind power generation device, at least one of highly accurate diagnosis and proposal of a highly accurate maintenance type can be realized.

Brief Description of the Drawings

[0009]

Figure 1

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Figure 11

Embodiments for Carrying Out the Invention

[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 denoted by the same reference numerals, and the description thereof will not be repeated.

[0011] <First Embodiment> FIG. 1 is a diagram showing a configuration example of the management system 10 according to the first embodiment. The management system 10 of the present disclosure includes M (where M is an integer of 1 or more) wind power generation units 45, a diagnostic device 100, a user terminal 50, a maintenance terminal 70, and a network NW. The collection device 30, the diagnostic device 100, the user terminal 50, and the maintenance terminal 70, which will be described later, can communicate with each other through the network NW.

[0012] The wind power generation unit 45 includes a wind power generation device 20, a collection device 30, and N vibration sensors Sn (n = 1,..., N, where N is an integer of 1 or more).

[0013] Identification information (ID: Identification) and attribute information are assigned to each of the M wind power generation devices 20. The identification information is information for identifying the wind power generation device 20. The attribute information is, for example, information indicating the attributes of the wind power generation device 20, and in the present embodiment, it is model information indicating the model of the wind power generation device 20. Note that the attribute information may include, for example, the manufacturing date and the like.

[0014] The wind power generation device 20 is a device that generates electricity by receiving wind power. The wind power generation device 20 includes a main bearing portion, a generator, a speed increaser, and the like. Each of the vibration sensors Sn detects the vibration value of a diagnosis target location (for example, the main bearing portion, the speed increaser, and the generator) of the wind power generation device 20. The vibration value is represented by, for example, any one of displacement, speed, and acceleration at the predetermined location. The vibration value detected by the vibration sensor Sn and the sensor ID of the vibration sensor are associated with each other and output to the collection device 30 as time series data.

[0015] The time series data collected by the collection device 30 is output to the diagnosis device 100. Further, from the collection device 30, the wind power generation device ID and the attribute information of the wind power generation device 20 corresponding to the collection device 30 are output to the diagnosis device 100 in association with the time series data.

[0016] The user terminal 50 is a terminal device owned by user A. "User A" typically refers to a person who owns the wind power generation device 20, for example, a power generation business operator. The user terminal 50 is typically a portable terminal that can be carried by user A. Note that the user terminal 50 may also be a dedicated computer terminal.

[0017] When an abnormality of the wind power generation device 20 is detected by the diagnosis device 100, a worker performs maintenance on the wind power generation device 20. The maintenance terminal 70 is a terminal operated by maintenance manager C of a maintenance company. For example, the maintenance terminal 70 is a terminal that receives a request for the maintenance. Specifically, when the diagnosis device 100 determines that maintenance of the wind power generation device 20 is necessary, the diagnosis device 100 transmits maintenance information for requesting the maintenance to the maintenance terminal 70. The diagnosis device 100 refers to a predetermined database (not shown) and the like regarding the work plan of the worker and the delivery status of repair parts, and formulates a construction plan such as the schedule of work and parts arrangement. The diagnosis device 100 generates maintenance information based on these processes.

[0018] The display unit of the maintenance terminal 70 displays a request image based on the maintenance information. The request image includes, for example, the address of the wind power generation device 20 to be maintained, the maintenance date and time, and the maintenance type (work content) described later. The maintenance manager C who has confirmed the request image arranges for the operator to arrive at the address and time displayed in the image. The "operator" typically refers to a person who performs maintenance on the abnormality of the wind power generation device 20. The operator executes the maintenance of the wind power generation device 20 according to the construction plan.

[0019] The diagnostic device 100 specifies the diagnostic result of the abnormality diagnosis and the maintenance type, etc. by the operations described later. Then, the diagnostic device 100 transmits a report (report 300 in FIG. 6) including the diagnostic result of the abnormality diagnosis and the maintenance type to the user terminal 50. The user terminal 50 corresponds to the "external device" of the present disclosure. Also, the diagnostic device 100 is a terminal operated by the administrator B.

[0020] The user terminal 50 can cause the user A to recognize the diagnostic result of the abnormality diagnosis and the maintenance type by displaying the report on the display unit. Also, the diagnostic device 100 transmits the maintenance information including the abnormal location to the maintenance terminal 70. Thereby, the maintenance manager C can be made to recognize the abnormal location etc. in advance.

[0021] The diagnostic device 100 includes a processing device 102, a memory 104, and a communication interface 106. The communication interface is described as "communication I / F" in FIG. 1. The processing device 102 executes various processes and operations. Each component is interconnected by a data bus. The memory 104 includes a ROM (Read Only Memory), a RAM (Random Access Memory), etc.

[0022] The processing device 102 is composed of a CPU (Central Processing Unit), an FPGA (Field-Programmable Gate Array), a GPU (Graphics Processing Unit), etc. Note that the processing device 102 may be composed of at least one of the CPU, FPGA, and GPU. Also, the processing device 102 may be composed of a processing circuitry. The processing device 102 is also referred to as "at least one processor" or "processing circuitry".

[0023] The memory 104 includes a volatile storage area (e.g., a working area) that temporarily stores program codes, work memories, etc. when the processing device 102 executes an arbitrary program. For example, the memory 104 includes a RAM (Random Access Memory) and a ROM (Read Only Memory).

[0024] The ROM stores the program to be executed by the processing device 102. The RAM temporarily stores data generated by the execution of the program in the processing device 102. The RAM can function as a temporary data memory used as a working area.

[0025] The communication interface 106 is configured to communicate with external devices (such as the collection device 30, the user terminal 50, and the maintenance terminal 70) of the diagnostic device 100.

[0026] An input device 108 and a display device 110 are connected to the diagnostic device 100. The input device 108 is composed of, for example, a mouse, a keyboard, etc. The diagnostic administrator B can input predetermined information using the input device 108. The display device 110 displays predetermined information.

[0027] [Database] Next, the database used in this embodiment will be described. The database is also referred to as a table. FIG. 2 is a diagram showing an example of the first database (DB: Date Base). The first database is created in advance based on past diagnostic results by the diagnostic device 100 and simulations using the diagnostic device 100. In the example of FIG. 2, the following diagnostic information is associated with each model information of the wind power generation device. The diagnostic information is the characteristics of waveform data, damage level, life of the diagnostic target part, diagnostic result, recommended maintenance type, advice, and appropriateness. Also, a diagnostic ID is assigned to each piece of diagnostic information. That is, the diagnostic ID is associated with one piece of diagnostic information. Although not shown in FIG. 2, the first database is configured such that in one piece of diagnostic information, the diagnostic target part and the diagnostic device 100 can be specified.

