A crude oil electric heating furnace control system and a crude oil electric heating furnace

Abstract

The present invention belongs to the technical field of crude oil electric heating furnaces and relates to a crude oil electric heating furnace control system and a crude oil electric heating furnace. The control system collects temperature eigenvectors of multiple independent heating sections to generate a dynamic weight matrix for characterizing the degree of thermal inertia imbalance. Real-time analysis of crude oil viscosity-temperature data is combined to generate temperature control compensation gains. The numerical values ​​of corresponding elements in the dynamic weight matrix are adaptively adjusted to output segmented power control instructions. Redundant power of the main and auxiliary coils is preferentially invoked for collaborative heating. Compensatory heating of adjacent sections is initiated when the main and auxiliary power are insufficient. Thermal balance constraints and deviation monitoring termination conditions are also set. This significantly improves power resource utilization in the crude oil electric heating furnace while avoiding local over-focusing. Through closed-loop feedback of viscosity data after heating, the control instructions are iteratively optimized to quickly converge the viscosity to a steady-state range, significantly improving the long-term operational stability of the system and the speed at which control targets are achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of crude oil electric heating furnaces and relates to a crude oil electric heating furnace control system and a crude oil electric heating furnace. Background Art

[0002] Electric crude oil heaters maintain crude oil fluidity through heating with resistance coils. Their simple structure and high thermal efficiency make them widely used in heavy oil extraction and transportation. However, with the scale-up and intelligent development of oil and gas fields, differences in crude oil properties and complex operating conditions are placing higher demands on the temperature control accuracy, energy efficiency, and operational stability of the heaters. The development of control systems for electric crude oil heaters is of great significance for improving the reliability of gathering and transportation and promoting the intelligent upgrading of equipment.

[0003] In the prior art, there are also some solutions related to the control of crude oil electric heating furnaces. For example, China Patent Publication No. CN201126265Y is a heating furnace automatic control system. Its gas source main valve is connected to the mother fire burner through the solenoid valve and the mother fire regulating valve in sequence, and the electronic igniter is electrically connected to the solenoid valve and the mother fire burner. It not only has the functions of temperature control and flameout protection for the heating furnace, but also can perform electronic ignition of the heating furnace. Its operation is very convenient and the ignition is safe and reliable.

[0004] Another Chinese patent, CN210135689U, is an oilfield electric heating vacuum phase change heating furnace. It is equipped with a furnace body, electric heating tubes, crude oil heating coils, multiple sets of temperature and pressure monitoring mechanisms, and automatic control devices. It can monitor the liquid level, the inlet and outlet temperatures of the furnace body and coils in real time, adjust the power according to the temperature difference, monitor the pressure abnormality and alarm, and has a high degree of automation.

[0005] Although the above two schemes propose solutions for the control of crude oil electric heating furnaces, they still have certain limitations: 1. The existing crude oil electric heating furnace control technology relies on single-point or local temperature monitoring, which cannot timely capture the situation of significant temperature gradients and uncontrolled heat flow direction in the heating furnace, which can easily cause local overheating and coking or underheating and viscosity.

[0006] 2. Existing crude oil electric heating furnace controls rely on fixed parameters, resulting in a delayed response to the nonlinear changes in crude oil viscosity with temperature. The compensation gain also lacks dynamic adaptability, leading to cumulative deviations between temperature control commands and actual demand. Furthermore, power allocation relies on single-use regulation of the main coil, resulting in insufficient utilization of redundant capacity. This makes it impossible to flexibly allocate compensatory heating to adjacent heating sections based on viscosity improvement rates and thermal balance constraints, further exacerbating energy waste and instability. Summary of the Invention

[0007] In view of this, in order to solve the problems raised in the above background technology, a crude oil electric heating furnace control system and a crude oil electric heating furnace are proposed.

[0008] The objectives of the present invention can be achieved through the following technical solutions: In a first aspect, the present invention provides a crude oil electric heating furnace control system, including: a data acquisition module, a temperature control compensation module, a power distribution module and a closed-loop calibration module.

[0009] The data acquisition module is connected to the temperature control compensation module, the temperature control compensation module is connected to the power distribution module, and the power distribution module is connected to the closed-loop calibration module.

[0010] The data acquisition module collects the temperature characteristic vectors of multiple independent heating sections divided into three dimensions of the heating furnace in real time and generates a dynamic weight matrix.

