Intelligent monitoring system and method for electric heat conversion heat conduction components

Abstract

The present application relates to the technical field of intelligent monitoring of electrothermal conversion, and specifically to an intelligent monitoring system and method for electrothermal conversion heat-conducting components, the method comprising: obtaining the current of each heat-generating unit in the electrothermal conversion device and the temperature data of each position of the heat-conducting component in the electrothermal conversion device, and determining the synchronization deviation of each heat-generating unit at the current sampling moment; according to the similarity between each heat-generating unit and the adjacent heat-generating unit about the characteristic vector at the current sampling moment, combined with the synchronization deviation, obtaining the radiation coupling influence of each heat-generating unit at the current sampling moment, and calculating the transfer deviation value of each heat-generating unit at the current sampling moment; and then determining the current adjustment degree of each heat-generating unit at the current sampling moment, and using an optimization algorithm to adjust the current of each heat-generating unit at the next moment. The present application can accurately control the current of each heat-generating unit and improve the thermal conductivity efficiency of the electrothermal conversion heat-conducting component.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent monitoring of electrothermal conversion, and in particular to an intelligent monitoring system and method for electrothermal conversion heat-conducting components. Background Art

[0002] Vulcanizers, condensers and other equipment are widely used in industries such as plastics and rubber, process industries, and clothing manufacturing. The heat exchange efficiency and uniformity of heat-conducting components are the key to improving the efficiency of vulcanizers and condensers. Therefore, the development of efficient, stable and energy-saving heat-conducting components is an important issue in related fields. At present, the innovation of heat-conducting components is achieved through the modular structure innovation of thick-film chips, and their stability and reliability are easily limited by the oxidation and corrosion and fusing of the electrode terminals of the thick-film heating plate in a high-temperature environment.

[0003] In electrical projects, the effective use of electric energy, the improvement of conversion efficiency, and the performance optimization of related components are all important research directions. Efficient electrothermal conversion components can play an important role in many fields such as energy utilization, industrial heating, and civil heating, and have high application value and research significance. Electrothermal conversion refers to the process of converting electrical energy into thermal energy. Usually, in order to improve the electrothermal conversion efficiency and heat exchange uniformity, the heat generating unit of electrothermal conversion needs to be connected to the heat conducting component, and the heat conducting component is used to improve the heat transfer efficiency, thereby improving the temperature uniformity. Generally, in order to maintain the stability of the external environment, the heat conducting component needs to be able to dissipate heat evenly, so the heat conducting component needs to be monitored.

[0004] In the electrothermal conversion heat-conducting component, one electric heating element is used as a heat-generating unit, and multiple heat-generating units are connected to a single heat-conducting component to improve the overall heat uniformity. In the traditional way, the thermal uniformity of the heat-conducting component is achieved by adjusting the current of the heat-generating unit. However, in actual situations, each heat-generating unit is located at a different position on the heat-conducting component, and heat radiation will be generated between the heat-generating units, affecting the uniformity of thermal conductivity. At the same time, the connection between the heat-generating unit and the heat-conducting component is not completely coupled, and there may be a small gap between the two, which affects the thermal conductivity efficiency and further affects the uniformity of the heat-conducting component. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of this application is to provide an intelligent monitoring system and method for electric heat conversion heat conduction components. The technical solutions adopted are as follows:

[0006] The embodiment of the present application provides an intelligent monitoring method for an electrothermal conversion heat-conducting component, comprising the following steps:

[0007] Obtaining the current of each heat generating unit in the electrothermal conversion device and the temperature data of each position of the heat conducting component in the electrothermal conversion device, and obtaining each block corresponding to each heat generating unit on the heat conducting component;

[0008] Based on the differences between the temperature data and the current data of each heat generating unit at multiple sampling moments before the current sampling moment, and the change trends of the temperature data and the current data, the synchronization deviation of each heat generating unit at the current sampling moment is obtained;

[0009] The characteristic vector of each heat-generating unit at the current sampling moment is constructed by the current of each heat-generating unit and the temperature in the corresponding block at the current sampling moment, and the radiation coupling influence of each heat-generating unit at the current sampling moment is obtained according to the similarity between each heat-generating unit and the adjacent heat-generating unit about the characteristic vector at the current sampling moment and the synchronization deviation;

