Weighing sensor test compensation method based on fuzzy recognition

Abstract

The invention discloses a weighing sensor test compensation method based on fuzzy recognition, and relates to the technical field of sensor test compensation, and the method comprises the following compensation steps: inputting an original reading of a weighing sensor into a calculation module, and outputting a final compensated reading by the calculation module. According to the invention, the influence of various environmental factors such as ground flatness, power supply stability, temperature, humidity, air pressure, altitude and the like on reading is comprehensively considered, preliminary compensation and comprehensive compensation based on position and time are realized, and the adaptability and measurement precision of the weighing sensor under different environmental conditions are remarkably improved; a vibration correction coefficient is introduced to effectively compensate the influence of vibration on reading, the direct influence of vibration strength is considered, the compensation strength is dynamically adjusted through a modulation factor, the compensation effect is more accurate and effective, automatic adjustment and optimization of compensation parameters can be achieved, and the method is suitable for large-scale popularization and application. Therefore, the weighing sensor can automatically adapt to a complex and changeable measurement environment.

Description

Technical Field

[0001] The invention relates to the technical field of sensor test compensation, and in particular to a weighing sensor test compensation method based on fuzzy recognition. Background Art

[0002] A weighing sensor is a commonly used sensing device. In essence, it is a device that converts mass signals into measurable electrical signal outputs. In modern industry and logistics, weighing sensors are key equipment for measuring the weight of goods. Their accuracy and stability are directly related to production efficiency and product quality. However, due to the instability of the working environment, when the weighing sensor is operating, the measurement accuracy may be reduced due to various factors. In order to avoid large deviations in the measurement data, it is necessary to compensate for the deviation of the sensor data of the weighing sensor according to the actual situation.

[0003] However, the environmental adaptability of the existing traditional weighing sensors may be poor. Under complex and changeable environmental conditions, such as when the parameters such as temperature, humidity, and air pressure fluctuate greatly, the measurement accuracy and stability of the weighing sensors may drop significantly, making it difficult to meet the needs of high-precision weighing. The existing test compensation methods may only compensate for a single or a few environmental factors, and fail to fully consider the combined impact of multiple environmental factors, resulting in limited compensation effects. In addition, external vibration is one of the common interference factors in the weighing sensing process. Traditional methods may ignore or simply deal with the impact of vibration on readings, which may result in large measurement errors in a vibrating environment. Existing compensation methods may mostly rely on manual adjustment of parameters, lacking an automated and intelligent real-time compensation mechanism, making it difficult to meet the requirements of modern industry for efficient and accurate measurement. Summary of the invention

[0004] The purpose of the present invention is to provide a weighing sensor test compensation method based on fuzzy recognition, which solves the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a weighing sensor test compensation method based on fuzzy recognition, comprising the following compensation method:

[0006] Step I: collect the original data of the weighing sensor and the surrounding and environmental data based on the data acquisition module, and output the original reading of the weighing sensor, the ground flatness index, the power supply stability index, the ambient temperature value and the ambient humidity value;

[0007] Step II, input the original reading of the weighing sensor, the ground flatness index, the power stability index, the ambient temperature value and the ambient humidity value into the data processing module, the data processing module integrates the time and position information accordingly, and outputs the original reading of the weighing sensor at the time t position (x, y), the ground flatness index at the time t position (x, y), the power stability index at the time t position (x, y), the temperature value at the time t position (x, y) and the humidity value at the time t position (x, y);

[0008] Step III, inputting the original reading of the weighing sensor at the time t position (x, y), the ground flatness index at the time t position (x, y), the power supply stability index at the time t position (x, y), the temperature value at the time t position (x, y) and the humidity value at the time t position (x, y) into the calculation module, and the calculation module outputs the reading after preliminary compensation at the time t position (x, y), the reading after comprehensive compensation at the time t position (x, y) and the reading after final compensation at the time t position (x, y);

[0009] Step IV: Apply the final compensated reading at the time position (x, y) as the actual measurement result, record the original data and compensated data of each measurement, summarize the data based on the display module and display it on the display terminal, and then adjust the calculation module according to the actual application effect and data feedback, and regularly check the operating status of the data acquisition module.

[0010] Optionally, the calculation module includes: a preliminary compensation submodule, an environmental compensation submodule, a comprehensive compensation output submodule and a loop iteration submodule.

[0011] Optionally, the calculation formula of the preliminary compensation submodule is as follows:

[0012] FPX t，x，y =AZX t，x，y ×[1+a1×|AZQ t，x，y -AZQ n |+a2×|ASX t，x，y -ASX n |];

[0013] in:

[0014] FPX t，x，y Refers to the reading after preliminary compensation at time t position (x, y);

[0015] AZX t，x，y Refers to the raw reading of the weighing sensor at the time t position (x, y), AZQ t，x，y Refers to the ground flatness index at the time t position (x, y), ASXt，x，y Refers to the power stability index, AZQ, at the time t position (x, y) n Refers to the benchmark value of ground flatness, ASX n Refers to the reference value of power supply stability, a1 refers to the compensation coefficient of ground flatness deviation, a2 refers to the compensation coefficient of power supply stability deviation, |AZQ t，x，y -AZQ n | Refers to the absolute value of the ground flatness deviation, |ASX t，x，y -ASX n | refers to the absolute value of the power supply stability deviation;

[0016] The processing process of the preliminary compensation submodule is as follows: the original reading AZX of the weighing sensor at the time t position (x, y) t，x，y , the ground roughness index AZQ at the time t position (x, y) t，x，y and the power stability index ASX at time t position (x,y) t，x，y Substitute it into the preliminary compensation submodule and calculate the ground flatness based on the reference value AZQ n and power stability benchmark ASX n The initial compensation submodule outputs the initial compensation reading FPX at the time position (x, y) t，x，y .