[0011] The temperature control compensation module synchronously receives the viscosity-temperature combination data of crude oil in the independent heating section, generates temperature control compensation gain based on the characteristic analysis of crude oil viscosity changing with temperature, and outputs segmented power control instructions in combination with the dynamic weight matrix.

[0012] The power distribution module triggers the multi-stage coil collaborative heating logic according to the segmented power control instructions, and determines whether to start compensatory heating in adjacent heating sections based on power redundancy and viscosity improvement.

[0013] The closed-loop calibration module obtains the crude oil viscosity data after heating control in the independent heating section, corrects the segmented power control instructions through closed-loop feedback, and outputs the steady-state crude oil results.

[0014] The second aspect of the present invention provides a crude oil electric heating furnace, comprising a crude oil electric heating furnace control system as described in the first aspect of the present invention, wherein each module of the system is implemented by executing a corresponding program by a processor of the crude oil electric heating furnace.

[0015] Compared with the existing technology, the beneficial effects of the present invention are as follows: (1) The present invention constructs a three-dimensional temperature field by collecting the temperature characteristic vectors of the three-dimensionally distributed independent heating sections, combining the ring topology layout and spatial interpolation processing of the thermocouple group, which helps to more comprehensively and accurately reflect the temperature distribution in the heating furnace and provide a reliable data basis for the subsequent crude oil electric heating furnace control.

[0016] (2) The present invention quantifies the degree of thermal inertia imbalance through a dynamic weight matrix, and generates temperature control compensation gain by combining real-time analysis of crude oil viscosity-temperature data. The weight value is corrected through fuzzy similarity matching and historical control effects, dynamically adapting to the nonlinear change of crude oil viscosity with temperature, and optimizing the real-time performance and accuracy of power distribution.

[0017] (3) The present invention proposes a strategy for coordinated heating of the main and auxiliary coils, giving priority to the use of redundant power capacity, and starting compensatory heating in adjacent heating sections when the main and auxiliary power is insufficient. At the same time, thermal balance constraints and deviation monitoring termination conditions are set, which significantly improves the power resource utilization rate of the crude oil electric heating furnace, avoids local overload, and ensures a stable and efficient heating process.

[0018] (4) The present invention uses the viscosity data of the heated crude oil as feedback, combines it with the proportional-integral correction algorithm to dynamically adjust the weight matrix, and iteratively optimizes the segmented power control instructions, so that the viscosity data converges quickly to the preset steady-state range, significantly improving the long-term operation stability of the system and the speed of achieving the control target. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For passengers with ordinary technical skills in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 Schematic diagram of module connection of the system of the present invention.

[0021] Figure 2 The figure is a logical diagram of the temperature feature vector acquisition process in the data acquisition module of the system of the present invention.

[0022] Figure 3 This is a logic diagram of the collaborative heating of multiple coils in the power distribution module of the system of the present invention. DETAILED DESCRIPTION

[0023] The above contents described below in conjunction with the implementation of the present invention are merely examples and explanations of the concept of the present invention. Technical passengers in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall fall within the scope of protection of the present invention.

[0024] See also Figure 1 As shown, the purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present invention provides a crude oil electric heating furnace control system, including: a data acquisition module, a temperature control compensation module, a power distribution module and a closed-loop calibration module.

[0025] The data acquisition module is connected to the temperature control compensation module, the temperature control compensation module is connected to the power distribution module, and the power distribution module is connected to the closed-loop calibration module.

[0026] The data acquisition module collects temperature characteristic vectors of multiple independent heating sections divided into three dimensions of the heating furnace in real time and generates a dynamic weight matrix.

[0027] See also Figure 2As shown, in a preferred embodiment of the present invention, the temperature feature vector acquisition process includes: S1. Embedding a multi-stage thermocouple group into the heating furnace wall in a ring topology structure, and each thermocouple group covers an independent heating section.

[0028] S2. Time-synchronize and align the temperature data of the multi-stage thermocouple group and periodically perform zero-point calibration to eliminate sensor drift errors.

[0029] S3. Perform spatial interpolation processing on the temperature data of multiple thermocouple nodes within the same independent heating section to construct a three-dimensional temperature field, calculate the radial temperature difference change rate and the axial temperature difference change rate of the three-dimensional temperature field within the sliding space window, and generate the temperature gradient intensity of the independent heating section.