[0028] The model information A of the wind power generation device is as described above. The characteristics of the waveform data have a feature quantity B and a damage frequency F. The feature quantity B is calculated by a predetermined operation. Specifically, the predetermined operation is, for example, an operation for calculating at least one of the effective value of the waveform data, the peak value of the waveform data, the crest factor of the waveform data, the kurtosis of the waveform data, the skewness of the waveform data, and the OA (Overall) value of the waveform data. Also, raw waveform data may be used for calculating the feature quantity B, or waveform data obtained by applying a predetermined band-pass filter to the raw waveform data may be used. In the example of FIG. 2, feature quantities B1 to B6 and the like are defined as the feature quantity B.

[0029] The damage frequency F is the frequency of vibration generated by damage, which is given from the internal specifications of the parts of the wind power generation device 20 and the rotational frequency of the mounting shaft. The damage frequency F is the frequency at which energy peaks in the frequency spectrum and corresponds to the damaged part. The frequency spectrum is data obtained by performing, for example, a fast Fourier transform (FFT) on the vibration data detected by the vibration sensor Sn.

[0030] The damage level is information indicating the degree of damage to the component to be diagnosed. The lifespan is information indicating the length of the lifespan of the component to be diagnosed. The lifespan is the number of rotations and time of the blade that the component to be diagnosed can continuously operate. The diagnosis result is information indicating the result of the diagnosis regarding the abnormality of the wind power generation device 20. The maintenance type is information indicating the type of maintenance recommended for the component to be diagnosed. The advice is information indicating the content of the advice to be notified to the user when the wind power generation device 20 is continuously operated. The appropriateness is information indicating the degree (level) of the appropriateness of the diagnosis information (diagnosis result and maintenance type). The technical significance of the appropriateness will be described later.

[0031] The "model information of the wind power generation device" in FIG. 2 corresponds to the "attribute information of the wind power generation device" of the present disclosure. The "characteristics of the waveform data" in FIG. 2 correspond to the "diagnosis parameters of the wind power generation device" of the present disclosure. The "diagnosis result", "maintenance type", and "advice" in FIG. 2 correspond to the "diagnosis information" of the present disclosure. The first database in FIG. 2 corresponds to the "corresponding information" of the present disclosure. Thus, the first database in FIG. 2 is information in which the "combination of the attribute information of the wind power generation device and the diagnosis parameters of the wind power generation device" is associated with the "diagnosis result and the maintenance type of the wind power generation device 20". From different perspectives, the first database has the search condition group associated with the diagnosis information group. The search condition group includes the "combination of the attribute information of the wind power generation device, the diagnosis parameters of the wind power generation device, the damage level, and the lifespan". The diagnosis information group includes the "diagnosis result and the maintenance type of the wind power generation device 20". The diagnosis information group is also the search result of the search based on the search conditions.

[0032] FIG. 3 is a diagram showing an example of the second database. In the second database, the wind power generation device ID and the user terminal ID are associated. For example, for the wind power generation device ID: W1, the user terminal ID: U1 is associated. FIG. 4 is a diagram showing an example of the third database. In the third database, the maintenance ID and the estimate amount are associated. For example, for the maintenance ID: M1, the estimate amount: N1 is associated.

[0033] [Functional Block Diagram of Diagnostic Device] FIG. 5 is a functional block diagram of the diagnostic device 100. The diagnostic device 100 includes 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 processing device 102 in FIG. 1. The storage unit 118 corresponds to the memory 104 in FIG. 1, and at least a part of the storage area of the memory 104 is applied.

[0034] Stored in the storage unit 118 are the first database 141 shown in FIG. 2, the second database 142 shown in FIG. 3, the third database 143 shown in FIG. 4, the calculation formula 144 (formula (1) described later), and the like.

[0035] The receiving unit 112 acquires vibration data, which is time-series data, model information of the wind power generation device 20, and the wind power generation device ID of the wind power generation device 20 from M collection devices 30. The vibration data corresponds to the "acquired parameter" of the present disclosure. The vibration data is a parameter used for diagnosing the wind power generation device 20. Further, the model information corresponds to the "acquired attribute information" of the present disclosure.

[0036] The processing unit 114 detects the characteristics (feature amounts and presence or absence of damage frequency peaks) of the waveform data by performing the above-described predetermined operations and the like on the vibration data (acquired parameter). Further, the processing unit 114 estimates the damage level and the life of the component to be diagnosed by a predetermined estimation process based on this characteristic.

[0037] Then, the processing unit 114 specifies the diagnostic information by referring to the search conditions (the first database 141) using the model information, the characteristics of the waveform data, the damage level, and the lifespan as keys. That is, the processing unit 114 specifies the diagnostic information by referring to the search conditions (the first database 141) based on the vibration data (acquisition parameter) and the model information (acquisition attribute information). Then, the processing unit 114 creates a report including the specified diagnostic information. Note that the processing unit 114 also refers to the third database 143 to create the report.

[0038] Also, the processing unit 114 uses the wind power generation device ID to refer to the second database 142 and specifies the user terminal ID of the destination user terminal 50. Then, the processing unit 114 transmits the report to the user terminal 50 indicated by the specified user terminal ID via the transmission unit 116.

[0039] Also, when maintenance is required as a result of the abnormality diagnosis of the wind power generation device 20, the processing unit 114 transmits the above-mentioned maintenance information to the maintenance terminal 70.

[0040] [Report] FIG. 6 is a diagram showing an example of the report 300 created by the processing unit 114. The report 300 includes the diagnostic result (diagnostic information) by the processing unit 114. The report 300 is displayed as a report image on the user terminal 50. Specifically, the report 300 includes diagnostic result information 301, maintenance type information 302, estimate information 303, cost-effectiveness information 304, and maintenance confirmation information 305.

[0041] The diagnostic result information 301 is information indicating the result of the diagnosis using the first database 141. The diagnostic result information 301 in the example of FIG. 6 is information indicating that the diagnostic result is "the bearing device has moderate damage".

[0042] The maintenance type information 302 is information indicating the maintenance type. The maintenance type information 302 in the example of FIG. 6 is information indicating that the maintenance type is "inspection C3".

