Indirect electric heating safety interlocking control method and device

Abstract

The invention discloses an indirect electric heating safety interlocking control method and device, and relates to the technical field of heating equipment. The method comprises the following steps: carrying out heat supply analysis in combination with an application scene of the heat-conducting oil furnace, determining a salt bath temperature threshold value, executing proportion optimization of a multi-element mixed salt bath, and determining an optimal salt bath proportion scheme; according to the optimal salt bath proportioning scheme, equipment salt filling is conducted on the heat conduction oil furnace, and a target heat conduction oil furnace is obtained; performing sensing monitoring on the predetermined part to obtain a real-time monitoring data set; and the real-time monitoring data set is judged according to a preset early warning threshold value, and based on a judgment result, safety control is conducted on the target heat conduction oil furnace according to a preset interlocking control scheme. The technical problem that in the prior art, safety and stability are low in the operation process of the heat conduction oil furnace is solved, timely early warning and automatic safety regulation and control are achieved through real-time monitoring and intelligent interlocking control, and the technical effect of improving the operation safety and stability of the heat conduction oil furnace is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of heating equipment, and in particular to a safety interlocking control method and device for indirect electric heating. Background Art

[0002] In the field of industrial heating, thermal oil furnaces are widely used in various processes that require high-temperature heating as an efficient and energy-saving heating equipment. Thermal oil furnaces heat the thermal oil and transfer heat energy to the materials that need to be heated, thereby achieving the purpose of heating. However, with the expansion of industrial production scale and the improvement of process requirements, the safety and stability issues of thermal oil furnaces have become increasingly prominent. Traditional thermal oil furnace control systems mostly use simple temperature monitoring and control methods, lacking intelligent early warning and interlocking protection mechanisms. Once abnormal conditions occur during the operation of the thermal oil furnace, such as excessive temperature and abnormal pressure, it is often difficult to detect and effectively handle them in time, which may cause safety accidents. Summary of the invention

[0003] The present application provides a safety interlock control method and device for indirect electric heating, which solves the technical problem of low safety and stability during the operation of a thermal oil furnace in the prior art.

[0004] In view of the above problems, the present application provides an indirect electric heating safety interlock control method and device.

[0005] In a first aspect of the present application, a safety interlock control method for indirect electric heating is provided, the method comprising: A heat supply analysis is performed in combination with the application scenario of the thermal oil furnace to determine the salt bath temperature threshold, and a multi-component mixed salt bath ratio optimization is performed according to the salt bath temperature threshold to determine the optimal salt bath ratio scheme; according to the optimal salt bath ratio scheme, the thermal oil furnace is filled with salt to obtain a target thermal oil furnace, and when the target thermal oil furnace is working, a multi-source sensor monitoring network is used to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set; the real-time monitoring data set is judged according to a predetermined early warning threshold, and based on the judgment result, the target thermal oil furnace is safely controlled according to a predetermined interlocking control scheme.

[0006] A second aspect of the present application provides an indirect electric heating safety interlock control device, the device comprising: An analysis module, wherein the analysis module is used to perform heat supply analysis in combination with an application scenario of the thermal oil furnace, determine a salt bath temperature threshold, perform ratio optimization of a multi-component mixed salt bath according to the salt bath temperature threshold, and determine an optimal salt bath ratio scheme; a monitoring module, wherein the monitoring module is used to charge the thermal oil furnace with salt according to the optimal salt bath ratio scheme to obtain a target thermal oil furnace, and when the target thermal oil furnace is working, use a multi-source sensor monitoring network to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set; a control module, wherein the control module is used to judge the real-time monitoring data set according to a predetermined early warning threshold, and based on the judgment result, perform safety control on the target thermal oil furnace according to a predetermined interlocking control scheme.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, a heat supply analysis is conducted in combination with the application scenario of the thermal oil furnace to determine the salt bath temperature threshold. The multi-component mixed salt bath ratio optimization is performed according to the salt bath temperature threshold to determine the optimal salt bath ratio scheme. Then, according to the optimal salt bath ratio scheme, the thermal oil furnace is filled with salt to obtain the target thermal oil furnace. When the target thermal oil furnace is working, the multi-source sensor monitoring network is used to perform sensor monitoring on the predetermined components to obtain a real-time monitoring data set. Finally, the real-time monitoring data set is judged according to the predetermined early warning threshold, and based on the judgment result, the target thermal oil furnace is safely controlled according to the predetermined interlocking control scheme. The technical problem of low safety and stability during the operation of the thermal oil furnace in the prior art is solved. Through real-time monitoring and intelligent interlocking control, timely early warning and automatic safety regulation are achieved, and the technical effect of improving the safety and stability of the operation of the thermal oil furnace is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] 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.

