Flow valve position calibration method and system based on Hall matrix

Abstract

The invention relates to a flow valve position calibration method and system based on a Hall matrix, and belongs to the field of flow valve control. The position calibration method comprises the steps that voltage signals output by a Hall sensor array in the movement process of a valve rod of the flow valve are collected in real time, an original voltage signal data set is generated, differential signal noise reduction processing is carried out, and a feature signal set is obtained; identifying slope abrupt change points based on the characteristic signal set, performing segmentation to obtain positive and negative slope curve segments, and performing translation splicing and filtering processing to generate a displacement characteristic curve; according to the preset mechanical stroke of the valve rod of the flow valve, polynomial fitting is conducted on the displacement characteristic curve, and a discretized calibration parameter table is generated; a valve rod of the flow valve is driven to execute full-stroke motion, and an actual voltage signal sequence is collected in real time; and comparing the actual voltage signal sequence with the theoretical voltage signal in the calibration parameter table point by point, and outputting a calibration completion state and error distribution data. The accuracy and reliability of position calibration of the valve rod of the flow valve can be improved.

Description

Technical Field

[0001] The present application relates to the field of flow valve control, and in particular to a flow valve position calibration method and system based on a Hall matrix. Background Art

[0002] In automated control systems, flow valves are key components for controlling fluid flow, and their precise stem position control is essential for accurate flow regulation. To ensure the performance and reliability of the flow valve, the position of the valve stem must be accurately calibrated, and during the operation of the flow valve, the accuracy of the position feedback signal is a key factor in evaluating the accuracy of the flow control system. If the valve stem position feedback signal is inaccurate, it may cause system adjustment errors, thereby affecting the accuracy of the entire flow control. For example, in chemical processes or high-pressure transportation processes, precise valve position adjustment can ensure the stability of fluid flow, thereby avoiding equipment damage and waste of resources caused by excessive or insufficient flow.

[0003] Most common flow valve position calibration methods rely on mechanical measuring tools or optical sensors to determine the position of the valve stem by physically measuring the displacement of the valve stem. These methods usually require the installation of additional sensors or other measuring devices on the valve to monitor the position of the valve stem in real time through direct contact or optical scanning. However, in the actual monitoring process, mechanical sensors often have problems such as complex structure, difficult installation and easy wear, while optical sensors are easily disturbed by dust, oil and changes in ambient light, resulting in unstable measurement results. Therefore, how to improve the stability and reliability of the calibration process in a complex environment and accurately reflect the displacement changes of the valve stem is a technical problem that needs to be solved urgently. Summary of the invention

[0004] In order to improve the accuracy and reliability of flow valve stem position calibration, the present application provides a flow valve position calibration method and system based on a Hall matrix.

[0005] In a first aspect, the present application provides a flow valve position calibration method based on a Hall matrix, which adopts the following technical solution: A flow valve position calibration method based on a Hall matrix, the position calibration method comprising: The voltage signal output by the Hall sensor array during the movement of the valve stem of the flow valve is collected in real time to generate an original voltage signal data set; wherein the Hall sensor array is arranged in the valve cavity of the flow valve along the movement direction of the valve stem; Performing differential signal noise reduction processing on the original voltage signal data set to obtain a characteristic signal set; Identify slope mutation points based on the characteristic signal set, and segment to obtain positive and negative slope curve segments; Perform translation splicing and filtering processing on the segmented positive and negative slope curve segments to generate a displacement characteristic curve; According to the preset mechanical stroke of the flow valve stem, perform polynomial fitting on the displacement characteristic curve to generate a discretized calibration parameter table; Drive the flow valve stem to perform a full stroke movement, and collect the actual voltage signal sequence output by the Hall sensor array in real time; Compare the actual voltage signal sequence with the theoretical voltage signal in the calibration parameter table point by point, and output the calibration completion status and error distribution data.

[0006] By adopting the above technical solution, the voltage signals of the Hall sensor array are collected and denoised, segmented, spliced, filtered and polynomially fitted, and an accurate displacement-voltage mapping relationship is established. By comparing point by point with the actual voltage signal, the calibration error can be effectively detected and corrected. Through precise signal processing and real-time verification, the high-precision and high-reliability of the flow valve stem position calibration are ensured, which is applicable to high-precision flow control systems.

[0007] Optionally, the steps of performing differential signal denoising processing on the original voltage signal dataset to obtain a characteristic signal set include: Perform differential operations on the original voltage signals of adjacent sensors in the Hall sensor array to generate multiple groups of differential signals; Perform dynamic weighted fusion processing on multiple groups of the differential signals, and output the denoised characteristic signal set.

[0008] By adopting the above technical solution, performing differential operations and dynamic weighted fusion processing on the original voltage signal, this technical solution can significantly improve the signal accuracy in the flow valve position calibration. The differential operation effectively eliminates the common-mode noise and improves the signal clarity, while the weighted fusion further optimizes the quality of multiple differential signals, making the finally output characteristic signal more stable and reliable.

[0009] Optionally, the steps of performing translation splicing and filtering processing on the segmented positive and negative slope curve segments include: Perform translation connection processing on the positive slope curve segment, keeping the original direction unchanged; Perform vertical mirror transformation on the negative slope curve segment and then perform translation connection; Adopt a sliding window filtering algorithm to eliminate local signal distortion and obtain a displacement characteristic curve.

[0010] By adopting the above technical solution, the positive slope curve segment is processed by translation connection to ensure the continuity of the forward movement of the valve stem; the negative slope curve segment is vertically mirror-transformed so that the curve of the reverse movement can be seamlessly connected with the positive slope part. Finally, the sliding window filtering further eliminates the distortion of local signals and high-frequency noise, improving the smoothness and accuracy of the displacement characteristic curve.

