Temperature compensation system of magnetic sensor

Abstract

The invention discloses a temperature compensation system of a magnetic sensor, which comprises a temperature sensor, a heating element, a cooling module and a temperature control unit, and is characterized in that the temperature sensor monitors the environment temperature and the surface temperature of the magnetic sensor in real time and transmits temperature data to the temperature control unit, and the temperature control unit carries out processing through a self-adaptive control algorithm. According to the temperature compensation system of the magnetic sensor disclosed by the invention, by combining real-time data feedback and self-adaptive control calculation of the magnetic sensor, accurate temperature control is realized, and high-precision measurement of the magnetic sensor in a complex environment is ensured; the self-adaptive control algorithm can automatically adjust working parameters of the temperature control system according to magnetic field data and temperature data fed back by the magnetic sensor in real time, and by introducing the fuzzy control algorithm and PID control, the system can adaptively adjust heating and cooling power in different environments and quickly respond to temperature fluctuation.

Description

Technical Field

[0001] The invention belongs to the technical field of constant temperature control, and in particular relates to a temperature compensation system of a magnetic sensor. Background Art

[0002] Magnetic sensors are widely used in precision manufacturing, robot control, and medical equipment. They provide high-precision measurement data by detecting changes in magnetic fields, providing real-time magnetic field information for various application scenarios. However, the performance of magnetic sensors is often affected by changes in ambient temperature in actual applications. When the ambient temperature fluctuates, the output signal of the magnetic sensor will be offset or erroneous, resulting in reduced measurement accuracy and even error accumulation. Therefore, in order to ensure the accuracy and reliability of sensor data, the sensor working environment must be effectively temperature controlled.

[0003] Most of the existing constant temperature control systems for magnetic sensors rely on traditional constant temperature boxes or single temperature regulators, which aim to reduce the impact of temperature fluctuations on sensor measurement accuracy by maintaining a constant temperature around the sensor. Existing constant temperature control systems are usually not flexible enough. Because they rely on preset temperatures for adjustment, when the ambient temperature changes rapidly, the constant temperature box or temperature regulator responds slowly and cannot respond in time, causing the sensor measurement to be affected by temperature fluctuations and the measurement results to be unstable. Traditional constant temperature systems often do not combine real-time feedback from magnetic sensors. They usually rely only on data provided by temperature sensors for control, ignoring the changes in the temperature sensitivity of magnetic sensors under different working conditions. Since magnetic sensors have different sensitivities to temperature under different measurement tasks or different working conditions, this single data source makes it difficult to achieve accurate temperature compensation, resulting in less than ideal temperature control effects.

[0004] Existing thermostatic control systems are deficient in terms of temperature regulation accuracy. Existing temperature control systems usually rely on air convection or radiation in the thermostat to maintain temperature. Although this method is suitable for the regulation of the overall environment, it is difficult for existing systems to achieve high-precision temperature control when dealing with local small temperature changes, especially in application scenarios where magnetic sensors need to be accurately measured. The energy consumption of traditional thermostatic systems is also high. These systems often require a large range of temperature adjustment in the sensor working area. This global control method increases unnecessary energy consumption, especially the thermostat needs to run heating or cooling equipment for a long time to maintain a stable temperature, which further leads to energy waste. In addition, existing thermostatic control systems generally lack adaptive control capabilities. Most systems use a fixed parameter control method, such as adjusting the temperature by setting a fixed constant temperature point or a simple switch, and cannot be adaptively adjusted according to changes in the external environment or real-time feedback from the magnetic sensor. This fixed control mode cannot adapt to the ever-changing external environment or the real-time feedback of the magnetic sensor, resulting in unsatisfactory compensation effect and difficulty in coping with various dynamic changes in complex environments. Existing systems lack sufficient flexibility to meet these dynamic requirements.