[0009] Figure 1 A schematic flow chart of an indirect electric heating safety interlock control method provided in an embodiment of the present application; Figure 2 A schematic structural diagram of an indirect electric heating safety interlock control device provided in an embodiment of the present application.

[0010] Description of the accompanying drawings: analysis module 11, monitoring module 12, control module 13. DETAILED DESCRIPTION

[0011] The present application solves the technical problem of low safety and stability during the operation of a thermal oil furnace in the prior art by providing an indirect electric heating safety interlock control method and device.

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0013] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0014] Embodiment 1, as Figure 1 As shown, the present application provides an indirect electric heating safety interlock control method, wherein the method includes: A heat supply analysis is performed in combination with the application scenario of the thermal oil furnace to determine the salt bath temperature threshold, and the ratio optimization of the multi-component mixed salt bath is performed according to the salt bath temperature threshold to determine the optimal salt bath ratio scheme.

[0015] The thermal oil furnace includes a heat storage tank, an electric heater, a salt bath, thermal oil, and a heat exchanger. A comprehensive heat supply analysis is conducted based on the specific application scenarios of the thermal oil furnace (such as different types of heating requirements in industrial production) to determine the heat conduction requirements of the thermal oil furnace under different working conditions; based on the results of the heat supply analysis, the appropriate salt bath temperature threshold is determined (usually set with reference to industry standards and actual operating data). Different application scenarios may require different temperature thresholds to adapt to the corresponding heat conduction characteristics. According to the required temperature threshold, select a suitable combination of salts, such as nitrates, chlorides, or sulfates, to form a multi-component mixed salt bath; according to relevant information, set the initial multi-component mixed salt bath ratio, and verify the heating effect, stability, and cost-effectiveness of the initial ratio through experiments. According to the experimental results, adjust the ratio, optimize the salt bath performance, and repeat the experimental verification until the optimal salt bath ratio is found.

[0016] Furthermore, performing the ratio optimization of the multi-component mixed salt bath according to the salt bath temperature threshold to determine the optimal salt bath ratio scheme includes: The adaptive salt bath melting point is set according to the salt bath temperature threshold, and the adaptive salt bath type is selected according to the adaptive salt bath melting point, wherein the salt bath type includes multi-component mixed chloride salt and multi-component mixed nitrate salt; in order to meet the salt bath temperature threshold and the adaptive salt bath melting point, the ratio optimization of the multi-component mixed salt bath is performed according to the adaptive salt bath type, and the optimal salt bath ratio scheme is output.

[0017] Specifically, according to the determined salt bath temperature threshold, a corresponding salt bath melting point is set to ensure that the selected salt bath operates stably within the expected operating temperature range; when the melting point of the adapted salt bath is not less than 500 degrees Celsius, a multi-component mixed chloride salt is selected as the adapted salt bath type, and the multi-component mixed chloride salt includes barium chloride (BaCl2), sodium chloride (NaCl) and potassium chloride (KCl); when the melting point of the adapted salt bath is lower than 500 degrees Celsius, a multi-component mixed nitrate is selected as the adapted salt bath type, and the multi-component mixed nitrate includes potassium nitrate (KNO3), sodium nitrate (NaNO3) and sodium nitrite (NaNO2).

[0018] The ratio of the multi-component mixed salt bath is optimized with the goal of meeting the salt bath temperature threshold and adapting to the salt bath melting point. Specifically, an optimization algorithm (such as genetic algorithm or linear programming) is used to iteratively solve the salt ratio to ensure that the final ratio meets the thermodynamic requirements under the set conditions and avoids phase separation or physical property instability; based on the optimization results, the optimal salt bath ratio that meets the salt bath temperature threshold and adapts to the melting point requirements is output.

[0019] Exemplarily, as shown in Table 1, the salt formula for commonly used salt baths, the multi-component mixed salt can adjust the melting point by adjusting the proportion of different components to adapt to different heating and energy storage temperatures.

