Wind turbine generator intelligent inspection method based on big data

Abstract

The invention discloses a wind turbine generator intelligent inspection method based on big data, and the method comprises the steps: obtaining the information of a wind turbine generator operation data collection device and the coordinate data of a wind turbine generator station, receiving the data collected by the wind turbine generator operation data collection device, and carrying out the preprocessing of the data collected by the wind turbine generator operation data collection device, analyzing and processing the data in the data analysis basic database to obtain intelligent interaction equipment inspection data, comparing coordinate data in the intelligent interaction equipment inspection data with the station yard coordinate data, if a data comparison result is not abnormal, generating an intelligent interaction equipment inspection execution command, and sending the intelligent interaction equipment inspection execution command to the station yard. The problem that in the prior art, a power management system cannot be in butt joint with intelligent interactive equipment for inspection, and the operation condition of a wind turbine generator cannot be obtained in real time is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine inspection, and in particular to a big data-based intelligent inspection method for wind turbines. Background Art

[0002] A wind turbine is a system that converts wind kinetic energy into electrical energy. A wind turbine consists of a rotor and a generator; the rotor contains blades, a hub, and reinforcements. The blades rotate in response to wind power, generating electricity, and the generator head rotates. A wind power source consists of a wind turbine, a tower supporting the turbine, a battery charge controller, an inverter, an unloader, a grid connection controller, and a battery pack. Wind turbines are often located in mountainous areas, making on-site inspections difficult for maintenance personnel because the turbines are located far from their workstations and are very high.

[0003] With the development of the times, the method of collecting image data of inspection objects through intelligent interactive equipment robots and drones, and then analyzing the image data to obtain inspection results has begun to be used more and more. However, in the scenario where wind turbines are used, if the inspection results are only obtained through image recognition technology, it can only be used to detect deformation of objects, etc. Whether there are abnormalities in the operating data inside the wind turbine cannot be identified, and it is impossible to realize the need for the power management system to connect with the intelligent interactive equipment for inspection to obtain the operating status of the wind turbine in real time. For this purpose, a smart inspection method for wind turbines based on big data has been developed. Summary of the Invention

[0004] The purpose of the present invention is to provide a wind turbine intelligent inspection method based on big data to solve the problem that the existing technology cannot realize the connection between the power management system and the intelligent interactive equipment for inspection to obtain the operating status of the wind turbine in real time.

[0005] The present invention provides a wind turbine intelligent inspection method based on big data, comprising:

[0006] Obtain wind turbine operation data acquisition device information and wind turbine station coordinate data;

[0007] Receiving data collected by the wind turbine operation data acquisition device, preprocessing the data collected by the wind turbine operation data acquisition device, and storing the preprocessed data collected by the wind turbine operation data acquisition device;

[0008] Build a big data platform, classify the stored data, and obtain a basic database for data analysis;

[0009] Analyze and process the data in the data analysis basic database to obtain intelligent interactive device inspection data;

[0010] The coordinate data in the intelligent interactive device inspection data is compared with the station coordinate data. If there is no abnormality in the data comparison result, an intelligent interactive device inspection execution command is generated.

[0011] Preferably, obtaining wind turbine operation data acquisition device information and wind turbine station coordinate data includes:

[0012] Construct a three-dimensional coordinate system for the wind turbine station, which includes X-axis coordinates, Y-axis coordinates, and Z-axis coordinates;

[0013] Matching the wind turbine operation data acquisition device in the wind turbine station and each position in the wind turbine station with a three-dimensional coordinate system to obtain the coordinates of objects in the wind turbine station;

[0014] The validity of the coordinates of the objects in the wind turbine station is checked. If the data of the coordinates of the objects in the wind turbine station cannot be displayed in the preset three-dimensional model, the abnormal data is re-tested.

[0015] Preferably, receiving data collected by the wind turbine operation data collection device, preprocessing the data collected by the wind turbine operation data collection device, and completing data storage of the preprocessed data collected by the wind turbine operation data collection device, comprises:

[0016] Classify and pre-store the data collected by the wind turbine operation data collection device, and label the classified pre-stored data;

[0017] Convert and sort the pre-stored data with labels into different formats;

[0018] The sorting information is converted according to the data format, and the pre-stored data is converted into a standard format.