[0011] Optionally, the steps of performing polynomial fitting on the displacement characteristic curve according to the preset mechanical stroke of the flow valve stem to generate a discretized calibration parameter table include: Obtain the preset mechanical stroke range of the flow valve stem; wherein, the preset mechanical stroke range is the maximum allowable displacement of the flow valve stem, physically restricted by a mechanical limit device; Discretize the displacement characteristic curve into equally spaced calibration points based on the preset mechanical stroke range; Perform polynomial fitting calculations on each equally spaced calibration point to generate a discretized calibration parameter table containing the displacement-voltage mapping relationship.

[0012] By adopting the above technical solution, obtaining the preset mechanical stroke range of the valve stem and discretizing the displacement characteristic curve into equally spaced calibration points can accurately convert the relationship between the displacement and voltage of the valve stem into discretized data. Through polynomial fitting, these discrete points are converted into a smooth and accurate mathematical model, establishing the mapping relationship between displacement and voltage. This process provides a reliable calibration parameter table for the precise position control of the flow valve, ensuring a high-precision match between the valve stem position and the voltage signal, and thus improving the accuracy and reliability of the flow control system.

[0013] Optionally, the steps of comparing the actual voltage signal sequence with the theoretical voltage signal in the calibration parameter table point by point and outputting the calibration completion status and error distribution data include: Query the calibration parameter table according to the displacement value in the actual voltage signal sequence to obtain the corresponding theoretical voltage signal value; Based on the actual voltage signal sequence and the corresponding theoretical voltage signal value, perform point-by-point comparison to calculate the absolute error value of each displacement point; Dynamically adjust the preset error threshold according to the real-time temperature data; Compare the absolute error value of each displacement point with the preset error threshold, mark the set of points exceeding the threshold, and construct an error distribution data set; Generate a calibration completion status identifier according to the number of points exceeding the threshold and the maximum error value in the set of points exceeding the threshold.

[0014] By adopting the above technical solution, the actual voltage signal is compared with the theoretical voltage signal point by point, the error value is calculated, and the error threshold is dynamically adjusted according to the real-time temperature, so as to accurately evaluate the calibration state of the flow valve. Through the marking of the points exceeding the threshold and the construction of the error distribution data set, the system can automatically judge whether the calibration is completed and generate a calibration status identifier (success, warning, failure). This technical solution can monitor the error change in the calibration process in real time and make adaptive adjustments when the temperature or environmental conditions change, ensuring the accurate control of the flow valve under various working conditions.

[0015] Optionally, the calibration method further includes: Real-time monitoring of the environmental parameters of the flow valve; the environmental parameters include the real-time temperature of the valve cavity and the mechanical vibration spectrum; Dynamically adjusting the compensation coefficient in the calibration parameter table based on the environmental parameters; Updating the displacement-voltage mapping relationship based on the adjusted compensation coefficient to generate an optimized calibration parameter table.

[0016] By adopting the above technical solution, the environmental parameters (temperature and vibration spectrum) of the flow valve are monitored in real time, and the compensation coefficient can be dynamically adjusted based on environmental changes, and then the displacement-voltage mapping relationship is updated. This technical solution can timely cope with the interference of environmental factors during actual operation, ensuring the accuracy and stability of calibration. With the adjustment of the compensation coefficient, the generated optimized calibration parameter table can effectively eliminate the measurement errors caused by temperature and vibration changes, thereby improving the overall performance and reliability of the flow valve system and ensuring that the equipment can still provide accurate control under complex and changing working environments.

[0017] In a second aspect, the present application provides a flow valve position calibration system based on a Hall matrix, adopting the following technical solution: A flow valve position calibration system based on a Hall matrix, the position calibration system includes: A data acquisition module, configured to collect in real time the voltage signals output by the Hall sensor array during the movement of the valve stem of the flow valve to generate an original voltage signal data set; wherein, the Hall sensor array is arranged in the valve cavity of the flow valve along the movement direction of the valve stem; A data differential processing module, configured to perform differential signal noise reduction processing on the original voltage signal data set to obtain a characteristic signal set; A curve segmentation module, configured to identify slope mutation points based on the characteristic signal set and segment positive and negative slope curve segments; A displacement feature curve generation module, configured to perform translation splicing and filtering processing on the segmented positive and negative slope curve segments to generate a displacement feature curve; A calibration parameter table generation module, configured to perform polynomial fitting on the displacement characteristic curve according to the preset mechanical stroke of the flow valve stem, and generate a discretized calibration parameter table; A driving module, configured to drive the flow valve stem to perform a full-stroke movement; A voltage signal acquisition module, configured to collect the actual voltage signal sequence output by the Hall sensor array in real time; A displacement calibration module, configured to compare the actual voltage signal sequence with the theoretical voltage signal in the calibration parameter table point by point, and output the calibration completion status and error distribution data.

[0018] Optionally, the calibration system further includes: An environment monitoring module, configured to monitor the environmental parameters of the flow valve in real time; the environmental parameters include the real-time temperature of the valve cavity and the mechanical vibration spectrum; A compensation adjustment module, configured to dynamically adjust the compensation coefficient in the calibration parameter table based on the environmental parameters; A calibration parameter table optimization module, configured to update the displacement-voltage mapping relationship based on the adjusted compensation coefficient, and generate an optimized calibration parameter table.

[0019] In a third aspect, the present application provides a computer device, adopting the following technical solution: A computer device includes a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of the method as described in the first aspect.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution: A computer-readable storage medium stores a computer program that can be loaded and executed by a processor to implement any one of the methods in the first aspect.

