Intelligent Temperature Control System and Method for Electric Tracing Tape of Control Box

Abstract

The present invention relates to the technical field of electric tracing heating control, and discloses an intelligent temperature control system and method for the electric tracing of a control box. The method includes obtaining electromagnetic interference information and constructing an electromagnetic interference distribution map to accurately characterize the distribution of electromagnetic field intensity values, noise peak values, current fluctuation amplitude values, and transient pulse widths at different positions, so as to identify the regions that have a greater impact on the temperature control signal, enabling the deviation of the temperature control signal to be effectively quantified. Then, based on the spatial distribution information, spatial interpolation processing is performed on the electromagnetic interference information, so that the influence degree of electromagnetic interference can be accurately reflected on the surface of the entire target to be heated, providing data support for the correction of real-time temperature control information. Finally, based on the electromagnetic interference distribution map, the real-time temperature control information is corrected, so that the acquisition and transmission of the temperature control signal can still maintain accuracy and stability under the influence of electromagnetic interference information, improving the accuracy of the temperature control system and ensuring the temperature control effect during segmented heating of the electric tracing tape.

Description

Technical Field

[0001] The present invention relates to the technical field of electric tracing heating control, and more specifically, to an intelligent temperature control system and method for electric tracing belts in a control box. Background Art

[0002] In the fields of industrial production and construction, electric tracing belts are widely used for anti-freezing and heat preservation of pipelines, equipment or storage tanks. Usually, in order to meet the requirements of different regions and different working conditions, electric tracing belts are often designed with a segmented power supply method to heat each segment specifically. Segmented power supply can not only optimize energy consumption but also facilitate maintenance and management, with strong flexibility.

[0003] However, when the prior art performs segmented heating on electric tracing belts, it often only focuses on how to achieve independent switching and temperature control of each segment, but ignores the impact of electromagnetic interference generated during the segmented power supply process of electric tracing belts on the accuracy of the temperature control system. Since when different segments work simultaneously or alternately, the changes in current and voltage will form non-uniform and differently intense electromagnetic fields around, and these electromagnetic fields will interfere with the acquisition and transmission of temperature sensors or temperature control signals, resulting in deviations or delays in the temperature control system. Especially when multiple segments work simultaneously, the interference signals are superimposed on each other, further amplifying the errors in temperature detection or temperature control instructions.

[0004] In view of this, the present invention proposes an intelligent temperature control system and method for electric tracing belts in a control box to solve the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides an intelligent temperature control system and method for electric tracing belts in a control box.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] In a first aspect, an intelligent temperature control method for electric tracing belts in a control box is provided, including:

[0008] The electric tracing belt is arranged on the surface of the target to be heated in a segmented manner. When the electric tracing belt heats the target to be heated, real-time temperature control information and electromagnetic interference information are obtained. The electromagnetic interference information represents the interference degree of the electromagnetic field intensity generated at different positions during the segmented heating process of the electric tracing belt on the temperature control signal;

[0009] The spatial distribution information corresponding to the electromagnetic interference information is obtained, and the electromagnetic interference information is subjected to spatial interpolation processing according to the spatial distribution information to obtain an electromagnetic interference distribution map;

[0010] Based on the electromagnetic interference distribution map, the real-time temperature control information is corrected to obtain optimized temperature control information, and the working state of the electric tracing belt is regulated according to the optimized temperature control information.

[0011] In some embodiments, the method for obtaining electromagnetic interference information includes:

[0012] Establish an electromagnetic field distribution model generated when the electric tracing band works in different segments, analyze the electromagnetic field distribution model, and obtain the interference influence range of the electric tracing band;

[0013] Based on the interference influence range, determine the installation position of the preset sensor, and obtain the electromagnetic interference information corresponding to the sensor according to the installation position. The interference influence range represents the influence range of the electromagnetic field generated by the electric tracing band on the surrounding area.

[0014] In some embodiments, the method for determining the installation position of the preset sensor based on the interference influence range includes:

[0015] In the interference influence range of each electric tracing band, use simulation to draw an isogram of the electromagnetic field intensity, and determine the electromagnetic field intensity of each point in the interference influence range according to the isogram;

[0016] Based on a preset tolerance threshold, determine a candidate influence range where the electromagnetic field intensity is lower than this value, and select any point from the candidate influence range as the installation position.

[0017] In some embodiments, the method for obtaining the spatial distribution information corresponding to the electromagnetic interference information includes:

[0018] Perform normalization processing on the electromagnetic interference information, construct an interference information matrix according to the normalized electromagnetic interference information, and calculate the corresponding covariance matrix according to the interference information matrix;

[0019] Perform eigenvalue decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor, correspond the comprehensive interference scores of each sensor to their spatial positions, and use the mapping relationship between the comprehensive interference scores and the spatial positions as the spatial distribution information. Among them, the comprehensive interference score represents the comprehensive influence degree of the electromagnetic interference information collected by each sensor.

[0020] In some embodiments, the method for performing eigenvalue decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor includes:

[0021] Perform eigenvalue decomposition on the covariance matrix to obtain the principal component eigenvectors, project the normalized electromagnetic interference information corresponding to each sensor onto the principal component eigenvectors, and calculate the comprehensive interference scores corresponding to each sensor.