[0019] Preferably, a big data platform is constructed to classify the stored data to obtain a basic database for data analysis, including:

[0020] The big data platform includes a data service module and a data calculation and analysis module;

[0021] Extracting the classified stored data to the data service module, and the data service module extracting the classified stored data and generating a three-dimensional model;

[0022] The three-dimensional model generated by combining the extracted data is used to generate a basic database for data analysis.

[0023] Preferably, analyzing and processing the data in the data analysis basic database to obtain intelligent interactive device inspection data includes:

[0024] Acquire wind turbine intelligent inspection and monitoring parameter data, and build a wind turbine intelligent monitoring module based on the wind turbine intelligent inspection and monitoring parameter data;

[0025] The wind turbine intelligent monitoring module includes a vibration monitoring module, a patrol detection module and an auxiliary equipment acquisition module;

[0026] The auxiliary device acquisition module includes video, audio and infrared imaging data collected by the smart terminal device.

[0027] Preferably, the coordinate data in the inspection data of the intelligent interactive device is compared with the station coordinate data. If the data comparison result is normal, an intelligent interactive device inspection execution command is generated, including:

[0028] Establishing a virtual image of the station's internal coordinates in the three-dimensional model according to the station coordinate data;

[0029] Substitute the coordinate data in the intelligent interactive device inspection data into the three-dimensional model to obtain the intelligent interactive device inspection path;

[0030] The inspection path of the intelligent interactive device is compared with the virtual image of the station coordinates established in the three-dimensional model. If there is a difference in the path or a breakpoint in the path, the path coordinate information is listed as abnormal.

[0031] The beneficial effects of the present invention are as follows: The present invention provides a wind turbine intelligent inspection method based on big data, which obtains wind turbine operation data acquisition device information and wind turbine station coordinate data, receives data collected by the wind turbine operation data acquisition device, and preprocesses the data collected by the wind turbine operation data acquisition device, completes data storage for the preprocessed data collected by the wind turbine operation data acquisition device, builds a big data platform, classifies the stored data, obtains a data analysis basic database, analyzes and processes the data in the data analysis basic database, obtains intelligent interactive device inspection data, compares the coordinate data in the intelligent interactive device inspection data with the station coordinate data, and generates an intelligent interactive device inspection execution command if the data comparison result is normal. By processing and analyzing wind turbine data collected by intelligent terminals such as sensors in wind turbines and data collected by drones or robots for intelligent inspection, a variety of data inside and outside the wind turbine are summarized and analyzed through the big data platform, solving the problem that the existing technology cannot realize the need for the power management system to connect with the intelligent interactive device for inspection and obtain the operation status of the wind turbine in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0033] Figure 1 A schematic flow chart of a big data-based intelligent inspection method for wind turbines provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. The technical solutions provided by each embodiment of the present invention are described in detail below in conjunction with the drawings.

[0035] See also Figure 1 ,A wind turbine intelligent inspection method based on big data, including;

[0036] In step 101, wind turbine operation data acquisition device information and wind turbine station coordinate data are obtained;

[0037] The wind turbine operation data acquisition device includes sensors, individual devices, measuring equipment and video acquisition devices located at various positions of the wind turbine. The sensors, individual devices, measuring equipment and video acquisition devices located at various positions of the wind turbine transmit the collected data to the server. The coordinate data of the wind turbine site is used to mark the positions of the sensors, individual devices, measuring equipment and video acquisition devices. When the collected data is abnormal, the location information of the abnormal data source can be obtained.

[0038] In step 102, data collected by a wind turbine operation data collection device is received, and the data collected by the wind turbine operation data collection device is preprocessed, and the preprocessed data collected by the wind turbine operation data collection device is stored;

[0039] Receive data collected by the wind turbine operation data acquisition device, pre-process the collected data to facilitate subsequent data processing and analysis, and then store the processed data for subsequent use in building a big data platform.

[0040] In step 103, a big data platform is constructed to classify the stored data and obtain a basic database for data analysis;

[0041] The big data platform includes a data service module and a data calculation and analysis module; the classified stored data is extracted to the data service module, and the data service module extracts the classified stored data and generates a three-dimensional model; the three-dimensional model generated by combining the extracted data is used to generate a data analysis basic database.