[0021] In summary, the present application includes at least one of the following beneficial technical effects: The voltage signal during the movement of the valve stem is collected in real time by the Hall sensor array, and after a series of steps such as differential signal noise reduction, slope mutation point identification, positive and negative slope curve segment segmentation, translation and splicing, and filtering processing, an accurate displacement characteristic curve and calibration parameter table are generated. On this basis, by comparing with the actual voltage signal sequence point by point, the system can output the calibration completion status and error distribution data. This technical solution not only improves the accuracy and robustness of the calibration process, but also ensures high-precision control of the flow valve within the full stroke range by dynamically adjusting and optimizing the calibration parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is the first flow chart of the flow valve position calibration method in one embodiment of the present application.

[0023] Figure 2 It is a schematic diagram of the arrangement of the Hall sensor array in the valve cavity of the flow valve in one embodiment of the present application.

[0024] Figure 3 It is the second process schematic diagram of the flow valve position calibration method in one embodiment of the present application.

[0025] Figure 4 It is the third process schematic diagram of the flow valve position calibration method in one embodiment of the present application.

[0026] Figure 5 It is the fourth process schematic diagram of the flow valve position calibration method in one embodiment of the present application.

[0027] Figure 6 It is the fifth process schematic diagram of the flow valve position calibration method in one embodiment of the present application.

[0028] Figure 7 It is the sixth process schematic diagram of the flow valve position calibration method in one embodiment of the present application. Detailed implementation manners

[0029] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the following further elaborates on the present application in conjunction with the accompanying Figure 1-7 drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0030] The embodiments of the present application disclose a flow valve position calibration method based on a Hall matrix.

[0031] Referring to Figure 1 , a flow valve position calibration method based on a Hall matrix, the position calibration method includes: Step S101, collecting in real time the voltage signals output by the Hall sensor array during the movement of the valve stem of the flow valve to generate an original voltage signal data set; wherein, the Hall sensor array is arranged in the valve cavity of the flow valve along the movement direction of the valve stem; Referring to Figure 2 , during the operation of the flow valve, the Hall sensor array (such as S1 - S6) is arranged on the movement path of the valve stem to detect the position of the valve stem in real time. S1, S2, S3, S4, S5, and S6 in the figure are a high-precision linear Hall sensor array. A neodymium iron boron permanent magnet formed by injection molding is provided on the valve stem of the flow valve, and the magnetic pole direction forms a 45° angle with the sensor plane. When the flow valve is operating, the movement of the valve stem drives the permanent magnet to move horizontally above the Hall sensor array composed of S1 to S6. The Hall sensor outputs a voltage signal proportional to the position of the valve stem by sensing the change of the magnetic field, and these signals form the original voltage data set for subsequent processing.

[0032] Step S102: Perform differential signal noise reduction processing on the original voltage signal dataset to obtain a feature signal set; Among them, since the voltage signal output by the Hall sensor may be affected by noise interference (such as factors like temperature changes and mechanical vibrations), it is necessary to perform noise reduction processing on the original voltage signal. This step eliminates most of the common-mode noise by performing differential operations on the voltage signals of adjacent sensors, and further optimizes the signal through dynamic weight allocation and fusion processing, and outputs a feature signal set.

[0033] Step S103: Identify slope mutation points based on the feature signal set, and segment to obtain positive and negative slope curve segments; Specifically, in the displacement characteristic curve, the movement of the valve stem may exhibit a phenomenon of sudden slope change, especially during the operation of the valve stem. These mutation points indicate that the movement mode of the valve stem has changed. By identifying these slope mutation points based on the feature signal set, the original curve can be segmented into two parts: positive slope and negative slope.

[0034] Step S104: Perform translation splicing and filtering processing on the segmented positive and negative slope curve segments to generate a displacement characteristic curve; Among them, after segmentation, translation splicing and filtering correction are performed on the positive and negative slope curve segments. The purpose is to eliminate curve discontinuity or noise problems caused by slope mutation points. The adjacent curve segments are connected through translation splicing, and then high-frequency noise is removed through filtering to ensure the continuity and differentiability of the displacement characteristic curve.

[0035] Step S105: According to the preset mechanical stroke of the flow valve stem, perform polynomial fitting on the displacement characteristic curve to generate a discretized calibration parameter table; Among them, according to the preset mechanical stroke range of the flow valve stem, the displacement characteristic curve is discretized into multiple equally spaced calibration points. For each calibration point, polynomial fitting calculation is performed to generate the mapping relationship between each displacement and voltage, and a calibration parameter table is formed.

[0036] It can be understood that through polynomial fitting, the relationship between displacement and voltage can be accurately established, providing a theoretical basis for subsequent calibration verification. The discretization of the calibration parameter table can provide accurate calibration point data, ensuring the accuracy and consistency during the calibration process.

[0037] Step S106: Drive the flow valve stem to perform a full stroke movement, and collect the actual voltage signal sequence output by the Hall sensor array in real time; Among them, during calibration verification, the drive valve stem is actuated to perform a full stroke movement, and the actual voltage signal sequence output by the Hall sensor array is collected in real time. These actual voltage signals will be compared with the theoretical values in the calibration parameter table subsequently to check the accuracy of the calibration. Through the full stroke movement and real-time data collection, the working condition of the valve stem under actual working conditions can be simulated, providing real voltage signals for subsequent calibration verification, thereby ensuring the accuracy of the calibration table.

[0038] Step S107: Compare the actual voltage signal sequence point by point with the theoretical voltage signals in the calibration parameter table, and output the calibration completion status and error distribution data.

[0039] Specifically, the actual voltage signal sequence is compared point by point with the theoretical voltage signals in the calibration parameter table. If the voltage differences at multiple consecutive calibration points exceed the set threshold, the system will trigger a calibration failure alarm and generate an error report, indicating the maximum deviation value and the position coordinates.

