An Error Diagnosis and Compensation Method for an Ultrasonic Wind Measurement System with Multi-Sensor Fusion

Abstract

The present invention relates to the technical field of ultrasonic anemometers, and particularly to a method for error diagnosis and compensation of an ultrasonic wind measurement system with multi-sensor fusion. The method includes: monitoring the real-time wind measurement data at the data acquisition point through an ultrasonic anemometer, and monitoring the environmental parameters through an environmental sensor group; calculating the deviation value of the environmental parameters according to the environmental data, and calculating the pollution index and vibration amplitude of the ultrasonic anemometer at the data acquisition point; calculating the equipment state deviation value of the ultrasonic anemometer at the data acquisition point based on the real-time wind measurement data, pollution index and vibration amplitude; performing an overall deviation evaluation of the ultrasonic anemometer based on the environmental parameter deviation value and the equipment state deviation value, and comparing the overall deviation evaluation result with a preset deviation threshold to determine whether to trigger a compensation strategy; when the overall deviation is greater than the preset deviation threshold, different compensation strategies are activated.

Description

Background Art

[0002] With the continuous improvement of the requirements for the measurement accuracy of wind speed and wind direction in the fields of wind energy development, ocean engineering, and meteorological monitoring, ultrasonic anemometry technology has been widely used due to its advantages such as non-contact, rapid response, and high accuracy. However, in practical applications, ultrasonic anemometers not only need to accurately collect data such as wind speed and wind direction, but are also affected by various interference factors such as environmental factors and the state 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 anemometry systems often rely solely on a single sensor to obtain wind speed and wind direction data, and lack effective monitoring of environmental parameters such as temperature, humidity, salt spray, and wave height. This results in the difficulty of timely identifying and correcting the errors generated by the sensor due to environmental influences in complex or changing environments; ultrasonic probes are prone to contamination and vibration interference during long-term operation. Traditional technologies usually do not perform real-time monitoring of the reflectivity of the probe surface or equipment vibration, and lack corresponding error diagnosis mechanisms, thus being unable to accurately judge the current state deviation of the equipment; traditional systems usually adopt fixed compensation coefficients or single compensation means, making it difficult to perform targeted dynamic compensation for different error sources, and thus 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 anemometry system with multi-sensor fusion. By integrating an ultrasonic anemometer, temperature, humidity, salt spray concentration, wave height sensors, and a triaxial accelerometer, comprehensive monitoring of environmental parameters and equipment status is achieved. Through multi-source information fusion, the actual anemometry environment can be more accurately reflected, thus providing sufficient basis for error diagnosis; a clear mathematical model is used to calculate the environmental parameter deviation and equipment status deviation, and the weighted coefficients are used to integrate them into an overall deviation value. This quantitative evaluation method enables the clear distinction of error sources and provides a quantitative basis for subsequent compensation strategies; not only real-time diagnosis of various errors using multi-sensor data, but also the coordination between different compensation measures is considered, improving the accuracy and robustness of compensation.

[0005] The technical solution of the present invention is as follows:

[0006] In the first aspect, an error diagnosis and compensation method for an ultrasonic anemometry system with multi-sensor fusion is proposed. The method includes the following steps:

[0007] S1. Monitor the real-time anemometry data at the data acquisition point through an ultrasonic anemometer, and monitor the environmental parameters through an environmental sensor group;

[0008] 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 acquisition point;

[0009] S3. Calculate the equipment status deviation value of the ultrasonic anemometer at the data acquisition point based on the real-time wind measurement data, pollution index, and vibration amplitude;

[0010] S4. Based on the environmental parameter deviation value and the equipment status deviation value, conduct an overall deviation assessment of the ultrasonic anemometer, and compare the overall deviation assessment result with the preset deviation threshold to determine whether to trigger the compensation strategy;

[0011] S5. When the overall deviation is greater than the preset deviation threshold, activate different compensation strategies.

[0012] A further improvement of the present invention is that the specific content of S1 is: monitor the real-time wind measurement data of the data acquisition point through the ultrasonic anemometer, and the real-time wind measurement data includes the real-time wind speed and the real-time wind direction ; at the same time, use a temperature sensor to monitor the environmental temperature , a humidity sensor to monitor the relative humidity , a salt fog concentration sensor to monitor the salt fog particle density , and a wave height sensor to monitor the wave height .