[0005] Therefore, the existing technology has certain limitations in terms of temperature control flexibility, real-time feedback, accuracy, energy consumption and adaptability, and cannot effectively meet the precise temperature control requirements of magnetic sensors in complex environments. Therefore, the magnetic sensor must be temperature-controlled to keep the temperature constant. Summary of the invention

[0006] The main purpose of the present invention is to provide a temperature compensation system for a magnetic sensor. The system realizes precise temperature control by combining real-time data feedback of the magnetic sensor with adaptive control calculation, thereby ensuring high-precision measurement of the magnetic sensor in complex environments.

[0007] Another object of the present invention is to provide a temperature compensation system for a magnetic sensor. The adaptive control algorithm can automatically adjust the working parameters of the temperature control system according to the magnetic field data and temperature data fed back by the magnetic sensor in real time. By introducing fuzzy control algorithm and PID control, the system can adaptively adjust the heating and cooling power in different environments, quickly respond to temperature fluctuations, and ensure that the sensor operates within the optimal temperature range.

[0008] To achieve the above purpose, a temperature compensation system of a magnetic sensor includes a temperature sensor, a heating element, a cooling module and a temperature control unit, wherein:

[0009] The temperature sensor monitors the ambient temperature and the surface temperature of the magnetic sensor in real time, and transmits the temperature data to the temperature control unit, which processes the temperature data through an adaptive control algorithm, which is specifically implemented as follows:

[0010] Step S1: The temperature error is converted into a control signal through a fuzzy controller, and adaptive adjustment is performed according to the working state of the magnetic sensor. The two input variables of the fuzzy controller are the temperature error e(t) and the temperature error change rate Δe(t). The input variable formula is as follows:

[0011] e(t)=T targ et -T actual ;

[0012] Δe(t)=e(t)-e(t-1);

[0013] The fuzzy controller generates a fuzzy control signal based on the temperature error e(t) and the temperature error change rate Δe(t) through a set of preset fuzzy rules. The output u of the fuzzy controller is fuzzy (t) is generated based on the temperature error e(t) and the error change rate Δe(t) after fuzzy rules and reasoning process, which is expressed as: fuzzy (t) = Fuzzy(e(t), Δe(t)); the inference result is used as the adjustment signal input of the PID controller;

[0014] Step S2: The PID controller combines the fuzzy control signal to accurately adjust the output power of the heating element and the cooling module to achieve the constant temperature target and ensure the stability of the constant temperature control system. The input of the PID controller is the adjustment signal u generated by the fuzzy control algorithm. PID (t), the specific formula is as follows:

[0015]

[0016] Among them, K p Represents the proportional gain, which is adjusted according to the current value of the fuzzy control signal; K i Indicates the integral gain, which is corrected according to the accumulated value of the fuzzy control signal to eliminate long-term deviation; K d represents the differential gain, which is used to predict the rate of change of the fuzzy control signal and adjust the output in advance. τ represents the time variable in the integral operation, which is used to traverse all time points from 0 to t. Through PID control, the system adaptively adjusts the power output according to the real-time temperature data of the magnetic sensor to ensure that the working environment of the magnetic sensor remains within the set temperature range;

[0017] Step S3: For the data feedback and adjustment of the magnetic sensor, the real-time measurement data of the magnetic sensor is transmitted to the temperature control unit. By analyzing the magnetic field measurement data of the magnetic sensor at different temperatures, the temperature control parameters are optimized in real time. When the temperature change causes the measurement error of the magnetic sensor to exceed the preset range, the output power of the heating element or the cooling module is adjusted to ensure the measurement accuracy of the magnetic sensor. The formula for the measurement error of the magnetic sensor is as follows:

[0018] e B (t) = B ref -B(t);

[0019] Among them, e B (t) represents the measurement error of the magnetic sensor at time t; B ref represents the reference magnetic field signal, that is, the magnetic field signal value expected by the system, and B(t) represents the magnetic field signal actually measured by the magnetic sensor at time t. If the measurement error e B (t) exceeds the preset threshold, the system activates the feedback mechanism to re-evaluate the gain parameter K of the PID controller p , K i , K d , the adjusted PID output u PID (t) is fed back to the heating or cooling module, changing its power output to stabilize the system temperature.