[0043] The estimate information 303 is information indicating the maintenance estimate amount for the maintenance type indicated by the maintenance type information 302. The estimate information 303 in the example of FIG. 6 is information indicating that the maintenance estimate amount is "X1 yen".

[0044] The cost-effectiveness information 304 is information indicating the cost-effectiveness of performing the maintenance of the maintenance type indicated by the maintenance type information 302. For example, the diagnostic device 100 calculates the reduction effect of maintenance costs (downtime reduction effect by advance arrangement) when immediately ordering the maintenance of the wind power generation device 20 using the evaluation result of the life of the wind power generation device 20. This calculation uses, for example, a predetermined database and calculation formula. The cost-effectiveness information 304 in the example of FIG. 6 is information indicating that the cost-effectiveness amount is "X2 yen".

[0045] The maintenance confirmation information 305 is information for receiving from the user whether to perform maintenance. The maintenance confirmation information 305 in the example of FIG. 6 includes the statement "Do you want to perform maintenance?", a YES button, and a NO button.

[0046] When the user checks the content of the report 300 and desires the maintenance indicated by the maintenance type information 302, the user operates the YES button, and when the user does not desire the maintenance, the user operates the NO button.

[0047] When the YES button is operated by the user, the user terminal 50 transmits a YES signal indicating that the YES button has been operated to the diagnostic device 100. When the diagnostic device 100 receives the YES signal, it transmits the maintenance information based on the content of the report 300 to the maintenance terminal 70.

[0048] On the other hand, when the NO button is operated by the user, the user terminal 50 transmits an NO signal indicating that the NO button has been operated to the diagnostic device 100. When receiving the NO signal, the diagnostic device 100 does not transmit the maintenance information to the maintenance terminal 70.

[0049] [Appropriateness information] Next, the appropriateness information will be described. The user can input, into the user terminal 50, appropriateness information regarding the appropriateness (usefulness) of the executed maintenance indicated by the report in FIG. 6 and the maintenance type information 302 of the report. The input appropriateness information is transmitted to the diagnostic device 100. The diagnostic device 100 updates the appropriateness (see FIG. 2) corresponding to the identified diagnostic information based on the appropriateness information input by the user.

[0050] First, the input screen for the appropriateness information will be described. FIG. 7 is a diagram showing an example of the input screen 400 for the appropriateness information. The diagnostic device 100 displays the input screen 400 in FIG. 7 on the user terminal 50, for example, after a certain period (for example, one month) from when the report is transmitted. In other words, the input screen 400 is a questionnaire input screen for the report in FIG. 6 and the executed maintenance.

[0051] Referring to FIG. 7, the input screen 400 includes a first piece of information 401 and a second piece of information 402. The second piece of information 402 further includes information 411, information 412, information 413, and information 414.

[0052] The first information 401, information 411, information 412, information 413, and information 414 are information regarding questions to the user. Therefore, the first information 401, information 411, information 412, information 413, and information 414 are also referred to as the first question, the second question, the third question, the fourth question, and the fifth question, respectively (see steps S304 and S306 in FIG. 11). A YES button and a NO button are displayed for each of the first information 401, information 411, information 412, information 413, and information 414. Then, the user operates the YES button or the NO button for all of the first information 401, information 411, information 412, information 413, and information 414. Note that the user asks the maintenance operator about matters that are unknown regarding the first information 401, information 411, information 412, information 413, and information 414.

[0053] The first information 401 indicates whether maintenance of the maintenance type recommended by the report in FIG. 6 could be performed. In FIG. 7, the first information 401 is a text image saying "Could maintenance be performed?". For example, when maintenance has been performed on the wind power generation device 20 (maintenance was possible), the user operates the YES button. On the other hand, when maintenance has not been performed on the wind power generation device 20 (maintenance was impossible) due to a structural problem or the like of the wind power generation device 20, the user operates the NO button.

[0054] The second information 402 is information indicating the satisfaction of user A with respect to the report (diagnostic information). As described above, it includes information 411, information 412, information 413, and information 414.

[0055] Information 411 is information indicating whether an abnormality in the wind power generation device 20 has been discovered by an operator. In FIG. 7, the information 411 is a text image saying "Has an abnormality been discovered in the wind power generation device 20?". For example, if an abnormality is discovered in the location indicated by the diagnosis result information 301 in the report of FIG. 6, the user operates the YES button. On the other hand, if no abnormality is discovered in the wind power generation device 20, the user operates the NO button.

[0056] Information 412 is information indicating whether there is an improvement due to maintenance of the wind power generation device 20. In FIG. 7, the information 412 is a text image saying "Has the wind power generation device been improved by maintenance?". The improvement of the wind power generation device 20 by maintenance means, for example, an increase in the power generation amount by the wind power generation device 20 compared to before maintenance. If the wind power generation device 20 has been improved, the user operates the YES button. On the other hand, if the wind power generation device 20 has not been improved, the user operates the NO button.

[0057] Information 413 is information regarding the validity of the degree of abnormality of the wind power generation device. In FIG. 7, the information 413 is a text image saying "Was the damage level appropriate?". For example, the user asks the operator who performed the maintenance about the damage level, and if the damage level in the diagnosis result information 301 shown in the report of FIG. 6 is appropriate, the user operates the YES button. On the other hand, if the damage level is not appropriate, the user operates the NO button.

[0058] Information 414 is information regarding the validity of the replacement of parts of the wind power generation device 20. When the diagnostic device 100 identifies component replacement maintenance (such as replacement of the bearing and speed increaser in FIG. 2, etc.) as the maintenance type, the diagnostic device 100 displays the information 414 on the user terminal 50. If the component replacement maintenance is appropriate, the user operates the YES button. On the other hand, if the component replacement maintenance is not appropriate, the user operates the NO button.

[0059] As is clear from the question contents of Information 411 to Information 414, the operation of the YES button indicates that the user is satisfied with the contents of the report or maintenance. On the other hand, the operation of the NO button indicates that the user is not satisfied with the contents of the report or maintenance.

[0060] In this way, the user can input appropriateness information indicating the appropriateness of the user with respect to the diagnosis result. Also, there may be cases where appropriateness information is input by a plurality of users for one piece of diagnostic information (diagnosis result and maintenance type). Hereinafter, the number of appropriateness information input for one piece of diagnostic information is also referred to as the "number of records".

[0061] Next, the update of the appropriateness information will be described. The user terminal 50 transmits the appropriateness information input to the user terminal 50 to the diagnostic apparatus 100. The processing unit 114 of the diagnostic apparatus 100 calculates the appropriateness using the appropriateness information and predetermined update information. Then, the processing unit 114 updates the stored appropriateness E to the calculated appropriateness.