[0013] A further improvement of the present invention is that the calculation formula for the environmental parameter deviation value in S2 is:

[0014] ;

[0015] where, is the environmental parameter deviation value, is the value closest to in the temperature threshold range, is the relative humidity threshold, is the salt fog particle density threshold, is the wave height threshold, is the temperature deviation weight factor, is the humidity deviation weight factor, is the salt fog deviation weight factor, is the wave height deviation weight factor, , and .

[0016] A further improvement of the present invention is that the calculation of the pollution index of the ultrasonic anemometer at the data acquisition point in S2 includes the following specific steps:

[0017] S21. Record the reflectivity of the probe surface when the probe surface of the ultrasonic anemometer is in a clean state , the reflectance is the reference reflectance value;

[0018] S22. Under the fully contaminated state of the ultrasonic anemometer probe surface, record the minimum reflectance value of the probe surface ;

[0019] S23. The calculation formula of the pollution index is: , where R is the reflectance of the ultrasonic anemometer probe surface in the current state.

[0020] A further improvement of the present invention is that the method for calculating the vibration amplitude of the ultrasonic anemometer at the data acquisition point in S2 is: using a triaxial accelerometer to measure the acceleration values of the ultrasonic anemometer in three orthogonal directions at the acquisition point , , , and using the peak method to determine the vibration amplitude of the ultrasonic anemometer , and the calculation formula is expressed as .

[0021] A further improvement of the present invention is that the calculation formula of the equipment state deviation value in S3 is:

[0022] ;

[0023] Among them, is the wind speed fluctuation deviation of the data acquisition point within the preset acquisition duration, is the standard deviation of the wind speed of the data acquisition point within the preset acquisition duration, is the average wind speed of the data acquisition point within the preset acquisition duration, is the vibration amplitude threshold, is the wind speed fluctuation deviation weight factor, is the probe surface pollution index weight factor, is the vibration amplitude deviation weight factor, .

[0024] A further improvement of the present invention is that S4 includes the following specific steps:

[0025] S41. Based on the environmental parameter deviation value and the equipment state deviation value , calculate the overall deviation value of the ultrasonic anemometer, and the calculation formula is: ; is the weight factor of the environmental parameter deviation value;

[0026] S42. Preset the deviation threshold , and compare with the deviation threshold The size relationship, when is greater than or equal to the deviation threshold trigger the compensation strategy.

[0027] A further improvement of the present invention is that the S5 includes the following specific contents:

[0028] S51. Compare with for the size relationship. If is greater than , trigger the cleaning compensation, start the high-pressure gas pulse cleaning. If the pollution index after cleaning does not decrease by 50%, switch to the spare probe;

[0029] S52. Compare with for the size relationship. If is greater than , trigger the pose compensation, and use hydraulic drive to adjust the height of the ultrasonic anemometer;

[0030] S53. If the wind speed fluctuation deviation , trigger the wind speed fluctuation compensation;

[0031] S54. Compare the vibration amplitude with for the size relationship. If is greater than , trigger the vibration compensation and start the shock-absorbing bracket.

[0032] A further improvement of the present invention is that the specific method of the wind speed fluctuation compensation in the S53 is: deploy a number of error compensation points around the data acquisition point, and deploy ultrasonic anemometers respectively to record the real-time wind measurement data of different error compensation points, obtain the straight-line distances between different error compensation points and the data acquisition point, and extract the real-time wind speeds recorded by the ultrasonic anemometers at the 3 error compensation points with the smallest straight-line distances , where i takes values from 1 to 3, and perform wind speed correction at the data acquisition point. The formula is:

[0033] ;

[0034] Among them, respectively represent the straight-line distances between the data acquisition point and the 3 error compensation points with the smallest straight-line distances.

[0035] The technical effects of the present invention are as follows:

[0036] A method for error diagnosis and compensation of an ultrasonic anemometry system with multi-sensor fusion is constructed. By integrating an ultrasonic anemometer, temperature, humidity, salt spray concentration, wave height sensors, and a triaxial accelerometer, comprehensive monitoring of environmental parameters and equipment status is achieved. Through multi-source information fusion, the actual anemometry environment can be more accurately reflected, thus providing sufficient basis for error diagnosis. A clear mathematical model is used to calculate the deviations of environmental parameters and equipment status, and the weighted coefficients are used to integrate them into an overall deviation value. This quantitative evaluation method enables clear distinction of error sources and provides a quantitative basis for subsequent compensation strategies. Not only real-time diagnosis of various errors is carried out using multi-sensor data, but also the coordination between different compensation measures is considered, improving the accuracy and robustness of compensation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments read in conjunction with the accompanying drawings:

[0038] Figure 1 It is a schematic flowchart of a method for error diagnosis and compensation of an ultrasonic anemometry system with multi-sensor fusion according to Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] Embodiment 1

[0040] This embodiment presents a method for error diagnosis and compensation of an ultrasonic anemometry system with multi-sensor fusion. By integrating an ultrasonic anemometer, temperature, humidity, salt spray concentration, wave height sensors, and a triaxial accelerometer, comprehensive monitoring of environmental parameters and equipment status is achieved. Through multi-source information fusion, the actual anemometry environment can be more accurately reflected, thus providing sufficient basis for error diagnosis. A clear mathematical model is used to calculate the deviations of environmental parameters and equipment status, and the weighted coefficients are used to integrate them into an overall deviation value. This quantitative evaluation method enables clear distinction of error sources and provides a quantitative basis for subsequent compensation strategies. Not only real-time diagnosis of various errors is carried out using multi-sensor data, but also the coordination between different compensation measures is considered, improving the accuracy and robustness of compensation.

[0041] Specifically, as Figure 1 shown, a method for error diagnosis and compensation of an ultrasonic anemometry system with multi-sensor fusion proposed in this embodiment includes the following specific steps:

[0042] S1. Monitor the real-time anemometry data at the data acquisition point through the ultrasonic anemometer, and monitor the environmental parameters through the environmental sensor group;

[0043] S2. Calculate the deviation value of the environmental parameters according to the environmental data, and calculate the pollution index and vibration amplitude of the ultrasonic anemometer at the data acquisition point;

[0044] S3. Calculate the equipment status deviation value of the ultrasonic anemometer at the data acquisition point based on the real-time wind measurement data, pollution index, and vibration amplitude;

[0045] S4. Based on the environmental parameter deviation value and the equipment status deviation value, conduct an overall deviation assessment of the ultrasonic anemometer, and compare the overall deviation assessment result with a preset deviation threshold to determine whether to trigger a compensation strategy;

[0046] S5. When the overall deviation is greater than the preset deviation threshold, activate different compensation strategies.

[0047] In this embodiment, the specific content of S1 is: monitor the real-time wind measurement data of the data acquisition point through the ultrasonic anemometer, and the real-time wind measurement data includes the real-time wind speed and the real-time wind direction ; at the same time, use a temperature sensor to monitor the environmental temperature , a humidity sensor to monitor the relative humidity , a salt mist concentration sensor to monitor the salt mist particle density , and a wave height sensor to monitor the wave height .

[0048] In this embodiment, the calculation formula for the environmental parameter deviation value in S2 is:

[0049] ;

[0050] where, is the environmental parameter deviation value, is the value closest to in the temperature threshold range, is the relative humidity threshold, is the salt mist particle density threshold, is the wave height threshold, is the temperature deviation weight factor, is the humidity deviation weight factor, is the salt mist deviation weight factor, is the wave height deviation weight factor, , and .

[0051] In this embodiment, the specific steps for calculating the pollution index of the ultrasonic anemometer at the data acquisition point in S2 are as follows:

[0052] S21. Record the reflectivity on the surface of the ultrasonic anemometer probe in a clean state, and the reflectivity is the reflectivity reference value;

[0053] S22. Record the minimum reflectivity of the ultrasonic anemometer probe surface in a completely contaminated state. ;

[0054] S23. The calculation formula for the pollution index is: , where R is the reflectivity of the ultrasonic anemometer probe surface in the current state.

[0055] In this embodiment, the method for calculating the vibration amplitude of the ultrasonic anemometer at the data acquisition point in S2 is as follows: Use a three-axis accelerometer to measure the acceleration values of the ultrasonic anemometer in three orthogonal directions at the acquisition point , , , and use the peak method to determine the vibration amplitude of the ultrasonic anemometer , and the calculation formula is expressed as .

[0056] In this embodiment, the calculation formula for the equipment state deviation value in S3 is:

[0057] ;

[0058] Among them, is the wind speed fluctuation deviation at the data acquisition point within the preset acquisition duration, is the standard deviation of the wind speed at the data acquisition point within the preset acquisition duration, is the average value of the wind speed at the data acquisition point within the preset acquisition duration, is the vibration amplitude threshold, is the wind speed fluctuation deviation weight factor, is the probe surface pollution index weight factor, is the vibration amplitude deviation weight factor, .