[0030] It should be noted that the radial temperature difference change rate of the three-dimensional temperature field in the sliding space window is defined as the temperature change rate per unit distance in the radial direction in the sliding space window, wherein the radial direction specifically refers to the direction extending from the center of the independent heating section to the periphery. The specific calculation process of the radial temperature difference change rate is as follows: multiple radial paths are selected in the sliding space window, and the temperature difference of each adjacent thermocouple node on each radial path is obtained. The ratio of the temperature difference of the adjacent thermocouple nodes to the radial distance between the two nodes is used as the local radial temperature difference change rate. In this way, all local radial temperature difference change rates on each radial path in the sliding space window are counted, and the radial temperature difference change rate of the three-dimensional temperature field in the sliding space window is obtained by double mean calculation.

[0031] The axial temperature difference change rate is defined as the temperature change rate per unit distance in the axial direction within the sliding space window, where the axial direction specifically refers to the direction parallel to the length or height of the crude oil electric heating furnace. The specific calculation process of the axial temperature difference change rate is as follows: select an axial section within the sliding space window, obtain the temperature difference between adjacent section layers, and use the ratio of the temperature difference to the axial distance between the layers as the local axial temperature difference change rate. The local axial temperature difference change rates of all axial sections within the sliding space window are averaged to obtain the axial temperature difference change rate of the three-dimensional temperature field within the sliding space window.

[0032] It should also be noted that the above-mentioned sliding space window usually adopts a cubic or cylindrical structure, and its geometric parameters and moving step are pre-set based on the standard design parameters of the crude oil electric heating furnace in the early stage of system development. Full coverage traversal of the entire independent heating section is achieved through fixed step movement.

[0033] S4. Obtain the average temperature value of the thermocouple group corresponding to each independent heating section in real time, calculate the instantaneous rate of change of the temperature difference between adjacent heating sections within the sliding time window, and generate the heat flow direction coefficient and instability score based on time domain trend analysis.

[0034] It should be noted that the instantaneous rate of change of the temperature difference between the adjacent heating sections within the sliding time window is calculated by substituting the average temperature difference of the thermocouple groups corresponding to the adjacent heating sections at each unit time point in the sliding time window into the first-order difference formula in sequence. Taking independent heating sections A and B as adjacent heating sections as an example, if the instantaneous rate of change of the temperature difference between the adjacent heating sections AB at a unit time point in the sliding time window is greater than 0, it means that the temperature of section A continues to rise relative to section B, and heat is positively concentrated in section A. On the contrary, if it is less than 0, it means that the temperature of section B rises relative to section A, and the direction of heat flow is reversed.

[0035] The process of obtaining the heat flow direction coefficient includes: sorting out the instantaneous change rate sequence of the temperature difference between adjacent heating sections within the sliding time window, and obtaining the slope value of the sequence by linear fitting. Continuing with the above-mentioned adjacent heating section AB example, if the slope value is greater than 0, it means that heat continues to flow to section A, and the heat flow direction coefficient logical label value is assigned to 1. Conversely, if the slope value is less than 0, it means that heat continues to flow to section B, and the heat flow direction coefficient logical label value is assigned to -1. The absolute value of the sequence slope value is normalized according to the preset allowable slope threshold, and the product of the normalized value and the heat flow direction coefficient logical label value is used as the heat flow direction coefficient.

[0036] The process of obtaining the instability score includes: calculating the variance value and range value in the instantaneous change rate sequence of the temperature difference between adjacent heating sections within the sliding time window, performing fast Fourier transform on the instantaneous change rate sequence of the temperature difference to obtain the amplitude ratio of the high-frequency fluctuation component, normalizing the variance value, range value and the amplitude ratio of the high-frequency fluctuation component respectively, and performing weighted fusion based on a preset weight allocation strategy to obtain an instability score, wherein the preset weight allocation strategy is specifically expressed as variance value > range value > amplitude ratio of the high-frequency fluctuation component, which can be exemplified as: 0.5, 0.3, 0.2.

[0037] S5. Combining the temperature gradient intensity, heat flow direction coefficient, and instability score into a temperature feature vector.