[0062] The update information is, for example, a predetermined calculation formula 144 (function) shown in FIG. 5. More specifically, when the calculation formula 144 is information indicating that maintenance is not being performed in the first information 401, the calculation formula 144 is a formula for updating the appropriateness so that the appropriateness becomes an extremely low value. In the present disclosure, the "extremely low value" is assumed to be the minimum value of the appropriateness (for example, "0"). The calculation formula 144 is a formula for updating the appropriateness so that the appropriateness increases when the second information 402 is information indicating a high satisfaction level. For example, the calculation formula 144 is represented by the following formula (1).

[0063] Appropriateness E = a × ((b + c + d + e) / N) (1) Here, as described above, the minimum value of the appropriateness E is "0". Also, "a" in formula (1) is a value that becomes "1" when the YES button is operated in the first information 401 and becomes "0" when the NO button is operated in the first information 401.

[0064] Further, N in formula (1) is the number of all records of one piece of diagnostic information corresponding to the calculated appropriateness E. "b", "c", "d", and "e" in formula (1) are the numbers of records operated as YES for information 411, information 412, information 413, and information 414, respectively.

[0065] [Flowchart] FIG. 8 is a flowchart showing the main processing of the diagnostic apparatus 100 according to the present embodiment. Note that the three-point reader in FIG. 8 indicates that a certain period has elapsed. Further, the processing in FIG. 8 is executed every predetermined period. The predetermined period is, for example, the accumulation period of time-series data necessary for diagnosing an abnormality of the wind power generation apparatus 20.

[0066] In step S2, the diagnostic apparatus 100 executes a report creation process. The report creation process is mainly a process for creating the report in FIG. 6. Next, in step S4, the diagnostic apparatus 100 executes a maintenance confirmation process. The maintenance confirmation process is mainly a process for confirming whether maintenance is to be executed. Next, in step S6, the diagnostic apparatus 100 executes an update process. The update process is mainly a process for updating the first database in FIG. 2.

[0067] FIG. 9 is a flowchart showing the report creation process in step S2. First, in step S102, the diagnostic apparatus 100 acquires the attribute information (acquired attribute information) of the wind power generation apparatus 20, the vibration data (acquired parameter) for a predetermined period (accumulation period), and the wind power generation apparatus ID from the collection apparatus 30. The vibration data for a certain period is the time-series data described above.

[0068] Next, in step S104, the diagnostic apparatus 100 calculates a feature amount by executing the above-described predetermined calculation from the time-series data.

[0069] Next, in step S106, the diagnostic device 100 determines whether the feature amount exceeds the threshold value. If it is determined as NO in step S106, since there is no abnormality in the wind power generation device 20 to be diagnosed, the process in FIG. 9 ends. On the other hand, if it is determined as YES in step S106, the process proceeds to step S108.

[0070] In step S108, the diagnostic device 100 executes a peak determination process. Specifically, the diagnostic device 100 generates a frequency spectrum by performing a fast Fourier transform on the time series data. Then, the diagnostic device 100 calculates the peak energy of the damage frequency of each component using a band-pass filter. And when the peak energy exceeds the second threshold value, the diagnostic device 100 determines that there is a peak that matches the damage frequency (that is, there is a damaged component). Note that the damage frequency may include harmonic components.

[0071] In step S110, the diagnostic device 100 executes an estimation process. As described above, the estimation process is a process of estimating the damage level and the remaining life of the component to be diagnosed based on the characteristics of the waveform data (the feature amount and the presence or absence of the damage frequency peak). The estimation process is executed by, for example, a predetermined calculation.

[0072] Next, in step S112, the diagnostic device 100 temporarily stores the search conditions, for example, in the above-mentioned RAM. The search conditions include the model information of the wind power generation device 20, the characteristics of the waveform data (the feature amount exceeding the first threshold value and the presence or absence of the peak determined in step S108), and the estimation results in step S110 (the damage level and the remaining life).

[0073] Next, in step S114, a specifying process for specifying diagnostic information is executed on the first database (see FIG. 2) using the search conditions stored in step S112. This specifying process is also a "search process" for searching for diagnostic information.

[0074] Here, for the specific process of diagnostic information (diagnostic information search process), it is determined whether there is a search condition that matches the search condition in step S112 from the search condition group in FIG. 2. And when there is a search condition in the search condition group in FIG. 2 that completely matches the search condition in step S112, the number of candidates (hit number) of diagnostic information is the number of search conditions that completely match. Also, when there is a search condition in the search condition group in FIG. 2 that is similar to the search condition in step S112, the number of candidates of diagnostic information is the number of the similar search conditions. Further, when there is no search condition in the search condition group in FIG. 2 that is the same as or similar to the search condition in step S112, the number of candidates of diagnostic information is "0".

[0075] In step S116, the diagnostic apparatus 100 determines whether the number of candidates of diagnostic information is 2 or more. When the number of candidates is 2 or more (YES in step S116), in step S118, the diagnostic apparatus 100 specifies the diagnostic information from the candidates of diagnostic information based on the appropriateness associated with the candidate diagnostic information. Specifically, in step S118, the diagnostic apparatus 100 specifies the diagnostic information with the maximum appropriateness E (see FIG. 2) from the diagnostic information of two or more candidates. Then, the process proceeds to step S130.

[0076] Also, in step S116, when the number of candidates of diagnostic information is not 2 or more (NO in step S116), in step S120, the diagnostic apparatus 100 determines whether the number of candidates of diagnostic information is 1. When the number of candidates of diagnostic information is 1 (YES in step S120), in step S122, the diagnostic apparatus 100 specifies the diagnostic information that is the one candidate.

[0077] Also, in step S120, when the number of candidates of diagnostic information is not 1 (NO in step S120), the process proceeds to step S124. The case where the number of candidates of diagnostic information is not 1 is the case where the number of candidates of diagnostic information is "0".

[0078] In step S124, the diagnostic device 100 determines whether the search conditions include model information. In the determination of the first step S124, since the search conditions include model information, it is determined as YES in step S124. Next, in step S128, the model information is excluded (deleted) from the search conditions and a re-search for diagnostic information is executed.