[0040] In the above embodiments, the voltage signals of the Hall sensor array are collected and denoised, segmented, spliced, filtered, and polynomially fitted, establishing an accurate displacement-voltage mapping relationship. Through point-by-point comparison with the actual voltage signals, calibration errors can be effectively detected and corrected. Through precise signal processing and real-time verification, the high-precision and high-reliability of the flow valve stem position calibration are ensured, which is applicable to high-precision flow control systems.

[0041] Refer to Figure 3 , as an embodiment of step S102, the steps of performing differential signal denoising processing on the original voltage signal dataset to obtain the feature signal set include: Step S201: Perform differential operations on the original voltage signals of adjacent sensors in the Hall sensor array to generate multiple groups of differential signals; Among them, during the flow valve position calibration process, the voltage signals output by the Hall sensor array (such as S1 - S6) usually contain the influence of external interference (such as mechanical vibration, electromagnetic interference, etc.) and sensor noise. These noises are often common-mode, that is, multiple sensors are affected by similar noise sources. Therefore, by performing differential operations on the output signals of adjacent sensors, this part of the common-mode noise can be effectively eliminated, thereby enhancing the accuracy of the signals.

[0042] In the embodiments of the present application, the voltage signals of sensors S1 and S2 generate the first differential signal (Δ1 = S1 - S2) through differential operations, sensors S3 and S4 generate the second differential signal (Δ2 = S3 - S4), and sensors S5 and S6 generate the third differential signal (Δ3 = S5 - S6). This method is based on the premise that adjacent sensors are affected by similar interference, and suppresses the common-mode noise by calculating the signal differences, retaining the effective signals brought about by the change in the valve stem position.

[0043] Exemplarily, assume that the original output voltages of sensors S1 and S2 are 2.3V and 2.4V respectively, and these signals contain the same environmental noise. Through differential operation, we get: Δ1 = S1 - S2 = -0.1V. This value can better represent the small displacement change of the valve stem, and the same noise part is eliminated.

[0044] Step S202: Perform dynamic weighted fusion processing on multiple groups of differential signals and output a set of denoised feature signals.

[0045] Among them, the principle of weighted fusion is to assign different weights to each differential signal according to the quality of different signals. In practical applications, the signals of different sensors may have different credibility due to the influence of factors such as position, noise level, or other environmental factors. Through the weighting method, the weights of the signals can be dynamically adjusted, so that the fused signal can better reflect the actual change of the valve stem position.

[0046] Specifically, the credibility of each group of differential signals can be evaluated according to factors such as the noise level and sensor status (such as temperature, vibration) in practical applications. For example, if the differential signal between S1 and S2 is less affected by temperature changes, then Δ1 can obtain a higher weight. When performing weighted fusion on multiple differential signals, a weighted average algorithm can be used to calculate the final set of feature signals by combining the signal quality and weight coefficients.

[0047] Exemplarily, if the weight of Δ1 is 0.6, the weight of Δ2 is 0.3, and the weight of Δ3 is 0.1, then the final output set of feature signals can be obtained by weighted average calculation: Feature signal = 0.6×Δ1 + 0.3×Δ2 + 0.1×Δ3; Among them, a more accurate signal (such as Δ1) will have a greater impact on the final result, thus optimizing the signal quality.

[0048] In the above embodiments, by performing differential operation and dynamic weighted fusion processing on the original voltage signal, the technical solution of the present invention can significantly improve the signal accuracy in the position calibration of the flow valve. The differential operation effectively eliminates the common-mode noise and improves the clarity of the signal, while the weighted fusion further optimizes the quality of multiple differential signals, making the finally output feature signal more stable and reliable.

[0049] Refer to Figure 4 , as an implementation manner of step S104, the steps of performing translation splicing and filtering processing on the segmented positive and negative slope curve segments include: Step S301: Perform translation connection processing on the positive slope curve segment while keeping the original direction unchanged; Among them, in the displacement characteristic curve, the positive slope part usually represents the forward movement of the valve stem. When the valve stem moves along the predetermined direction, the voltage signal should show an upward trend. However, during the movement of the valve stem, due to the appearance of slope mutation points, the curve may be discontinuous or jump. To ensure the smoothness and consistency of the curve, it is first necessary to perform a translation and connection process on the positive slope curve segment.

[0050] Specifically, the purpose of the translation and connection process is to splice the segmented curve segments according to the original movement direction of the valve stem (usually the forward movement direction) to ensure that the linear relationship between the displacement of the valve stem and the voltage is not misconnected. The translation operation ensures that the transition between curve segments is smooth and there are no breakpoints or jumps caused by the splicing of curve segments.

[0051] Exemplarily, assume that the starting point of the positive slope curve segment is (x1, y1), the ending point is (x2, y2), and the starting point of the next curve segment is (x3, y3), whose position is slightly offset from the previous segment. At this time, the translation and connection process will adjust the starting point of the second segment to (x2, y2) to ensure that the transition between curve segments is continuous.

[0052] Step S302, perform a vertical mirror transformation on the negative slope curve segment and then perform a translation and connection; Among them, the negative slope curve segment represents the reverse movement of the valve stem, and the voltage signal should show a downward trend. However, during the reverse movement of the valve stem, the curve may also be discontinuous due to mutation points. To ensure that this part of the curve can also be correctly connected, it is necessary to perform a vertical mirror transformation on the negative slope curve segment and then perform a translation and connection.

[0053] Specifically, the principle of the vertical mirror transformation is to reverse the voltage values of the negative slope curve so that the decreasing voltage signal can be transformed into an upward trend, which can make the connection between the curve segment and the positive slope part smoother. After this transformation, a translation and connection is performed to ensure that there are no obvious breakpoints or uneven transitions between curve segments.

