Fault prediction platform for wind driven generator

Abstract

The utility model discloses a fault prediction platform used for a wind driven generator. The fault prediction platform comprises a data acquisition module, a master control module, a data abnormity alarm module and a display module. The data acquisition module, the data abnormity alarm module and the display module are all in communication connection with the main control module; the data acquisition module comprises an anemograph, a rotating speed sensor, a vibration sensor, thermal imaging monitoring equipment, a voltage sensor and a current sensor; the main control module comprises a data storage unit and a data processing unit; the data acquisition module transmits acquired monitoring data to the data processing unit, and the data processing unit compares the received monitoring data with the same type of data threshold stored in the data storage unit. The data processing unit transmits data abnormity signals to the data abnormity alarm module and the display module, the data abnormity alarm module carries out on-site and remote alarm, and the display module carries out abnormal data display.

Description

TECHNICAL FIELD

[0001] The utility model relates to wind driven generator fault prediction technical field, concretely is a kind of fault prediction platform for wind driven generator. BACKGROUND

[0002] Wind driven generator usually operates in complex and harsh environment, such as high altitude, strong wind, sand, salt fog etc., these factors cause wind driven generator to be prone to various faults, and traditional fault detection is often carried out after maintenance after fault has occurred, which not only causes long downtime loss and increases maintenance cost, but also can cause more serious damage due to failure to handle in time;Therefore, a platform capable of predicting fault in advance is needed.

[0003] In the prior art, the utility model discloses a kind of wind driven generator system and wind driven generator's fault analysis equipment of patent No.CN202022020459.1, it includes: sensor data collector, it respectively from the hall type sensor collects the voltage current signal of first frequency, from the vibration sensor collects the vibration signal of first frequency, from the data acquisition transmitter collects the current voltage signal of second frequency;First signal executor, the voltage current signal of the first frequency is converted from time domain to frequency domain and data dimension is reduced;Data transmission preprocessor, the voltage current signal of the first frequency after the first signal executor processing and the voltage current signal of the second frequency and the vibration signal obtained from the sensor data collector are respectively executed data cleaning, dimension reduction processing and time sequence data queuing processing;Data edge cloud transmitter;verifier;Memory.This wind driven generator system and wind driven generator's fault analysis equipment can accurately monitor operating state and predict its future operating condition.

[0004] The above-mentioned patent provides a device that can predict wind driven generator fault, the device detects voltage current signal through hall sensor, can detect voltage current signal change in set frequency range, and analyzes whether wind driven generator appears fault in time;But wind driven generator damage is caused by many factors, and the device detects single factor, cannot comprehensively detect wind driven generator;Further improvement is needed. UTILITY MODEL CONTENTS

[0005] The utility model aims at providing a kind of fault prediction platform for wind driven generator, to improve the single factor of the existing wind driven generator fault prediction equipment detection, cannot comprehensively monitor the running condition of wind driven generator, lead to the problem that the fault prediction function of existing wind driven generator is not perfect.

[0006] The utility model discloses a kind of fault prediction platforms for wind generator, including data acquisition module, main control module, data abnormality alarm module and display module;The data acquisition module, data abnormality alarm module and display module are all connected with main control module communication;The data acquisition module includes anemograph, speed sensor, vibration sensor, thermal imaging monitoring equipment, voltage sensor and current sensor;The main control module includes data storage unit and data processing unit;The monitoring data collected by the data acquisition module is passed to data processing unit, the monitoring data received by the data processing unit is compared with the same type data threshold value stored in data storage unit, when data anomaly occurs, the data processing unit passes data anomaly signal to data abnormality alarm module and display module, the data abnormality alarm module carries out on-site and remote alarm, and the display module carries out abnormal data display.

[0007] Preferably, the anemograph model is ft-wqx2, the speed sensor model is Hangzhen HZ-860, the vibration sensor model is SSF-VIB-Z300, the thermal imaging monitoring equipment model is AK-TPC2000, and the voltage / current sensor adopts ABB current / voltage sensor.

[0008] Preferably, the utility model further comprises a data input module, which is connected with the main control module in communication, and the data input module can be used for file input, interface input and manual input.

[0009] Preferably, the data storage unit comprises a mysql database and an unstructured file storage.

[0010] Preferably, the data processing unit can also be used for data cleaning and data classification, and the historical monitoring data stored in the data storage unit can be archived and saved through the data cleaning and data classification.

[0011] Compared with the prior art, the utility model has the advantages that:

[0012] 1、The utility model discloses a plurality of sensors with multiple monitoring functions are arranged, the running state of wind turbine generator unit is monitored in real time, the running reliability of wind turbine generator unit is improved, and the received monitoring data is compared with the same type data threshold value stored in data storage unit through data processing unit, so that abnormal value can be found in time, the staff can predict wind turbine generator unit fault, and abnormal early warning can be realized through data abnormality alarm module and display module, and equipment life can be analyzed and evaluated through display report, so that the fault prediction function of wind generator is improved from various aspects. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 It is the flow structure schematic diagram of the utility model fault prediction platform.