[0020] Table 1

[0021] Furthermore, performing the ratio optimization of the multi-component mixed salt bath according to the adapted salt bath type and outputting the optimal salt bath ratio scheme includes: Acquire multiple proportion thresholds of the adapted salt bath type, and randomly generate a first salt bath ratio scheme within the multiple proportion thresholds; input the first salt bath ratio scheme into a salt bath temperature identifier, and output a first predicted temperature threshold and a first predicted melting point, wherein the salt bath temperature identifier is constructed based on the principle of ensemble learning; based on the salt bath temperature threshold and the adapted salt bath melting point, perform deviation calculation on the first predicted temperature threshold and the first predicted melting point to obtain a first deviation calculation result; use a scheme fitness evaluation function to determine the fitness of the first scheme according to the first deviation calculation result; continue to perform random scheme selection and fitness calculation within the multiple proportion thresholds until the convergence times are met, and output the salt bath ratio scheme with the largest fitness as the optimal salt bath ratio scheme.

[0022] Specifically, for the selected adaptive salt bath type (such as multi-component mixed chloride salt or multi-component mixed nitrate salt), obtain the proportion threshold of each component salt; according to the obtained proportion threshold, randomly generate an initial salt bath ratio scheme (first salt bath ratio scheme), ensure that the sum of the salt bath ratios in the ratio scheme is 1 to meet the ratio requirements; based on the principle of ensemble learning (such as random forest, gradient boosting tree, etc.), construct a salt bath temperature identifier, and the salt bath temperature identifier predicts the temperature threshold and melting point of the salt bath by inputting the salt bath ratio; use sample data with known ratios and corresponding temperature thresholds and melting points to train the salt bath temperature identifier until the model converges, that is, the difference between the predicted result and the actual value reaches an acceptable range; input the generated first salt bath ratio scheme into the trained salt bath temperature identifier, and output the predicted temperature threshold and melting point; with the salt bath temperature threshold and the adapted salt bath melting point as the benchmark, perform deviation calculation on the predicted temperature threshold and melting point to obtain the first deviation calculation result; use the scheme fitness evaluation function to determine the first scheme fitness of the first salt bath ratio scheme according to the first deviation calculation result; continue to randomly select salt bath ratios within multiple proportion thresholds to generate new ratio schemes; for each newly generated ratio scheme, repeat the above steps of prediction, calculation and determination of fitness; record the scheme with the highest fitness in each iteration, and update the optimal scheme; set a convergence number or convergence condition (such as the fitness improvement is less than a certain threshold) to determine whether the iterative process is over; when the convergence number is reached or the convergence condition is met, stop the iteration; output the salt bath ratio scheme with the largest fitness as the optimal scheme.

[0023] Based on the principle of ensemble learning, the salt bath temperature identifier is constructed. When the random forest model is used, specifically, a large amount of sample data of known salt bath ratio schemes is collected. These samples include the ratios of different salt combinations, the actual measured temperature thresholds and melting points; randomly extract training set samples (using the Bootstrap sampling method, the training samples of each tree are randomly selected with replacement); when each tree selects a split node, it randomly selects some features to determine the optimal split point; repeat the above steps until a specified number of decision trees are constructed; for the input salt bath ratio scheme, each tree of the random forest model outputs a predicted temperature threshold and predicted melting point; the final prediction result is obtained by voting (classification problem) or averaging (regression problem) the outputs of each decision tree. Use the data in the training set to train each decision tree so that it can output the corresponding predicted temperature threshold and melting point under a given input; according to the performance of the model, optimize the model performance by adjusting the number of decision trees, the depth of the tree, the minimum number of split samples and other hyperparameters; after training, the salt bath temperature identifier is obtained.

[0024] Furthermore, a scheme fitness evaluation function is constructed, including: ; Among them, RTE is the fitness of the solution, is the temperature threshold weight, is the melting point weight, Characterizes the overlap between the predicted temperature threshold and the salt bath temperature threshold, m is the intersection of the predicted temperature threshold and the salt bath temperature threshold, M is the salt bath temperature threshold, S is the adapted salt bath melting point, and s is the predicted melting point.