[0020] As a further preferred technical solution of the above technical solution, before step S1, the temperature compensation system of the magnetic sensor is initialized, the temperature sensor, the heating element and the cooling module are started, and the target temperature is set within the optimal working range of the magnetic sensor.

[0021] As a further preferred technical solution of the above technical solution, the temperature sensor is connected to the input end of the temperature control unit.

[0022] As a further preferred technical solution of the above technical solution, the heating element is connected to the first output end of the temperature control unit.

[0023] As a further preferred technical solution of the above technical solution, the cooling module is connected to the second output end of the temperature control unit.

[0024] The beneficial effects of the present invention are:

[0025] By using fuzzy control and PID control, combined with real-time data feedback from the sensor, the temperature control accuracy of the system is improved, and the measurement performance of the sensor in different temperature environments is significantly improved. In addition, the system has the advantages of rapid response to temperature changes and adaptive adjustment of temperature control parameters, ensuring the long-term stability and high accuracy of the sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the present invention.

[0027] Figure 2 It is the fuzzy control block diagram of the present invention. DETAILED DESCRIPTION

[0028] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles of the present invention defined in the following description can be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not deviate from the spirit and scope of the present invention.

[0029] In the preferred embodiments of the present invention, those skilled in the art should note that the magnetic sensor and the like involved in the present invention may be regarded as prior art.

[0030] Preferred embodiments.

[0031] The present invention discloses a temperature compensation system for a magnetic sensor, comprising a temperature sensor, a heating element, a cooling module and a temperature control unit, wherein:

[0032] The temperature sensor monitors the ambient temperature and the surface temperature of the magnetic sensor in real time, and transmits the temperature data to the temperature control unit, which processes the temperature data through an adaptive control algorithm, which is specifically implemented as follows:

[0033] Step S1: The temperature error (the difference between the target temperature and the actual temperature, the temperature error is divided into the ambient temperature error and the sensor surface temperature error, so as to control the system more accurately) is converted into a control signal through a fuzzy controller, and adaptive adjustment is performed according to the working state of the magnetic sensor. The two input variables of the fuzzy controller are the temperature error e(t) and the temperature error change rate Δe(t). The input variable formula is as follows:

[0034] e(t)=T targ et -T actual ;

[0035] Δe(t)=e(t)-e(t-1) (used to determine the trend of temperature change);

[0036] The fuzzy controller generates a fuzzy control signal based on the temperature error e(t) and the temperature error change rate Δe(t) through a set of preset fuzzy rules. The output u of the fuzzy controller is fuzzy (t) is generated based on the temperature error e(t) and the error change rate Δe(t), after fuzzy rules and reasoning process, which can be expressed as: fuzzy (t) = Fuzzy(e(t), Δe(t));

[0037] The inference result is used as the adjustment signal input of the PID controller (if e(t) is large and Δe(t) is large, the heating power is increased; if e(t) is small and Δe(t) is small, the current state is maintained. When the temperature difference is large and the rate of change is large, such as a sudden change in the environment, the system needs a strong response (for example, increase the heating power) to quickly correct the temperature deviation. When the temperature difference is small and the rate of change is small, the system is close to the target temperature and no additional adjustment is required to maintain the stability of the system. This avoids temperature oscillations or fluctuations caused by over-adjustment); fuzzy control is a control method based on linguistic variables and fuzzy rules, which is suitable for handling control problems of nonlinear systems with strong uncertainty. In the present invention, fuzzy control is used to handle uncertainties in temperature control systems, calculate temperature differences and generate control signals;

[0038] Step S2: The PID controller combines the fuzzy control signal to accurately adjust the output power of the heating element and the cooling module to achieve the constant temperature target and ensure the stability of the constant temperature control system. The input of the PID controller is the adjustment signal u generated by the fuzzy control algorithm. PID (t), the specific formula is as follows:

[0039]