[0022] In some embodiments, the method for performing spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain an electromagnetic interference distribution map includes:

[0023] A regular grid is established on the surface of the target to be heated. Based on the spatial distribution information and the preset Kriging method, the predicted interference value is calculated for each grid point within the regular grid. A continuous electromagnetic interference distribution map is generated based on the predicted interference values of each grid point, where each grid point in the regular grid represents the position of the predicted interference value to be calculated.

[0024] In some embodiments, the method for calculating the predicted interference value for each grid point within the regular grid based on the spatial distribution information and the preset Kriging method includes:

[0025] For each grid point within the regular grid, the Euclidean distance between each grid point and each spatial position is determined. Based on the Kriging method and the Euclidean distance, the weight corresponding to each grid point is solved. The comprehensive interference score of each sensor is multiplied by the corresponding weight, and all the products are summed to obtain the predicted interference value of this grid point.

[0026] In some embodiments, the method for correcting the real-time temperature control information based on the electromagnetic interference distribution map to obtain the optimized temperature control information includes:

[0027] The electromagnetic interference distribution map and the real-time temperature control information are input into a pre-trained information correction model to obtain the optimized temperature control information.

[0028] In some embodiments, the training method of the information correction model includes:

[0029] Taking a preset fully connected neural network as the basic model, the input layer in the fully connected neural network receives the electromagnetic interference distribution map and the real-time temperature control information, and the output layer in the fully connected neural network outputs the optimized temperature control information. When training the fully connected neural network, the cross-entropy loss function is selected as the loss function, and the loss function is minimized by the gradient descent method to update the weight parameters of the fully connected neural network. Through iterative training, the information correction model is obtained.

[0030] The intelligent temperature control system for the electric tracing band of the control box, which is used to implement the above-mentioned intelligent temperature control method for the electric tracing band of the control box, includes:

[0031] Data acquisition module: The electric tracing band is arranged on the surface of the target to be heated in a segmented manner. When the electric tracing band heats the target to be heated, the real-time temperature control information and the electromagnetic interference information are acquired. The electromagnetic interference information characterizes the interference degree of the electromagnetic field intensity generated at different positions on the temperature control signal during the segmented heating process of the electric tracing band.

[0032] Data processing module: It is used to acquire the spatial distribution information corresponding to the electromagnetic interference information, and perform spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain the electromagnetic interference distribution map.

[0033] Data correction module: Based on the electromagnetic interference distribution map, the real-time temperature control information is corrected to obtain optimized temperature control information, and the working state of the electric tracing band is regulated according to the optimized temperature control information.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0035] The present invention first obtains electromagnetic interference information and constructs an electromagnetic interference distribution map to accurately represent the distribution of electromagnetic field strength values, noise peak values, current fluctuation amplitude values, and transient pulse widths at different positions, thereby identifying the regions with greater influence on the temperature control signal, enabling the deviation of the temperature control signal to be effectively quantified. Then, spatial interpolation processing is performed on the electromagnetic interference information based on the spatial distribution information, so that the influence degree of electromagnetic interference can be accurately reflected on the surface of the entire target to be heated, providing data support for the correction of real-time temperature control information. Finally, the real-time temperature control information is corrected based on the electromagnetic interference distribution map, so that the acquisition and transmission of the temperature control signal can still maintain accuracy and stability under the influence of electromagnetic interference information, improving the accuracy of the temperature control system and ensuring the temperature control effect during segmented heating of the electric tracing band. Brief Description of the Drawings

[0036] Figure 1 It is a schematic flow chart of the intelligent temperature control method for the electric tracing band of the control box in the present invention;

[0037] Figure 2 It is a schematic structural diagram of the intelligent temperature control system for the electric tracing band of the control box in the present invention;

[0038] Figure 3 It is a schematic flow chart of obtaining electromagnetic interference information in the present invention;

[0039] Figure 4 It is a schematic flow chart of obtaining the spatial distribution information corresponding to the electromagnetic interference information in the present invention. Detailed Embodiments

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the described embodiments of the present invention belong to the scope of protection of the present invention.

[0041] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the field to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Terms such as "comprising" or "including" mean that the elements or objects appearing before this term cover the elements or objects listed after this term and their equivalents, without excluding other elements or objects. Terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0042] Example 1

[0043] Please refer to Figure 1 as shown. This embodiment discloses and provides an intelligent temperature control method for the electric tracing heating tape of a control box, including:

[0044] S10: The electric tracing heating tape is arranged on the surface of the target to be heated in a segmented manner. When the electric tracing heating tape heats the target to be heated, real-time temperature control information and electromagnetic interference information are obtained. The electromagnetic interference information characterizes the interference degree of the electromagnetic field intensity generated at different positions on the temperature control signal during the segmented heating process of the electric tracing heating tape;

[0045] In this embodiment, the control box can be an intelligent maintenance power box. The main function of the intelligent maintenance power box is to realize the intelligent management and control of the electricity use in the enterprise production process, ensuring safe, efficient and convenient electricity use. The electric tracing heating tape is a heating device used for pipelines, equipment or cables, and is usually used together with the control box to prevent pipelines or equipment from freezing in low-temperature environments, maintain the temperature, or ensure the temperature stability during system operation. It usually consists of an electric tracing heating tape and a control system. The control box is responsible for adjusting and monitoring the working state of the electric tracing heating tape. The above-mentioned target to be heated can be a pipeline or a cable. The heating principle of the electric tracing heating tape is usually based on the Ohmic resistance heating method. The heating elements inside the electric tracing heating tape are usually composed of conductive materials (such as nickel-chromium alloy, copper, etc.). The resistance characteristics of these materials determine the heating effect of the electric tracing heating tape. When an electric current passes through the electric tracing heating tape, due to the resistance of the electric tracing heating tape, electrical energy is converted into heat energy, thereby generating heat.