[0025] Preferably, a scheme fitness evaluation function is constructed to evaluate the effect of the generated salt bath ratio scheme, wherein RTE identifies the scheme fitness and evaluates the extent to which the scheme meets the salt bath temperature threshold and melting point requirements. is the temperature threshold weight, is the melting point weight, Characterizes the overlap between the predicted temperature threshold and the salt bath temperature threshold, m is the intersection of the predicted temperature threshold and the salt bath temperature threshold, M is the salt bath temperature threshold, S is the adapted salt bath melting point, and s is the predicted melting point. By substituting the predicted temperature threshold and melting point of the generated salt bath ratio scheme into the fitness function, the RTE value of the scheme is calculated. The higher the RTE value, the better the scheme is in meeting the salt bath temperature threshold and melting point adaptation requirements. Using RTE as the evaluation criterion, the generated different ratio schemes are sorted and selected. During multiple iterations and optimization processes, the RTE values ​​of each scheme are compared to select the scheme with the highest fitness as the optimal salt bath ratio scheme.

[0026] According to the optimal salt bath ratio scheme, the thermal oil furnace is filled with salt to obtain a target thermal oil furnace, and when the target thermal oil furnace is working, a multi-source sensor monitoring network is used to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set.

[0027] According to the optimal salt bath ratio scheme, the thermal oil furnace is filled with salt to complete the target thermal oil furnace preparation after salt filling. For example, about 16m of mixed salt of 50% potassium nitrate + 50% potassium nitrite is prepared. 3 ; Open the salt injection port of the thermal oil furnace, and start adding solid salt from the salt injection port closest to the electric heater; in the process of injecting salt, pay attention to the height of the salt surface; when the upper surface of the salt exceeds the upper surface of the uppermost coil by about 100mm, turn on the electric heater to make the solid salt begin to melt. The melting point of molten salt is 142℃. When this temperature is reached, the salt begins to gradually turn into liquid; when the temperature meter on the furnace body shows 150℃, you can start the burner to continue heating the thermal oil furnace to ensure that the salt bath temperature reaches the set working threshold.

[0028] Various types of sensors, including temperature sensors, pressure sensors, flow sensors, and liquid level sensors, are arranged at key components of the thermal oil furnace (such as the heat storage tank, electric heater, salt bath, and thermal oil pipeline); the sensors are located at various key nodes to obtain comprehensive data, such as the liquid level of the heat storage tank, the operating temperature of the electric heater, the melting state of the salt bath, and the flow rate of the thermal oil. When the target thermal oil furnace is running, the heat storage tank, electric heater, salt bath, and thermal oil are monitored by sensors with the help of a multi-source sensor monitoring network to collect real-time monitoring data sets.

[0029] Furthermore, when the target thermal oil boiler is working, a multi-source sensor monitoring network is used to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set, including: The predetermined components include a heat storage tank, an electric heater, a salt bath and heat transfer oil of a target thermal oil furnace; a multi-source sensor monitoring network is configured, wherein the multi-source sensor monitoring network at least includes an electric heating element temperature monitoring array, a heat transfer oil temperature monitoring array, a heat transfer oil pressure monitoring array, a heat transfer oil quantity monitoring array, a salt bath temperature monitoring array, a heat storage tank temperature monitoring array and a fire monitoring sensor, wherein the temperature monitoring array includes a number of evenly distributed temperature sensors; the multi-source sensor monitoring network is used to perform sensor monitoring on the heat storage tank, the electric heater, the salt bath and the heat transfer oil respectively to obtain a real-time monitoring data set.

[0030] Specifically, a multi-source sensor monitoring network is established and configured to cover the thermal oil furnace and its key components. The multi-source sensor monitoring network at least includes an electric heating element temperature monitoring array (used to monitor the temperature of the electric heater), a thermal oil temperature monitoring array (used to monitor the temperature distribution of the thermal oil in different pipelines and containers), a thermal oil pressure monitoring array (used to monitor the pressure of the thermal oil in real time), a thermal oil volume monitoring array (used to detect the liquid level and flow of the thermal oil), a salt bath temperature monitoring array (monitoring the temperature of the salt bath to ensure that it remains within the working range), a heat storage tank temperature monitoring array (used to monitor the uniformity and changes of the temperature in the heat storage tank) and a fire monitoring sensor (used to monitor the fire hazards of the thermal oil furnace and its surroundings to provide additional safety protection). Among them, the temperature monitoring array is composed of a number of evenly distributed temperature sensors to ensure comprehensive monitoring of temperature changes in different parts.