[0038] In a preferred embodiment of the present invention, the temperature feature vector performs the following steps to generate a dynamic weight matrix: (a) fuzzy similarity matching is performed on the temperature feature vector of each independent heating section with a preset heat flux distribution pattern library, and the heat flux distribution pattern with the highest similarity is selected as the reference pattern.

[0039] It should be noted that the above-mentioned preset heat flux distribution pattern library is a predefined set of heat flux distribution scenarios. Each pattern contains the standardized temperature gradient intensity, heat flux direction coefficient, and instability score corresponding to the standard numerical range, and each pattern is associated with its corresponding initial weight value, which is mainly based on simulation or historical optimal control data settings.

[0040] The above-mentioned fuzzy similarity matching process includes: defining a corresponding fuzzy membership function for each eigenvalue in the temperature feature vector, using the Euclidean distance formula to quantify the degree of membership of each eigenvalue to a certain pattern, and calculating the mean to obtain the fuzzy similarity between the temperature feature vector and the pattern, wherein the fuzzy membership function can be a triangular function or a Gaussian function.

[0041] (b) extracting the initial weight value of the benchmark mode, and combining it with the mode confidence score in the historical control effect feedback data, and correcting the initial weight value through weighted operation.

[0042] It should be noted that the above-mentioned initial weight value correction process includes: comparing the mode confidence score with the preset mode confidence reasonable score threshold, taking the difference between the two and the pre-calibrated correction coefficient for controlling the adjustment amplitude and the initial weight value for cumulative operation, and the cumulative operation result is the corrected weight part, which is superimposed on the initial weight value to achieve correction.

[0043] (c) Linearly scale the corrected weight values ​​and map them to a preset numerical range to generate a dynamic weight matrix.

[0044] In a preferred embodiment of the present invention, the element values ​​of the dynamic weight matrix are used to characterize the degree of thermal inertia imbalance of the corresponding independent heating section. If the element value is greater than or equal to a first preset threshold, it is determined to be a thermal inertia overload state and power compensation is triggered. If it is less than or equal to a second preset threshold, it is determined to be a thermal inertia underload state and power suppression is triggered. If it is between the first and second preset thresholds, the current power input is maintained.

[0045] This embodiment constructs a three-dimensional temperature field by collecting temperature feature vectors of independent heating sections with three-dimensional distribution, combining the annular topology layout of the thermocouple group and spatial interpolation processing. This helps to more comprehensively and accurately reflect the temperature distribution in the heating furnace, and provides a reliable data basis for subsequent crude oil electric heating furnace control.

[0046] The temperature control compensation module synchronously receives the viscosity-temperature combination data of the crude oil in the independent heating section, generates a temperature control compensation gain based on the characteristic analysis of the crude oil viscosity changing with temperature, and outputs a segmented power control instruction in combination with a dynamic weight matrix.

[0047] In a preferred embodiment of the present invention, the logic for generating the temperature control compensation gain includes: integrating the viscosity-temperature combination data in a receiving time sequence to obtain a viscosity-temperature fitting curve.

[0048] A temperature domain with the current temperature value of the independent heating section as the center position is retrieved, and based on a preset standard mapping relationship between crude oil viscosity and temperature, a relative viscosity deviation ratio of each temperature value point in the temperature domain is obtained.

[0049] It should be noted that the specific calculation process of the above relative viscosity deviation ratio is: subtract the monitored viscosity value corresponding to the temperature value point from the preset standard mapping viscosity value corresponding to the temperature value, and further compare the difference with the preset standard mapping viscosity value corresponding to the temperature value.

[0050] The relative viscosity deviation ratio is weighted and fused according to the preset weight rule to obtain the dynamic compensation factor of the temperature domain. .

[0051] It should be noted that the above preset weight rule is that the weight of each temperature value point in the temperature domain is inversely proportional to its distance from the center temperature value, that is: the closer to the center temperature value point, the greater the weight, the farther from the center temperature value point, the smaller the weight, the center temperature value point has the largest weight, and the sum of the weights of all temperature value points is strictly equal to 1. The specific distribution weight can be calculated by applying the attenuation exponential function.

[0052] Substituting the dynamic compensation factor into the formula Get the temperature control compensation gain, where The pre-calibrated unit temperature deviation corresponds to the reference compensation power. They are the preset proportional coefficient and integral coefficient respectively.