[0017] Optionally, the calculation formula of the environmental compensation submodule is as follows:

[0018] FNC t，x，y =FPX t，x，y ×{1+b1×(TT t，x，y -TT n ) 3 +b2×(HU t，x，y -HU n ) 2 +

[0019] b3×[(AUG t，x，y -AUG n ) / AUG n ]+b4×log[1+(EUY t，x，y -EUY n )] / EUY n};

[0020] in:

[0021] FNC t，x，y Refers to the reading after comprehensive compensation at time t position (x, y);

[0022] TT t，x，yRefers to the temperature value at the position (x, y) at time t, TT n Refers to the adjustable temperature reference value, HU t，x，y Refers to the humidity value at the time t position (x, y), HU n Refers to the corresponding humidity reference value, AUG t，x，y Refers to the air pressure value at the position (x, y) at time t, AUG n Refers to the corresponding air pressure reference value, EUY t，x，y Refers to the altitude at the position (x, y) at time t, EUY n Refers to the corresponding altitude reference value, b1 refers to the compensation coefficient of temperature deviation, b2 refers to the compensation coefficient of humidity deviation, b3 refers to the compensation coefficient of air pressure deviation, and b4 refers to the compensation coefficient of altitude deviation;

[0023] The processing process of the environmental compensation submodule is as follows: the reading FPX after preliminary compensation at the time position (x, y) is t，x，y , the temperature value TT at the position (x,y) at time t t，x，y , Humidity value HU at position (x,y) at time t t，x，y Input to the environmental compensation submodule and based on the air pressure value AUG at the position (x, y) at time t t，x，y and EUY t，x，y The altitude at the time t position (x, y), the environmental compensation submodule outputs the reading FNC after comprehensive compensation at the time t position (x, y) t，x，y .

[0024] Optionally, the calculation formula of the comprehensive compensation output submodule is as follows:

[0025] LNC t，x，y =FNC t，x，y ×[1+d1×max(0,VAV t，x，y -VAV n )×MDDFC t，x，y ]×

[0026] FPX t，x，y ;

[0027] in:

[0028] LNC t，x，y Refers to the final compensated reading at time t position (x, y);

[0029] VAV t，x，y Refers to the vibration intensity at the position (x, y) at time t, VAV n Refers to the baseline threshold of vibration intensity, MDDFC t，x，yrefers to the vibration modulation factor at the time position (x, y), d1 refers to the coefficient of vibration correction, [1+d1×max(0, VAV t，x，y -VAV n ) refers to the degree of adjustment of the reading caused by vibration;

[0030] The processing process of the comprehensive compensation output submodule is as follows: Based on the reading FNC after comprehensive compensation at the time t position (x, y) t，x，y and the initial compensation reading FPX at time t position (x,y) t，x，y , and the vibration intensity VAV at the position (x, y) at time t t，x，y and the reference threshold value VAV of vibration intensity n Input to the comprehensive compensation output submodule, the comprehensive compensation output submodule outputs the final compensated reading LNC at time t position (x, y) t，x，y .

[0031] Optionally, the processing process of the loop iteration submodule is as follows:

[0032] Step I: TT n，new =TT n，old +s1×(MBZZ-LNC t，x，y );

[0033] Step II: Establish convergence conditions;

[0034] Convergence condition 1: |TT n，new -TT n，old |<μ;

[0035] Convergence condition 2: The number of iterations is 357;

[0036] in:

[0037] TT n，new Refers to the adjustable temperature reference value after iteration;

[0038] MBZZ refers to the target value of expected convergence, s1 refers to the adjustment factor, μ refers to the comparison threshold, TT n，new -TT n，old Refers to the adjustable temperature reference value TT after iteration n The previous adjustable temperature reference value TT n The difference between

[0039] Based on the final compensated reading LNC at time t position (x, y) t，x，y The operation with the target value MBZZ that is expected to converge, and the adjustable temperature reference value TT is limited by the adjustment factor s1 n The loop iteration submodule outputs the adjustable temperature reference value TT after iteration.n，new , the iterative adjustable temperature reference value TT n，new Replace the adjustable temperature reference value TT in the environmental compensation submodule n , to continue to influence FNC t，x，y and LNC t，x，y , and the purpose of iterative termination convergence is achieved through convergence conditions one and two.

[0040] Optionally, the devices used by the data acquisition module include a ground flatness measuring instrument, a power monitoring device, a temperature sensor and a humidity sensor.

[0041] Optionally, the data processing module is used to clean and summarize the original readings of the weighing sensor, the ground flatness index, the power supply stability index, the ambient temperature value and the ambient humidity value, and to integrate the time information and the location information accordingly.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] 1. The present invention outputs the reading FPX after preliminary compensation at the time position (x, y) through the preliminary compensation submodule t，x，y By accurately compensating for the effects of ground flatness and power supply stability, FPX t，x，y It can significantly improve the measurement accuracy of the sensor in complex environments, and in applications that require high quality of basic readings, this method uses a special compensation algorithm to handle ground flatness and power supply stability issues, and FPX t，x，y The number of factors that need to be processed in the subsequent compensation steps is reduced, thereby reducing the complexity and computational cost of the entire system.