[0054] Exemplarily, assume that the voltage values of the negative slope curve segment are from (x1, y1) to (x2, y2), and this segment of the curve shows a downward trend due to reverse movement. After the vertical mirror transformation, the voltage signal will be reversed to (x1, -y1) to (x2, -y2), and then a translation and connection process is performed to ensure that the entire curve is smoothly connected to the previous curve segment.

[0055] Step S303, use the sliding window filtering algorithm to eliminate local signal distortion and obtain the displacement characteristic curve.

[0056] Among them, although the curves after translation splicing and mirror transformation have been well connected, due to reasons such as sensor noise, environmental interference, or mechanical errors, local distortions or high-frequency noises may still exist in the curves. To eliminate these distortions and further smooth the curves, a sliding window filtering algorithm needs to be adopted.

[0057] Specifically, the sliding window filtering algorithm applies a window of a fixed size to each point on the curve and averages or weighted-averages the data within the window. In this way, the filtering algorithm can effectively suppress high-frequency noises and small-amplitude distortions in the signal, making the curve smoother. In some embodiments, the filtering algorithm usually includes simple mean filtering, weighted filtering, or median filtering, etc., and a suitable method is selected according to actual requirements.

[0058] In the above-described embodiments, the positive-slope curve segment is processed by translation connection to ensure the coherence of the forward movement of the valve stem; the negative-slope curve segment is vertically mirror-transformed so that the curve of the reverse movement can be seamlessly connected to the positive-slope part. Finally, the sliding window filtering further eliminates the distortions and high-frequency noises of the local signal, improving the smoothness and accuracy of the displacement characteristic curve.

[0059] Referring to Figure 5 , as an implementation manner of step S105, the steps of performing polynomial fitting on the displacement characteristic curve according to the preset mechanical stroke of the flow valve stem and generating a discretized calibration parameter table include: Step S401, obtaining the preset mechanical stroke range of the flow valve stem; Among them, the preset mechanical stroke range is the maximum allowable displacement of the flow valve stem, which is physically restricted by a mechanical limiting device; Specifically, the valve stem of the flow valve usually has a certain physical stroke range, which represents the maximum displacement that the valve stem can freely move in the valve cavity. This stroke range is restricted by the structural design of the valve and the mechanical limiting device. Through the mechanical limiting device, the maximum movement range of the valve stem is clearly set, avoiding excessive movement of the valve stem or exceeding the predetermined range, and ensuring the safety and reliability of the system.

[0060] In the embodiments of the present application, first, it is necessary to clarify the preset mechanical stroke range of the valve stem, that is, the maximum allowable displacement of the flow valve stem. This range is usually determined by mechanical engineers during the design stage of the valve and is restricted by physical devices (such as limit screws or stop rings). Usually, this stroke range will be between 15 - 20 mm.

[0061] Step S402, discretizing the displacement characteristic curve into equally spaced calibration points based on the preset mechanical stroke range; Among them, the displacement characteristic curve is usually a relationship graph based on the voltage signal output by the sensor and the position of the valve stem. When the valve stem of the flow valve moves, the voltage signal changes with the change of the valve stem position, usually showing a continuous linear or non-linear relationship. For the convenience of calibration and practical application, this continuous displacement characteristic curve needs to be converted into multiple discrete calibration points. Since the preset mechanical stroke range determines the upper and lower limits of the displacement, the curve can be equally spaced into several calibration points according to this range. The interval of the equally spaced calibration points can be set according to needs, usually 0.1mm or smaller, to ensure sufficient accuracy.

[0062] Step S403, perform polynomial fitting calculation on each equally spaced calibration point to generate a discretized calibration parameter table containing the displacement-voltage mapping relationship.

[0063] Among them, each equally spaced calibration point corresponds to a displacement value and a voltage value (or voltage signal). The task of polynomial fitting is to establish a mathematical model between displacement and voltage based on these calibration point data. Through polynomial fitting (such as quadratic, cubic or higher-order polynomials), a smooth curve can be found, which can accurately describe the relationship between the position of the valve stem and the voltage.

[0064] Specifically, in the fitting process, numerical calculation methods such as the least squares method can be used to select the best fitting function to ensure that the error between the fitting curve and the actual data points is minimized. Through polynomial fitting, the generated function can describe the voltage value at any position point within the predetermined range.

[0065] Exemplarily, assume that a series of calibration points are obtained, such as: (0,0.1),(0.2,0.15),(0.4,0.22),…,(20,3.5); using polynomial fitting can obtain a polynomial model such as: V(x)=a3x 3 +a2x 2 +a1x+a0, where a0,a1,a2,a3 are the coefficients obtained by least squares fitting, and this polynomial model is the mapping relationship between displacement and voltage.

[0066] In the above embodiments, obtaining the preset mechanical stroke range of the valve stem and discretizing the displacement characteristic curve into equally spaced calibration points can accurately convert the relationship between the displacement of the valve stem and the voltage into discretized data. Through polynomial fitting, these discrete points are converted into a smooth and accurate mathematical model, establishing the mapping relationship between displacement and voltage. This process provides a reliable calibration parameter table for the precise position control of the flow valve, ensuring a high-precision match between the valve stem position and the voltage signal, and thus improving the accuracy and reliability of the flow control system.

[0067] Refer to Figure 6, as an implementation of step S107, the steps of comparing the actual voltage signal sequence with the theoretical voltage signal in the calibration parameter table point by point and outputting the calibration completion status and error distribution data include: Step S501, query the calibration parameter table according to the displacement value in the actual voltage signal sequence to obtain the corresponding theoretical voltage signal value; Among them, during the calibration of the flow valve, the actual voltage signal sequence comes from the Hall sensor array and is used to reflect the actual displacement of the valve stem. To ensure the accuracy of calibration, it is necessary to compare these actual displacement values with the corresponding theoretical voltage signal values. The theoretical voltage signal values come from the generated calibration parameter table, which is generated by methods such as polynomial fitting based on the mapping relationship between valve stem displacement and voltage.