[0079] Then, the diagnostic device 100 executes the processes of steps S116 and S120, etc. Also, in step S124 after it is determined as NO in step S116 and determined as NO in step S120 (in the determination of the second step S124), since the search conditions do not include model information, it is determined as NO in step S124. In this case, no matter how many times the search process is executed, the number of candidates for diagnostic information will not be 1 or more. Therefore, in step S126, the diagnostic device 100 allows the input of diagnostic information by administrator B (engineer). In step S126, the diagnostic device 100 displays a character image of "Please input diagnostic information" on the display device 110 (see FIG. 1). Administrator B inputs diagnostic information to the display device 110 using the input device 108.

[0080] In step S130, based on any one of the diagnostic information specified in step S118, the diagnostic information specified in step S122, and the diagnostic information input in step S126, an estimate of maintenance and cost-effectiveness is calculated. Next, in step S132, the diagnostic device 100 generates the report 300 in FIG. 6 and transmits it to the user terminal 50. This report 300 includes any one of the diagnostic information specified in step S118, the diagnostic information specified in step S122, and the diagnostic information input in step S126, and the estimate of maintenance and cost-effectiveness calculated in step S130. Then, the report creation process ends.

[0081] FIG. 10 is a flowchart of the maintenance confirmation process in step S4. The maintenance confirmation process is executed when the YES button or the NO button in the maintenance confirmation information 305 of the report 300 output in step S132 of FIG. 9 is operated.

[0082] In step S204, the diagnostic device 100 determines whether to perform maintenance. In step S204, it is determined as YES when the YES button in the maintenance confirmation information 305 is operated, and it is determined as NO when the NO button is operated.

[0083] If it is determined as YES in step S204, in step S206, the diagnostic device 100 transmits the maintenance information (see FIG. 5) to the maintenance terminal 70. When it is determined as NO in step S204 and when the process of step S206 is completed, the maintenance confirmation process ends.

[0084] FIG. 11 is a flowchart of the update process in step S6. The update process is executed when the appropriateness information in FIG. 7 is transmitted to the diagnostic device 100 by user A.

[0085] In step S302, the diagnostic device 100 acquires the appropriateness information input by the user. Next, in step S304, the diagnostic device 100 determines whether the first question (first information 401) is a YES answer.

[0086] Here, the case where it is determined as NO in step S304 is the case where the user is recommended a maintenance type that could not be executed. In this case, the user feels discomfort. Therefore, in step S308, the specific process (search process) of the diagnostic information is executed again.

[0087] In step S308, the diagnostic information associated with the next highest appropriateness level after the appropriateness level of the most recently identified diagnostic information in step S118 or step S122 is identified. Then, the process returns to step S130 in FIG. 9. In step S130, the diagnostic apparatus 100 executes the process of step S132 based on the diagnostic information identified in step S308.

[0088] When it is determined as YES in step S304, the diagnostic apparatus 100 determines, in step S306, whether all of the second to fifth questions (information 411 to information 414 in FIG. 7) are NO. When it is determined as YES in step S306, it means that the user's satisfaction with the diagnostic information is extremely low. In this case, the user feels discomfort. Therefore, in this case, the diagnostic apparatus 100 executes the process of step S308.

[0089] When it is determined as NO in step S306, the process proceeds to step S310. When it is determined as NO in step S306, it corresponds to the case of "when the appropriateness information meets a predetermined standard" in the present disclosure.

[0090] In step S310, the diagnostic apparatus 100 transmits the advice (see FIG. 2) included in the identified diagnostic information to the user terminal 50. Then, in step S312, the combination of the search conditions stored in step S112 and the identified diagnostic information is additionally stored in the first database. Also, the appropriateness level corresponding to this combination is set to a predetermined value. Further, in step S312, the diagnostic apparatus 100 updates the appropriateness level corresponding to the identified diagnostic information using the above formula (1).

[0091] [Summary] (1) The diagnostic device 100 of the present embodiment acquires, as acquisition parameters, parameters used for diagnosing a wind power generation device. Along with this, the diagnostic device 100 acquires, as acquisition attribute information, 20 attribute information of the wind power generation device. The diagnostic device 100 has a memory 104 that stores a first database 141. In the first database 141, a combination of diagnostic parameters of the wind power generation device 20 and attribute information of the wind power generation device 20 is associated with diagnostic information including a diagnostic result regarding an abnormality of the wind power generation device 20 and a maintenance type of the wind power generation device 20. The processing device (processing unit 114) uses the first database 141 to specify diagnostic information based on the acquisition parameters and the acquisition attribute information, and outputs the diagnostic information to the user terminal 50.

[0092] For example, in a diagnosis using only the diagnostic parameters of the wind power generation device 20 without using the attribute information of the wind power generation device 20 as in a conventional diagnostic device, the accuracy of the diagnostic result may decrease due to reasons such as an excessive increase in the number of candidates for the diagnostic result. On the other hand, in the case of the diagnostic device 100 of the present embodiment, the diagnostic result is specified based not only on the diagnostic parameters of the wind power generation device 20 but also on the attribute information of the wind power generation device 20 using past diagnostic results (first database). Therefore, the diagnostic device 100 can automatically perform a highly accurate diagnosis of damages frequently occurring in wind power generation devices of the same type. Therefore, compared with a diagnosis using only the diagnostic parameters of the wind power generation device 20 without using the attribute information of the wind power generation device 20, the diagnostic device 100 of the present embodiment can perform a highly accurate diagnosis. Also, in the case of the diagnostic device 100 of the present embodiment, recommended maintenance is also specified from past maintenance cases. Depending on the wind power generation device, there is maintenance that is impossible to perform due to the structure of the equipment. By utilizing the past data accumulated in the database, it is possible to automatically determine the maintenance suitable for wind power generation devices of the same type. Therefore, since it is not necessary for technicians or the like to devise maintenance for wind power generation devices, a prompt maintenance service can be provided, and the problem of taking a long time can be suppressed.

[0093] (2) The diagnostic device 100 has a first database 141 created in advance, and executes a specifying process for specifying candidates for diagnostic information with reference to the first database 141. Then, the diagnostic device 100 specifies diagnostic information from the candidates for diagnostic information.

[0094] According to such a configuration, candidates for diagnostic information can be specified using the previously created first database 141, and the diagnostic information can be specified.

[0095] (3) The diagnostic device 100 executes an estimation process (step S110 in FIG. 9) for estimating at least one of the life of the target component of the wind power generation device 20 and the damage level of the target component. Then, the diagnostic device 100 executes a specifying process (step S114 in FIG. 9) with reference to the first database 141 using the estimation result of the estimation process as a search condition.

