Error diagnosis and compensation method for multi-sensor fusion ultrasonic anemometry system

Abstract

The invention relates to the technical field of ultrasonic anemometers, in particular to a multi-sensor fusion ultrasonic anemometry system error diagnosis and compensation method, which comprises the following steps of: monitoring real-time anemometry data of a data acquisition point through an ultrasonic anemometer, and monitoring environmental parameters through an environmental sensor group; according to the environmental data, calculating an environmental parameter deviation value, and calculating a pollution index and a vibration amplitude of the ultrasonic anemometer at the data acquisition point; based on the real-time wind measurement data, the pollution index and the vibration amplitude, calculating an equipment state deviation value of the ultrasonic wind meter at the data acquisition point; based on the environmental parameter deviation value and the equipment state deviation value, carrying out overall deviation evaluation on the ultrasonic anemometer, comparing an overall deviation evaluation result with a preset deviation threshold value, and judging whether a compensation strategy is triggered or not; and when the overall deviation is greater than a preset deviation threshold value, starting different compensation strategies.

Description

Background Art

[0002] As the requirements for wind speed and direction measurement accuracy continue to increase in fields such as wind energy development, marine engineering, and meteorological monitoring, ultrasonic wind measurement technology has been widely used due to its advantages such as non-contact, rapid response, and high precision. However, in practical applications, ultrasonic anemometers not only need to accurately collect data such as wind speed and direction, but are also affected by various interference factors such as environmental factors and the status of the equipment itself. This requires the system to have effective error diagnosis and compensation capabilities to ensure the reliability and accuracy of the measurement results.

[0003] Existing ultrasonic wind measurement systems often rely on only a single sensor to obtain wind speed and direction data, but lack effective monitoring of environmental parameters such as temperature, humidity, salt spray and wave height. This makes it difficult to identify and correct errors caused by environmental influences on sensors in a complex or changing environment; ultrasonic probes are susceptible to interference such as pollution and vibration during long-term operation. Traditional technologies usually do not monitor the reflectivity of the probe surface or the vibration of the equipment in real time, and lack corresponding error diagnosis mechanisms, making it impossible to accurately judge the current state deviation of the equipment; traditional systems usually use fixed compensation coefficients or single compensation methods, which makes it difficult to perform targeted dynamic compensation for different error sources, making it difficult to meet the requirements of high-precision measurement in practical applications. Summary of the invention

[0004] The main purpose of the present invention is to provide an error diagnosis and compensation method for an ultrasonic wind measurement system with multi-sensor fusion. By integrating ultrasonic anemometers, temperature, humidity, salt spray concentration, wave height sensors and triaxial accelerometers, comprehensive monitoring of environmental parameters and equipment status is achieved. Through multi-source information fusion, the actual wind measurement environment can be more accurately reflected, thereby providing sufficient basis for error diagnosis; a clear mathematical model is used to calculate environmental parameter deviations and equipment status deviations, and weighted coefficients are used to integrate them into an overall deviation value. This quantitative evaluation method enables the error sources to be clearly distinguished and provides a quantitative basis for subsequent compensation strategies; it not only uses multi-sensor data to perform real-time diagnosis of various errors, but also considers the coordination between different compensation measures, thereby improving the accuracy and robustness of compensation.

[0005] The technical solution of the present invention is as follows: In the first aspect, a multi-sensor fusion ultrasonic wind measurement system error diagnosis and compensation method is proposed, the method comprising the following steps: S1, monitor the real-time wind measurement data of the data collection point through the ultrasonic anemometer, and monitor the environmental parameters through the environmental sensor group; S2. Calculate the environmental parameter deviation value based on the environmental data, and calculate the pollution index and vibration amplitude of the ultrasonic anemometer at the data collection point; S3. Calculate the equipment state deviation value of the ultrasonic anemometer at the data collection point based on the real-time wind measurement data, pollution index and vibration amplitude; S4. Based on the environmental parameter deviation value and the device status deviation value, an overall deviation evaluation of the ultrasonic anemometer is performed, and the overall deviation evaluation result is compared with a preset deviation threshold to determine whether a compensation strategy is triggered; S5. When the overall deviation is greater than a preset deviation threshold, different compensation strategies are initiated.