[0046] It should be added that when the target to be heated is a pipeline, the method of installing the electric tracing heating tape in a segmented manner can be as follows: The electric tracing heating tape is attached to the surface of the pipeline in a parallel straight line along the length direction of the pipeline, and the length and position of the electric tracing heating tape are segmented and designed according to the equal-distance principle, so that it is evenly distributed in each area of the pipeline to ensure the uniformity and stability of the heating effect.

[0047] It should be noted that the real-time temperature control information includes, but is not limited to, the current temperature value, the current heating power, and the temperature change rate value. The electromagnetic interference information includes, but is not limited to, the electromagnetic field strength value, the noise peak value, the current fluctuation amplitude value, and the transient pulse width. The electromagnetic field strength value refers to the magnitude of the electromagnetic field strength at different positions during the segmented heating process of the electric heat tracing tape. The noise peak value refers to the maximum intensity value of the interference noise in the electromagnetic interference signal, which is used to describe the degree of burst noise interference in the signal. The current fluctuation amplitude value refers to the fluctuation range of the current signal relative to the reference current value during the segmented heating process of the electric heat tracing tape. The transient pulse width refers to the time interval experienced by the transient interference signal from the start to the end during the segmented switching process of the electric heat tracing tape.

[0048] As Figure 3 shown, the method for obtaining electromagnetic interference information includes:

[0049] Establish an electromagnetic field distribution model generated when the electric heat tracing tape works in different segments, analyze the electromagnetic field distribution model, and obtain the interference influence range of the electric heat tracing tape;

[0050] Based on the interference influence range, determine the installation position of the preset sensor, and obtain the electromagnetic interference information corresponding to the sensor according to the installation position. The interference influence range characterizes the influence range of the electromagnetic field generated by the electric heat tracing tape on the surrounding area.

[0051] It should be noted that taking the pipeline as the heating target, the electric heat tracing tape can be arranged on the surface of the pipeline in a segmented manner along the length direction of the pipeline. Then, using finite element analysis (FEA) software (such as ANSYS Maxwell, COMSOL Multiphysics, etc.), a three-dimensional model including the pipeline, the segmented electric heat tracing tape, and the surrounding environment is established. The material properties, current distribution, grounding conditions, and geometric structure are accurately set. Through simulation, the electromagnetic field strength, frequency spectrum characteristics, and interference attenuation law along the surface and surrounding area of the pipeline under different segmented working conditions are obtained, and then an electromagnetic field distribution model is constructed. Establishing the corresponding three-dimensional model is the prior art, and this embodiment will not elaborate on it too much.

[0052] The method for determining the installation position of the preset sensor based on the interference influence range includes:

[0053] In the interference influence range of each electric heat tracing tape, use simulation to draw an isoline map of the electromagnetic field strength, and determine the electromagnetic field strength of each point in the interference influence range according to the isoline map;

[0054] Based on a preset tolerance threshold, determine a candidate influence range where the electromagnetic field strength is lower than this value, and select any point from the candidate influence range as the installation position.

[0055] It can be understood that in this embodiment, the post - processing module of the software extracts the electromagnetic field intensity data on the surface of the pipeline to be heated and its surrounding area, and performs data interpolation on the selected two - dimensional section. Subsequently, according to the preset electromagnetic field intensity level setting, the software automatically generates an isogram to intuitively display the distribution and attenuation trend of the electromagnetic field intensity in each area, thereby providing a quantitative basis for determining the optimal installation position of the sensor.

[0056] In this embodiment, the electric tracing tape is arranged on the surface of the object to be heated in a segmented manner, and when the electric tracing tape heats the object to be heated, real - time temperature control information and electromagnetic interference information can be obtained simultaneously; by using the electromagnetic field distribution model established by finite - element analysis software and drawing the isogram of the electromagnetic field intensity through simulation, the interference influence range of the electric tracing tape can be accurately obtained; then, according to the preset tolerance threshold, the installation position of the preset sensor is determined, so that each electric tracing tape corresponds to a sensor, and the sensor is installed at a position with less interference, thereby ensuring the accuracy and stability of the temperature control signal acquisition.