[0044] 2. The present invention outputs the reading FNC after comprehensive compensation at the time t position (x, y) through the environmental compensation submodule t，x，y ,This environmental compensation submodule comprehensively considers various environmental factors and performs real-time compensation,FNC t，x，y It can significantly improve the measurement accuracy of weighing sensors. In applications that are sensitive to environmental factors, FNC t，x，y The comprehensive compensation mechanism enables the sensor to maintain stable measurement performance under various complex and changing environmental conditions, thereby enhancing its environmental adaptability.

[0045] 3. The present invention outputs the final compensated reading LNC at the time t position (x, y) through the comprehensive compensation output submodule t，x，y The comprehensive compensation output submodule can effectively eliminate or reduce the interference and error caused by vibration on the sensor reading. By introducing fuzzy recognition technology and modulation factors, LNC t，x，yIt realizes intelligent compensation for sensor readings, comprehensively considers multiple factors and introduces vibration compensation and intelligent compensation mechanisms. t，x，y The measurement accuracy and stability of the weighing sensor are significantly improved, which is not only reflected in the accuracy of a single measuring point, but also in the stability and reliability of the entire measurement process. The method uses fuzzy recognition technology to process the uncertainty and ambiguity in sensor data and environmental data, and realizes automatic adjustment and optimization of compensation parameters. At the same time, through real-time perception and compensation of changes in environmental factors, the weighing sensor can automatically adapt to complex and changeable measurement environments, thereby improving the intelligence and automation level of the system.

[0046] 4. The present invention uses a loop iteration submodule to adjust the adjustable temperature reference value TT in the environmental compensation submodule. n Perform loop iteration, by iterating TT n Can directly adjust the output of the sensor to make it closer to the true value and iterate TT n Based on LNC t，x，y This feedback mechanism can ensure the effectiveness and accuracy of the iterative process. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of the steps of the weighing sensor test compensation method based on fuzzy recognition;

[0048] Figure 2 This is a schematic diagram of the overall structure of the weighing sensor test compensation method based on fuzzy recognition;

[0049] Figure 3 It is a structural diagram of the calculation module in the weighing sensor test compensation method based on fuzzy recognition. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] The present weighing sensor test and compensation method based on fuzzy recognition is different from the existing weighing sensor test and compensation method. When the weighing sensor is actually used under complex and changeable environmental conditions, such as when the temperature, humidity, air pressure and other parameters fluctuate greatly, its measurement accuracy and stability will be significantly reduced, and it is difficult to meet the needs of high-precision weighing. In addition, most of the existing compensation methods only compensate for a single or a few environmental factors, and fail to fully consider the comprehensive impact of multiple environmental factors, resulting in limited compensation effect.

[0052] The module of this weighing sensor test compensation system method based on fuzzy recognition comprehensively considers the impact of various environmental factors on the readings, such as ground flatness, power supply stability, temperature, humidity, air pressure and altitude, and realizes preliminary compensation and comprehensive compensation based on position and time, which significantly improves the adaptability and measurement accuracy of the weighing sensor under different environmental conditions, and can perceive and compensate for changes in environmental factors in real time, so that the weighing sensor can automatically adapt to complex and changeable measurement environments, thereby improving the intelligence and automation level of the system.

[0053] Example: See Figures 1 to 3 , this implementation provides a weighing sensor test compensation method based on fuzzy recognition, including the following compensation methods:

[0054] Step I: collect the original data of the weighing sensor and the surrounding and environmental data based on the data acquisition module, and output the original reading of the weighing sensor, the ground flatness index, the power supply stability index, the ambient temperature value and the ambient humidity value;

[0055] Step II, input the original reading of the weighing sensor, the ground flatness index, the power stability index, the ambient temperature value and the ambient humidity value into the data processing module, the data processing module integrates the time and position information accordingly, and outputs the original reading of the weighing sensor at the time t position (x, y), the ground flatness index at the time t position (x, y), the power stability index at the time t position (x, y), the temperature value at the time t position (x, y) and the humidity value at the time t position (x, y);

[0056] Step III, inputting the original reading of the weighing sensor at the time t position (x, y), the ground flatness index at the time t position (x, y), the power supply stability index at the time t position (x, y), the temperature value at the time t position (x, y) and the humidity value at the time t position (x, y) into the calculation module, and the calculation module outputs the reading after preliminary compensation at the time t position (x, y), the reading after comprehensive compensation at the time t position (x, y) and the reading after final compensation at the time t position (x, y);

[0057] Step IV: Apply the final compensated reading at the time t position (x, y) as the actual measurement result, record the original data and compensated data of each measurement, summarize the data based on the display module and display it on the display terminal, and then adjust the calculation module according to the actual application effect and data feedback, and regularly check the operation status of the data acquisition module;

[0058] The calculation module includes: a preliminary compensation submodule, an environmental compensation submodule, a comprehensive compensation output submodule and a loop iteration submodule.

[0059] In this embodiment: First, the weighing sensor test compensation method is a technology that uses fuzzy logic principles to improve the measurement accuracy of weighing sensors. This method is mainly used in occasions where weighing is performed in complex or changing environments. In these environments, weighing sensors may be affected by various interference factors, which may lead to reduced measurement accuracy. The core of fuzzy recognition theory is to deal with uncertainty in the real world. In the weighing sensor test process, various environmental factors, such as ground flatness, power supply stability, temperature, humidity, air pressure, altitude, and vibration, as well as the nonlinear characteristics of the sensor itself, will introduce varying degrees of uncertainty. These uncertainties are quantified into processable values, thereby achieving effective management and compensation of uncertainties. Through fuzzy reasoning, the system can more accurately judge the degree of influence of the current environment on the sensor readings, and make corresponding compensation decisions accordingly. The application of fuzzy recognition in weighing sensor test compensation is also reflected in the comprehensive compensation of multiple factors. The system can simultaneously consider the influence of multiple environmental factors and the characteristics of the sensor itself, and through the method of fuzzy comprehensive judgment, the weight distribution and comprehensive evaluation of each influencing factor are performed. This multi-factor comprehensive compensation mechanism can more comprehensively reflect the actual situation and improve the accuracy and effectiveness of compensation;