[0010] Based on the current difference between each heat-generating unit and its adjacent heat-generating unit at the current sampling moment, and the temperature extreme difference within the corresponding block of each heat-generating unit, the transfer deviation value of each heat-generating unit at the current sampling moment is obtained;

[0011] Determine the current adjustment degree of each heat generating unit at the current sampling moment in combination with the radiation coupling influence degree and the transfer deviation value;

[0012] Based on the current adjustment degree of each heat generating unit at the current sampling moment, the current of each heat generating unit at the next moment is adjusted.

[0013] Preferably, obtaining the blocks corresponding to the heat generating units on the heat conducting component includes:

[0014] Based on the position of each heat generating unit on the heat conducting component, the heat conducting component is divided into blocks, wherein each heat generating unit corresponds to a block on the heat conducting component.

[0015] Preferably, the expression of the synchronization deviation of each heat generating unit at the current sampling moment is:

[0016] ; Wherein, A represents the synchronization deviation of the heat generating unit at the current sampling time, L and W represent the current data sequence and temperature data sequence of the heat generating unit at the current sampling time, respectively, DTW() represents the DTW distance, and They respectively represent the trend strength of the current data series and the temperature data series of the heat generating unit at the current sampling moment.

[0017] Preferably, the current data sequence and the temperature data sequence are composed of the current and the temperature of the heat generating unit at multiple sampling moments before the current sampling moment, respectively arranged in time sequence.

[0018] Preferably, the characteristic vector of each heat generating unit at the current sampling moment is composed of the current of each heat generating unit at the current sampling moment and the average temperature in the corresponding block.

[0019] Preferably, the expression of the radiation coupling influence degree of each heat generating unit at the current sampling moment is:

[0020] ; In the formula, B and A represent the radiation coupling influence and synchronization deviation of the heat generating unit at the current sampling time, respectively, M represents the number of adjacent heat generating units of the heat generating unit, and cos() represents the cosine similarity. and They respectively represent the characteristic vectors of the heat producing unit and its adjacent i-th heat producing unit at the current sampling moment.

[0021] Preferably, the expression of the transfer deviation value of each heat generating unit at the current sampling moment is:

[0022] ; In the formula, C represents the transfer deviation value of the heat generating unit at the current sampling time, Indicates the extreme value of the temperature in the block corresponding to the heat generating unit at the current sampling moment. It represents the average absolute deviation between the current of the heat generating unit and the current of all its adjacent heat generating units at the current sampling moment.

[0023] Preferably, the current adjustment degree of each heat generating unit at the current sampling moment is a result of normalizing the average of the radiation coupling influence degree and the transfer deviation value of each heat generating unit at the current sampling moment.

[0024] Preferably, the adjusting the current of each heat generating unit at the next moment further includes:

[0025] The current and current adjustment degree of all heat generating units at the current sampling moment and the average temperature of the corresponding block are used as the input of the optimization algorithm to obtain the current of each heat generating unit on the heat conducting component through the optimization algorithm as the current value of each heat generating unit at the next moment.

[0026] An embodiment of the present application also provides an intelligent monitoring system for electrothermal conversion heat-conducting components, including a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the steps of any one of the above methods when executing the computer program.

[0027] As can be seen from the above, the electric heat conversion heat conduction component intelligent monitoring system and method provided by the present application have at least the following beneficial effects:

[0028] The present application analyzes the current of the heat generating unit and the temperature value of the block on the corresponding heat-conducting component under the electrothermal conversion device, obtains the synchronization deviation based on the coordination between the current value of a single heat generating unit and the temperature of the corresponding block, measures the degree of coordination between the current transformation and the temperature fluctuation of the heat generating unit, and obtains the radiation coupling influence degree in combination with the difference in the characteristic vectors of adjacent heat generating units, measures the influence of the heat radiation of the adjacent heat generating unit on the heat generating unit, and at the same time, in combination with the situation in actual conditions where the heat generating unit and the heat-conducting component are not tightly coupled, obtains the transfer deviation value of a single heat generating unit based on the difference in temperature distribution in the corresponding block of the heat generating unit, obtains the current adjustment degree in combination with the radiation coupling influence degree, and finally uses the particle swarm optimization algorithm to obtain the current adjustment amount of each heat generating unit at each sampling moment to achieve thermal conductivity uniformity of the heat-conducting component. Unlike traditional electrothermal conversion devices, in which the current size is directly adjusted based on the relationship between the current size and the heat generation situation, the mutual interference of the heat radiation between adjacent heat generating units and the interference to the heat transfer when there is a gap between the heat generating unit and the heat-conducting component are not taken into account. The current adjustment degree of each heat generating unit is obtained as the attention level of each heat generating unit in the particle swarm optimization algorithm, so as to adjust the current of each heat generating unit at the next moment, thereby improving the temperature uniformity and heat conduction efficiency of the heat-conducting component, realizing efficient and stable precise monitoring of the intelligent heat-conducting component, and improving the application effect of the electrothermal conversion heat-conducting component of the present application in equipment such as vulcanizers. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 A flowchart of the steps of the intelligent monitoring method for the electrothermal conversion heat-conducting component provided in this application;

[0031] Figure 2 Schematic diagram of the electrothermal conversion device provided in the present application, wherein FIG2 (a) is a schematic diagram of a bottom view of the electrothermal conversion device, Figure 2 (b) is a schematic diagram of a side view of the electrothermal conversion device;

[0032] Figure 3 Schematic diagram of the gap on the bonding surface of the electrothermal conversion device. DETAILED DESCRIPTION

[0033] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation, structure, features and effects of the intelligent monitoring system and method for electric heat conversion heat conducting components proposed in the present application in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0034] Unless otherwise specified and limited, terms such as "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a circuit structure, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, an element defined by the sentence "comprising a ..." does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items. All technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of this application.

[0035] The specific scheme of the intelligent monitoring system and method for electric heat conversion heat conducting components provided by the present application is described in detail below with reference to the accompanying drawings.

[0036] See also Figure 1 , which shows a flowchart of a method for intelligently monitoring an electrothermal conversion heat-conducting component provided by an embodiment of the present application, comprising the following steps:

[0037] Step 1: Obtain the current of each heat generating unit in the electrothermal conversion device and the temperature data of the heat conducting component in the electrothermal conversion device, and obtain the blocks corresponding to each heat generating unit on the heat conducting component.

[0038] Heat-conducting components are widely used in many fields. Among them, the heat exchange efficiency and heat exchange uniformity of heat-conducting components are the key to improving the efficiency of vulcanizers and condensers. Efficient, stable and energy-saving heat-conducting components are the key factors to improve the efficiency of vulcanizers and condensers.

[0039] In this embodiment, each heat generating unit in the electrothermal conversion device can be independently controlled. Each heat generating unit is also a heat generating power source. All heat generating power sources are connected to the entire heat conducting component. Heat conversion is achieved through the heat conducting component, thereby improving the heat exchange efficiency and heat uniformity of the heat conducting component.

[0040] Specifically, the schematic diagram of the electrothermal conversion device is as follows Figure 2 As shown, the bottom view of the electrothermal conversion device is shown in Figure 2As shown in (a), Figure 2 (b) is a schematic diagram of a side view of the electrothermal conversion device, Figure 2 (a) and Figure 2 In (b), number 1 represents a heat-conducting component for achieving heat transfer, number 2 represents a heat-generating unit, and the electrothermal conversion device includes a plurality of heat-generating units, wherein the heat-generating units and the heat-conducting component are bonded and connected.

[0041] In order to obtain the operating status of the electrothermal conversion device, the current value of each heat generating unit is obtained through the Hall current sensor, and the temperature image of the entire heat conducting component is obtained by infrared imaging directly above the electrothermal conversion device, and the sampling interval of all data acquisition devices is set to 1s. Since the positions of the heat generating unit and the heat conducting component are relatively fixed, the heat conducting component is divided into blocks based on each heat generating unit, and each heat generating unit corresponds to a block on the heat conducting component. Therefore, the temperature data of the block corresponding to each heat generating unit can be obtained in the temperature image of the heat conducting component (that is, in the temperature image of the heat conducting component, the block corresponding to each heat generating unit is divided without interval).