[0031] Start the multi-source sensor monitoring network, and use each array and sensor to collect real-time data. Each array and sensor is responsible for data collection at its specific location. The electric heating element temperature monitoring array monitors the heating status and temperature changes of the electric heater in real time; the thermal oil temperature monitoring array collects the temperature data of the thermal oil at different pipeline nodes to ensure that the thermal oil remains within the set temperature range during operation; the thermal oil pressure monitoring array records the pressure of the thermal oil system and detects whether there are abnormal pressure fluctuations; the thermal oil oil quantity monitoring array ensures that the liquid level and flow of the thermal oil are within the operating standard to prevent insufficient or excessive oil from affecting equipment performance; the salt bath temperature monitoring array continuously monitors the salt bath temperature to ensure that the salt bath maintains a stable heat transfer effect; the heat storage tank temperature monitoring array ensures that the heat in the heat storage tank is evenly distributed to avoid local overheating or overcooling; the fire monitoring sensor monitors possible fire risks in real time and provides early warnings to protect equipment and the environment. Collect real-time data from all sensors to form a complete real-time monitoring data set, which includes temperature, pressure, liquid level, flow, and fire monitoring information.

[0032] Furthermore, the thermal oil furnace includes a heat storage tank, an electric heater, a salt bath, thermal oil and a heat exchanger, wherein the electric heater is used to heat the salt bath, the salt bath is used to heat the thermal oil, and the thermal oil transfers heat through the heat exchanger.

[0033] When the target thermal oil furnace is working, the electric heater is started, and the salt bath is heated for the first time through the electric heating element, and the salt bath is heated to its operating temperature range; the heated salt bath is used as a heat transfer medium to heat the thermal oil for the second time, and the thermal oil absorbs heat through heat exchange with the high-temperature salt bath, so that its temperature rises to the required operating temperature; the thermal oil heated by the salt bath flows through the heat exchanger and transfers the heat to the equipment or medium that needs to be heated. In short, the use of indirect heating, that is, uniformly heating the thermal oil through a heat medium (such as a salt bath or a low-temperature heat conductor), can effectively avoid direct contact between the electric heating element and the thermal oil, and reduce the coking and cracking problems of the thermal oil caused by local high temperature.

[0034] The real-time monitoring data set is judged according to a predetermined early warning threshold, and based on the judgment result, the target thermal oil furnace is safely controlled according to a predetermined interlocking control scheme.

[0035] According to the operation standards and safety requirements of the thermal oil boiler, the warning thresholds of each key parameter (such as temperature, pressure, flow, etc.) are pre-set. These thresholds are defined based on historical operation data, equipment specifications and industry safety standards. The real-time monitoring data set obtained by the multi-source sensor monitoring network is compared with the warning threshold. Once the data exceeds the set threshold range, it is considered a potential risk; after identifying the abnormal situation, the automated response measures are executed according to the pre-set interlocking control scheme. For example, Table 2 is an interlocking control scheme.

[0036] Table 2

[0037] Furthermore, judging the real-time monitoring data set according to a predetermined warning threshold value also includes: A heat transfer oil temperature data set and a salt bath temperature data set are selected from the real-time monitoring data set; mean calculation is performed on the heat transfer oil temperature data set and the salt bath temperature data set respectively to obtain a heat transfer oil temperature mean and a salt bath temperature mean; with the heat transfer oil temperature mean and the salt bath temperature mean as a reference, deviation calculation is performed on the heat transfer oil temperature data set and the salt bath temperature data set, and mean calculation is performed on the deviation calculation results to obtain a heat transfer oil temperature difference coefficient and a salt bath temperature difference coefficient; if the heat transfer oil temperature difference coefficient is greater than a predetermined heat transfer oil temperature difference scalar and / or the salt bath temperature difference coefficient is greater than a predetermined salt bath oil temperature difference scalar, an equipment alarm signal is generated.