[0006] A further improvement of the present invention is that the specific content of S1 is: monitoring the real-time wind measurement data of the data collection point by an ultrasonic anemometer, and the real-time wind measurement data includes the real-time wind speed and real-time wind direction ; At the same time, a temperature sensor is used to monitor the ambient temperature , humidity sensor monitors relative humidity , salt spray concentration sensor monitors the density of salt spray particles , wave height sensor monitors wave height .

[0007] A further improvement of the present invention is that the calculation formula of the environmental parameter deviation value in S2 is: ; in, is the environmental parameter deviation value, The temperature threshold is the closest to The value of is the relative humidity threshold, is the salt spray particle density threshold, is the wave height threshold, is the temperature deviation weight factor, is the humidity deviation weight factor, is the salt spray deviation weight factor, is the wave height deviation weight factor, ,and .

[0008] A further improvement of the present invention is that the step of calculating the pollution index of the ultrasonic anemometer at the data collection point in S2 comprises the following specific steps: S21. When the ultrasonic anemometer probe surface is clean, record the reflectivity of the probe surface. , the reflectivity is the reflectivity reference value; S22. When the ultrasonic anemometer probe surface is completely contaminated, record the minimum reflectivity of the probe surface ; S23. The calculation formula of the pollution index is: , R is the reflectivity of the ultrasonic anemometer probe surface in the current state.

[0009] A further improvement of the present invention is that the method of calculating the vibration amplitude of the ultrasonic anemometer at the data collection point in S2 is: using a triaxial accelerometer to measure the acceleration values ​​of the ultrasonic anemometer in three orthogonal directions at the collection point , , , using the peak value method to determine the vibration amplitude of the ultrasonic anemometer , the calculation formula is expressed as .

[0010] A further improvement of the present invention is that the calculation formula of the device state deviation value in S3 is: ; in, is the wind speed fluctuation deviation at the data collection point within the preset collection time. is the standard deviation of wind speed at the data collection point within the preset collection time, is the average wind speed at the data collection point within the preset collection time. is the vibration amplitude threshold, is the wind speed fluctuation deviation weight factor, is the probe surface contamination index weight factor, is the vibration amplitude deviation weight factor, .

[0011] A further improvement of the present invention is that S4 comprises the following specific steps: S41, based on environmental parameter deviation value and equipment status deviation value , calculate the overall deviation value of the ultrasonic anemometer , the calculation formula is: ; is the weight factor of the environmental parameter deviation value; S42, preset deviation threshold ,Compare Deviation threshold The size relationship is Greater than or equal to the deviation threshold , triggers the compensation strategy.

[0012] A further improvement of the present invention is that S5 includes the following specific contents: S51. Comparison and If Greater than , trigger cleaning compensation, start high-pressure gas pulse cleaning, if the pollution index after cleaning If it is not reduced by 50%, switch to the backup probe; S52, Comparison and If Greater than , triggering posture compensation, and using hydraulic drive to adjust the height of the ultrasonic anemometer; S53, if the wind speed fluctuation deviation , triggering wind speed fluctuation compensation; S54, compare vibration amplitude and If Greater than , triggering vibration compensation and starting the shock-absorbing bracket.

[0013] A further improvement of the present invention is that the specific method of wind speed fluctuation compensation in S53 is: deploying a number of error compensation points around the data collection point, and respectively deploying ultrasonic anemometers to record the real-time wind measurement data of different error compensation points, obtaining the straight-line distances between different error compensation points and the data collection point, and extracting the real-time wind speed recorded by the ultrasonic anemometer at the three error compensation points with the smallest straight-line distances. , the value of i is 1-3, and the wind speed correction at the data collection point is performed. The formula is: ; in, They respectively represent the straight-line distances between the three error compensation points with the smallest straight-line distances from the data acquisition point.

