A cold-rolled strip cleaning liquid temperature control system and control method

Abstract

The present invention proposes a cold-rolled strip cleaning liquid temperature control system and control method, which relate to the technical field of cold-rolled strip cleaning. The control system obtains temperature data and power data of the cleaning liquid in different time periods, and establishes a mapping relationship between the temperature data and the power data; the temperature obtained by the mapping relationship is compared with a preset temperature threshold, and the temperature abnormality area is identified. The temperature in the temperature abnormal area is monitored to determine the temperature fluctuation value; the temperature fluctuation value is continuously obtained, and abnormal temperature monitoring is performed according to the temperature fluctuation value and the fluctuation threshold to obtain the abnormal fluctuation warning time period; and the PID algorithm is used to adjust the temperature corresponding to the warning time period.

Description

Technical Field

[0001] The present invention relates to the technical field of cold-rolled strip cleaning, and in particular to a cold-rolled strip cleaning liquid temperature control system and a control method. Background Art

[0002] During the cold-rolled strip cleaning process, the cleaning fluid temperature directly impacts surface oil removal, chemical activity, and the risk of strip oxidation. Temperature control requirements vary significantly depending on steel grade (such as high-strength steel and silicon steel) and specifications (thickness 0.3-3.0mm). The strip cleaning process is a crucial component of the cold rolling line. After cold rolling, rolling oil remains on the strip surface. Furthermore, dust and other contaminants are introduced during coil transfer and temporary storage. Inadequate coil cleaning can lead to defects in subsequent processes, particularly for coated substrates.

[0003] Electrolytic cleaning is a key component of the cleaning process, and the main factors affecting the effectiveness of electrolytic cleaning are the control of electrolyte concentration and temperature. The electrolyte used for cleaning strip steel is generally a 2%-5% NaOH electrolyte, and the temperature is generally controlled at 40-80°C. The high temperature can enhance the emulsification effect and enhance the degreasing effect. It can also reduce the resistance of the solution, improve the conductivity, and accelerate the degreasing process.

[0004] Traditional systems often use simple temperature control algorithms, relying on manual experience to set parameters. This results in a response lag (delay > 1s), making them incapable of handling dynamic conditions (such as changes in strip speed and ambient temperature fluctuations). Furthermore, monitoring only the local temperature of the cleaning tank fails to reflect the overall temperature distribution, which can easily lead to local overheating, causing large amounts of solution to evaporate and increasing the burden on the purification equipment. Localized low temperatures can also reduce cleaning effectiveness. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention proposes a method for controlling the temperature of a cold-rolled strip cleaning liquid, comprising the following steps:

[0006] S1. Obtain temperature data and power data of the cleaning liquid at different time periods, and establish a mapping relationship between the temperature data and the power data;

[0007] S2. Compare the temperature obtained by the mapping relationship with a preset temperature threshold, identify an abnormal temperature area, perform temperature monitoring on the abnormal temperature area, and determine a temperature fluctuation value;

[0008] S3. Continuously obtain temperature fluctuation values, perform abnormal temperature monitoring based on the temperature fluctuation values ​​and fluctuation thresholds, and obtain an abnormal fluctuation warning time period;

[0009] S4. Use PID algorithm to adjust the temperature corresponding to the warning time period.

[0010] In a preferred embodiment, in step S1, a mapping relationship between the temperature data and the power data of the system is established: Among them, T(p) represents the temperature obtained according to the mapping relationship, p represents the power, 、 and represents the fitting coefficient.

[0011] In a preferred embodiment, in step S1, the fitting coefficient is determined: in, and They represent the power loss and target power of the i-th sampling point respectively, and n represents the total number of sampling points.

[0012] In a preferred embodiment, in step S2, if the temperature obtained by the mapping relationship Not greater than the temperature threshold , then the corresponding temperature change area is marked as the normal temperature area; otherwise, the corresponding temperature change area is marked as the abnormal temperature area;

[0013] The minimum mean square error algorithm is used to correct and monitor the test data corresponding to the temperature abnormality area to obtain the corrected temperature fluctuation value.