[0057] S20: Obtain the spatial distribution information corresponding to the electromagnetic interference information, perform spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain an electromagnetic interference distribution map;

[0058] In this embodiment, the spatial distribution information includes, but is not limited to, the distribution of electromagnetic field intensity values, noise peak values, current fluctuation amplitude values, and transient pulse width values at different positions. The distribution of different positions refers to the spatial distribution of the numerical values of the electromagnetic interference information (including electromagnetic field intensity values, noise peak values, current fluctuation amplitude values, and transient pulse width) collected at the positions of each preset sensor on the surface of the pipeline to be heated and its surrounding area. That is to say, after the data collected by each sensor is associated with its specific installation position, it can show the trend and law of how parameters such as electromagnetic interference intensity change with position at different positions on the surface of the pipeline and its periphery. For example, at some positions, due to being close to the electric tracing tape or being strongly interfered by other segments, the electromagnetic field intensity at that place may be higher, while at other positions, it may be lower. Such a distribution provides a quantitative basis for subsequent spatial interpolation of the overall electromagnetic interference information and drawing the interference distribution map.

[0059] As Figure 4 shown, the method for obtaining the spatial distribution information corresponding to the electromagnetic interference information includes:

[0060] Perform normalization processing on the electromagnetic interference information, construct an interference information matrix according to the normalized electromagnetic interference information, and calculate the corresponding covariance matrix according to the interference information matrix;

[0061] Perform eigen - decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor. Correlate the comprehensive interference scores of each sensor with its spatial position, and use the mapping relationship between the comprehensive interference scores and the spatial position as the spatial distribution information, where the comprehensive interference score represents the comprehensive influence degree of the electromagnetic interference information collected by each sensor.

[0062] The method of performing eigen - decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor includes:

[0063] Perform eigen - decomposition on the covariance matrix to obtain the principal - component eigen - vectors. Project the normalized electromagnetic interference information corresponding to each sensor onto the principal - component eigen - vectors, and calculate the comprehensive interference scores corresponding to each sensor.

[0064] It should be added that normalizing the electromagnetic interference information means processing the electromagnetic interference data collected by each sensor to a unified scale, enabling parameters with different dimensions and value ranges to be compared under the same standard. Usually, methods such as Z - score standardization or min - max normalization are used to convert each item of electromagnetic interference data into data without units, with a mean of 0 and a covariance of 1 to eliminate the scale differences between different indicators. The covariance matrix is a matrix that describes the linear relationship between multiple variables, which contains the covariance values between every two variables. The covariance reflects the degree of correlation between two variables. For the case of electromagnetic interference information, the covariance matrix can reflect the correlation between indicators such as the electromagnetic - field strength value, the noise - peak - current fluctuation amplitude value, and the transient - pulse width.

[0065] In this embodiment, the principal - component eigen - vector is a vector obtained by performing eigen - decomposition on the covariance matrix. It represents the combined coefficients of parameters such as the electromagnetic - field strength value, the noise peak, the current - fluctuation amplitude value, and the transient - pulse width in the direction of the maximum variation in the data. Projecting the normalized electromagnetic interference information corresponding to each sensor onto this principal - component eigen - vector is equivalent to calculating the coordinate value of the sensor data in the direction of the maximum variation. This coordinate value reflects the degree of comprehensive influence of each indicator, that is, the comprehensive interference score corresponding to each sensor. The specific example is as follows:

[0066] Suppose there are three sensors, and the interference - information matrix formed by their normalized electromagnetic interference data (in the order of electromagnetic - field strength value, noise peak, current - fluctuation amplitude value, transient - pulse width) is:

[0067] ;

[0068] Next, calculate the covariance matrix based on this matrix. The data has been centered (the mean is 0 after normalization), so the covariance matrix can be approximated by the formula , where n = 3), and among them, is the covariance matrix, is the interference information matrix transpose, n is the number of samples, that is, the number of sensors, and the calculation results in:

[0069] ;

[0070] After performing eigen decomposition on the covariance matrix, the obtained principal component eigenvector is:

[0071] ;

[0072] Project the normalized electromagnetic interference information of each sensor onto the principal component eigenvector, that is, calculate the dot product, to obtain the comprehensive interference score (this score characterizes the comprehensive influence degree of the electromagnetic interference data collected by this sensor). For example:

[0073] For the first sensor, its normalized electromagnetic interference information is [0.8, 0.5, -0.2, 0.3];

[0074] Comprehensive interference score = 0.8×0.7 + 0.5×0.7 + (-0.2)×(-0.1) + 0.3×0.3 = 0.56 + 0.35 + 0.02 + 0.09 = 1.02. The same applies to the other two sensors, and this embodiment will not elaborate on this too much.

[0075] The method for performing spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain the electromagnetic interference distribution map includes:

[0076] Establish a regular grid on the surface of the target to be heated. Through the spatial distribution information and the preset Kriging method, calculate the predicted interference value for each grid point within the regular grid, and generate a continuous electromagnetic interference distribution map based on the predicted interference values of each grid point. Each grid point in the regular grid represents the position of the predicted interference value to be calculated.

[0077] It should be noted that the regular grid refers to the geometric boundary and range determined according to the electromagnetic field distribution model on the surface of the target to be heated, divided into uniformly distributed small units according to a predetermined spacing. Each grid point represents the position of the predicted interference value to be calculated. The Kriging method refers to a spatial interpolation method that calculates the interference value at this position and generates a continuous electromagnetic interference distribution map by establishing a spatial correlation model between data and predicting each point within the grid using the collected sensor data.