[0060] Secondly, for the subscripts t and coordinates (x, y) in the formula designed by this method, the emphasis on time t means that this method can track and compensate for the dynamic changes of sensor readings in real time. Since environmental factors such as temperature, humidity and sensor characteristics such as creep and zero drift may change over time, only real-time compensation can ensure the accuracy of the measurement results. By recording the compensation data at different times, a database of sensor performance changes over time can be established, which provides strong support for subsequent fault diagnosis, performance evaluation and predictive maintenance. In most weighing sensor application scenarios, such as industrial production lines, logistics warehousing, etc., the layout of sensors is usually two-dimensional, that is, plane layout. Therefore, the use of two-dimensional coordinates (x, y) can accurately describe the position of the sensor on the plane, which is convenient for data collection, processing and analysis. Compared with three-dimensional coordinates, two-dimensional coordinates are simpler and more efficient in data processing and calculation. In application scenarios where height or depth information does not need to be considered, the use of two-dimensional coordinates can reduce unnecessary calculations and complexity. The use of t and coordinates (x, y) makes the parameters have excellent accuracy;

[0061] By calculating FPX t，x，y 、FNC t，x，y and LNC t，x，y These three values, this method can significantly improve the test compensation effect of the weighing sensor. Through multi-level compensation, it can effectively eliminate or reduce the influence of various factors on the sensor readings, such as ground flatness, power supply stability, ambient temperature, humidity, air pressure, altitude and vibration, thereby improving the accuracy and reliability of the measurement. This method can automatically adapt to different working environments and conditions, and can achieve accurate measurement compensation without manual intervention, enhancing the environmental adaptability and stability of the sensor. The readings after comprehensive compensation are closer to the true value, reducing the interference of errors and noise, and improving the quality and credibility of the data. This method comprehensively considers the influence of multiple factors on the sensor readings, including ground flatness, power supply stability, ambient temperature, humidity, air pressure , altitude and vibration, etc., to achieve more comprehensive compensation. This method can monitor and compensate for the impact of changes in various factors on sensor readings in real time, and has high dynamic response capability and real-time performance. This method can automatically adapt to different working environments and conditions to achieve intelligent measurement compensation. This method establishes a multi-level compensation mechanism from preliminary compensation to comprehensive compensation to final compensation, gradually eliminating or reducing the impact of various factors on sensor readings, and can comprehensively consider the impact of multiple factors on sensor readings, and realize real-time dynamic compensation, which improves the comprehensiveness of measurement and dynamic response capability. Through the application of comprehensive compensation and intelligent algorithms, the measurement accuracy and stability of weighing sensors are significantly improved, providing more reliable and accurate measurement data for applications in related fields.

[0062] See also Figures 1 to 3 , the initial compensation submodule processing process is as follows:

[0063] FPX t，x，y =AZX t，x，y ×[1+a1×|AZQ t，x，y -AZQ n |+a2×|ASX t，x，y -ASX n |];

[0064] in:

[0065] FPX t，x，y Refers to the reading after preliminary compensation at time t position (x, y);

[0066] AZX t，x，y Refers to the raw reading of the weighing sensor at the time t position (x, y), AZQ t，x，y Refers to the ground flatness index at the time t position (x, y), ASX t，x，y Refers to the power stability index, AZQ, at the time t position (x, y) n Refers to the benchmark value of ground flatness, ASX n Refers to the reference value of power supply stability, a1 refers to the compensation coefficient of ground flatness deviation, a2 refers to the compensation coefficient of power supply stability deviation, |AZQ t，x，y -AZQ n | Refers to the absolute value of the ground flatness deviation, |ASX t，x，y -ASX n | refers to the absolute value of the power supply stability deviation;

[0067] The raw reading of the weighing sensor at the time t position (x, y) is AZX t，x，y , the ground roughness index AZQ at the time t position (x, y) t，x，y and the power stability index ASX at time t position (x,y) t，x，y Substitute it into the preliminary compensation submodule and calculate the ground flatness based on the reference value AZQ n and power stability benchmark ASX n The initial compensation submodule outputs the initial compensation reading FPX at the time position (x, y) t，x，y .

[0068] In this embodiment: FPX t，x，y It is the result of a preliminary correction of the raw readings, aiming to eliminate or reduce the effects of uneven ground and power supply fluctuations on sensor readings. t，x，y With AZQ n Deviation, FPX t，x，yIt can effectively eliminate or reduce the error in sensor readings caused by uneven ground, which is particularly important for weighing measurements on complex terrain or dynamically changing ground. t，x，y Power stability ASX is also considered t，x，y The influence of ground flatness and power supply stability is corrected, which ensures that the sensor can provide relatively stable readings under different power supply conditions. By considering the two key factors of ground flatness and power supply stability, FPX t，x，y It provides a more accurate and reliable preliminary reading basis for the subsequent compensation step, thus helping to further improve the overall measurement accuracy. t，x，y Specially designed to compensate for ground flatness and power supply stability, which are aspects that many existing technologies ignore, FPX uses precise compensation algorithms to t，x，y It can effectively reduce the reading errors caused by uneven ground and power supply fluctuations, and the formula calculation process can be carried out in real time to ensure timely adjustment during the measurement process to reflect the current ground and power supply conditions. t，x，y As the preliminary compensation result, it is used as the basis for the subsequent comprehensive compensation FNC t，x，y and final compensation LNC t，x，y Provides a solid foundation. It ensures that the readings have been basically corrected before more complex compensations are made, and FPX t，x，y The calculation is relatively independent and can be used as a compensation solution in scenarios with specific requirements for ground flatness and power supply stability. In general, by accurately compensating for the impact of ground flatness and power supply stability, FPX t，x，y Significantly improves the measurement accuracy of the sensor in complex environments, especially in applications that require high quality of basic readings. Through a dedicated compensation algorithm to handle ground flatness and power supply stability issues, FPX t，x，y The number of factors that need to be processed in the subsequent compensation steps is reduced, thereby reducing the complexity and computational cost of the entire system.