[0096] According to such a configuration, since the diagnostic information is specified by combining the estimation result of the current estimation process and the database created in the past, the accuracy of the diagnostic information can be improved.

[0097] (4) As shown in FIG. 2, in the first database 141, an appropriateness degree E indicating the appropriateness of each of a plurality of pieces of diagnostic information is associated with each piece of diagnostic information. When the number of candidates for diagnostic information is two or more (YES in step S116), the diagnostic device 100 specifies diagnostic information from the candidates for diagnostic information based on the appropriateness degree associated with the diagnostic information that has become the candidate (step S118).

[0098] According to such a configuration, when the number of candidates for diagnostic information is two or more, the diagnostic information can be narrowed down based on the appropriateness degree associated with the diagnostic information that has become the candidate, so that the accuracy of the diagnostic information can be improved.

[0099] (5) After the diagnostic device 100 outputs diagnostic information (report 300 in FIG. 6) to an external device (user terminal 50), it allows the user terminal to receive appropriateness information (see FIG. 7) regarding the appropriateness of the diagnostic information. The diagnostic device 100 updates the appropriateness based on the appropriateness information (step S312 in FIG. 11).

[0100] According to such a configuration, since the user's intention can be reflected in the appropriateness, it is possible to improve the accuracy of the diagnostic information while improving the convenience for the user.

[0101] (6) When the number of candidates for the diagnostic information is two or more, the diagnostic device 100 identifies the diagnostic information with the maximum appropriateness from the two or more candidates (step S118). Also, as shown in FIG. 7, the appropriateness information includes first information 401 indicating whether or not maintenance of the maintenance type has been executed. When the first information 401 is information indicating that the maintenance has not been executed, the diagnostic device 100 updates it so that the appropriateness becomes the minimum value (see calculation formula 144 which is the above formula (1)).

[0102] According to such a configuration, it is possible to suppress the output of the maintenance type of the maintenance that could not be executed to the external device.

[0103] (7) As shown in FIG. 7, the appropriateness information includes second information 402 indicating the satisfaction of the user of the wind power generation device 20 with respect to the report 300. When the second information indicates that the satisfaction is high, the diagnostic device 100 updates it so that the appropriateness increases (see calculation formula 144 which is the above formula (1)).

[0104] According to such a configuration, it is possible to make it easier for the diagnostic information with high user satisfaction to be output to the external device.

[0105] (8) As shown in FIG. 7, the second information 402 includes information 411, information 412, information 413, and information 414. Information 411 is information indicating whether an abnormality in the wind power generation device 20 has been detected. Information 412 is information indicating whether there is improvement by maintenance on the wind power generation device 20. Information 413 is information regarding the validity of the degree of abnormality of the wind power generation device. Information 414 is information regarding the validity of replacement of parts of the wind power generation device 20.

[0106] According to such a configuration, information 411, information 412, information 413, and information 414 can be reflected appropriately.

[0107] (9) When the appropriateness information satisfies a predetermined standard (NO in step S306), the diagnostic device 100 outputs advice information regarding the operation of the wind power generation device 20 to the user terminal 50 (step S310).

[0108] According to such a configuration, the user can be made to recognize the advice information regarding the operation of the wind power generation device 20.

[0109] (10) When the appropriateness information does not satisfy the predetermined standard (NO in step S304 or YES in step S306), the diagnostic device 100 executes the specifying process again based on the appropriateness from the diagnostic information excluding the specified diagnostic information among the plurality of diagnostic information (step S308).

[0110] According to such a configuration, when the appropriateness information does not satisfy the predetermined standard, the specifying process for specifying the diagnostic information is executed again. That is, the diagnostic device 100 can execute a search for similar cases in other models and output the diagnostic information for which the appropriateness information satisfies the predetermined standard to an external device.

[0111] (11) The diagnostic device 100 repeats the specifying process until the appropriateness information satisfies the predetermined standard (repeats the processes of steps S130, S132, S204, S206, S302, S304, S306, and S308 until it is determined that NO in step S306).

[0112] According to such a configuration, diagnostic information that satisfies a predetermined standard for appropriateness information can be output to an external device.

[0113] (12) When the number of candidates for diagnostic information is 1 (YES in step S120), the diagnostic device 100 outputs the diagnostic information that is the candidate (step S122).

[0114] According to such a configuration, appropriate diagnostic information can be output to an external device. (13) When the number of candidates for diagnostic information is 0 (NO in step S120), the diagnostic device 100 executes a new identification process based on acquisition parameters without using model information (acquired attribute information) (step S128).

[0115] According to such a configuration, even when the number of candidates for diagnostic information is 0, since a new identification process is executed without using acquired attribute information, the number of candidates for diagnostic information can be made 1 or more.

[0116] (14) When the number of candidates for diagnostic information is 0 even after executing the new identification process (when the process of step S128 is executed but it is determined as NO in step S120), the diagnostic device 100 permits the input of new diagnostic information (step S126). Then, the diagnostic device 100 outputs this new diagnostic information to the user terminal 50.

[0117] According to such a configuration, when the number of candidates for diagnostic information is 0 even after executing the new identification process, new diagnostic information input by an administrator or the like can be output to an external device.

[0118] (15) The diagnostic information (report 300) includes an estimated cost of maintenance (estimated cost information 303) according to the maintenance type.

[0119] According to such a configuration, the estimated cost of maintenance can be output to an external device. (16) The diagnostic information (report 300) includes the cost - effectiveness amount (cost - effectiveness information 304) obtained by performing maintenance according to the maintenance type.

[0120] According to such a configuration, the cost - effectiveness amount can be output to an external device. The diagnostic device 100 outputs maintenance information indicating that the maintenance is to be executed to the maintenance terminal 70 of the operator who performs the maintenance of the wind power generation device (step S206 in FIG. 10).

[0121] According to such a configuration, without causing the user to perform a maintenance order process, the maintenance of the wind power generation device 20 can be performed by an operator or the like.

[0122] [Modification Example] (1) In the above - described embodiment, the sensor used to detect the presence or absence of an abnormality in the wind power generation device 20 has been described as a vibration sensor. However, the sensor may be other sensors. Other sensors are, for example, a temperature sensor, an AE (Acoustic Emission) sensor, a displacement sensor, or a sound sensor.

[0123] (2) In the above - described embodiment, the correspondence information has been described as the first database 141. However, the correspondence information may be other information. For example, the correspondence information may be a function that outputs a diagnostic result and a maintenance type when the model information of the wind power generation device 20 and the characteristics of the waveform data are input.