[0014] In a preferred embodiment, in step S3, a sliding window algorithm is used to analyze the temperature fluctuation value. The window length of the sliding window algorithm is w, the window step is s, and the sequence of temperature changes over time is T(t), where t represents the time point, and the temperature fluctuation value within the sliding window is The calculation formula is: in, Represents the average temperature in the kth sliding window, and the calculation formula is: The starting time point of the sliding window , where k represents the window number;

[0015] The calculated fluctuation value With the preset fluctuation threshold For comparison, if Less than or equal to , then the period corresponding to the fluctuation value is marked as the continuous monitoring period; if Greater than , then the period corresponding to the fluctuation value Mark as warning time period.

[0016] In a preferred embodiment, in step S4, according to the temperature fluctuation value in the kth sliding window Use PID formula to calculate temperature control value : According to the temperature control value , calculate the temperature compensation value C(t): Among them, K p , K i , K d Represents the preset proportional coefficient, integral coefficient and differential coefficient, and A and B represent the preset compensation coefficients.

[0017] The present invention also proposes a cold-rolled strip cleaning liquid temperature control system for implementing the above-mentioned cold-rolled strip cleaning liquid temperature control method, comprising: a data acquisition and storage module, a temperature power mapping module, an abnormal temperature detection module, a real-time warning module and an intelligent control module;

[0018] The data acquisition and storage module is used to acquire and store the temperature data of the cleaning liquid and the power data of the heater in different time periods;

[0019] The temperature-power mapping module is used to establish a mapping relationship between temperature data and power data;

[0020] The abnormal temperature detection module is used to compare the temperature obtained through the mapping relationship with the preset temperature threshold to identify the temperature abnormality area;

[0021] The real-time warning module is used to continuously monitor the temperature fluctuation value, perform abnormal temperature monitoring based on the temperature fluctuation value and the fluctuation threshold, and obtain the abnormal fluctuation warning time period;

[0022] The intelligent control module is used to adjust the temperature corresponding to the warning time period using a PID algorithm.

[0023] Compared with the prior art, the present invention has the following beneficial technical effects:

[0024] By establishing a temperature-power mapping relationship, the system can precisely adjust power according to the actual temperature required. During the cleaning process, when high temperatures are not required, the system can reduce power output to avoid energy waste; however, when rapid temperature increase or maintenance is required, sufficient power can be provided in a timely manner. During the initial cleaning process, when rapid temperature increase is required, the system can increase power output according to the mapping relationship; in the later stages of cleaning, when the temperature stabilizes, the power can be appropriately reduced, thus achieving rational energy utilization.

[0025] By monitoring and adjusting the temperature in real time, we avoid the overheating and overcooling that can occur with traditional control methods. Overheating not only wastes energy but can also damage the cleaning equipment and the strip, while overcooling can compromise cleaning effectiveness. This method allows for precise temperature control based on actual conditions, reducing unnecessary energy consumption.

[0026] Stable temperature control can reduce the thermal shock of temperature fluctuations on cleaning equipment and reduce the risk of equipment damage due to frequent temperature changes. By effectively controlling temperature fluctuations, the service life of the equipment is extended and the cost of equipment repair and replacement is reduced.

[0027] By continuously monitoring temperature fluctuations and performing abnormal temperature monitoring, temperature anomalies caused by equipment failures can be discovered in a timely manner. The entire temperature control process is automated. From data acquisition, mapping relationship establishment, anomaly monitoring to temperature adjustment, the system can automatically complete a series of operations, reducing manual intervention and improving production efficiency and management level. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 This is a flow chart of the method for controlling the opening of an electric regulating valve according to the present invention.

[0030] Figure 2 This is a temperature control circuit diagram of the temperature control module of the present invention.

[0031] Figure 3 This is a monitoring and control circuit diagram of the temperature control module of the present invention. DETAILED DESCRIPTION

[0032] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0033] In the drawings of the specific embodiments of the present invention, in order to better and more clearly describe the working principles of the various components in the system, the connection relationship of the various parts in the device is shown, which only clearly distinguishes the relative position relationship between the various components, and does not constitute a limitation on the signal transmission direction, connection sequence and size, dimension and shape of the components or structures. Example 1

[0034] like Figure 1 FIG. 1 is a flow chart of a method for controlling the temperature of a cold-rolled steel strip cleaning liquid according to the present invention. The method comprises the following steps:

[0035] S1. Acquire temperature data and power data of the cleaning liquid in different time periods, and establish a mapping relationship between the temperature data and the power data.

[0036] During the cold-rolled strip production process, precise control of the cleaning fluid temperature has a critical impact on product surface quality and production efficiency. This step focuses on the dynamic mapping relationship between the cleaning fluid temperature and the heater power.