[0014] The technical effects of the present invention are as follows: A multi-sensor fusion ultrasonic wind measurement system error diagnosis and compensation method was constructed. By integrating ultrasonic anemometers, temperature, humidity, salt spray concentration, wave height sensors and triaxial accelerometers, comprehensive monitoring of environmental parameters and equipment status was achieved. Through multi-source information fusion, the actual wind measurement environment can be more accurately reflected, thus providing sufficient basis for error diagnosis. A clear mathematical model was used to calculate environmental parameter deviations and equipment status deviations, and weighted coefficients were used to integrate them into an overall deviation value. This quantitative evaluation method enables the error sources to be clearly distinguished and provides a quantitative basis for subsequent compensation strategies. Not only does it use multi-sensor data to diagnose various errors in real time, but it also considers the coordination between different compensation measures, thereby improving the accuracy and robustness of compensation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1This is a flow chart of an error diagnosis and compensation method for an ultrasonic wind measurement system using multi-sensor fusion according to Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0016] Example 1 This embodiment proposes a multi-sensor fusion ultrasonic wind measurement system error diagnosis and compensation method. By integrating ultrasonic anemometers, temperature, humidity, salt spray concentration, wave height sensors and three-axis accelerometers, it realizes comprehensive monitoring of environmental parameters and equipment status. Through multi-source information fusion, it can more accurately reflect the actual wind measurement environment, thereby providing sufficient basis for error diagnosis; a clear mathematical model is used to calculate environmental parameter deviations and equipment status deviations, and weighted coefficients are used to integrate them into an overall deviation value. This quantitative evaluation method allows the error sources to be clearly distinguished and provides a quantitative basis for subsequent compensation strategies; it not only uses multi-sensor data to perform real-time diagnosis of various errors, but also considers the coordination between different compensation measures, thereby improving the accuracy and robustness of compensation.

[0017] Specifically, Figure 1 As shown, the error diagnosis and compensation method of a multi-sensor fusion ultrasonic wind measurement system proposed in this embodiment includes the following specific steps: S1, monitor the real-time wind measurement data of the data collection point through the ultrasonic anemometer, and monitor the environmental parameters through the environmental sensor group; S2. Calculate the environmental parameter deviation value based on the environmental data, and calculate the pollution index and vibration amplitude of the ultrasonic anemometer at the data collection point; S3. Calculate the equipment state deviation value of the ultrasonic anemometer at the data collection point based on the real-time wind measurement data, pollution index and vibration amplitude; S4. Based on the environmental parameter deviation value and the device status deviation value, an overall deviation evaluation of the ultrasonic anemometer is performed, and the overall deviation evaluation result is compared with a preset deviation threshold to determine whether a compensation strategy is triggered; S5. When the overall deviation is greater than a preset deviation threshold, different compensation strategies are initiated.

[0018] In this embodiment, the specific content of S1 is: using an ultrasonic anemometer to monitor the real-time wind measurement data of the data collection point, the real-time wind measurement data includes real-time wind speed and real-time wind direction ; At the same time, a temperature sensor is used to monitor the ambient temperature , humidity sensor monitors relative humidity , salt spray concentration sensor monitors the density of salt spray particles , wave height sensor monitors wave height .

[0019] In this embodiment, the calculation formula of the environmental parameter deviation value in S2 is: ; in, is the environmental parameter deviation value, The temperature threshold is the closest to The value of is the relative humidity threshold, is the salt spray particle density threshold, is the wave height threshold, is the temperature deviation weight factor, is the humidity deviation weight factor, is the salt spray deviation weight factor, is the wave height deviation weight factor, ,and .

[0020] In this embodiment, the calculation of the pollution index of the ultrasonic anemometer at the data collection point in S2 includes the following specific steps: S21. When the ultrasonic anemometer probe surface is clean, record the reflectivity of the probe surface. , the reflectivity is the reflectivity reference value; S22. When the ultrasonic anemometer probe surface is completely contaminated, record the minimum reflectivity of the probe surface ; S23. The calculation formula of the pollution index is: , R is the reflectivity of the ultrasonic anemometer probe surface in the current state.