[0059] In this embodiment, S4 includes the following specific steps:

[0060] S41. Based on the environmental parameter deviation value and the equipment state deviation value , calculate the overall deviation value of the ultrasonic anemometer, and the calculation formula is: ; is the weight factor of the environmental parameter deviation value;

[0061] S42. Preset the deviation threshold , compare with the deviation threshold , and when is greater than or equal to the deviation threshold , trigger the compensation strategy.

[0062] In this embodiment, S5 includes the following specific contents:

[0063] S51. Compare with to determine their magnitude relationship. If is greater than , trigger cleaning compensation, start high-pressure gas pulse cleaning. If the pollution index after cleaning does not decrease by 50%, switch to the spare probe;

[0064] S52. Compare with to determine their magnitude relationship. If is greater than , trigger pose compensation, and use hydraulic drive to adjust the height of the ultrasonic anemometer;

[0065] S53. If the wind speed fluctuation deviation , trigger wind speed fluctuation compensation;

[0066] S54. Compare the vibration amplitude with to determine their magnitude relationship. If is greater than , trigger vibration compensation and start the shock-absorbing bracket.

[0067] In this embodiment, the specific method of wind speed fluctuation compensation in S53 is as follows: Deploy a number of error compensation points around the data acquisition point, and deploy ultrasonic anemometers respectively to record the real-time wind measurement data of different error compensation points. Obtain the straight-line distances between different error compensation points and the data acquisition point, and extract the real-time wind speeds recorded by the ultrasonic anemometers at the 3 error compensation points with the smallest straight-line distances , where i takes values from 1 to 3, and perform wind speed correction at the data acquisition point. The formula is:

[0068] ;

[0069] where respectively represent the straight-line distances between the data acquisition point and the 3 error compensation points with the smallest straight-line distances.

[0070] The setting of the threshold and weight can be based on the default settings of the present invention or can be set by the operator himself.

[0071] Embodiment 2

[0072] This embodiment provides an electronic device, including: a processor and a memory. Among them, the memory stores a computer program that can be called by the processor; the processor executes the above-mentioned method for error diagnosis and compensation of a multi-sensor fusion ultrasonic anemometer system by calling the computer program stored in the memory.

[0073] The electronic device may vary greatly due to different configurations or performances, and can include one or more processors (Central Processing Units, CPUs) and one or more memories. Among them, at least one computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement a multi-sensor fusion ultrasonic anemometer system error diagnosis and compensation method provided by the above method embodiment. The electronic device can also include other components for realizing the functions of the device. For example, the electronic device can also have components such as wired or wireless network interfaces and input / output interfaces for inputting and outputting data. This embodiment will not be elaborated here.

[0074] Those skilled in the art of the present technology know that the present invention can be implemented as a system, a method, or a computer program product. Therefore, the present disclosure can be specifically implemented in the following forms: it can be completely hardware, can also be completely software (including firmware, resident software, microcode, etc.), and can also be in the form of a combination of hardware and software, which is generally referred to as "circuit", "module", or "system" in this article. 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 media contains computer-readable program code.

[0075] Any combination of one or more computer-readable media can be adopted. The computer-readable media can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium 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 of the above. In this document, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, device, or component.

[0076] The present invention will be described with reference to the flowcharts and block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow or block in the flowcharts and block diagrams, as well as the combination of flows and blocks in the flowcharts or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and blocks Figure 1 or one or more of the blocks.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more of the flows Figure 1 one or more of the flows and blocks Figure 1 or one or more of the blocks.

[0078] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the claims of the present invention. All of these are within the protection scope of the present invention.