[0042] In step 104, the data in the data analysis basic database is analyzed and processed to obtain intelligent interactive device inspection data;

[0043] Intelligent interactive devices include drones and intelligent patrol robots. After the big data platform analyzes the coordinate location of the fault, the coordinate data is sent to the intelligent interactive device, which then goes to the site for inspection. The intelligent interactive inspection data includes the inspection path of the drone or intelligent patrol robot and the target location for data collection.

[0044] In step 105, the coordinate data in the intelligent interactive device inspection data is compared with the station coordinate data. If there is no abnormality in the data comparison result, an intelligent interactive device inspection execution command is generated.

[0045] Substitute the location coordinates of the intelligent interactive device that needs to be inspected into the coordinate system of the station and verify the coordinates to avoid incorrect coordinates that may cause the intelligent inspection robot or drone to be unable to inspect normally.

[0046] Specifically, the information of the wind turbine operation data acquisition device and the wind turbine station coordinate data are obtained, including:

[0047] Construct a three-dimensional coordinate system for the wind turbine station, which includes X-axis coordinates, Y-axis coordinates, and Z-axis coordinates;

[0048] Matching the wind turbine operation data acquisition device in the wind turbine station and each position in the wind turbine station with a three-dimensional coordinate system to obtain the coordinates of objects in the wind turbine station;

[0049] The validity of the coordinates of the objects in the wind turbine station is checked. If the data of the coordinates of the objects in the wind turbine station cannot be displayed in the preset three-dimensional model, the abnormal data is re-tested.

[0050] Specifically, receiving data collected by the wind turbine operation data collection device, preprocessing the data collected by the wind turbine operation data collection device, and completing data storage of the preprocessed data collected by the wind turbine operation data collection device, including:

[0051] Classify and pre-store the data collected by the wind turbine operation data collection device, and label the classified pre-stored data;

[0052] Convert and sort the pre-stored data with labels into different formats;

[0053] The sorting information is converted according to the data format, and the pre-stored data is converted into a standard format.

[0054] Specifically, we build a big data platform, classify the stored data, and obtain a basic database for data analysis, including:

[0055] The big data platform includes a data service module and a data calculation and analysis module;

[0056] Extracting the classified stored data to the data service module, and the data service module extracting the classified stored data and generating a three-dimensional model;

[0057] The three-dimensional model generated by combining the extracted data is used to generate a basic database for data analysis.

[0058] Specifically, the data in the data analysis basic database is analyzed and processed to obtain the intelligent interactive device inspection data, including:

[0059] Acquire wind turbine intelligent inspection and monitoring parameter data, and build a wind turbine intelligent monitoring module based on the wind turbine intelligent inspection and monitoring parameter data;

[0060] The wind turbine intelligent monitoring module includes a vibration monitoring module, a patrol detection module and an auxiliary equipment acquisition module;

[0061] The auxiliary device acquisition module includes video, audio and infrared imaging data collected by the smart terminal device.

[0062] Specifically, the coordinate data in the inspection data of the intelligent interactive device is compared with the station coordinate data. If the data comparison result is normal, an intelligent interactive device inspection execution command is generated, including:

[0063] Establishing a virtual image of the station's internal coordinates in the three-dimensional model according to the station coordinate data;

[0064] Substitute the coordinate data in the intelligent interactive device inspection data into the three-dimensional model to obtain the intelligent interactive device inspection path;

[0065] The inspection path of the intelligent interactive device is compared with the virtual image of the station coordinates established in the three-dimensional model. If there is a difference in the path or a breakpoint in the path, the path coordinate information is listed as abnormal.

[0066] It can be seen from the above embodiments that the present invention provides a wind turbine intelligent inspection method based on big data, which obtains wind turbine operation data acquisition device information and wind turbine station coordinate data, receives data collected by the wind turbine operation data acquisition device, and preprocesses the data collected by the wind turbine operation data acquisition device, completes data storage of the preprocessed data collected by the wind turbine operation data acquisition device, builds a big data platform, classifies the stored data, obtains a data analysis basic database, analyzes and processes the data in the data analysis basic database, obtains intelligent interactive equipment inspection data, compares the coordinate data in the intelligent interactive equipment inspection data with the station coordinate data, and generates an intelligent interactive equipment inspection execution command if there is no abnormality in the data comparison result. By processing and analyzing wind turbine data collected by smart terminals such as sensors inside wind turbines and data collected by drones or robots during intelligent inspections, various data inside and outside the wind turbines are summarized and analyzed through a big data platform. Intelligent inspections are carried out at the locations of wind turbines with abnormal data to obtain the latest operating status of the wind turbines in real time, solving the problem that existing technologies cannot achieve the connection between the power management system and the intelligent interactive equipment for inspections to obtain the operating status of the wind turbines in real time.