[0040] Among them, K p Represents the proportional gain, which is adjusted according to the current value of the fuzzy control signal; K i Indicates the integral gain, which is corrected according to the accumulated value of the fuzzy control signal to eliminate long-term deviation; K d represents the differential gain, which is used to predict the rate of change of the fuzzy control signal and adjust the output in advance. τ represents the time variable in the integral operation, which is used to traverse all time points from 0 to t. Through PID control, the system adaptively adjusts the power output according to the real-time temperature data of the magnetic sensor to ensure that the working environment of the magnetic sensor remains within the set temperature range;

[0041] The input of the fuzzy controller is the temperature error e(t) and the rate of change of the error Δe(t). Based on the input, a fuzzy control signal u is generated using fuzzy rules. fuzzy (t) (indicates how the system should adjust the power to approach the target temperature), the input of the PID controller is the output u of the fuzzy controller fuzzy (t), this output value is used as the input signal of the PID controller to adjust its control output. fuzzy (t) Generate the final adjustment signal u PID (t), which is the output of PID, is used to accurately adjust the power of the heating or cooling module. PID When u(t) is positive, the heating module increases the output power and raises the system temperature. PIDWhen (t) is negative, the cooling module increases the output power and reduces the system temperature.

[0042] Step S3: For the data feedback and adjustment of the magnetic sensor, the real-time measurement data of the magnetic sensor is transmitted to the temperature control unit. By analyzing the magnetic field measurement data of the magnetic sensor at different temperatures, the temperature control parameters are optimized in real time. When the temperature change causes the measurement error of the magnetic sensor to exceed the preset range, the output power of the heating element or the cooling module is adjusted to ensure the measurement accuracy of the magnetic sensor. The formula for the measurement error of the magnetic sensor is as follows:

[0043] e B (t) = B ref -B(t);

[0044] Among them, e B (t) represents the measurement error of the magnetic sensor at time t; B ref represents the reference magnetic field signal, that is, the magnetic field signal value expected by the system, and B(t) represents the magnetic field signal actually measured by the magnetic sensor at time t. If the measurement error e B (t) exceeds the preset threshold, the system activates the feedback mechanism to re-evaluate the gain parameter K of the PID controller p , K i , K d , the adjusted PID output u PID (t) is fed back to the heating or cooling module, changing its power output to stabilize the system temperature.

[0045] Specifically, before step S1, the temperature compensation system of the magnetic sensor is initialized, the temperature sensor, the heating element and the cooling module are started, and the target temperature is set within the optimal working range of the magnetic sensor.

[0046] More specifically, the temperature sensor is connected to an input end of the temperature control unit.

[0047] Furthermore, the heating element is connected to the first output end of the temperature control unit.

[0048] Furthermore, the cooling module is connected to the second output end of the temperature control unit.

[0049] For the present invention:

[0050] Temperature detection and control: The temperature sensor in the constant temperature control system monitors the ambient temperature and the surface temperature of the magnetic sensor in real time, and inputs the temperature data into the control unit.

[0051] Fuzzy control and PID regulation: The adaptive control algorithm first calculates the temperature difference and control signal through fuzzy control, and then accurately adjusts the output power of the heating element and cooling module through the PID controller.

[0052] Sensor data feedback optimization: According to the real-time data of the magnetic sensor, the system adaptively adjusts the working state of the temperature control system to ensure the accuracy of the sensor.

[0053] The process of the present invention is:

[0054] Constant temperature system initialization: start the temperature sensor, heating element, cooling module, and set the target temperature within the optimal working range of the magnetic sensor.

[0055] Real-time temperature monitoring and adjustment: The ambient temperature and sensor surface temperature are monitored by temperature sensors. Fuzzy control and PID controller work together to accurately adjust the heating and cooling modules to maintain a constant temperature.

[0056] Magnetic sensor data feedback adjustment: Based on the real-time data of the magnetic sensor, the impact of temperature fluctuations on sensor accuracy is determined. If it exceeds the set threshold, the system will further adjust the temperature control parameters to optimize the working environment of the sensor.

[0057] It is worth mentioning that the temperature control compensation of the present invention is not only applicable to magnetic sensors, but also to other sensors, such as multi-dimensional force sensors.