[0078] It should be added that the method for generating a continuous electromagnetic interference distribution map based on the predicted interference values of each grid point is specifically as follows: associate the predicted interference value of each grid point with its spatial position on the surface of the target to be heated, and then use an interpolation algorithm to convert the data of discrete grid points into a continuous function for the entire region; then, through color mapping, grayscale processing, or contour plotting, visualize the continuous function as a graph to intuitively display the spatial variation trend of the electromagnetic interference intensity within the region.

[0079] The method for calculating the predicted interference value for each grid point within a regular grid through spatial distribution information and a preset Kriging method includes:

[0080] For each grid point within the regular grid, determine the Euclidean distance between each grid point and each spatial position, solve the weights corresponding to each grid point based on the Kriging method and the Euclidean distance, multiply the comprehensive interference scores of each sensor by the corresponding weights, and sum all the products to obtain the predicted interference value of this grid point.

[0081] It can be understood that for each regular grid point, first calculate the Euclidean distance between it and all sampling points (i.e., sensor positions), then use a preset variogram to convert these distances into semivariogram values to reflect spatial correlation. Next, construct a Kriging equation system based on these semivariogram values and add an unbiasedness constraint with the sum of weights equal to 1. Finally, solve this linear equation system to obtain the weights corresponding to each sampling point. In this embodiment, the purpose of obtaining the predicted interference value is to form a continuous electromagnetic interference distribution map within the region to be heated, rather than simply relying on the discrete data collected by each sensor. By calculating the predicted interference value of each grid point through spatial interpolation, the spatial variation trend of the interference intensity throughout the region can be comprehensively reflected, thereby providing a quantitative basis for optimizing the installation position of sensors, reducing the interference of temperature control signals, and improving the temperature control accuracy and stability of the system.

[0082] In this embodiment, based on the combination of steps S10 and S20, a complete set of analysis and optimization processes is formed for the acquisition of electromagnetic interference information from simulation analysis to sensor data collection and then to spatial interpolation optimization. First, S10 determines the installation positions of the preset sensors based on the electromagnetic field distribution model to ensure that the sensors are installed in positions with less electromagnetic interference, reduce the interference of temperature control signals, and improve the accuracy and stability of temperature control signal acquisition.

[0083] Next, S20 uses spatial interpolation processing to calculate the predicted interference value based on the spatial distribution information of the electromagnetic interference information and generate an electromagnetic interference distribution map, which not only optimizes the evaluation of the electromagnetic interference influence range but also improves the temperature control accuracy and uniformity during the segmented heating process of the electric heating tape.

[0084] Finally, S10 and S20 are executed in sequence, enabling the system to dynamically optimize the electromagnetic interference suppression strategy based on simulation analysis and real-time data fusion, enhancing the intelligent control ability of the electric tracing heating process, and ensuring the safety, stability, and efficiency of the system operation.

[0085] S30: Correct the real-time temperature control information based on the electromagnetic interference distribution map to obtain optimized temperature control information, and regulate the working state of the electric tracing belt according to the optimized temperature control information;

[0086] The method for correcting the real-time temperature control information based on the electromagnetic interference distribution map includes:

[0087] Input the electromagnetic interference distribution map and the real-time temperature control information into a pre-trained information correction model to obtain optimized temperature control information.

[0088] The training method of the information correction model includes:

[0089] Use a preset fully connected neural network as the basic model. The input layer in the fully connected neural network receives the electromagnetic interference distribution map and the real-time temperature control information, and the output layer in the fully connected neural network outputs the optimized temperature control information. When training the fully connected neural network, select the cross-entropy loss function as the loss function, minimize the loss function through the gradient descent method, update the weight parameters of the fully connected neural network, and obtain the information correction model through iterative training.

[0090] It should be noted that during the electric tracing heating process, electromagnetic interference at different positions (including electromagnetic field strength values, noise peaks, current fluctuation amplitude values, transient pulse widths, etc.) will affect the temperature control data collected by the sensor, causing deviations. The electromagnetic interference distribution map can reflect the interference degree of the entire heating target surface and the surrounding area, thus providing a reference basis for temperature control data correction. For example, in high electromagnetic interference areas, the temperature control data collected by the sensor is greatly interfered, resulting in large fluctuations in the measured values and even abnormal jumps. Therefore, in the model training process, a non-linear mapping is used to learn the influence mode of electromagnetic interference on temperature control information, extract the true change trend of the data, and thus eliminate the influence of high electromagnetic interference areas on temperature control information and reduce data fluctuations and abnormal jumps.

[0091] It should be added that regulating the working state of the electric tracing belt according to the optimized temperature control information can be to adjust the heating power of the electric tracing belt, dynamically adjust the segmented heating mode of the electric tracing belt, adjust the heating start-stop strategy, etc. For example, taking the adjustment of the heating start-stop strategy as an example, based on the optimized temperature control information, determine the start-stop time of the electric tracing belt to ensure that the temperature remains within the target range, reduce the heating intensity when the temperature approaches the set value, prevent temperature overshoot, and improve the system stability.