[0014] Figure 2 is a structural schematic view of the data input module of the utility model;

[0015] Figure 3 is a structural schematic view of the data storage unit of the utility model. DETAILED DESCRIPTION

[0016] In the utility model, unless another explicit provision and limitation, the terms "mount", "connect", "connection", "fix" and other terms should be broad sense understanding, for example, can be fixed connection, also can be detachable connection, or integral; can be mechanical connection, also can be electrical connection; can be directly connected, also can be indirectly connected through intermediate medium, can be the communication of two elements or the interaction of two elements. For ordinary skilled in the art, the above terms can be understood according to the specific meaning of the utility model.

[0017] The following is further described in conjunction with the drawings and specific embodiments:

[0018] Example 1

[0019] A kind of fault prediction platform for wind turbine, including data acquisition module, main control module, data exception alarm module and display module;Data acquisition module, data exception alarm module and display module are all connected with main control module communication;Data acquisition module includes temperature sensor, anemograph, speed sensor, vibration sensor, camera, voltage sensor and current sensor;Data exception alarm module carries out on-site and remote alarm, on-site alarm can be alarmed by on-site alarm, and it is convenient to remind staff abnormal state appears.Remote alarm can be through GSM alarm to its internal preset telephone number dial and send alarm short message, display module carries out abnormal data display.Display module can show real-time data by computer display screen, and pass main control module to data analysis and statistics, generate chart and report, help user to intuitively understand equipment operation condition and trend, so as to make corresponding decision and adjustment.

[0020] The anemometer is of the model ft-wqx2, which is an ultrasonic anemometer, the wind speed measurement range is 0-60 m / s, the resolution is 0.01 m / s, and the accuracy is 0.1 m / s; the wind direction measurement range is 0-360°, the resolution is 0.1°, and the accuracy is ±1°. The wind speed and direction are detected by transmitting continuous variable frequency ultrasonic signals through the measurement of the relative phase, and the rotation speed of the wind turbine generator set can be adjusted in time according to the wind speed and direction. The rotation speed sensor is of the model Hangzhen HZ-860, which can convert the angular displacement into an electrical signal for counting by the counter, and can measure the rotation speed and linear speed of the gear and impeller without contact, facilitating the rotation speed measurement of the impeller, rotating shaft and gear in the wind turbine generator set. The vibration sensor is of the model SSF-VIB-Z300, which can automatically calculate the time domain statistics of the vibration signal such as acceleration peak value, peak-to-peak value and effective value; by setting the vibration sensor on the motor main shaft, the vibration frequency and amplitude of the main shaft can be detected, and the working state of the motor main shaft can be monitored in time. The thermal imaging monitoring device is of the model AK-TPC2000, which has the function of network video transmission, and can transmit the collected temperature and image data to the main control module. The visible light camera outputs full-color images in the daytime, and can monitor the wind turbine generator set in real time. The thermal imaging assembly can process images and calculate temperature for 24 hours, can detect a large range through the thermal imaging assembly, can accurately locate abnormal parts, the temperature measurement range is-30℃ to +500℃, and the temperature of the generator set and the environment can be monitored conveniently. The voltage / current sensor is an ABB current / voltage sensor; by setting the voltage / current sensor, the changes of the input and output current and voltage of the generator set can be monitored in time, and the cable fault can also be detected through the changes of the current and voltage.

[0021] The main control module includes a data storage unit and a data processing unit; the data processing unit adopts a CPU chip. The data storage unit includes a mysql database and an unstructured file storage. The data storage unit includes a mysql database and an unstructured file storage. The mysql database can be used to manage and operate data using structured query language (SQL), facilitating the storage and query of data. The unstructured file storage can be used to store various types of data materials such as documents, images, audio and video. The data acquisition module transmits the collected monitoring data to the data processing unit, and the data processing unit compares the received monitoring data with the same type of data threshold stored in the data storage unit, and transmits a data abnormality signal to the data abnormality alarm module and the display module when data abnormality occurs.

[0022] The data input module is further included, and the data input module is in communication connection with the main control module; the data input module can be used for file form input, interface input, and manual input. By setting the data input module, it is convenient to store the parameters of external equipment into the data storage unit by manual operation. The parameters of external equipment include the data of key equipment such as wind turbine generators, wind wheels, variable pitch systems, frequency converters, transformers, cables, inverters, and power collection lines. When the data processing unit evaluates the received monitoring data, it is convenient to perform fault evaluation according to the key parameters of the equipment, and to timely pay attention to whether the related components are damaged. The data processing unit can also be used for data cleaning and data classification; the historical monitoring data stored in the data storage unit is archived and saved by data cleaning and data classification. Data cleaning is to clean dirty data, that is, to correct and identify the historical monitoring data stored in the data storage unit, and to process invalid and repeated data. Data classification is used to classify and save the historical monitoring data stored in the data storage unit; data classification adopts DAMA data classification method and other common data classification methods, and other common data classification methods include classification according to data generation link, data governance type, and common data classification method in production practice. For example, when storing historical detection data, the historical detection data of the wind turbine generator can be classified in multiple angles according to components, functions, and time, to facilitate staff to find.