[0053] It should be noted that the above temperature control compensation gain calculation formula structure can be specifically decomposed into: proportional term , integral item and the reference gain term , where the proportional term is used to quickly generate the compensation gain based on the real-time value of the current dynamic compensation factor, the integral term is used to accumulate historical compensation requirements and eliminate steady-state errors, and the reference gain term is used to map the output of the proportional and integral terms to the actual unit temperature deviation corresponding to the compensation power unit to ensure that the compensation gain matches the actual heating demand. It is obtained by iterative optimization based on the trial-and-error method with the goals of fast response without significant overshoot, elimination of steady-state error and non-saturation of integration.

[0054] In a preferred embodiment of the present invention, the step-by-step power control instruction output process includes: obtaining a curvature value of a current temperature value of an independent heating section on the viscosity-temperature fitting curve.

[0055] The deviation value between the current viscosity value of the crude oil in the independent heating section and the preset steady-state flow benchmark viscosity range of the crude oil is obtained, and the ratio of the deviation value to the curvature value is further used as the control temperature value.

[0056] The product of the control temperature value and the temperature compensation gain is used as the basic control power. The independent heating segments are combined with the corresponding element values ​​of the dynamic weight matrix to perform adaptive adjustment on the basic control power to determine the final control power and control direction, thereby outputting the segmented power control instructions.

[0057] It should be noted that the above adaptive adjustment execution process is as follows: if the basic control power is greater than 0, the control direction is determined to be power increase, and the excess ratio of the corresponding element value of the independent heating section in the dynamic weight matrix relative to the first preset threshold is obtained. , and the ratio of basic control power to the current heating power of the independent heating section ,like , maintain the original basic control power, if , then As the upper limit, the current heating power of the independent heating section is The product of is used as the basic control power value.

[0058] Similarly, if the basic control power is less than 0, the control direction is determined to be power reduction, and the absolute deviation ratio of the corresponding element value of the independent heating section in the dynamic weight matrix relative to the second preset threshold is obtained, as well as the ratio of the basic control power relative to the current heating power of the independent heating section. The two ratios are compared to achieve adaptive adjustment of the basic control power.

[0059] The embodiment of the present invention quantifies the degree of thermal inertia imbalance through a dynamic weight matrix and generates temperature control compensation gains based on real-time analysis of crude oil viscosity-temperature data. The weight values ​​are corrected through fuzzy similarity matching and historical control effects, dynamically adapting to the nonlinear changes in crude oil viscosity with temperature and optimizing the real-time and accuracy of power distribution.

[0060] The power distribution module triggers the multi-stage coil cooperative heating logic according to the segmented power control instruction, and determines whether to start compensatory heating in adjacent heating sections based on power redundancy and viscosity improvement.

[0061] See also Figure 3 As shown, in a preferred embodiment of the present invention, the multi-stage coil collaborative heating logic includes: detecting the current power and redundant power capacity of the main coil and the auxiliary coil based on the control power value and control direction in the segmented power control instruction of the independent heating section.

[0062] When the control direction is power increase, the redundant power capacity of the primary coil is preferentially allocated to perform power increase. If the redundant power capacity of the primary coil is insufficient, the redundant power capacity of the auxiliary coil is added.

[0063] When the control direction is power reduction, the current power output of the auxiliary coil is reduced first. If the power of the auxiliary coil still needs to be reduced after it drops to zero, the current power output of the main coil is reduced.

[0064] In a preferred embodiment of the present invention, the adjacent heating section compensatory heating start determination process is as follows: when the control direction is power increase, if the redundant power capacity of the main and auxiliary coils is insufficient, or the crude oil viscosity improvement rate of the independent heating section does not reach the preset standard within the preset duration, then it is determined to start the adjacent heating section compensatory heating.

[0065] The adjacent heating sections calculate the remaining power carrying capacity of the main and auxiliary coils based on their segmented power control instructions , and determine the upper limit of compensation power of adjacent heating sections based on thermal balance constraints, and call them according to the main and auxiliary priority order.

[0066] It should be noted that the upper limit of the compensation power of adjacent heating sections determined based on the thermal balance constraint can be converted into the formula ,in It is derived from Fourier's law based on the relationship between power and temperature difference, material heat conduction characteristics and geometric parameters in thermodynamics. It is the preset allowable temperature difference threshold between adjacent heating zones. In order to integrate the equivalent heat transfer coefficient of the heat transfer area and heat transfer path length of adjacent heating sections, the numerical calculation process is as follows: the preset standard heat transfer coefficient between adjacent heating sections is multiplied by the heat transfer area of ​​the adjacent heating sections, and the product is further compared with the heat transfer path length.