[0037] The collected cleaning fluid temperature data (dependent variable) and heater power data (independent variable) were cleaned, outliers were removed, and they were aligned and matched according to the time dimension to form a structured data set.

[0038] According to the structured data set, a quadratic polynomial model is selected as the mathematical expression of the mapping relationship, which can capture the nonlinear relationship between temperature and power.

[0039] Specifically, the mapping relationship between the system temperature data and the heater power data is: Among them, T(p) represents the temperature obtained according to the mapping relationship, p represents the power, 、 and represents the fitting coefficient.

[0040] It should be noted that in the above formula, although temperature data and power data belong to different physical quantities, there is no need to pay attention to the difference in units, only the values. When establishing the mapping relationship, the mathematical model focuses on the relationship between the variable values, not whether the units are consistent. The unit difference does not affect the calculation of the fitting coefficient.

[0041] In a preferred embodiment, a piecewise cubic polynomial is used to construct a smooth curve for the mapping relationship, ensuring continuity of the first and second-order derivatives. This is suitable for physical processes where temperature varies continuously with power, and can more naturally reflect data trends. Furthermore, to address uneven data errors, weights are assigned to different data points (e.g., points with smaller errors are given higher weights), minimizing the weighted sum of squared errors and optimizing the fit of the fitting result to key data. This is applicable to scenarios with inconsistent temperature or power measurement accuracy.

[0042] In a preferred embodiment, a quadratic polynomial model is fitted by the least squares method to describe the power loss at the i-th sampling point. With target power Specifically, the formula determines the three fitting coefficients of the model by minimizing the sum of squared errors between the predicted values ​​and the actual observed values 、 and .

[0043] The fitting coefficients are determined by the following model: in, and Denote the power loss and target power at the i-th sampling point, respectively, and n represents the total number of sampling points. The above model establishes a quadratic nonlinear relationship between power loss and target power, which can capture the impact of power changes on loss.

[0044] By minimizing the sum of squared errors, the optimal fitting coefficients are obtained. 、 and , so that the model prediction value is as close as possible to the actual observed value, and the fitting model is used to predict the power loss under different target powers, or to analyze the trend of loss changing with power.

[0045] S2, the temperature obtained by the mapping relationship of step S1 With the preset temperature threshold Compare and identify temperature abnormality areas, monitor the temperature in these areas, and determine the temperature fluctuation value.

[0046] like , then the corresponding temperature change area is marked as the normal temperature area; if , the corresponding temperature change area is marked as a temperature anomaly area.

[0047] The minimum mean square error algorithm is used to correct the test data corresponding to the temperature abnormality area, obtain the corrected data, and determine the temperature fluctuation value.

[0048] Table 1. Process simulation of temperature monitoring and correction (for illustration only, not representing actual working values) Through this table, you can clearly see the entire process of temperature monitoring and correction, including how to identify abnormal areas, correct data, and calculate fluctuation values.

[0049] For areas with abnormal temperature, further temperature monitoring can be carried out to determine the temperature fluctuation value.

[0050] Preferably, the minimum mean square error algorithm is used to correct the test data in the temperature abnormality area to obtain the corrected data and determine the temperature fluctuation value.

[0051] S3. Continuously monitor the temperature fluctuation value, perform abnormal temperature monitoring based on the temperature fluctuation value and a preset fluctuation threshold, and obtain an abnormal fluctuation warning time period.

[0052] First, a sliding window algorithm is used to analyze temperature fluctuations. The window length of the sliding window algorithm is w, the window step is s, and the sequence of temperature changes over time is T(t), where t represents the time point.

[0053] Temperature fluctuation within the sliding window The calculation formula is: in, Represents the average temperature in the kth sliding window, and the calculation formula is: The starting time point of the sliding window for: , where k represents the window number.

[0054] The calculated fluctuation value With the preset fluctuation threshold Compare. Less than or equal to , then the period corresponding to the fluctuation value Mark as continuous monitoring period; if Greater than , then the period corresponding to the fluctuation value Mark as warning time period.

[0055] A sliding window algorithm analyzes temperature fluctuations and identifies warning time periods based on preset fluctuation thresholds. By quantifying the degree of temperature fluctuation and comparing it to the fluctuation threshold, potential abnormal time periods are identified.