[0068] Specifically, the displacement values in each actual voltage signal sequence correspond one by one to the displacement points in the calibration parameter table. By querying the calibration parameter table, the theoretical voltage value corresponding to each displacement can be obtained, providing a basis for subsequent error calculation.

[0069] Exemplarily, assume that a displacement value in the actual voltage signal sequence is 10 mm. Then, by querying the calibration parameter table, the corresponding theoretical voltage value is obtained. For example, the theoretical voltage is 2.5 V. This process ensures the accurate comparison between the actual voltage signal and the theoretical value.

[0070] Step S502, perform point-by-point comparison based on the actual voltage signal sequence and the corresponding theoretical voltage signal value, and calculate the absolute error value of each displacement point; Among them, after obtaining the actual voltage signal and the theoretical voltage signal, it is necessary to perform point-by-point comparison for each corresponding point. The core of the point-by-point comparison is to calculate the absolute error value of each displacement point, and the formula is: Δv i =∣v i ,real−v i ,theory∣; where vi,real is the actual voltage value and vi,theory is the theoretical voltage value.

[0071] Step S503, dynamically adjust the preset error threshold according to the real-time temperature data; Among them, temperature changes have a certain impact on the voltage output of the Hall sensor. Therefore, it is necessary to dynamically adjust the error threshold according to the real-time temperature data. For example, when the temperature is high, the performance of the sensor may be affected, and at this time, the error threshold needs to be appropriately relaxed.

[0072] Exemplarily, the specific adjustment logic is as follows: when the temperature T > 25 °C, the error threshold will be relaxed accordingly, and the relaxation formula is: θ=θ0×[1 + 0.005×(T - 25)]; where θ0 is the initial threshold.

[0073] Step S504: Compare the absolute error value of each displacement point with a preset error threshold, mark the set of points exceeding the threshold, and construct an error distribution data set; Among them, after calculating the error value of each displacement point, it is necessary to compare the error value with the dynamically adjusted error threshold. If the error exceeds the threshold, mark this displacement point as a point exceeding the threshold and add it to the set of points exceeding the threshold. In addition, all error data can be summarized into an error distribution data set, recording the displacement, error value, and relative error (ratio to the threshold) of each point.

[0074] Exemplarily, if the error of a certain displacement point is 0.025V and the current error threshold is 0.02V, then this point will be marked as a point exceeding the threshold and added to the set of points exceeding the threshold. At the same time, the error information of this point will be added to the error distribution data set.

[0075] Step S505: Generate a calibration completion status flag according to the number of points exceeding the threshold and the maximum error value in the set of points exceeding the threshold.

[0076] Among them, after constructing the error distribution data set and marking the set of points exceeding the threshold, generate a calibration completion status flag according to these data. There are three possible calibration statuses: success, warning, and failure.

[0077] Exemplarily, when the number of points exceeding the threshold N over ≤ 3N_ and the maximum error Δv max < 2θ, the calibration is considered successful; when the number of points exceeding the threshold 3 < N over ≤ 10 or there are consecutive points exceeding the threshold, the calibration status is a warning; when the number of points exceeding the threshold N over > 10 or the maximum error Δv max ≥ 2θ, the calibration status is a failure.

[0078] In the above embodiments, the actual voltage signal is compared with the theoretical voltage signal point by point, the error value is calculated, and the error threshold is dynamically adjusted according to the real-time temperature, so as to accurately evaluate the calibration status of the flow valve. Through the marking of points exceeding the threshold and the construction of the error distribution data set, the system can automatically judge whether the calibration is completed and generate a calibration status flag (success, warning, failure). This technical solution can monitor the error change during the calibration process in real time and make adaptive adjustments when the temperature or environmental conditions change, ensuring the accurate control of the flow valve under various working conditions.

[0079] Referring to Figure 7 , as a further embodiment of the flow valve position calibration method, the calibration method further includes: Step S601: Monitor the environmental parameters of the flow valve in real time; the environmental parameters include the real-time temperature of the valve cavity and the mechanical vibration spectrum; Specifically, in practical applications, the performance of the flow valve is affected by various environmental factors, especially the two parameters of temperature and mechanical vibration. Temperature changes can affect the electrical characteristics of the sensor and the moving parts of the flow valve, resulting in changes in voltage signals. Mechanical vibration may interfere with the sensor or other electronic components, leading to unstable measurement signals. Therefore, real-time monitoring of these environmental parameters (such as the real-time temperature in the valve cavity and the mechanical vibration spectrum) is crucial for improving the calibration accuracy.

[0080] Among them, the change in the temperature in the valve cavity may cause the drift of the sensor voltage output. Generally, as the temperature rises, the sensitivity of the sensor may decrease, or its output signal shows a non-linear change. Using a temperature sensor, such as a thermocouple or an RTD (resistance temperature detector), can monitor the valve cavity temperature in real time. The working environment of the flow valve may have vibrations, which affect the accuracy of the voltage signal. A vibration sensor (such as an accelerometer or a vibration sensor array) can detect the vibration frequency and amplitude of the device and convert this information into spectral data.

[0081] For example, assume that the temperature in the valve cavity rises to 30 °C, and the vibration spectrum shows significant changes in the low-frequency band, indicating that the environmental change may affect the normal operation of the valve and corresponding compensation is required.