[0067] During the call, the temperature changes inside the adjacent heating sections are monitored in real time. If the temperature value is detected to exceed the preset allowable deviation compared with the segmented power control instruction, the compensatory heating is terminated.

[0068] The embodiment of the present invention proposes a collaborative heating strategy for the main and auxiliary coils, giving priority to the use of redundant power capacity, and starting compensatory heating in adjacent heating sections when the main and auxiliary power are insufficient. At the same time, thermal balance constraints and deviation monitoring termination conditions are set, which significantly improves the power resource utilization rate of the crude oil electric heating furnace, avoids local overload, and ensures a stable and efficient heating process.

[0069] The closed-loop calibration module obtains crude oil viscosity data after heating control of the independent heating section, corrects the segmented power control instructions through closed-loop feedback, and outputs a steady-state crude oil result.

[0070] In a preferred embodiment of the present invention, the closed-loop feedback correction process of the segmented power control command includes: obtaining the deviation between the crude oil viscosity data after heating control and its target viscosity data.

[0071] The weight matrix element values ​​are dynamically adjusted based on the proportional-integral correction algorithm, and the segmented power control instructions are recalculated according to the corrected weight matrix element values ​​and viscosity deviation.

[0072] The crude oil viscosity data is converged to the preset steady-state range through iterative optimization.

[0073] The embodiment of the present invention uses the feedback of crude oil viscosity data after heating, combines it with a proportional-integral correction algorithm to dynamically adjust the weight matrix, and iteratively optimizes the segmented power control instructions, so that the viscosity data quickly converges to a preset steady-state range, significantly improving the long-term stability of the system and the speed of achieving control targets.

[0074] The second aspect of the present invention provides a crude oil electric heating furnace, comprising a crude oil electric heating furnace control system as described in the first aspect of the present invention, wherein each module of the system is implemented by executing a corresponding program by a processor of the crude oil electric heating furnace.

[0075] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0076] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0077] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0078] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0079] 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 changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0080] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A crude oil electric heating furnace control system, characterized in that: include: The data acquisition module collects the temperature characteristic vectors of multiple independent heating sections divided into three dimensions of the heating furnace in real time and generates a dynamic weight matrix; The temperature control compensation module synchronously receives the viscosity-temperature combination data of crude oil in the independent heating section, generates temperature control compensation gain based on the characteristic analysis of crude oil viscosity change with temperature, and outputs segmented power control instructions based on the dynamic weight matrix; The power distribution module triggers the multi-stage coil collaborative heating logic according to the segmented power control instructions, and determines whether to start compensatory heating in adjacent heating sections based on power redundancy and viscosity improvement; The closed-loop calibration module obtains the crude oil viscosity data after heating control in the independent heating section, corrects the segmented power control instructions through closed-loop feedback, and outputs the steady-state crude oil results; The temperature characteristic vector acquisition process includes: S1. embedding a multi-stage thermocouple group into the heating furnace wall in a ring topology structure, with each thermocouple group correspondingly covering an independent heating section; S2. Time-synchronize and align the temperature data of the multi-stage thermocouple group and periodically perform zero-point calibration to eliminate sensor drift errors; S3. Perform spatial interpolation processing on the temperature data of multiple thermocouple nodes in the same independent heating section to construct a three-dimensional temperature field, calculate the radial temperature difference change rate and the axial temperature difference change rate of the three-dimensional temperature field within the sliding spatial window, and generate the temperature gradient intensity of the independent heating section; S4. Obtain the average temperature value of the thermocouple group corresponding to each independent heating section in real time, calculate the instantaneous rate of change of the temperature difference between adjacent heating sections within the sliding time window, and generate the heat flow direction coefficient and instability score based on time domain trend analysis; S5. Combining the temperature gradient intensity, heat flow direction coefficient and instability score into a temperature feature vector; The generation logic of the temperature control compensation gain includes: integrating the viscosity-temperature combination data in the order of receiving time and obtaining a viscosity-temperature fitting curve; Retrieving a temperature domain centered on the current temperature value of the independent heating section, and obtaining a relative viscosity deviation ratio of each temperature value point within the temperature domain based on a preset standard mapping relationship between crude oil viscosity and temperature; The relative viscosity deviation ratio is weighted and fused according to the preset weight rule to obtain the dynamic compensation factor of the temperature domain. ; The Substitute into the formula Get the temperature control compensation gain, where The pre-calibrated unit temperature deviation corresponds to the reference compensation power. They are the preset proportional coefficient and integral coefficient respectively; The step-by-step power control instruction output process includes: obtaining a curvature value of a current temperature value of an independent heating section on the viscosity-temperature fitting curve; Obtaining a deviation between the current viscosity of the crude oil in the independent heating section and a preset steady-state flow benchmark viscosity range of the crude oil, and further using the ratio of the current viscosity to the curvature value as the control temperature value; The product of the control temperature value and the temperature compensation gain is used as the basic control power. The independent heating segments are combined with the corresponding element values ​​of the dynamic weight matrix to perform adaptive adjustment on the basic control power to determine the final control power and control direction, thereby outputting the segmented power control instructions.