[0056] In order to more intuitively demonstrate the calculation process of the sliding window, the following is a schematic diagram in Table 2

[0057] Table 2 Calculation data of sliding window S4. Use PID algorithm to adjust the temperature corresponding to the warning time period and optimize the working state and transient response of the control system under dynamic load.

[0058] Specifically, the temperature control value is calculated using a PID formula, and the temperature compensation value is calculated based on the temperature control value using a preset compensation function.

[0059] The temperature control value and temperature compensation value are calculated by the following formula:

[0060] According to the temperature fluctuation value in the kth sliding window Use PID formula to calculate temperature control value :

[0061] in, The term takes into account the accumulation of historical errors and is used to eliminate steady-state errors; The term takes into account the rate of change of the error and is used to suppress rapidly changing interference.

[0062] According to the temperature control value , calculate the temperature compensation value C(t): Among them, K p , K i , K d Indicates the preset proportional coefficient, integral coefficient and differential coefficient, A and B indicate the preset compensation coefficient. The above formula uses logarithmic form to convert the temperature control value Convert to temperature compensation value C(t).

[0063] Table 3 shows the calculation process in an exemplary manner. Through this table, we can clearly see the calculation process of the PID controller and the compensation function, as well as how to calculate the final temperature compensation value based on the temperature fluctuation value. Table 3 Numerical display of the calculation process Example 2

[0064] This embodiment provides a schematic structural diagram of a cold-rolled strip cleaning liquid temperature control system, which includes: a data acquisition and storage module, a temperature power mapping module, an abnormal temperature detection module, a real-time warning module and an intelligent control module.

[0065] The data acquisition and storage module is used to acquire and store the temperature data of the cleaning liquid and the power data of the heater at different time periods. It includes: a temperature sensor group, a power monitoring unit, and a time series database.

[0066] Temperature sensor group: distributed in key areas of the cleaning tank to collect liquid temperature data in real time.

[0067] Power monitoring unit: Connects to the heating / cooling equipment to obtain the current equipment operating power data.

[0068] Time series database: stores temperature data and heater power data in time series, supporting historical data backtracking analysis.

[0069] The temperature-power mapping module is used to establish a mapping relationship between temperature data and power data, and includes a data preprocessing unit, a mapping relationship modeling unit, and a model updating unit.

[0070] Data preprocessing unit: filter, reduce noise and normalize the original data;

[0071] Mapping relationship modeling unit: uses machine learning algorithms (such as LSTM neural networks or regression analysis) to establish a temperature-power dynamic mapping model;

[0072] Model update unit: Regularly iteratively optimizes mapping model parameters using the latest data.

[0073] The abnormal temperature detection module is used to compare the temperature obtained through the mapping relationship with the preset temperature threshold to identify the temperature abnormality area. It includes: a threshold comparator, a fluctuation analysis unit, and an abnormal area positioning unit.

[0074] Threshold comparator: preset temperature upper / lower thresholds and compare with current temperature in real time.

[0075] Fluctuation analysis unit: calculates temperature fluctuation values ​​based on sliding window algorithm;

[0076] The real-time warning module is used to continuously monitor the temperature fluctuation value, perform abnormal temperature monitoring based on the temperature fluctuation value and fluctuation threshold, and obtain the abnormal fluctuation warning time period.

[0077] The intelligent control module is used to adjust the temperature corresponding to the warning time period using a PID algorithm.

[0078] In a preferred embodiment, the temperature control system of the present invention also includes a system management module, which is used to coordinate data interaction and task scheduling of each module through a central controller, has a parameter configuration interface, supports threshold setting, control parameter adjustment and other operations, and stores operation records, alarm information and control parameter changes through a log recording system. Example 3

[0079] The zoned constant temperature control method is adopted to reduce the temperature difference in different positions of the tank, reduce the temperature fluctuation of each zone, and improve the control accuracy.

[0080] Zoned thermostats are a technology that enables targeted temperature control based on the temperature requirements of different spaces. Different areas have varying temperature control requirements. Zoned thermostats can be used to create multiple independent temperature control zones, increasing flexibility and reducing energy consumption. This technology maintains a set temperature range by precisely controlling the heat source. It is typically equipped with a temperature sensor that monitors ambient temperature changes in real time and automatically adjusts the output.