[0023] Embodiment 2

[0024] A fault prediction platform for a wind turbine includes a data acquisition module, a main control module, a data anomaly alarm module, and a display module; the data acquisition module, the data anomaly alarm module, and the display module are in communication connection with the main control module. The data acquisition module includes an anemometer, a speed sensor, a vibration sensor, a thermal imaging monitoring device, a voltage sensor, and a current sensor; the anemometer is of ft-wqx2 type, the speed sensor is of navigation vibration HZ-860 type, the vibration sensor is of SSF-VIB-Z300 type, the thermal imaging monitoring device is of AK-TPC2000 type, and the voltage / current sensor adopts ABB current / voltage sensor.

[0025] The master control module comprises a data storage unit and a data processing unit; the data processing unit adopts an MCU chip. The data storage unit comprises a mysql database and an unstructured file storage. The data storage unit comprises a mysql database and an unstructured file storage. The data storage unit comprises a mysql database and an unstructured file storage. By setting the mysql database, the structured query language (SQL) can be used to manage and operate data, facilitating the storage and query of data. By setting the unstructured file storage, documents, images, audio, video and other types of data materials can be stored. The data acquisition module transmits the collected monitoring data to the data processing unit, and the data processing unit compares the received monitoring data with the same type of data threshold stored in the data storage unit. When data anomalies occur, the data processing unit transmits data anomaly signals to the data anomaly alarm module and the display module, the data anomaly alarm module performs on-site and remote alarm, and the display module displays abnormal data.

[0026] The data processing unit can also be used for data cleaning and data classification; through data cleaning and data classification, the historical monitoring data stored in the data storage unit is archived and saved. Data cleaning is to clean dirty data, which refers to correcting and identifying invalid and repeated data of the historical monitoring data stored in the data storage unit. Data classification is used to classify and save the historical monitoring data stored in the data storage unit; data classification adopts DAMA data classification method and other common data classification methods, other common data classification methods include classification according to data generation link, data governance type and production practice commonly used data classification method, etc. In addition, it also includes a data input module, which is in communication connection with the master control module; the data input module can be used for file form input, interface input and manual input. In addition, it also includes a data input module, which is in communication connection with the master control module; the data input module can be used for file form input, interface input and manual input. By setting the data input module, it is convenient to store the parameters of external equipment into the data storage unit by manual. The parameters of external equipment include the data of key equipment such as wind turbine generator unit, wind wheel, variable pitch system, frequency converter, transformer, cable, inverter and power collection line. When the data processing unit evaluates the received monitoring data, it is convenient to evaluate the fault according to the key parameters of the equipment, and to pay attention to whether the related parts are damaged in time.

[0027] In summary, the utility model discloses through setting up the sensor with multiple monitoring function, to the operation state of wind turbine generator system is real -time period monitoring, improve the operation reliability of wind turbine generator system, compare the monitoring data received with the same type data threshold value stored in data storage unit through data processing unit simultaneously, can discover abnormal value in time, the staff is convenient to predict wind turbine generator system failure, and realize abnormal early warning through data anomaly alarm module and display module and through display report analysis and evaluation equipment life, improve the fault prediction function of wind driven generator from all aspects.

[0028] The above is only preferred embodiment of the utility model, and does not limit the utility model, and the utility model can have various changes and changes for the person skilled in the art. Any modification, equivalent replacement, improvement etc. that is made within the spirit and principle of the utility model should be included in the protection scope of the utility model.

Claims

1. A fault prediction platform usable for a wind power generator, characterized in that, The application relates to a wind turbine monitoring system, which comprises a data acquisition module, a main control module, a data exception alarm module and a display module; the data acquisition module, the data exception alarm module and the display module are in communication connection with the main control module; the data acquisition module comprises an anemograph, a rotating speed sensor, a vibration sensor, a thermal imaging monitoring device, a voltage sensor and a current sensor; the main control module comprises a data storage unit and a data processing unit; the data acquisition module transmits the collected monitoring data to the data processing unit; the data processing unit compares the received monitoring data with the same type of data threshold stored in the data storage unit; when data exception occurs, the data processing unit transmits a data exception signal to the data exception alarm module and the display module; the data exception alarm module performs on-site and remote alarm; and the display module performs abnormal data display.

2. A fault prediction platform for wind turbine as claimed in claim 1, wherein, The anemograph is of the ft-wqx2 type, the rotating speed sensor is of the hangzhen HZ-860 type, the vibration sensor is of the SSF-VIB-Z300 type, the thermal imaging monitoring device is of the AK-TPC2000 type, and the voltage / current sensor adopts an ABB current / voltage sensor.

3. A fault prediction platform for wind turbine as claimed in claim 1, wherein, In addition, the application further comprises a data input module, which is in communication connection with the main control module; the data input module can be used for file form input, interface input and manual input.

4. A fault prediction platform for wind turbine as claimed in claim 1, wherein, The data storage unit comprises a mysql database and an unstructured file storage.

5. A fault prediction platform for wind turbine as claimed in claim 1, wherein, The data processing unit can also be used for data cleaning and data classification; the historical monitoring data stored in the data storage unit are filed and saved through the data cleaning and data classification.

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