[0069] See also Figures 1 to 3 , the processing process of the environmental compensation submodule is as follows:

[0070] FNC t，x，y =FPX t，x，y ×{1+b1×(TT t，x，y -TT n ) 3 +b2×(HU t，x，y -HU n ) 2 +

[0071] b3×[(AUG t，x，y -AUG n ) / AUGn ]+b4×log[1+(EUY t，x，y -EUY n )] / EUY n};

[0072] in:

[0073] FNC t，x，y Refers to the reading after comprehensive compensation at time t position (x, y);

[0074] TT t，x，y Refers to the temperature value at the position (x, y) at time t, TT n Refers to the adjustable temperature reference value, HU t，x，y Refers to the humidity value at the time t position (x, y), HU n Refers to the corresponding humidity reference value, AUG t，x，y Refers to the air pressure value at the position (x, y) at time t, AUG n Refers to the corresponding air pressure reference value, EUY t，x，y Refers to the altitude at the position (x, y) at time t, EUY n Refers to the corresponding altitude reference value, b1 refers to the compensation coefficient of temperature deviation, b2 refers to the compensation coefficient of humidity deviation, b3 refers to the compensation coefficient of air pressure deviation, and b4 refers to the compensation coefficient of altitude deviation;

[0075] The initial compensated reading FPX at time t position (x, y) t，x，y , the temperature value TT at the position (x,y) at time t t，x，y , Humidity value HU at position (x,y) at time t t，x，y Input to the environmental compensation submodule and based on the air pressure value AUG at the position (x, y) at time t t，x，y and EUY t，x，y The altitude at the time t position (x, y), the environmental compensation submodule outputs the reading FNC after comprehensive compensation at the time t position (x, y) t，x，y .

[0076] In this embodiment: FNC t，x，y The value is in FPX t，x，y Based on this, environmental factors such as temperature, humidity, air pressure and altitude deviation are further considered. t，x，y It is a more comprehensive correction of the reading after the initial compensation, aiming to eliminate or reduce the impact of environmental changes on the sensor reading, so as to obtain a reading closer to the true value. t，x，yTaking into account the impact of multiple environmental factors such as temperature, humidity, air pressure and altitude on sensor readings, this comprehensive environmental factor compensation significantly improves the accuracy and reliability of measurement results. Since it can sense and compensate for changes in environmental factors in real time, FNC t，x，y The sensor can maintain stable measurement performance under various complex and changing environmental conditions, thereby enhancing its environmental adaptability. Through comprehensive compensation, FNC t，x，y It reduces the reading fluctuations and errors caused by environmental factors, improves the quality and credibility of data, and provides a more solid foundation for subsequent data processing and analysis. t，x，y It can monitor and compensate the impact of environmental factors on sensor readings in real time, and has high dynamic response capability, which makes FNC t，x，y FNC can still maintain stable measurement performance in application scenarios with large environmental changes. t，x，y As a comprehensive compensation result, it combines the compensation effects of various environmental factors to provide a more accurate and reliable basis for the final measurement readings. t，x，y The comprehensive consideration of multiple environmental factors has reflected the preliminary intelligent compensation idea. In general, by comprehensively considering multiple environmental factors and performing real-time compensation, FNC t，x，y The FNC significantly improves the measurement accuracy of load cells, especially in applications that are sensitive to environmental factors. t，x，y The comprehensive compensation mechanism enables the sensor to maintain stable measurement performance under various complex and changing environmental conditions, thereby enhancing its environmental adaptability.

[0077] See also Figures 1 to 3 , the processing process of the comprehensive compensation output submodule is as follows:

[0078] LNC t，x，y =FNC t，x，y ×[1+d1×max(0,VAV t，x，y -VAV n )×MDDFC t，x，y ]×

[0079] FPX t，x，y ;

[0080] in:

[0081] LNC t，x，y Refers to the final compensated reading at time t position (x, y);

[0082] VAV t，x，y Refers to the vibration intensity at the position (x, y) at time t, VAV n Refers to the baseline threshold of vibration intensity, MDDFC t，x，yrefers to the vibration modulation factor at the time position (x, y), d1 refers to the coefficient of vibration correction, [1+d1×max(0, VAV t，x，y -VAV n ) refers to the degree of adjustment of the reading caused by vibration;

[0083] Based on the integrated compensated reading FNC at time t position (x, y) t，x，y and the initial compensation reading FPX at time t position (x,y) t，x，y , and the vibration intensity VAV at the position (x, y) at time t t，x，y and the reference threshold value VAV of vibration intensity n Input to the comprehensive compensation output submodule, the comprehensive compensation output submodule outputs the final compensated reading LNC at time t position (x, y) t，x，y .