[0038] Preferably, in the real-time monitoring data set, a heat transfer oil temperature data set and a salt bath temperature data set are selected; the heat transfer oil temperature data set is calculated to obtain the mean value of the heat transfer oil temperature for evaluating the overall temperature state of the heat transfer oil; the salt bath temperature data set is calculated to obtain the mean value of the salt bath temperature for evaluating the overall temperature state of the salt bath; taking the mean value of the heat transfer oil temperature as a reference, the deviation of each data point in the heat transfer oil temperature data set from the mean is calculated to obtain a set of deviation values ​​of the heat transfer oil temperature; taking the mean value of the salt bath temperature as a reference, the deviation of each data point in the salt bath temperature data set from the mean is calculated to obtain a set of deviation values ​​of the salt bath temperature; the set of deviation values ​​of the heat transfer oil temperature is averaged. Calculate the heat transfer oil temperature difference coefficient to obtain the overall fluctuation degree of the heat transfer oil temperature; calculate the mean of the salt bath temperature deviation value set to obtain the salt bath temperature difference coefficient to characterize the overall fluctuation degree of the salt bath temperature; judge whether the heat transfer oil temperature difference coefficient is greater than the predetermined heat transfer oil temperature difference scalar, if it is greater than the scalar, it means that the heat transfer oil temperature fluctuation exceeds the safety range; judge whether the salt bath temperature difference coefficient is greater than the predetermined salt bath temperature difference scalar, if it is greater than the scalar, it means that the salt bath temperature fluctuation exceeds the safety range; if the heat transfer oil temperature difference coefficient and / or the salt bath temperature difference coefficient exceed their respective predetermined scalars, an equipment alarm signal is generated to prompt the operator to pay attention to the abnormal temperature and make necessary inspections or adjustments.

[0039] In summary, the embodiments of the present application have at least the following technical effects: First, a heat supply analysis is conducted in combination with the application scenario of the thermal oil furnace to determine the salt bath temperature threshold. The multi-component mixed salt bath ratio optimization is performed according to the salt bath temperature threshold to determine the optimal salt bath ratio scheme. Then, according to the optimal salt bath ratio scheme, the thermal oil furnace is filled with salt to obtain the target thermal oil furnace. When the target thermal oil furnace is working, the multi-source sensor monitoring network is used to perform sensor monitoring on the predetermined components to obtain a real-time monitoring data set. Finally, the real-time monitoring data set is judged according to the predetermined early warning threshold, and based on the judgment result, the target thermal oil furnace is safely controlled according to the predetermined interlocking control scheme. The technical problem of low safety and stability during the operation of the thermal oil furnace in the prior art is solved. Through real-time monitoring and intelligent interlocking control, timely early warning and automatic safety regulation are achieved, and the technical effect of improving the safety and stability of the operation of the thermal oil furnace is achieved.

[0040] Embodiment 2 is based on the same inventive concept as the indirect electric heating safety interlock control method in the above embodiment. Figure 2 As shown, the present application provides an indirect electric heating safety interlock control device, wherein the device comprises: An analysis module 11 is used to perform heat supply analysis in combination with an application scenario of a thermal oil furnace, determine a salt bath temperature threshold, perform ratio optimization of a multi-component mixed salt bath according to the salt bath temperature threshold, and determine an optimal salt bath ratio scheme; a monitoring module 12 is used to charge the thermal oil furnace with salt according to the optimal salt bath ratio scheme to obtain a target thermal oil furnace, and when the target thermal oil furnace is working, use a multi-source sensor monitoring network to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set; a control module 13 is used to judge the real-time monitoring data set according to a predetermined early warning threshold, and based on the judgment result, perform safety control on the target thermal oil furnace according to a predetermined interlocking control scheme.

[0041] Furthermore, the analysis module 11 is used to perform the following method: The thermal oil furnace comprises a heat storage tank, an electric heater, a salt bath, thermal oil and a heat exchanger, wherein the electric heater is used to heat the salt bath, the salt bath is used to heat the thermal oil, and the thermal oil transfers heat through the heat exchanger.

[0042] Furthermore, the analysis module 11 is used to perform the following method: The adaptive salt bath melting point is set according to the salt bath temperature threshold, and the adaptive salt bath type is selected according to the adaptive salt bath melting point, wherein the salt bath type includes multi-component mixed chloride salts and multi-component mixed nitrate salts; in order to meet the salt bath temperature threshold and the adaptive salt bath melting point, the ratio optimization of the multi-component mixed salt bath is performed according to the adaptive salt bath type, and the optimal salt bath ratio scheme is output.