[0058] It is worth mentioning that the technical features such as magnetic sensors involved in the patent application of the present invention should be regarded as prior art. The specific structure, working principle and possible control method and spatial arrangement method of these technical features can be selected by conventional methods in the field and should not be regarded as the inventive point of the patent of the present invention. The patent of the present invention will not be further elaborated.

[0059] For those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A temperature compensation system for a magnetic sensor, characterized in that: It includes a temperature sensor, a heating element, a cooling module and a temperature control unit, wherein: The temperature sensor monitors the ambient temperature and the surface temperature of the magnetic sensor in real time, and transmits the temperature data to the temperature control unit, which processes the temperature data through an adaptive control algorithm, which is specifically implemented as follows: Step S1: The temperature error is converted into a control signal through a fuzzy controller, and adaptive adjustment is performed according to the working state of the magnetic sensor. The two input variables of the fuzzy controller are the temperature error e(t) and the temperature error change rate Δe(t). The input variable formula is as follows: e(t)=t target -T actual ; Δe(t)=e(t)-e(t-1); The fuzzy controller generates a fuzzy control signal based on the temperature error e(t) and the temperature error change rate Δe(t) through a set of preset fuzzy rules. The output u of the fuzzy controller is fuzzy (t) is generated based on the temperature error e(t) and the error change rate Δe(t), after fuzzy rules and reasoning process, and is expressed as: fuzzy (t) = Fuzzy(e(t), Δe(t)); the inference result is used as the adjustment signal input of the PID controller; Step S2: The PID controller combines the fuzzy control signal to accurately adjust the output power of the heating element and the cooling module to achieve the constant temperature target and ensure the stability of the constant temperature control system. The input of the PID controller is the adjustment signal u generated by the fuzzy control algorithm. PID (t), the specific formula is as follows: Among them, K p Represents the proportional gain, which is adjusted according to the current value of the fuzzy control signal; K i Indicates the integral gain, which is corrected according to the accumulated value of the fuzzy control signal to eliminate long-term deviation; K d represents the differential gain, which is used to predict the rate of change of the fuzzy control signal and adjust the output in advance. τ represents the time variable in the integral operation, which is used to traverse all time points from 0 to t. Through PID control, the system adaptively adjusts the power output according to the real-time temperature data of the magnetic sensor to ensure that the working environment of the magnetic sensor remains within the set temperature range; Step S3: For the data feedback and adjustment of the magnetic sensor, the real-time measurement data of the magnetic sensor is transmitted to the temperature control unit. By analyzing the magnetic field measurement data of the magnetic sensor at different temperatures, the temperature control parameters are optimized in real time. When the temperature change causes the measurement error of the magnetic sensor to exceed the preset range, the output power of the heating element or the cooling module is adjusted to ensure the measurement accuracy of the magnetic sensor. The formula for the measurement error of the magnetic sensor is as follows: e B (t)=B ref -B(t); Among them, e B (t) represents the measurement error of the magnetic sensor at time t; B ref represents the reference magnetic field signal, that is, the magnetic field signal value expected by the system, and B(t) represents the magnetic field signal actually measured by the magnetic sensor at time t. If the measurement error e B (t) exceeds the preset threshold, the system activates the feedback mechanism to re-evaluate the gain parameter K of the PID controller p , K i , K d , the adjusted PID output u PID (t) is fed back to the heating or cooling module, changing its power output to stabilize the system temperature.

2. A temperature compensation system for a magnetic sensor according to claim 1, characterized in that: Before step S1 , the temperature compensation system of the magnetic sensor is initialized, the temperature sensor, the heating element and the cooling module are started, and the target temperature is set within the optimal working range of the magnetic sensor.

3. A temperature compensation system for a magnetic sensor according to claim 2, characterized in that: The temperature sensor is connected to the input end of the temperature control unit.

4. A temperature compensation system for a magnetic sensor according to claim 3, characterized in that: The heating element is connected to the first output end of the temperature control unit.

5. A temperature compensation system for a magnetic sensor according to claim 4, characterized in that: The cooling module is connected to the second output end of the temperature control unit.

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