[0082] Step S602, dynamically adjust the compensation coefficient in the calibration parameter table based on the environmental parameters; Among them, the calibration parameter table of the flow valve is generated based on the calibration data under ideal conditions. However, in practical applications, environmental conditions (such as temperature and vibration) will affect the working state of the device. Therefore, the compensation coefficient in the calibration parameter table needs to be dynamically adjusted according to the real-time monitored environmental parameters.

[0083] Specifically, temperature changes may cause changes in the sensitivity of the sensor. Assume that when the temperature rises, the voltage output deviation of the sensor increases, and the compensation coefficient needs to be increased. It can be adjusted through the temperature-compensation coefficient mapping relationship. For example, at 30 °C, the compensation coefficient may need to be increased by 5% to adapt to the response change of the sensor. And, vibration will affect the stability of the sensor signal, thus causing errors. Therefore, when the vibration is strong, the compensation coefficient can be appropriately adjusted to reduce the impact of vibration on the measured value. For example, when the high-frequency components in the vibration spectrum exceed a certain threshold, the compensation coefficient can be increased to reduce the signal fluctuation caused by vibration.

[0084] Step S603, update the displacement-voltage mapping relationship based on the adjusted compensation coefficient to generate an optimized calibration parameter table.

[0085] Among them, updating the calibration parameter table is to reflect the effect of environmental compensation into the displacement-voltage mapping relationship, ensuring that the calibration process is more accurate. By monitoring real-time environmental parameters and adjusting compensation coefficients, the calibration parameter table can be optimized to better conform to the actual working conditions.

[0086] Specifically, based on the adjusted compensation coefficients, all displacement-voltage mapping relationships are recalculated. The voltage values corresponding to each displacement point need to be adjusted by the new compensation coefficients to correct the previous deviations caused by environmental changes. Through the update of the compensation coefficients, an optimized calibration parameter table is finally generated. This table contains the theoretical voltage values corresponding to all displacement points, and the voltage values after dynamic adjustment can more accurately reflect the measurement results in actual working conditions.

[0087] In the above embodiments, by real-time monitoring of the environmental parameters (temperature and vibration spectrum) of the flow valve, the compensation coefficients can be dynamically adjusted based on environmental changes, and then the displacement-voltage mapping relationship can be updated. This technical solution can timely cope with the interference of environmental factors during actual operation, ensuring the accuracy and stability of calibration. With the adjustment of the compensation coefficients, the generated optimized calibration parameter table can effectively eliminate the measurement errors caused by temperature and vibration changes, thereby improving the overall performance and reliability of the flow valve system, and ensuring that the device can still provide precise control in complex and changing working environments.

[0088] In practical applications, this solution can effectively solve the interference of external factors such as temperature and vibration on the calibration accuracy, improve the reliability and stability of the flow valve in industrial control, and has important engineering application value and technical significance.

[0089] The embodiment of the present application also discloses a flow valve position calibration system based on a Hall matrix.

[0090] A flow valve position calibration system based on a Hall matrix, the position calibration system includes: A data acquisition module, configured to collect in real time the voltage signals output by the Hall sensor array during the movement of the flow valve stem, and generate an original voltage signal data set; wherein, the Hall sensor array is arranged in the flow valve cavity along the movement direction of the valve stem; A data differential processing module, configured to perform differential signal noise reduction processing on the original voltage signal data set to obtain a feature signal set; A curve segmentation module, configured to identify slope mutation points based on the feature signal set and segment positive and negative slope curve segments; A displacement feature curve generation module, configured to perform translation splicing and filtering processing on the segmented positive and negative slope curve segments to generate a displacement feature curve; A calibration parameter table generation module, which is used to perform polynomial fitting on the displacement characteristic curve according to the preset mechanical stroke of the flow valve stem to generate a discretized calibration parameter table; A driving module, which is used to drive the flow valve stem to perform a full-stroke movement; A voltage signal acquisition module, which is used to collect the actual voltage signal sequence output by the Hall sensor array in real time; A displacement calibration module, which is used to compare the actual voltage signal sequence with the theoretical voltage signal in the calibration parameter table point by point, and output the calibration completion status and error distribution data.

[0091] As a further implementation of the flow valve position calibration system, it further includes: An environment monitoring module, which is used to monitor the environmental parameters of the flow valve in real time; the environmental parameters include the real-time temperature of the valve cavity and the mechanical vibration spectrum; A compensation adjustment module, which is used to dynamically adjust the compensation coefficient in the calibration parameter table based on the environmental parameters; A calibration parameter table optimization module, which is used to update the displacement-voltage mapping relationship based on the adjusted compensation coefficient to generate an optimized calibration parameter table.

[0092] The flow valve position calibration system based on the Hall matrix in the embodiment of the present application can implement any one of the above flow valve position calibration methods, and the specific working processes of each module in the flow valve position calibration system can refer to the corresponding processes in the above method embodiments.

[0093] In several embodiments provided by the present application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative; for example, the division of a certain module is only a logical function division, and there may be other division methods in actual implementation. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0094] The embodiment of the present application also discloses a computer device.

[0095] The computer device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements a flow valve position calibration method based on the Hall matrix as described above.

[0096] The embodiment of the present application also discloses a computer-readable storage medium.

[0097] The computer-readable storage medium stores a computer program that can be loaded and executed by a processor to implement any one of the flow valve position calibration methods based on the Hall matrix as described above.

[0098] Among them, the computer-readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device; the program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0099] It should be noted that in the above embodiments, the descriptions of the various embodiments have their own emphases. For parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0100] The above are all preferred embodiments of the present application. The protection scope of the present application is not limited thereby. Any feature disclosed in this specification (including the abstract and drawings), unless specifically described, can be replaced by other equivalent or similar-purpose alternative features. That is, unless specifically described, each feature is only an example in a series of equivalent or similar features.