[0081] The temperature control module's power is fed through a master circuit breaker, a fast-acting fuse, and a power regulator. The power regulator controls multiple high-power liquid heaters, each with its own operating indicator light for intuitive status. Each heater also has its own circuit breaker, enabling flexible modular control and preventing a single heater failure from impacting the entire system.

[0082] like Figure 2 The figure shows the temperature control circuit diagram of the temperature control module, which includes two parts: power supply startup and temperature control instrument.

[0083] The power startup part includes: multiple circuit breakers, leakage detection devices, multiple heaters, and start-stop control devices.

[0084] 1Q in the temperature control circuit diagram is a circuit breaker with leakage protection, which is used to control the on and off of the circuit and automatically cut off the power supply when a fault such as leakage occurs in the circuit. The SL connected below is a leakage detection device.

[0085] Heater H obtains power through circuit breaker 1Q to achieve heating function; DX1 and DX2 are grounding terminal blocks, of which DX2 has a protective grounding terminal PE, which is used to connect the grounding line of the equipment to ensure power safety.

[0086] 2Q is another circuit breaker. It works with the 1SB stop button, the 2SB start button, and the 1K contactor to form a start-stop control device, enabling circuit start and stop control. Pressing the 2SB start button energizes the 1K contactor's coil, closing its normally open contacts and maintaining circuit continuity. Pressing the 1SB stop button deenergizes the 1K contactor's coil, disconnecting the circuit.

[0087] 1H is another heater, which heats the circuit when the 1K contactor is closed and the circuit is operating normally. The temperature control instrument section includes: temperature sensor, temperature control instrument, and fuse.

[0088] The LW6043 temperature sensor is responsible for collecting temperature signals. It has two inputs (1+, 1-; 2+, 2-) and one output (1P+, 1P-). Temperature controller 2 receives the temperature signal from the LW6043 temperature sensor, monitors and controls the temperature, compares it with the set temperature, and controls external devices to adjust the temperature.

[0089] When the circuit current of fuse 7F is too large, its fuse element will melt and cut off the circuit, protecting equipment such as temperature control instruments from damage.

[0090] like Figure 3 The figure shows the monitoring and control circuit diagram of the temperature control module, which is mainly used for controlling and monitoring the heater, including: power input part, voltage monitoring part, current monitoring and control part, control module part and load part.

[0091] In the power input section, L11, L21, and L31 are the incoming three-phase AC power lines, providing power. Circuit breaker Q controls the circuit's on / off state and provides short-circuit and overload protection. When an abnormally high current flows through the circuit, circuit breaker Q automatically trips and cuts off power.

[0092] In the voltage monitoring part, SV is a voltage transformer, which is used to convert high voltage into low voltage in proportion. V1 and V2 are voltmeters. The voltage signal is obtained through the voltage transformer SV, and the voltage values ​​of two phases in the three-phase power supply are displayed in real time to monitor the power supply voltage status.

[0093] In the current monitoring and control section, the main contacts of the AC contactor 1KM are used to control the power on and off of the heater. When the contactor coil is energized, the main contacts close, allowing current to flow to the heater. When the power is off, the main contacts open, cutting off the power to the heater.

[0094] Current transformers A1-A6: Convert high currents to smaller currents proportionally for easier measurement and protection. Used in conjunction with an ammeter to monitor the current in the circuit.

[0095] When the current of fuse 1-3F is too large, the fuse element will melt, cutting off the circuit and protecting subsequent equipment.

[0096] In the control module, the ST30 is an intelligent temperature control module with multiple interfaces, including I2, O1, O2, X1, M, GND, 1+, and 1-. I2 is the current signal input interface, O1 and O2 are control signal output interfaces for controlling other devices or providing status feedback, X1 and M are communication interfaces, GND is the ground terminal, and 1+ and 1- are temperature sensor signal inputs for monitoring actual temperature.

[0097] In the load section, 1 represents the zone heaters: they consist of two 100kW heating units (100kW I and 100kW II) connected in a delta configuration, drawing power from the neutral and three-phase lines. These heaters are the loads of the entire circuit, and their operating status is regulated by the control and monitoring circuits described above.