[0084] In this embodiment: the final compensated reading LNC at time t position (x, y) t，x，y It's FNC t，x，y The final calibration is to eliminate or reduce the impact of vibration on the sensor readings, thereby obtaining the most accurate and stable readings, and the vibration intensity VAV at the time t position (x, y) t，x，y The reference threshold VAV of the vibration intensity n Comparison of the vibration modulation factor MDDFC at the time t position (x, y) t，x，y Application of LNC t，x，y It can effectively eliminate or reduce the interference and error caused by vibration on the sensor reading, which is of great significance for accurate weighing measurement in a vibrating environment. Vibration is one of the important factors affecting the stability of weighing sensor readings. By introducing a vibration compensation mechanism, LNC t，x，y Significantly improves the stability of the measurement results, allowing the sensor to maintain high-precision measurement performance under vibration conditions. t，x，y The calculation process of LNC integrates intelligent algorithms such as fuzzy recognition technology and modulation factor to realize intelligent compensation of sensor readings. This intelligent compensation not only improves the accuracy and efficiency of compensation, but also enhances the adaptive ability and flexibility of the system. t，x，y In FNC t，x，y On the basis of the above, the influence of vibration on sensor readings is further considered, and a vibration compensation mechanism is introduced, which is a function that many existing technologies do not have, especially when making accurate measurements in a vibrating environment. By introducing fuzzy recognition technology and modulation factors, LNC t，x，yThe intelligent compensation of sensor readings is realized. This intelligent compensation not only improves the accuracy and efficiency of compensation, but also enhances the adaptive ability and flexibility of the system. t，x，y As the final compensation result, all the previous compensation effects are integrated, and vibration compensation and intelligent compensation mechanisms are introduced to ensure the accuracy and stability of the measurement readings. t，x，y The intelligent compensation mechanism enables the sensor to automatically adapt to various complex and changing environmental conditions and perform real-time and accurate compensation, thus realizing comprehensive intelligent measurement. By comprehensively considering multiple factors and introducing vibration compensation and intelligent compensation mechanisms, LNC t，x，y The measurement accuracy and stability of the weighing sensor have been significantly improved. This improvement is not only reflected in the accuracy of a single measurement point, but also in the stability and reliability of the entire measurement process.

[0085] See also Figures 1 to 3 , the loop iteration submodule processing process is as follows:

[0086] Step I: TT n，new =TT n，old +s1×(MBZZ-LNC t，x，y );

[0087] Step II: Establish convergence conditions;

[0088] Convergence condition 1: |TT n，new -TT n，old |<μ;

[0089] Convergence condition 2: The number of iterations is 357;

[0090] in:

[0091] TT n，new Refers to the adjustable temperature reference value after iteration;

[0092] MBZZ refers to the target value of expected convergence, s1 refers to the adjustment factor, μ refers to the comparison threshold, TT n，new -TT n，old Refers to the adjustable temperature reference value TT after iteration n The previous adjustable temperature reference value TT n The difference between

[0093] Based on the final compensated reading LNC at time t position (x, y) t，x，y The operation with the target value MBZZ that is expected to converge, and the adjustable temperature reference value TT is limited by the adjustment factor s1 n The loop iteration submodule outputs the adjustable temperature reference value TT after iteration. n，new , the iterative adjustable temperature reference value TTn，new Replace the adjustable temperature reference value TT in the environmental compensation submodule n , to continue to influence FNC t，x，y and LNC t，x，y , and the purpose of iterative termination convergence is achieved through convergence conditions one and two.

[0094] In this embodiment: by iteratively adjusting the temperature reference value TT n , making it closer to the temperature conditions in the actual working environment, thereby improving the measurement accuracy of the weighing sensor, and based on LNC t，x，y The real-time feedback can reflect the working status and environmental changes of the sensor in real time. Through iterative optimization, the system can automatically adjust parameters to adapt to different working environments and conditions, reduce measurement errors caused by environmental changes, and thus enhance the stability and reliability of the entire system. The iterative algorithm usually has an excellent convergence speed and can find the optimal TT in a short time. n The method combines fuzzy recognition technology and iterative optimization algorithm to process the uncertainty and ambiguity in the sensor output data, and continuously adjusts TT through iterative optimization algorithm. n This combination enables the method to handle complex environments and has the characteristics of efficient optimization. Different from the traditional static compensation method, this method uses real-time iteration TT n This dynamic compensation can track the impact of environmental changes on sensor performance in real time, and adjust and optimize it in real time, thereby improving the accuracy and reliability of measurement results. t，x，y It is the comprehensive output result of the weighing sensor under specific conditions. It directly reflects the working state of the sensor and the influence of environmental changes on the measurement results. n As an adjustable temperature reference value, it is closely related to the output result of the sensor. n The output of the sensor can be directly adjusted to make it closer to the true value, iterating TT n Based on LNC t，x，y This feedback mechanism can ensure the effectiveness and accuracy of the iterative process.

[0095] In the specific implementation process, the various sub-modules in this method are used to form a xx system, and the original reading AZX of the weighing sensor at the time t position (x, y) is obtained. t，x，y , the ground roughness index AZQ at the time t position (x, y) t，x，y and the power stability index ASX at time t position (x,y)t，x，y Substitute it into the preliminary compensation submodule and output the reading FPX after preliminary compensation at time t position (x, y) t，x，y By accurately compensating for the effects of ground flatness and power supply stability, FPX t，x，y Significantly improves the measurement accuracy of the sensor in complex environments, especially in applications that require high quality of basic readings. Through a dedicated compensation algorithm to handle ground flatness and power supply stability issues, FPX t，x，y The number of factors that need to be processed in the subsequent compensation steps is reduced, thereby reducing the complexity and computational cost of the entire system.