[0021] In this embodiment, the method of calculating the vibration amplitude of the ultrasonic anemometer at the data collection point in S2 is: using a three-axis accelerometer to measure the acceleration values ​​of the ultrasonic anemometer in three orthogonal directions at the collection point , , , using the peak value method to determine the vibration amplitude of the ultrasonic anemometer , the calculation formula is expressed as .

[0022] In this embodiment, the calculation formula of the device state deviation value in S3 is: ; in, is the wind speed fluctuation deviation at the data collection point within the preset collection time. is the standard deviation of wind speed at the data collection point within the preset collection time, is the average wind speed at the data collection point within the preset collection time. is the vibration amplitude threshold, is the wind speed fluctuation deviation weight factor, is the probe surface contamination index weight factor, is the vibration amplitude deviation weight factor, .

[0023] In this embodiment, S4 includes the following specific steps: S41, based on environmental parameter deviation value and equipment status deviation value , calculate the overall deviation value of the ultrasonic anemometer , the calculation formula is: ; is the weight factor of the environmental parameter deviation value; S42, preset deviation threshold ,Compare Deviation threshold The size relationship is Greater than or equal to the deviation threshold , triggers the compensation strategy.

[0024] In this embodiment, S5 includes the following specific contents: S51. Comparison and If Greater than , trigger cleaning compensation, start high-pressure gas pulse cleaning, if the pollution index after cleaning If it is not reduced by 50%, switch to the backup probe; S52, Comparison and If Greater than , triggering posture compensation, and using hydraulic drive to adjust the height of the ultrasonic anemometer; S53, if the wind speed fluctuation deviation , triggering wind speed fluctuation compensation; S54, compare vibration amplitude and If Greater than , triggering vibration compensation and starting the shock-absorbing bracket.

[0025] In this embodiment, the specific method of wind speed fluctuation compensation in S53 is: deploy a number of error compensation points around the data collection point, and respectively deploy ultrasonic anemometers to record the real-time wind measurement data of different error compensation points, obtain the straight-line distance between different error compensation points and the data collection point, and extract the real-time wind speed recorded by the ultrasonic anemometer at the three error compensation points with the smallest straight-line distance. , the value of i is 1-3, and the wind speed correction at the data collection point is performed. The formula is: ; in, They respectively represent the straight-line distances between the three error compensation points with the smallest straight-line distances from the data acquisition point.

[0026] The threshold and weight may be set by default according to the present invention, or may be set by an operator.

[0027] Example 2 This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; the processor executes the above-mentioned multi-sensor fusion ultrasonic wind measurement system error diagnosis and compensation method by calling the computer program stored in the memory.

[0028] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a multi-sensor fusion ultrasonic wind measurement system error diagnosis and compensation method provided in the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0029] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as a "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0030] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0031] The present invention is described with reference to flowcharts and block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process or block in the flowchart and block diagram, as well as the combination of processes and blocks in the flowchart or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts. Figure 1 Process or multiple processes and boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0032] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 Process or multiple processes and boxes Figure 1 The steps for the functions specified in one or more boxes.

[0033] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

Claims

1. A multi-sensor fusion ultrasonic wind measurement system error diagnosis and compensation method, characterized by: The specific steps include: S1, monitor the real-time wind measurement data of the data collection point through the ultrasonic anemometer, and monitor the environmental parameters through the environmental sensor group; S2. Calculate the environmental parameter deviation value based on the environmental data, and calculate the pollution index and vibration amplitude of the ultrasonic anemometer at the data collection point; S3. Calculate the equipment state deviation value of the ultrasonic anemometer at the data collection point based on the real-time wind measurement data, pollution index and vibration amplitude; S4. Based on the environmental parameter deviation value and the device status deviation value, an overall deviation evaluation of the ultrasonic anemometer is performed, and the overall deviation evaluation result is compared with a preset deviation threshold to determine whether a compensation strategy is triggered; S5. When the overall deviation is greater than a preset deviation threshold, different compensation strategies are initiated.

2. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 1 is characterized by: The specific content of S1 is: using an ultrasonic anemometer to monitor the real-time wind measurement data of the data collection point, the real-time wind measurement data includes real-time wind speed and real-time wind direction ; At the same time, a temperature sensor is used to monitor the ambient temperature , humidity sensor monitors relative humidity , salt spray concentration sensor monitors the density of salt spray particles , wave height sensor monitors wave height .

3. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 2 is characterized by: The calculation formula of the environmental parameter deviation value in S2 is: ； in, is the environmental parameter deviation value, The temperature threshold is the closest to The value of is the relative humidity threshold, is the salt spray particle density threshold, is the wave height threshold, is the temperature deviation weight factor, is the humidity deviation weight factor, is the salt spray deviation weight factor, is the wave height deviation weight factor, ,and .

4. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 3 is characterized by: Calculating the pollution index of the ultrasonic anemometer at the data collection point in S2 includes the following specific steps: S21. When the ultrasonic anemometer probe surface is clean, record the reflectivity of the probe surface. , the reflectivity is the reflectivity reference value; S22. When the ultrasonic anemometer probe surface is completely contaminated, record the minimum reflectivity of the probe surface ; S23. The calculation formula of the pollution index is: , R is the reflectivity of the ultrasonic anemometer probe surface in the current state.

5. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 4 is characterized by: The method for calculating the vibration amplitude of the ultrasonic anemometer at the data collection point in S2 is: using a triaxial accelerometer to measure the acceleration values ​​of the ultrasonic anemometer in three orthogonal directions at the collection point , , , using the peak value method to determine the vibration amplitude of the ultrasonic anemometer , the calculation formula is expressed as .

6. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 5 is characterized by: The calculation formula of the device state deviation value in S3 is: ； in, is the wind speed fluctuation deviation at the data collection point within the preset collection time. is the standard deviation of wind speed at the data collection point within the preset collection time, is the average wind speed at the data collection point within the preset collection time. is the vibration amplitude threshold, is the wind speed fluctuation deviation weight factor, is the probe surface contamination index weight factor, is the vibration amplitude deviation weight factor, .

7. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 6 is characterized by: The S4 comprises the following specific steps: S41, based on environmental parameter deviation value and equipment status deviation value , calculate the overall deviation value of the ultrasonic anemometer , the calculation formula is: ; is the weight factor of the environmental parameter deviation value; S42, preset deviation threshold ,Compare Deviation threshold The size relationship is Greater than or equal to the deviation threshold , triggers the compensation strategy.

8. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 7 is characterized by: The S5 includes the following specific contents: S51. Comparison and If Greater than , trigger cleaning compensation, start high-pressure gas pulse cleaning, if the pollution index after cleaning If it is not reduced by 50%, switch to the backup probe; S52, Comparison and If Greater than , triggering posture compensation, and using hydraulic drive to adjust the height of the ultrasonic anemometer; S53, if the wind speed fluctuation deviation , triggering wind speed fluctuation compensation; S54, compare vibration amplitude and If Greater than , triggering vibration compensation and starting the shock-absorbing bracket.

9. The method for error diagnosis and compensation of ultrasonic wind measurement system with multi-sensor fusion according to claim 8, characterized in that: The specific method of wind speed fluctuation compensation in S53 is: deploy a number of error compensation points around the data collection point, and respectively deploy ultrasonic anemometers to record the real-time wind measurement data of different error compensation points, obtain the straight-line distance between different error compensation points and the data collection point, and extract the real-time wind speed recorded by the ultrasonic anemometer at the three error compensation points with the smallest straight-line distance. , the value of i is 1-3, and the wind speed correction at the data collection point is performed. The formula is: ； in, They respectively represent the straight-line distances between the three error compensation points with the smallest straight-line distances from the data acquisition point.

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