[0124] [Supplementary Note] The embodiments disclosed this time should be considered as illustrative in all respects and not restrictive. The scope of the present invention is shown not by the description of the above - described embodiments but by the claims, and it is intended that all modifications within the meaning and scope equivalent to the claims are included.

[0125] (Appendix 1) An interface that acquires parameters used for diagnosing a wind power generation device as acquisition parameters and acquires attribute information of the wind power generation device as acquisition attribute information, a combination of diagnostic parameters of the wind power generation device and attribute information of the wind power generation device, and a memory that stores correspondence information in which diagnostic information including at least one of a diagnostic result regarding an abnormality of the wind power generation device and a maintenance type of the wind power generation device is associated, and a processing device that uses the correspondence information to specify diagnostic information based on the acquisition parameters and the acquisition attribute information and outputs the diagnostic information to an external device. A diagnostic device.

[0126] According to such a configuration, diagnostic information including at least one of a diagnostic result regarding an abnormality of the wind power generation device and a maintenance type of the wind power generation device is specified using not only the diagnostic parameters of the wind power generation device but also the attribute information of the wind power generation device. Therefore, the accuracy of at least one of the diagnostic result and the maintenance type can be improved.

[0127] (Appendix 2) The correspondence information is a database in which a plurality of combinations and a plurality of pieces of diagnostic information corresponding to each of the plurality of combinations are associated, and the processing device executes a specifying process for specifying candidates for the diagnostic information by referring to the database, and specifies the diagnostic information from the candidates for the diagnostic information. The diagnostic device according to Appendix 1.

[0128] According to such a configuration, candidates for the diagnostic information can be specified and the diagnostic information can be specified using a previously created database.

[0129] (Appendix 3) The processing device executes an estimation process for estimating at least one of the lifespan of a target component of the wind power generation device and the damage level of the target component, and executes the specifying process by referring to the database using the estimation result of the estimation process as a search condition. The diagnostic device according to Appendix 2.

[0130] According to such a configuration, the accuracy of the diagnostic information can be improved because the diagnostic information is specified by combining the estimation result of the current estimation process and the database created in the past.

[0131] (Appendix 4) In a database, an appropriateness degree indicating the appropriateness of each of a plurality of pieces of diagnostic information is associated with each piece of diagnostic information. When the number of candidates for the diagnostic information is 2 or more, the processing device specifies the diagnostic information from the candidates for the diagnostic information based on the appropriateness degree associated with the diagnostic information that has become the candidate, which is the diagnostic device described in Appendix 2 or Appendix 3.

[0132] According to such a configuration, since the diagnostic information can be narrowed down based on the appropriateness degree associated with the diagnostic information that has become the candidate when the number of candidates for the diagnostic information is 2 or more, the accuracy of the diagnostic information can be improved.

[0133] (Appendix 5) After outputting the diagnostic information to an external device, the processing device allows reception of appropriateness information regarding the appropriateness degree for the diagnostic information by a user terminal, and updates the appropriateness degree based on the appropriateness information, which is the diagnostic device described in Appendix 4.

[0134] According to such a configuration, since the opinion of the user can be reflected in the appropriateness degree, the accuracy of the diagnostic information can be improved while improving the convenience of the user.

[0135] (Appendix 6) When the number of candidates for the diagnostic information is 2 or more, the processing device specifies the diagnostic information with the maximum appropriateness degree from the two or more candidates. The diagnostic information includes a diagnostic result and a maintenance type, and the appropriateness information includes first information indicating whether the maintenance of the maintenance type has been executable. When the first information is information indicating that the maintenance has not been performed, the processing device updates the appropriateness degree so as to be the minimum value, which is the diagnostic device described in Appendix 5.

[0136] According to such a configuration, it is possible to suppress the output of the maintenance type of the maintenance that could not be executed to the external device.

[0137] (Appendix 7) The appropriateness information includes second information indicating the satisfaction level of the user of the wind power generation device with respect to the diagnostic information. When the second information indicates that the satisfaction level is high, the processing device updates it so that the appropriateness increases, as described in Appendix 6.

[0138] According to such a configuration, it is possible to facilitate the output of diagnostic information with a high user satisfaction level to an external device.

[0139] (Appendix 8) The second information includes at least one of information indicating whether an abnormality of the wind power generation device has been detected, information indicating whether there is improvement by maintenance on the wind power generation device, information regarding the validity of the degree of abnormality of the wind power generation device, and information regarding the validity of replacement of parts of the wind power generation device, as described in Appendix 7.

[0140] According to such a configuration, at least one of these four pieces of information can be reflected in the appropriateness.

[0141] (Appendix 9) When the appropriateness information meets a predetermined standard, the processing device outputs advice information regarding the operation of the wind power generation device to an external device, as described in any one of Appendices 5 to 8.

[0142] According to such a configuration, it is possible to make the user recognize advice information regarding the operation of the wind power generation device.

[0143] (Appendix 10) When the appropriateness information does not meet a predetermined standard, the processing device executes a specific process again based on the appropriateness from the diagnostic information obtained by excluding the specified diagnostic information from among the plurality of diagnostic information, as described in Appendix 9.

[0144] According to such a configuration, when the appropriateness information does not meet a predetermined standard, since the specific process for specifying the diagnostic information is executed again, it is possible to output diagnostic information that meets the predetermined standard to an external device.

[0145] (Supplementary Note 11) The processing device is the diagnostic device according to Supplementary Note 10 that repeats a specific process until the appropriateness information satisfies a predetermined standard.

[0146] According to such a configuration, diagnostic information for which the appropriateness information satisfies a predetermined standard can be output to an external device.

[0147] (Supplementary Note 12) The processing device is the diagnostic device according to any one of Supplementary Notes 2 to 11 that outputs the diagnostic information that is the candidate when the number of candidates for the diagnostic information is 1.

[0148] According to such a configuration, appropriate diagnostic information can be output to an external device. (Supplementary Note 13) The processing device is the diagnostic device according to any one of Supplementary Notes 2 to 12 that executes a new specific process based on an acquisition parameter without using the acquired attribute information when the number of candidates for the diagnostic information is 0.

[0149] According to such a configuration, even when the number of candidates for the diagnostic information is 0, since a new specific process is executed without using the acquired attribute information, the number of candidates for the diagnostic information can be made 1 or more.