[0098] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted via the computer-readable storage medium. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or a data center that includes one or more available media integrations. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0099] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A cold-rolled strip cleaning liquid temperature control system, characterized in that: include: Data acquisition and storage module, temperature and power mapping module, abnormal temperature detection module, real-time warning module, temperature control module, fast fuse, power regulator, high-power liquid heater and intelligent control module; The data acquisition and storage module is used to acquire and store the temperature data of the cleaning liquid and the power data of the heater in different time periods; The data acquisition and storage module includes: a temperature sensor group, a power monitoring unit, and a time series database. The temperature sensor group is distributed in key areas of the cleaning tank to collect liquid temperature data in real time. The power monitoring unit is connected to the heating / cooling equipment to obtain the current equipment operating power data. The time series database stores temperature data and heater power data in time series. The temperature-power mapping module is used to establish a mapping relationship between temperature data and power data; The abnormal temperature detection module is used to compare the temperature obtained by the mapping relationship with the preset temperature threshold to identify the temperature abnormality area; The real-time warning module is used to continuously monitor the temperature fluctuation value, perform abnormal temperature monitoring according to the temperature fluctuation value and the fluctuation threshold, and obtain the abnormal fluctuation warning time period; the sliding window algorithm is used to analyze the temperature fluctuation value, the window length of the sliding window algorithm is w, the window step size is s, and the sequence of temperature changes over time is T(t), where t represents the time point and the temperature fluctuation value within the sliding window is for: ; Represents the average temperature in the kth sliding window, and the calculation formula is: ; The starting time point of the sliding window ; k represents the window number; the calculated fluctuation value With the preset fluctuation threshold For comparison, if Less than or equal to , then the period corresponding to the fluctuation value Mark as continuous monitoring period; if Greater than , then the period corresponding to the fluctuation value Mark as warning time period; The intelligent control module is used to adjust the temperature corresponding to the warning time period using the PID algorithm; according to the temperature fluctuation value in the kth sliding window Use PID formula to calculate temperature control value : ; According to the temperature control value , calculate the temperature compensation value ;K p , K i , K d Indicates the preset proportional coefficient, integral coefficient and differential coefficient, A and B indicate the preset compensation coefficients; The temperature control module is fed through a main circuit breaker and a fast fuse to a power regulator; the power regulator controls multiple high-power liquid heaters respectively to achieve zoned constant temperature control; the monitoring and control circuit of the temperature control module includes a load part, and the zoned heater of the load part includes two 100KW heating units connected in a triangle, and obtains power from the N line and the three-phase line for heating.

2. The cold-rolled strip cleaning liquid temperature control system according to claim 1, characterized in that: The temperature control module includes a power supply starting part and a temperature control instrument part; The power supply startup part includes: a circuit breaker, a leakage detection device, a heater, and a start-stop control device; the circuit breaker is used to control the on and off of the circuit, and the leakage detection device is connected below the circuit breaker; the heater realizes the heating function; the start-stop control device realizes the start and stop control of the circuit; The temperature control instrument part includes: temperature sensor, temperature control instrument, and fuse; the temperature sensor is responsible for collecting temperature signals; the temperature control instrument receives the temperature signal from the temperature sensor, monitors and controls the temperature, and controls external equipment to adjust the temperature by comparing it with the set temperature; the fuse cuts off the circuit when the circuit current is too large.

3. The cold-rolled strip cleaning liquid temperature control system according to claim 1, characterized in that: The temperature-power mapping module establishes a mapping relationship between temperature data and power data: Among them, T(p) represents the temperature obtained according to the mapping relationship, p represents the power, 、 and represents the fitting coefficient; Determine the fitting coefficients: ;in, and They represent the power loss and target power of the i-th sampling point respectively, and n represents the total number of sampling points; If the temperature obtained by the mapping relationship Not greater than the temperature threshold , then the corresponding temperature change area is marked as the normal temperature area; otherwise, the corresponding temperature change area is marked as the abnormal temperature area; The minimum mean square error algorithm is used to correct and monitor the test data corresponding to the temperature abnormality area to obtain the corrected temperature fluctuation value.

4. The cold-rolled strip cleaning liquid temperature control system according to claim 1, characterized in that: The monitoring and control circuit of the temperature control module also includes: a power input part, a voltage monitoring part, a current monitoring and control part and a control module part; the power input part provides a three-phase AC power supply; the voltage transformer of the voltage monitoring part is used to convert the high voltage into a low voltage in proportion, obtain the voltage signal through the voltage transformer, display the two-phase voltage values ​​in the three-phase AC power supply in real time, and monitor the power supply voltage status; the AC contactor of the current monitoring and control part is used to control the power on and off of the heater; the control module part is used to control the equipment or feedback status.

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