2. The crude oil electric heating furnace control system according to claim 1, characterized in that: The temperature feature vector performs the following steps to generate a dynamic weight matrix: (a) performing fuzzy similarity matching between the temperature feature vector of each independent heating section and a preset heat flux distribution pattern library, and selecting the heat flux distribution pattern with the highest similarity as the reference pattern; (b) extracting the initial weight value of the baseline mode, and modifying the initial weight value through weighted calculation in combination with the mode confidence score in the historical control effect feedback data; (c) Linearly scale the corrected weight values ​​and map them to a preset numerical range to generate a dynamic weight matrix.

3. The crude oil electric heating furnace control system according to claim 2, characterized in that: The element values ​​of the dynamic weight matrix are used to characterize the degree of thermal inertia imbalance of the corresponding independent heating section. If the element value is greater than or equal to the first preset threshold, it is determined to be a thermal inertia overload state and power compensation is triggered. If it is less than or equal to the second preset threshold, it is determined to be a thermal inertia underload state and power suppression is triggered. If it is between the first and second preset thresholds, the current power input is maintained.

4. The crude oil electric heating furnace control system according to claim 1, characterized in that: The multi-stage coil cooperative heating logic includes: detecting the current power and redundant power capacity of the main coil and the auxiliary coil based on the control power value and control direction in the segmented power control instructions of the independent heating sections; When the control direction is power increase, the redundant power capacity of the main coil is preferentially allocated to perform power increase. If the redundant power capacity of the main coil is insufficient, the redundant power capacity of the auxiliary coil is added; When the control direction is power reduction, the current power output of the auxiliary coil is reduced first. If the power of the auxiliary coil still needs to be reduced after it drops to zero, the current power output of the main coil is reduced.

5. The crude oil electric heating furnace control system according to claim 4, characterized in that: The adjacent heating section compensatory heating start determination process: when the control direction is power increase, if the redundant power capacity of the main and auxiliary coils is insufficient, or the crude oil viscosity improvement rate of the independent heating section does not meet the preset standard within the preset duration, then it is determined to start the adjacent heating section compensatory heating; Adjacent heating sections calculate the remaining power carrying capacity of the main and auxiliary coils based on their segmented power control instructions, and determine the upper limit of the compensation power of adjacent heating sections based on the thermal balance constraint, and call them according to the main and auxiliary priority order; During the call, the temperature changes inside the adjacent heating sections are monitored in real time. If the temperature value is detected to exceed the preset allowable deviation compared with the segmented power control instruction, the compensatory heating is terminated.

6. The crude oil electric heating furnace control system according to claim 1, characterized in that: The closed-loop feedback correction process of the segmented power control instruction includes: Obtain the deviation between the crude oil viscosity data after heating control and its target viscosity data; Dynamically adjust the weight matrix element values ​​based on the proportional-integral correction algorithm, and recalculate the segmented power control instructions based on the corrected weight matrix element values ​​and viscosity deviation; The crude oil viscosity data is converged to the preset steady-state range through iterative optimization.

7. A crude oil electric heating furnace, characterized in that: It comprises a crude oil electric heating furnace control system as claimed in any one of claims 1 to 6, wherein each module of the system is implemented by executing a corresponding program by a processor of the crude oil electric heating furnace.

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