[0043] Furthermore, the analysis module 11 is used to perform the following method: Acquire multiple proportion thresholds of the adapted salt bath type, and randomly generate a first salt bath ratio scheme within the multiple proportion thresholds; input the first salt bath ratio scheme into a salt bath temperature identifier, and output a first predicted temperature threshold and a first predicted melting point, wherein the salt bath temperature identifier is constructed based on the principle of ensemble learning; based on the salt bath temperature threshold and the adapted salt bath melting point, perform deviation calculation on the first predicted temperature threshold and the first predicted melting point to obtain a first deviation calculation result; use a scheme fitness evaluation function to determine the fitness of the first scheme according to the first deviation calculation result; continue to perform random scheme selection and fitness calculation within the multiple proportion thresholds until the convergence times are met, and output the salt bath ratio scheme with the largest fitness as the optimal salt bath ratio scheme.

[0044] Furthermore, the analysis module 11 is used to perform the following method: Construct a solution fitness evaluation function, including: ; Among them, RTE is the fitness of the solution, is the temperature threshold weight, is the melting point weight, Characterizes the overlap between the predicted temperature threshold and the salt bath temperature threshold, m is the intersection of the predicted temperature threshold and the salt bath temperature threshold, M is the salt bath temperature threshold, S is the adapted salt bath melting point, and s is the predicted melting point.

[0045] Furthermore, the monitoring module 12 is used to perform the following method: The predetermined components include a heat storage tank, an electric heater, a salt bath and heat transfer oil of a target thermal oil furnace; a multi-source sensor monitoring network is configured, wherein the multi-source sensor monitoring network at least includes an electric heating element temperature monitoring array, a heat transfer oil temperature monitoring array, a heat transfer oil pressure monitoring array, a heat transfer oil quantity monitoring array, a salt bath temperature monitoring array, a heat storage tank temperature monitoring array and a fire monitoring sensor, wherein the temperature monitoring array includes a number of evenly distributed temperature sensors; the multi-source sensor monitoring network is used to perform sensor monitoring on the heat storage tank, the electric heater, the salt bath and the heat transfer oil respectively to obtain a real-time monitoring data set.

[0046] Furthermore, the control module 13 is used to execute the following method: A heat transfer oil temperature data set and a salt bath temperature data set are selected from the real-time monitoring data set; mean calculation is performed on the heat transfer oil temperature data set and the salt bath temperature data set respectively to obtain a heat transfer oil temperature mean and a salt bath temperature mean; with the heat transfer oil temperature mean and the salt bath temperature mean as a reference, deviation calculation is performed on the heat transfer oil temperature data set and the salt bath temperature data set, and mean calculation is performed on the deviation calculation results to obtain a heat transfer oil temperature difference coefficient and a salt bath temperature difference coefficient; if the heat transfer oil temperature difference coefficient is greater than a predetermined heat transfer oil temperature difference scalar and / or the salt bath temperature difference coefficient is greater than a predetermined salt bath oil temperature difference scalar, an equipment alarm signal is generated.

[0047] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0048] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0049] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A safety interlock control method for indirect electric heating, characterized in that the method include: Conduct heat supply analysis based on the application scenario of the thermal oil furnace, determine the salt bath temperature threshold, perform multi-component mixed salt bath ratio optimization based on the salt bath temperature threshold, and determine the optimal salt bath ratio scheme; According to the optimal salt bath ratio scheme, the thermal oil furnace is charged with salt to obtain a target thermal oil furnace, and when the target thermal oil furnace is working, a multi-source sensor monitoring network is used to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set; The real-time monitoring data set is judged according to a predetermined early warning threshold, and based on the judgment result, the target thermal oil furnace is safely controlled according to a predetermined interlocking control scheme.

2. The indirect electric heating safety interlock control method according to claim 1, characterized in that: The thermal oil furnace comprises a heat storage tank, an electric heater, a salt bath, thermal oil and a heat exchanger, wherein the electric heater is used to heat the salt bath, the salt bath is used to heat the thermal oil, and the thermal oil transfers heat through the heat exchanger.

3. The indirect electric heating safety interlock control method according to claim 1, characterized in that: Optimizing the ratio of the multi-component mixed salt bath according to the salt bath temperature threshold to determine the optimal salt bath ratio scheme includes: Setting an adapted salt bath melting point according to the salt bath temperature threshold, and selecting an adapted salt bath type according to the adapted salt bath melting point, wherein the salt bath type includes a multi-component mixed chloride salt and a multi-component mixed nitrate salt; In anticipation of satisfying the salt bath temperature threshold and the melting point of the adapted salt bath, a ratio optimization of the multi-component mixed salt bath is performed according to the adapted salt bath type, and the optimal salt bath ratio scheme is output.