[0092] In this embodiment, by first obtaining electromagnetic interference information and constructing an electromagnetic interference distribution map, the distribution of electromagnetic field strength values, noise peak values, current fluctuation amplitude values, and transient pulse widths at different positions is accurately characterized, so as to identify the regions that have a greater impact on the temperature control signal, enabling the deviation of the temperature control signal to be effectively quantified. Then, based on the spatial distribution information, spatial interpolation processing is performed on the electromagnetic interference information, so that the impact degree of electromagnetic interference can be accurately reflected on the surface of the entire target to be heated, providing data support for the correction of real-time temperature control information. Finally, based on the electromagnetic interference distribution map, the real-time temperature control information is corrected, so that the acquisition and transmission of the temperature control signal can still maintain accuracy and stability under the influence of electromagnetic interference information, improving the accuracy of the temperature control system and ensuring the temperature control effect during segmented heating of the electric tracing tape.

[0093] It should be noted that when implementing the system combining the intelligent temperature control scheme of the control box electric tracing tape and the intelligent maintenance power box, in the hardware installation link, first connect the power supply line including A / B / C (three phase lines) / N (neutral line) / PE (protective line) to the wiring terminals inside the intelligent maintenance power box accurately and without error. At the same time, confirm that the input voltage is consistent with the requirements marked on the equipment nameplate, and ensure that the equipment shell is well grounded. Then, according to the actual use environment and requirements, select a suitable communication connection method from the 4G Cat1 network communication mode, wireless WIFI networking, and wireless AP, so as to achieve the stable data transmission function of the equipment.

[0094] After completing the hardware connection, according to the requirements of the temperature control scheme, the segmented electric tracing tape is reasonably arranged on the surface of the target to be heated. At this time, with the stable power supply of the intelligent maintenance power box, the electric tracing tape starts to heat the target to be heated. While heating, the data acquisition module starts to work: first, use technologies such as finite element analysis to establish an electromagnetic field distribution model generated by the electric tracing tape during different segmented operations, and deeply analyze the electromagnetic field distribution model to obtain the interference influence range of the electric tracing tape; then, within the interference influence range, use simulation to draw the electromagnetic field strength contour map, and determine the installation positions of the preset sensors in combination with the preset tolerance threshold. Through these sensors, real-time temperature control information and electromagnetic interference information including electromagnetic field strength values, noise peak values, current fluctuation amplitude values, transient pulse widths, etc. are collected.

[0095] The collected data will be transmitted to the data processing module. The data processing module first normalizes the electromagnetic interference information, constructs it into an interference information matrix, and further calculates to obtain the covariance matrix. By performing eigen decomposition on the covariance matrix, the principal component eigenvectors are obtained. The normalized electromagnetic interference information corresponding to each sensor is projected onto the principal component eigenvectors to obtain the comprehensive interference scores of each sensor, thereby determining the mapping relationship between the comprehensive interference scores and the spatial positions, that is, obtaining the spatial distribution information. Subsequently, a regular grid is constructed on the surface of the target to be heated. Using the preset Kriging method in combination with the spatial distribution information, the predicted interference values of each grid point within the regular grid are calculated, and then a continuous electromagnetic interference distribution map is generated to accurately display the distribution of electromagnetic interference on the surface of the target to be heated.

[0096] Finally, the data correction module comes into play. The electromagnetic interference distribution map and the real-time temperature control information are input into the pre-trained information correction model, and the optimized temperature control information is obtained after being processed by the information correction model. Based on this optimized temperature control information, the system can accurately regulate the working state of the electric tracing band, such as flexibly adjusting the heating power, intelligently controlling the heating start-stop strategy, etc. In addition, users can conveniently view information such as the on-off state, authorization state, alarm state, and power consumption of the device through a small program or the intelligent maintenance power box control platform, and can also perform operations such as user management, permission setting, device authorization and disabling, realizing the full-range monitoring and management of the electric tracing band temperature control system and the intelligent maintenance power box, and ensuring the safe, stable and efficient operation of the entire system.

[0097] Embodiment 2

[0098] Please refer to Figure 2 As shown, based on the same inventive concept, this embodiment publicly provides an intelligent temperature control system for the control box electric tracing band. For the details not described in this embodiment, please refer to the relevant parts in Embodiment 1. The system includes:

[0099] Data acquisition module: The electric tracing band is arranged on the surface of the target to be heated in a segmented manner. When the electric tracing band heats the target to be heated, real-time temperature control information and electromagnetic interference information are acquired. The electromagnetic interference information characterizes the interference degree of the electromagnetic field intensity generated at different positions on the temperature control signal during the segmented heating process of the electric tracing band.

[0100] In this embodiment, the control box can be an intelligent maintenance power box. The main function of the intelligent maintenance power box is to realize the intelligent management and control of the power consumption in the enterprise production process, ensuring safe, efficient and convenient power use. The electric tracing tape is a heating device used for pipelines, equipment or cables, and is usually used together with the control box to prevent pipelines or equipment from freezing, maintain the temperature, or ensure the temperature stability during the operation of the system in a low-temperature environment. It usually consists of an electric tracing tape and a control system. The control box is responsible for adjusting and monitoring the working state of the electric tracing tape. The above-mentioned target to be heated can be a pipeline or a cable. The heating principle of the electric tracing tape is usually based on the ohmic resistance heating method. The heating elements inside the electric tracing tape are usually composed of conductive materials (such as nickel-chromium alloy, copper, etc.). The resistance characteristics of these materials determine the heating effect of the electric tracing tape. When an electric current passes through the electric tracing tape, due to the resistance of the electric tracing tape, electrical energy is converted into heat energy, thus generating heat.