[0096] By taking the initial compensated reading FPX at time t position (x, y) t，x，y , the temperature value TT at the position (x,y) at time t t，x，y , Humidity value HU at position (x,y) at time t t，x，y Input to the environmental compensation submodule, output the reading FNC after comprehensive compensation at time t position (x, y) t，x，y By comprehensively considering various environmental factors and performing real-time compensation, FNC t，x，y The FNC significantly improves the measurement accuracy of load cells, especially in applications that are sensitive to environmental factors. t，x，y The comprehensive compensation mechanism enables the sensor to maintain stable measurement performance under various complex and changing environmental conditions, thereby enhancing its environmental adaptability.

[0097] By integrating the compensated reading FNC at time t position (x, y) t，x，y and the initial compensation reading FPX at time t position (x,y) t，x，y Input to the comprehensive compensation output submodule, and output the final compensated reading LNC at time t position (x, y) t，x，y , can effectively eliminate or reduce the interference and error caused by vibration on sensor readings. By introducing fuzzy recognition technology and modulation factors, LNC t，x，y It realizes intelligent compensation for sensor readings, comprehensively considers multiple factors and introduces vibration compensation and intelligent compensation mechanisms. t，x，y The measurement accuracy and stability of the weighing sensor have been significantly improved. This improvement is not only reflected in the accuracy of a single measuring point, but also in the stability and reliability of the entire measurement process.

[0098] By taking the final compensated reading LNC at time t position (x, y) t，x，y Input to the loop iteration submodule, the adjustable temperature reference value TT n Perform loop iteration, LNC t，x，yIt directly reflects the working state of the sensor and the impact of environmental changes on the measurement results, while TT n As an adjustable temperature reference value, it is closely related to the output result of the sensor. n The output of the sensor can be directly adjusted to make it closer to the true value, iterating TT n Based on LNC t，x，y This feedback mechanism can ensure the effectiveness and accuracy of the iterative process.

[0099] This allows the overall multiple sub-modules to cooperate with each other in calculations, and can also perform overall cycles and iterations, so that the overall system has the effect of automatic optimization and updating, and thus better adaptability.

[0100] Example: See Figure 1 , Figure 2 and Figure 3 The devices used in the data acquisition module include a ground flatness measuring instrument, a power monitoring device, a temperature sensor and a humidity sensor. The data processing module is used to clean and summarize the original reading of the weighing sensor, the ground flatness index, the power stability index, the ambient temperature value and the ambient humidity value, and to integrate the time information and the location information accordingly.

[0101] In this embodiment: a barometer, an altitude meter and a vibration sensor are also used in the data acquisition module to monitor the air pressure value, altitude data and vibration intensity of the weighing sensor itself and the surrounding area in real time, so that the corresponding data can be collected to input these data into the preliminary compensation submodule, environmental compensation submodule and comprehensive compensation output submodule of the calculation module. Therefore, in the weighing sensor test process, various environmental factors, namely ground flatness, power supply stability, temperature, humidity, air pressure, altitude and vibration, etc., as well as the nonlinear characteristics of the sensor itself, will introduce different degrees of uncertainty. These uncertainties are quantified into processable values ​​through fuzzy recognition, thereby achieving effective management and compensation of uncertainties.

[0102] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A weighing sensor test compensation method based on fuzzy recognition, characterized in that: The following compensation methods are included: Step I: collect the original data of the weighing sensor and the surrounding and environmental data based on the data acquisition module, and output the original reading of the weighing sensor, the ground flatness index, the power supply stability index, the ambient temperature value and the ambient humidity value; Step II, input the original reading of the weighing sensor, the ground flatness index, the power stability index, the ambient temperature value and the ambient humidity value into the data processing module, the data processing module integrates the time and position information accordingly, and outputs the original reading of the weighing sensor at the time t position (x, y), the ground flatness index at the time t position (x, y), the power stability index at the time t position (x, y), the temperature value at the time t position (x, y) and the humidity value at the time t position (x, y); Step III, inputting the original reading of the weighing sensor at the time t position (x, y), the ground flatness index at the time t position (x, y), the power supply stability index at the time t position (x, y), the temperature value at the time t position (x, y) and the humidity value at the time t position (x, y) into the calculation module, and the calculation module outputs the reading after preliminary compensation at the time t position (x, y), the reading after comprehensive compensation at the time t position (x, y) and the reading after final compensation at the time t position (x, y); Step IV: Apply the final compensated reading at the time position (x, y) as the actual measurement result, record the original data and compensated data of each measurement, summarize the data based on the display module and display it on the display terminal, and then adjust the calculation module according to the actual application effect and data feedback, and regularly check the operating status of the data acquisition module.

2. The weighing sensor test compensation method based on fuzzy recognition according to claim 1 is characterized in that: The calculation module includes a preliminary compensation submodule, an environmental compensation submodule, a comprehensive compensation output submodule and a loop iteration submodule.