Claims

1. An error diagnosis and compensation method for an ultrasonic wind measurement system with multi-sensor fusion, characterized in that: It includes the following specific steps: S1. Monitor the real-time wind measurement data at the data collection point through an ultrasonic anemometer, and monitor the environmental parameters through an 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. Conduct an overall deviation assessment of the ultrasonic anemometer based on the environmental parameter deviation value and the equipment state deviation value, and compare the overall deviation assessment result with a preset deviation threshold to determine whether to trigger a compensation strategy; S5. When the overall deviation is greater than the preset deviation threshold, start different compensation strategies; The specific content of S1 is as follows: monitor the real-time wind measurement data at the data acquisition point through an ultrasonic anemometer, and the real-time wind measurement data includes real-time wind speed and real-time wind direction ; at the same time, use a temperature sensor to monitor the ambient temperature , a humidity sensor to monitor the relative humidity , a salt fog concentration sensor to monitor the salt fog particle density , a wave height sensor to monitor the wave height ; The calculation formula for the environmental parameter deviation value in S2 is: ； Among them, is the environmental parameter deviation value, is the value closest to in the temperature threshold range, is the relative humidity threshold, is the salt mist particle density threshold, is the wave height threshold, is the temperature deviation weight factor, is the humidity deviation weight factor, is the salt mist deviation weight factor, is the wave height deviation weight factor, , and .

2. A method for error diagnosis and compensation of an ultrasonic wind measurement system with multi-sensor fusion according to claim 1, characterized in that: The specific steps for calculating the pollution index of the ultrasonic anemometer at the data collection point in S2 include: S21. Record the reflectivity of the surface of the ultrasonic anemometer probe under the condition that the surface of the probe is clean. , and the reflectivity is the reference reflectivity value. S22. Record the minimum reflectivity of the surface of the ultrasonic anemometer probe under the condition of complete contamination of the probe surface ; S23. The calculation formula for the pollution index is as follows: , where R is the reflectivity of the surface of the ultrasonic anemometer probe in the current state.

3. A method for error diagnosis and compensation of an ultrasonic anemometer system with multi-sensor fusion according to claim 2, characterized in that: The method for calculating the vibration amplitude of the ultrasonic anemometer at the data acquisition point in S2 is as follows: use a three-axis accelerometer to measure the acceleration values of the ultrasonic anemometer at the acquisition point in three orthogonal directions , , , and use the peak value method to determine the vibration amplitude of the ultrasonic anemometer , and the calculation formula is expressed as .

4. A method for error diagnosis and compensation of an ultrasonic wind measurement system with multi-sensor fusion according to claim 3, characterized in that: The calculation formula for the equipment state deviation value in S3 is: ； wherein, is the wind speed fluctuation deviation of the data acquisition point within the preset acquisition duration, is the standard deviation of the wind speed of the data acquisition point within the preset acquisition duration, is the average wind speed of the data acquisition point within the preset acquisition duration, 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, .

5. A method for error diagnosis and compensation of an ultrasonic wind measurement system with multi-sensor fusion according to claim 4, characterized in that: S4 includes the following specific steps: S41. Based on the environmental parameter deviation value and the device status deviation value , calculate the overall deviation value of the ultrasonic anemometer , and the calculation formula is: ; is the weight factor of the environmental parameter deviation value; S42, preset deviation threshold , compare with the deviation threshold to determine their magnitude relationship. When is greater than or equal to the deviation threshold , trigger the compensation strategy.

6. A method for error diagnosis and compensation of an ultrasonic wind measurement system with multi-sensor fusion according to claim 5, characterized in that: S5 includes the following specific content: S51. Compare with to determine the size relationship. If is greater than , trigger the cleaning compensation and start the high-pressure gas pulse cleaning. If the pollution index does not decrease by 50% after cleaning, switch to the spare probe; S52. Comparison With Compare their magnitude relationship. If is greater than , trigger pose compensation and use hydraulic drive to adjust the height of the ultrasonic anemometer; S53. If the wind speed fluctuation deviation , trigger wind speed fluctuation compensation; S54. Compare the vibration amplitudes with to determine their magnitude relationship. If is greater than , trigger vibration compensation and activate the shock-absorbing bracket.

7. A method for error diagnosis and compensation of an ultrasonic wind measurement system with multi-sensor fusion according to claim 6, characterized in that: The specific method for wind speed fluctuation compensation in S53 is as follows: Deploy a number of error compensation points around the data acquisition point, and deploy ultrasonic anemometers respectively to record the real-time wind measurement data of different error compensation points, obtain the straight-line distances between different error compensation points and the data acquisition point, and extract the real-time wind speeds recorded by the ultrasonic anemometers at the 3 error compensation points with the smallest straight-line distances , where the value of i is 1-3, and the wind speed at the data acquisition point is corrected. The formula is: ； Among them, respectively represent the straight-line distances between the three error compensation points with the smallest straight-line distances from the data acquisition points.

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