[0101] The methods for obtaining electromagnetic interference information include:

[0102] Establish an electromagnetic field distribution model generated when the electric tracing tape works in different segments, analyze the electromagnetic field distribution model, and obtain the interference influence range of the electric tracing tape;

[0103] Based on the interference influence range, determine the installation position of the preset sensor, and obtain the electromagnetic interference information corresponding to the sensor according to the installation position. The interference influence range represents the influence range of the electromagnetic field generated by the electric tracing tape on the surrounding area.

[0104] The method for determining the installation position of the preset sensor based on the interference influence range includes:

[0105] In the interference influence range of each electric tracing tape, use simulation to draw an isoline map of the electromagnetic field intensity, and determine the electromagnetic field intensity of each point within the interference influence range according to the isoline map;

[0106] Based on a preset tolerance threshold, determine a candidate influence range where the electromagnetic field intensity is lower than this value, and select any point from the candidate influence range as the installation position.

[0107] Data processing module: used to obtain the spatial distribution information corresponding to the electromagnetic interference information, perform spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information, and obtain an electromagnetic interference distribution map;

[0108] In this embodiment, the spatial distribution information includes, but is not limited to, the distribution of electromagnetic field strength values, noise peak values, current fluctuation amplitude values, and transient pulse width values at different positions. The distribution of different positions refers to the spatial distribution of the numerical values of the electromagnetic interference information (including electromagnetic field strength values, noise peak values, current fluctuation amplitude values, and transient pulse width) collected at the positions of each preset sensor on the surface of the pipeline to be heated and its surrounding area. That is to say, after the data collected by each sensor is associated with its specific installation position, it can show the trends and laws of how parameters such as electromagnetic interference intensity change with position at different positions on the pipeline surface and its periphery. For example, at some positions, due to being close to the electric tracing tape or being strongly interfered with by other segments, the electromagnetic field strength at that place may be relatively high, while at other positions, it may be relatively low. Such a distribution provides a quantitative basis for subsequent spatial interpolation of the overall electromagnetic interference information and drawing of the interference distribution map.

[0109] The method for obtaining the spatial distribution information corresponding to the electromagnetic interference information includes:

[0110] Perform normalization processing on the electromagnetic interference information, construct an interference information matrix based on the normalized electromagnetic interference information, and calculate the corresponding covariance matrix according to the interference information matrix;

[0111] The method for performing eigenvalue decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor includes:

[0112] Perform eigenvalue decomposition on the covariance matrix to obtain the principal component eigenvectors, project the normalized electromagnetic interference information corresponding to each sensor onto the principal component eigenvectors, and calculate the comprehensive interference scores corresponding to each sensor.

[0113] The method for performing spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain an electromagnetic interference distribution map includes:

[0114] Establish a regular grid on the surface of the target to be heated, calculate the predicted interference values for each grid point within the regular grid through the spatial distribution information and the preset Kriging method, and generate a continuous electromagnetic interference distribution map based on the predicted interference values of each grid point, where each grid point in the regular grid represents the position of the predicted interference value to be calculated.

[0115] The method for calculating the predicted interference values for each grid point within the regular grid through the spatial distribution information and the preset Kriging method includes:

[0116] For each grid point within the regular grid, determine the Euclidean distance between each grid point and each spatial position, solve the weights corresponding to each grid point based on the Kriging method and the Euclidean distance, multiply the comprehensive interference scores of each sensor by the corresponding weights, and sum all the products to obtain the predicted interference value of this grid point.

[0117] Data correction module: Based on the electromagnetic interference distribution map, correct the real-time temperature control information to obtain optimized temperature control information, and regulate the working state of the electric tracing tape according to the optimized temperature control information;

[0118] The method for correcting the real-time temperature control information based on the electromagnetic interference distribution map to obtain optimized temperature control information includes:

[0119] Input the electromagnetic interference distribution map and the real-time temperature control information into a pre-trained information correction model to obtain optimized temperature control information.

[0120] The training method of the information correction model includes:

[0121] Use a preset fully connected neural network as the basic model. The input layer in the fully connected neural network receives the electromagnetic interference distribution map and the real-time temperature control information, and the output layer in the fully connected neural network outputs the optimized temperature control information. When training the fully connected neural network, select the cross-entropy loss function as the loss function, minimize the loss function by the gradient descent method, update the weight parameters of the fully connected neural network, and obtain the information correction model through iterative training.