3. The weighing sensor test compensation method based on fuzzy recognition according to claim 2 is characterized in that: The calculation formula of the preliminary compensation submodule is as follows: FPX t，x，y =AZX t，x，y ×[1+a1×|AZQ t，x，y -AZQ n |+a2×|ASX t，x，y -ASX n |]: in: FPX t，x，y Refers to the reading after preliminary compensation at time t position (x, y); AZX t，x，y Refers to the raw reading of the weighing sensor at the time t position (x, y), AZQ t，x，y Refers to the ground flatness index at the time t position (x, y), ASX t，x，y Refers to the power stability index, AZQ, at the time t position (x, y) n Refers to the benchmark value of ground flatness, ASX n Refers to the reference value of power supply stability, a1 refers to the compensation coefficient of ground flatness deviation, a2 refers to the compensation coefficient of power supply stability deviation, |AZQ t，x，y -AZQ n | Refers to the absolute value of the ground flatness deviation, |ASX t，x，y -ASX n | refers to the absolute value of the power supply stability deviation; The processing process of the preliminary compensation submodule is as follows: the original reading AZX of the weighing sensor at the time t position (x, y) t，x，y , the ground roughness index AZQ at the time t position (x, y) t，x，y and the power stability index ASX at time t position (x,y) t，x，y Substitute it into the preliminary compensation submodule and calculate the ground flatness based on the reference value AZQ n and power stability benchmark ASX n The initial compensation submodule outputs the initial compensation reading FPX at the time position (x, y) t，x，y .

4. The weighing sensor test compensation method based on fuzzy recognition according to claim 3 is characterized in that: The calculation formula of the environmental compensation submodule is as follows: FNC t，x，y =FPX t，x，y ×{1+b1×(TT t，x，y -TT n ) 3 +b2×(HU t，x，y -hu n ) 2 + b3×[(AUG t，x，y -August n ) / AUG n ]+b4×log[1+(EUY t，x，y -EUY n )] / EUY n }; in: FNC t，x，y Refers to the reading after comprehensive compensation at time t position (x, y); TT t，x，y Refers to the temperature value at the position (x, y) at time t, TT n Refers to the adjustable temperature reference value, HU t，x，y Refers to the humidity value at the time t position (x, y), HU n Refers to the corresponding humidity reference value, AUG t，x，y Refers to the air pressure value at the time t position (x, y), AUG n Refers to the corresponding air pressure reference value, EUY t，x，y Refers to the altitude at the position (x, y) at time t, EUY n Refers to the corresponding altitude reference value, b1 refers to the compensation coefficient of temperature deviation, b2 refers to the compensation coefficient of humidity deviation, b3 refers to the compensation coefficient of air pressure deviation, and b4 refers to the compensation coefficient of altitude deviation; The processing process of the environmental compensation submodule is as follows: the reading FPX after preliminary compensation at the time position (x, y) is t，x，y , the temperature value TT at the position (x,y) at time t t，x，y , Humidity value HU at position (x,y) at time t t，x，y Input to the environmental compensation submodule and based on the air pressure value AUG at the position (x, y) at time t t，x，y and EUY t，x，y The altitude at the time t position (x, y), the environmental compensation submodule outputs the reading FNC after comprehensive compensation at the time t position (x, y) t，x，y .

5. The weighing sensor test compensation method based on fuzzy recognition according to claim 4 is characterized in that: The calculation formula of the comprehensive compensation output submodule is as follows: LNC t，x，y =FNC t，x，y ×[1+d1×max(0,VAV t，x，y -VAV n )×MDDFC t，x，y ]× FPX t，x，y ; in: LNC t，x，y Refers to the final compensated reading at time t position (x, y); VAV t，x，y Refers to the vibration intensity at the time t position (x, y), VAV n Refers to the baseline threshold of vibration intensity, MDDFC t，x，y refers to the vibration modulation factor at the time position (x, y), d1 refers to the coefficient of vibration correction, [1+d1×max(0, VAV t，x，y -VAV n ) refers to the degree of adjustment of the reading caused by vibration; The processing process of the comprehensive compensation output submodule is as follows: Based on the reading FNC after comprehensive compensation at the time t position (x, y) t，x，y and the initial compensation reading FPX at time t position (x,y) t，x，y , and the vibration intensity VAV at the position (x, y) at time t t，x，y and the reference threshold value VAV of vibration intensity n Input to the comprehensive compensation output submodule, the comprehensive compensation output submodule outputs the final compensated reading LNC at time t position (x, y) t，x，y .

6. The weighing sensor test compensation method based on fuzzy recognition according to claim 5 is characterized in that: The processing process of the loop iterator module is as follows: Step I: TT n，new =TT n，old +s1×(MBZZ-LNC t，x，y ); Step II: Establish convergence conditions; Convergence condition 1: |TT n，new -TT n，old |<μ; Convergence condition 2: The number of iterations is 357; in: TT n，new Refers to the adjustable temperature reference value after iteration; MBZZ refers to the target value of expected convergence, s1 refers to the adjustment factor, μ refers to the comparison threshold, TT n，new -TT n，old Refers to the adjustable temperature reference value TT after iteration n The previous adjustable temperature reference value TT n The difference between Based on the final compensated reading LNC at time t position (x, y) t，x，y The operation with the target value MBZZ that is expected to converge, and the adjustable temperature reference value TT is limited by the adjustment factor s1 n The loop iteration submodule outputs the adjustable temperature reference value TT after iteration. n，new , the iterative adjustable temperature reference value TT n，new Replace the adjustable temperature reference value TT in the environmental compensation submodule n , to continue to influence FNC t，x，y and LNC t，x，y , and the purpose of iterative termination convergence is achieved through convergence conditions one and two.

7. The weighing sensor test compensation method based on fuzzy recognition according to claim 1 is characterized in that: The devices used in the data acquisition module include a ground flatness measuring instrument, a power supply monitoring device, a temperature sensor and a humidity sensor.

8. The weighing sensor test compensation method based on fuzzy recognition according to claim 1 is characterized in that: The data processing module is used to clean and summarize the original readings of the weighing sensor, the ground flatness index, the power supply stability index, the ambient temperature value and the ambient humidity value, and to integrate the time information and the location information accordingly.

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