Claims

1. A method for calibrating the position of a flow valve based on a Hall matrix, characterized in that The position calibration method includes: Collecting in real time the voltage signals output by the Hall sensor array during the movement of the flow valve stem to generate an original voltage signal dataset; wherein, the Hall sensor array is arranged in the flow valve cavity along the movement direction of the valve stem; Performing differential signal noise reduction processing on the original voltage signal dataset to obtain a feature signal set; Identifying slope mutation points based on the feature signal set and segmenting to obtain positive and negative slope curve segments; Performing translation splicing and filtering processing on the segmented positive and negative slope curve segments to generate a displacement feature curve; Performing polynomial fitting on the displacement feature curve according to the preset mechanical stroke of the flow valve stem to generate a discretized calibration parameter table; Driving the flow valve stem to perform a full-stroke movement and collecting in real time the actual voltage signal sequence output by the Hall sensor array; Comparing the actual voltage signal sequence with the theoretical voltage signals in the calibration parameter table point by point and outputting the calibration completion status and error distribution data.

2. The flow valve position calibration method based on a Hall matrix according to claim 1, wherein The step of performing differential signal noise reduction processing on the original voltage signal dataset to obtain a feature signal set includes: Performing differential operations on the original voltage signals of adjacent sensors in the Hall sensor array to generate multiple groups of differential signals; Performing dynamic weighted fusion processing on multiple groups of the differential signals and outputting a noise-reduced feature signal set.

3. A method for calibrating the position of a flow valve based on a Hall matrix according to claim 1, characterized in that, The step of performing translation splicing and filtering processing on the segmented positive and negative slope curve segments includes: Performing translation connection processing on the positive slope curve segment while keeping the original direction unchanged; Performing vertical mirror transformation on the negative slope curve segment and then performing translation connection; Using a sliding window filtering algorithm to eliminate local signal distortion to obtain a displacement feature curve.

4. A method for calibrating the position of a flow valve based on a Hall matrix according to claim 3, characterized in that, The step of performing polynomial fitting on the displacement feature curve according to the preset mechanical stroke of the flow valve stem to generate a discretized calibration parameter table includes: Obtaining the preset mechanical stroke range of the flow valve stem; wherein, the preset mechanical stroke range is the maximum allowable displacement of the flow valve stem, physically constrained by a mechanical limit device; Discretizing the displacement feature curve into equally spaced calibration points based on the preset mechanical stroke range; Performing polynomial fitting calculations on each equally spaced calibration point to generate a discretized calibration parameter table including the displacement-voltage mapping relationship.

5. A method for calibrating the position of a flow valve based on a Hall matrix according to claim 4, characterized in that, The step of comparing the actual voltage signal sequence with the theoretical voltage signals in the calibration parameter table point by point and outputting the calibration completion status and error distribution data includes: Querying the calibration parameter table according to the displacement values in the actual voltage signal sequence to obtain the corresponding theoretical voltage signal values; Performing point-by-point comparison based on the actual voltage signal sequence and the corresponding theoretical voltage signal values and calculating the absolute error value of each displacement point; Dynamically adjusting the preset error threshold according to real-time temperature data; Comparing the absolute error value of each displacement point with the preset error threshold, marking the set of points exceeding the threshold, and constructing an error distribution dataset; Generating a calibration completion status identifier according to the number of points exceeding the threshold and the maximum error value in the set of points exceeding the threshold.

6. A method for calibrating the position of a flow valve based on a Hall matrix according to any one of claims 1 to 5, characterized in that, The calibration method further includes: Monitoring in real time the environmental parameters of the flow valve; the environmental parameters include the real-time temperature of the valve cavity and the mechanical vibration spectrum; Dynamically adjust the compensation coefficients in the calibration parameter table based on the environmental parameters; Update the displacement-voltage mapping relationship based on the adjusted compensation coefficients to generate an optimized calibration parameter table.

7. A flow valve position calibration system based on a Hall matrix, characterized in that, The position calibration system includes: A data acquisition module, configured to collect in real time the voltage signals output by the Hall sensor array during the movement of the flow valve stem, and generate an original voltage signal data set; wherein, the Hall sensor array is arranged in the flow valve cavity along the movement direction of the valve stem; A data differential processing module, configured to perform differential signal noise reduction processing on the original voltage signal data set to obtain a feature signal set; A curve segmentation module, configured to identify slope mutation points based on the feature signal set and segment positive and negative slope curve segments; A displacement feature curve generation module, configured to perform translation splicing and filtering processing on the segmented positive and negative slope curve segments to generate a displacement feature curve; A calibration parameter table generation module, configured to perform polynomial fitting on the displacement feature curve according to the preset mechanical stroke of the flow valve stem to generate a discretized calibration parameter table; A driving module, configured to drive the flow valve stem to perform a full stroke movement; A voltage signal acquisition module, configured to collect in real time the actual voltage signal sequence output by the Hall sensor array; A displacement calibration module, configured to compare the actual voltage signal sequence with the theoretical voltage signals in the calibration parameter table point by point, and output the calibration completion status and error distribution data.

8. A flow valve position calibration system based on a Hall matrix according to claim 7, characterized in that, The calibration system further includes: An environmental monitoring module, configured to monitor in real time the environmental parameters of the flow valve; the environmental parameters include the real-time temperature of the valve cavity and the mechanical vibration spectrum; A compensation adjustment module, configured to dynamically adjust the compensation coefficients in the calibration parameter table based on the environmental parameters; A calibration parameter table optimization module, configured to update the displacement-voltage mapping relationship based on the adjusted compensation coefficients to generate an optimized calibration parameter table.

9. A computer device, characterized in that: Including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: A computer program stored that can be loaded and executed by a processor to implement the method according to any one of claims 1 to 6.

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