[0122] In the accompanying drawings of the embodiments of the present invention, only the structures related to the embodiments of the present invention are involved. Other structures can refer to the general design. Without conflict, the features in the same embodiment and different embodiments of the present invention can be combined with each other. The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. Intelligent temperature control method for electric tracing heating belt of control box, characterized in that Including: By segmentally arranging the electric tracing band on the surface of the object to be heated, when the electric tracing band heats the object to be heated, real-time temperature control information and electromagnetic interference information are obtained. The electromagnetic interference information characterizes the interference degree of the electromagnetic field intensity generated at different positions during the segmented heating process of the electric tracing band on the temperature control signal; Obtain the spatial distribution information corresponding to the electromagnetic interference information, and perform spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain an electromagnetic interference distribution map; The method for obtaining the electromagnetic interference information includes: Establish an electromagnetic field distribution model generated when the electric tracing band works in different segments, analyze the electromagnetic field distribution model, and obtain the interference influence range of the electric tracing band; Based on the interference influence range, determine the installation position of the preset sensor, and obtain the electromagnetic interference information corresponding to the sensor according to the installation position. The interference influence range characterizes the influence range of the electromagnetic field generated by the electric tracing band on the surrounding area; The method for determining the installation position of the preset sensor based on the interference influence range includes: In the interference influence range of each electric tracing band, use simulation to draw an isogram of the electromagnetic field intensity, and determine the electromagnetic field intensity of each point within the interference influence range according to the isogram; Based on a preset tolerance threshold, determine a candidate influence range where the electromagnetic field intensity is lower than this value, and select any point from the candidate influence range as the installation position; Perform correction processing on the real-time temperature control information based on the electromagnetic interference distribution map to obtain optimized temperature control information, and adjust the working state of the electric tracing band according to the optimized temperature control information. The optimized temperature control information includes the heating power, segmented heating mode, and heating start / stop strategy of the electric tracing band.

2. The intelligent temperature control method for the electric tracing heat tape of the control box according to claim 1, wherein The method for obtaining the spatial distribution information corresponding to the electromagnetic interference information includes: Perform normalization processing on the electromagnetic interference information, construct an interference information matrix according to the normalized electromagnetic interference information, and calculate the corresponding covariance matrix according to the interference information matrix; Perform eigenvalue decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor, correspond the comprehensive interference scores of each sensor to their spatial positions, and use the mapping relationship between the comprehensive interference scores and the spatial positions as the spatial distribution information. Among them, the comprehensive interference score characterizes the comprehensive influence degree of the electromagnetic interference information collected by each sensor.

3. The intelligent temperature control method for the electric tracing band of the control box according to claim 2, wherein The method for performing eigenvalue decomposition on the covariance matrix to obtain the comprehensive interference scores corresponding to each sensor includes: Perform eigenvalue decomposition on the covariance matrix to obtain the principal component eigenvectors, project the normalized electromagnetic interference information corresponding to each sensor onto the principal component eigenvectors, and calculate the comprehensive interference scores corresponding to each sensor.

4. The intelligent temperature control method for the electric tracing band of the control box according to claim 2, wherein The method for performing spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information to obtain an electromagnetic interference distribution map includes: Establish a regular grid on the surface of the object to be heated, calculate the predicted interference value for each grid point within the regular grid through the spatial distribution information and a preset Kriging method, and generate a continuous electromagnetic interference distribution map based on the predicted interference values of each grid point. Each grid point in the regular grid represents the position of the predicted interference value to be calculated.

5. The intelligent temperature control method for the electric tracing heating belt of the control box according to claim 4, characterized in that, The method for calculating the predicted interference value for each grid point in the regular grid by using the spatial distribution information and the preset Kriging method includes: For each grid point in the regular grid, determine the Euclidean distance between each grid point and each spatial position, solve the weights corresponding to each grid point based on the Kriging method and the Euclidean distance, multiply the comprehensive interference scores of each sensor by the corresponding weights, sum all the products, and obtain the predicted interference value of the grid point.

6. The intelligent temperature control method for the electric tracing heating belt of the control box according to claim 4, characterized in that The method for correcting the real-time temperature control information based on the electromagnetic interference distribution map to obtain the optimized temperature control information includes: Input the electromagnetic interference distribution map and the real-time temperature control information into a pre-trained information correction model to obtain the optimized temperature control information.

7. The intelligent temperature control method for the electric tracing band of the control box according to claim 6, characterized in that, The training method of the information correction model includes: Use a preset fully connected neural network as the basic model. The input layer in the fully connected neural network receives the electromagnetic interference distribution map and the real-time temperature control information, and the output layer in the fully connected neural network outputs the optimized temperature control information. When training the fully connected neural network, select the cross-entropy loss function as the loss function, minimize the loss function by the gradient descent method, update the weight parameters of the fully connected neural network, and obtain the information correction model through iterative training.

8. The intelligent temperature control system for the electric tracing heating tape of the control box is used to implement the intelligent temperature control method for the electric tracing heating tape of the control box described in any one of claims 1-7, and is characterized in that, It includes: Data acquisition module: The electric tracing tape is arranged on the surface of the object to be heated in a segmented manner. When the electric tracing tape heats the object to be heated, acquire the real-time temperature control information and the electromagnetic interference information. The electromagnetic interference information characterizes the interference degree of the electromagnetic field intensity generated at different positions on the temperature control signal during the segmented heating process of the electric tracing tape; Data processing module: Used to obtain the spatial distribution information corresponding to the electromagnetic interference information, perform spatial interpolation processing on the electromagnetic interference information according to the spatial distribution information, and obtain the electromagnetic interference distribution map; Data correction module: Correct the real-time temperature control information based on the electromagnetic interference distribution map to obtain the optimized temperature control information, and adjust the working state of the electric tracing tape according to the optimized temperature control information.

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