[0150] (Supplementary Note 14) The processing device is the diagnostic device according to Supplementary Note 13 that permits reception of new diagnostic information and outputs the new diagnostic information to an external device when the number of candidates for the diagnostic information is 0 even after executing a new specific process.

[0151] According to such a configuration, when the number of candidates for the diagnostic information is 0 even after executing a new specific process, new diagnostic information input by an administrator or the like can be output to an external device.

[0152] (Supplementary Note 15) The diagnostic information includes an estimate amount for maintenance according to the maintenance type, and is the diagnostic device according to any one of Supplementary Notes 1 to 14.

[0153] According to such a configuration, the estimate amount for maintenance can be output to an external device. (Appendix 16) The diagnostic device according to any one of Appendices 1 to 15, wherein the diagnostic information includes the amount of cost-effectiveness due to maintenance performed according to the maintenance type.

[0154] According to such a configuration, the amount of cost-effectiveness can be output to an external device. (Appendix 17) The diagnostic device according to any one of Appendices 1 to 16, wherein the processing device outputs maintenance information indicating that the maintenance is to be executed to the terminal of the operator who performs the maintenance of the wind power generation device.

[0155] According to such a configuration, it is possible to cause an operator or the like to perform maintenance on the wind power generation device 20 without causing the user to perform a maintenance order process.

[0156] (Appendix 18) A diagnostic method comprising: obtaining parameters used for diagnosing a wind power generation device as acquisition parameters, and obtaining attribute information of the wind power generation device as acquisition attribute information; specifying diagnostic information based on the acquisition parameters and the acquisition attribute information using correspondence information; and outputting the diagnostic information to an external device, wherein the correspondence information is information in which a combination of diagnostic parameters of the wind power generation device and attribute information of the wind power generation device is associated with diagnostic information including at least one of a diagnostic result regarding an abnormality of the wind power generation device and a maintenance type of the wind power generation device.

Explanation of Reference Numerals

[0157] 10 Management system, 20 Wind power generation device, 30 Collection device, 45 Wind power generation unit, 50 User terminal, 70 Maintenance terminal, 100 Diagnostic device, 102 Processing device, 104 Memory, 106 Communication interface, 108 Input device, 110 Display device, 112 Receiver, 114 Processing section, 116 Transmitter, 118 Storage section, 141 First database, 142 Second database, 143 Third database, 144 Calculation formula, 300 Report, 301 Diagnostic result information, 302 Maintenance type information, 303 Estimate information, 304 Cost-effectiveness information, 305 Maintenance confirmation information, 400 Input screen, 401 First information, 402 Second information.

Claims

1. An interface that acquires parameters used for diagnosing a wind power generation device as acquisition parameters and acquires attribute information of the wind power generation device as acquisition attribute information, A memory that stores correspondence information in which a combination of the diagnosis parameters of the wind power generation device and the attribute information of the wind power generation device is associated with diagnosis information including at least one of a diagnosis result related to an abnormality of the wind power generation device and a maintenance type of the wind power generation device, A diagnostic device comprising: a processing device that uses the correspondence information to specify the diagnosis information based on the acquisition parameters and the acquisition attribute information and outputs the diagnosis information to an external device.

2. The correspondence information is a database in which a plurality of the combinations are associated with a plurality of the diagnosis information corresponding to each of the plurality of combinations, The processing device, Executes a specifying process for specifying candidates for the diagnosis information by referring to the database, The diagnostic device according to claim 1, which specifies the diagnosis information from the candidates for the diagnosis information.

3. The processing device, Executes an estimation process for estimating at least one of the lifespan of a target component of the wind power generation device and the damage level of the target component, The diagnostic device according to claim 2, which executes the specifying process by referring to the database using the estimation result of the estimation process as a search condition.

4. In the database, an appropriateness degree indicating the appropriateness of each of the plurality of diagnosis information is associated with each of the plurality of diagnosis information, The processing device specifies the diagnosis information from the candidates for the diagnosis information based on the appropriateness degree associated with the diagnosis information that has become the candidate when the number of candidates for the diagnosis information is two or more. The diagnostic device according to claim 2 or claim 3.

5. The processing device, After outputting the diagnosis information to an external device, allows reception of appropriateness information regarding the appropriateness degree of the diagnosis information at a user terminal, The diagnostic device according to claim 4, which updates the appropriateness degree based on the appropriateness information.

6. The processing device specifies the diagnosis information having the maximum appropriateness degree from the two or more candidates when the number of candidates for the diagnosis information is two or more, The diagnosis information includes the diagnosis result and the maintenance type, The appropriateness information includes first information indicating whether or not maintenance of the maintenance type could be performed. The diagnostic apparatus according to claim 5, wherein when the first information indicates that the maintenance has not been performed, the processing device updates the appropriateness so as to be the minimum value.

7. The diagnostic apparatus according to claim 5, wherein when the appropriateness information satisfies a predetermined criterion, the processing device outputs advice information regarding the operation of the wind power generation device to the external device.

8. The diagnostic apparatus according to claim 2 or 3, wherein when the number of candidates for the diagnostic information is 1, the processing device outputs the diagnostic information that is the candidate.

9. The diagnostic apparatus according to claim 2 or 3, wherein when the number of candidates for the diagnostic information is 0, the processing device executes new specific processing based on the acquired parameters without using the acquired attribute information.

10. The processing device permits reception of new diagnostic information when the number of candidates for the diagnostic information is 0 even after executing the new specific processing, and outputs the new diagnostic information to the external device. The diagnostic apparatus according to claim 9.

11. The diagnostic apparatus according to any one of claims 1 to 3, wherein the diagnostic information includes an estimate amount of maintenance according to the maintenance type.

12. The diagnostic apparatus according to any one of claims 1 to 3, wherein the diagnostic information includes an amount of cost-effectiveness due to performing maintenance according to the maintenance type.

13. The diagnostic apparatus according to any one of claims 1 to 3, wherein the processing device outputs maintenance information indicating that the maintenance is to be performed to a terminal of an operator who performs the maintenance of the wind power generation device.

14. Obtaining parameters used for diagnosing a wind power generation device as acquired parameters, and obtaining attribute information of the wind power generation device as acquired attribute information, using correspondence information in which a combination of the diagnostic parameters of the wind power generation device and the attribute information of the wind power generation device is associated with diagnostic information including at least one of a diagnostic result regarding an abnormality of the wind power generation device and a maintenance type of the wind power generation device, specifying the diagnostic information based on the acquired parameters and the acquired attribute information, and outputting the diagnostic information to an external device. A diagnostic method.

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