4. The indirect electric heating safety interlock control method according to claim 3, characterized in that: Optimizing the ratio of the multi-component mixed salt bath according to the adapted salt bath type and outputting the optimal salt bath ratio scheme includes: Acquire multiple proportion thresholds of the adapted salt bath type, and randomly generate a first salt bath ratio scheme within the multiple proportion thresholds; Inputting the first salt bath ratio scheme into a salt bath temperature identifier, and outputting a first predicted temperature threshold and a first predicted melting point, wherein the salt bath temperature identifier is constructed based on an ensemble learning principle; Based on the salt bath temperature threshold and the adapted salt bath melting point, performing deviation calculation on the first predicted temperature threshold and the first predicted melting point to obtain a first deviation calculation result; Determine the fitness of the first solution according to the first deviation calculation result by using the solution fitness evaluation function; Continue to randomly select schemes and calculate fitness within the multiple proportion thresholds until the convergence times are met, and output the salt bath ratio scheme with the maximum fitness as the optimal salt bath ratio scheme.

5. The indirect electric heating safety interlock control method according to claim 4, characterized in that: Construct a solution fitness evaluation function, including: ； Among them, RTE is the solution fitness, is the temperature threshold weight, is the melting point weight, Characterizes the overlap between the predicted temperature threshold and the salt bath temperature threshold, m is the intersection of the predicted temperature threshold and the salt bath temperature threshold, M is the salt bath temperature threshold, S is the adapted salt bath melting point, and s is the predicted melting point.

6. The indirect electric heating safety interlock control method according to claim 2, characterized in that: When the target thermal oil boiler is working, a multi-source sensor monitoring network is used to perform sensor monitoring on predetermined components to obtain real-time monitoring data sets, including: The predetermined components include a heat storage tank, an electric heater, a salt bath and heat transfer oil of a target thermal oil furnace; Configure a multi-source sensor monitoring network, wherein the multi-source sensor monitoring network at least includes an electric heating element temperature monitoring array, a thermal oil temperature monitoring array, a thermal oil pressure monitoring array, a thermal oil quantity monitoring array, a salt bath temperature monitoring array, a heat storage tank temperature monitoring array and a fire monitoring sensor, wherein the temperature monitoring array includes a plurality of evenly distributed temperature sensors; The multi-source sensor monitoring network is used to perform sensor monitoring on the heat storage tank, the electric heater, the salt bath, and the heat transfer oil respectively to obtain a real-time monitoring data set.

7. The indirect electric heating safety interlock control method according to claim 6, characterized in that: Judging the real-time monitoring data set according to a predetermined warning threshold value also includes: Selecting a heat transfer oil temperature data set and a salt bath temperature data set from the real-time monitoring data set; Performing mean calculations on the heat transfer oil temperature data set and the salt bath temperature data set respectively to obtain a heat transfer oil temperature mean and a salt bath temperature mean; Taking the mean value of the heat transfer oil temperature and the mean value of the salt bath temperature as a reference, performing deviation calculation on the heat transfer oil temperature data set and the salt bath temperature data set, and performing mean calculation on the deviation calculation results to obtain the heat transfer oil temperature difference coefficient and the salt bath temperature difference coefficient; If the heat transfer oil temperature difference coefficient is greater than a predetermined heat transfer oil temperature difference scalar and / or the salt bath temperature difference coefficient is greater than a predetermined salt bath oil temperature difference scalar, an equipment alarm signal is generated.

8. An indirect electric heating safety interlock control device, characterized in that: A method for implementing an indirect electric heating safety interlock control method as claimed in any one of claims 1 to 7, comprising: An analysis module, wherein the analysis module is used to perform heat supply analysis in combination with an application scenario of a thermal oil furnace, determine a salt bath temperature threshold, perform ratio optimization of a multi-component mixed salt bath according to the salt bath temperature threshold, and determine an optimal salt bath ratio scheme; A monitoring module, wherein the monitoring module is used to charge the thermal oil furnace with salt according to the optimal salt bath ratio scheme to obtain a target thermal oil furnace, and when the target thermal oil furnace is working, use a multi-source sensor monitoring network to perform sensor monitoring on predetermined components to obtain a real-time monitoring data set; A control module is used to judge the real-time monitoring data set according to a predetermined warning threshold, and based on the judgment result, perform safety control on the target thermal oil furnace according to a predetermined interlocking control scheme.

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