[0067] The same and similar parts between the various embodiments in this specification can be referred to each other. Since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0068] The above-described embodiments of the present invention do not limit the protection scope of the present invention.

Claims

1. A wind turbine intelligent inspection method based on big data, characterized in that: include; Obtain wind turbine operation data collection device information and wind turbine station coordinate data; Receiving data collected by the wind turbine operation data collection device, preprocessing the data collected by the wind turbine operation data collection device, and completing data storage of the preprocessed data collected by the wind turbine operation data collection device; Build a big data platform, classify the stored data, and obtain a basic database for data analysis; Analyze and process the data in the data analysis basic database to obtain intelligent interactive device inspection data; The coordinate data in the intelligent interactive device inspection data is compared with the station field coordinate data. If there is no abnormality in the data comparison result, an intelligent interactive device inspection execution command is generated.

2. The wind turbine intelligent inspection method based on big data according to claim 1, characterized in that: Obtain wind turbine operation data collection device information and wind turbine station coordinate data, including: Construct a three-dimensional coordinate system for the wind turbine station, which includes X-axis coordinates, Y-axis coordinates, and Z-axis coordinates; Matching the wind turbine operation data acquisition device in the wind turbine station and each position in the wind turbine station with the three-dimensional coordinate system to obtain the coordinates of the objects in the wind turbine station; The validity of the coordinates of the objects in the wind turbine station is checked. If the data of the coordinates of the objects in the wind turbine station cannot be displayed in the preset three-dimensional model, the abnormal data is retested.

3. The wind turbine intelligent inspection method based on big data according to claim 1, characterized in that: Receiving data collected by the wind turbine operation data collection device, preprocessing the data collected by the wind turbine operation data collection device, and completing data storage of the preprocessed data collected by the wind turbine operation data collection device, including: Classify and pre-store the data collected by the wind turbine operation data collection device, and label the classified pre-stored data; Convert and sort the pre-stored data with labels into different data formats; The pre-stored data is converted into a standard format according to the data format conversion sorting information.

4. The method for intelligent inspection of wind turbines based on big data according to claim 1, characterized in that: Build a big data platform, classify the stored data, and obtain a basic database for data analysis, including: The big data platform includes a data service module and a data calculation and analysis module; Extracting the classified stored data to the data service module, and the data service module extracts the classified stored data and generates a three-dimensional model; The three-dimensional model generated by combining the extracted data is used to generate a basic database for data analysis.

5. The method for intelligent inspection of wind turbines based on big data according to claim 1, characterized in that: Analyze and process the data in the data analysis basic database to obtain intelligent interactive device inspection data, including: Acquire wind turbine intelligent inspection and monitoring parameter data, and build a wind turbine intelligent monitoring module based on the wind turbine intelligent inspection and monitoring parameter data; The wind turbine intelligent monitoring module includes a vibration monitoring module, a patrol detection module and an auxiliary equipment acquisition module; The auxiliary device acquisition module includes video, audio and infrared imaging data collected by the intelligent terminal device.

6. The wind turbine intelligent inspection method based on big data according to claim 1, characterized in that: The coordinate data in the intelligent interactive device inspection data is compared with the station field coordinate data. If the data comparison result is normal, an intelligent interactive device inspection execution command is generated, including: Establishing a virtual image of the internal coordinates of the station in the three-dimensional model according to the station coordinate data; Substitute the coordinate data in the intelligent interactive device inspection data into the three-dimensional model to obtain the intelligent interactive device inspection path; The inspection path of the intelligent interactive device is compared with the virtual image of the station coordinates established in the three-dimensional model. If there are differences in the paths or breakpoints in the paths, the path coordinate information is listed as abnormal.

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