[0042] At this point, the current data of each heat generating unit and the temperature data of the corresponding block of each heat generating unit on the heat conducting component can be obtained.

[0043] Step 2: Based on the differences in temperature data and current data of each heat generating unit at multiple sampling moments before the current sampling moment, and the change trends of the temperature data and current data, the synchronization deviation of each heat generating unit at the current sampling moment is obtained.

[0044] Under normal circumstances, when electric current passes through the heat generating unit, it converts electrical energy into heat energy. Since the heat generating unit is connected to the heat conducting component, and the heat conducting component is generally composed of materials with high thermal conductivity, the heat energy of the heat generating unit can be quickly transferred and evenly radiated to the surrounding environment. In traditional heat conducting component monitoring, only the mapping relationship between the radiation temperature and the current value on the heat conducting component is used to adjust the current value to improve the uniformity and thermal conductivity efficiency of the heat conducting component. However, in actual situations, the heat generated by a single heat generating unit will affect the surrounding heat generating units, and due to the tiny gap between the heat generating unit and the heat conducting component, there is a difference in heat diffusion, so it may not be ideal to only adjust the current value of the heat generating unit by the radiation temperature to achieve the purpose of improving the temperature uniformity of the heat conducting component. Therefore, it is necessary to analyze the distribution of temperature and current data.

[0045] According to Joule's law, the current value of a single heat-generating unit is positively correlated with the heat generated by the unit, that is, the larger the current value, the more heat is generated. Therefore, the current value of a single heat-generating unit and the temperature value of the block in the temperature image corresponding to the unit should change synchronously. If the degree of synchronization between the current value of the heat-generating unit and the block temperature value is lower, the abnormality of the current heat-generating unit is higher; on the contrary, if the degree of synchronization between the current value of the heat-generating unit and the corresponding block temperature value is lower, the abnormality of the heat-generating unit is lower. It should be noted that the temperature values ​​of all pixels in the block corresponding to the heat-generating unit are averaged as the temperature value of the block.

[0046] In order to synchronize the current value of the heat generating unit with the temperature value of the corresponding block, the current and temperature of the heat generating unit at multiple sampling moments before the current sampling moment are arranged in time sequence to form the current data sequence and temperature data sequence of the heat generating unit at the current moment. In this embodiment, the temperature and current at n sampling moments before the current sampling moment are arranged in time sequence to construct the temperature data sequence and the current data sequence, and n=60 is set in this embodiment.

[0047] Based on the above analysis, taking any heat generating unit as an example, based on the difference between the temperature data sequence and the current data sequence of the heat generating unit at the current sampling moment, and the change trend of the temperature data sequence and the current data sequence, the synchronization deviation A of the heat generating unit at the current sampling moment is constructed. In this embodiment, the specific calculation formula is:

[0048] ; Wherein, A represents the synchronization deviation of the heat generating unit at the current sampling time, L and W represent the current data sequence and temperature data sequence of the heat generating unit at the current sampling time, respectively, DTW() represents the DTW distance, and They respectively represent the trend strength of the current data sequence and the temperature data sequence of the heat generating unit at the current sampling moment, wherein the trend item strength is obtained by performing STL decomposition (Seasonal and Trend Decomposition using LOESS) on the sequence, that is, time series data decomposition, to obtain the trend item, and the trend strength is calculated based on the trend item using the trend strength formula. The specific process is a well-known technology for those skilled in the art and will not be repeated here.

[0049] If the current distribution of the current heat generating unit deviates more from the temperature distribution of the corresponding block, the DTW distance between the current data sequence and the temperature data sequence will be larger, and the trend item between the current data sequence and the temperature data sequence will deviate, resulting in The larger the value is, the greater the synchronization deviation of the heat generating unit at the current sampling moment will be.

[0050] Step 3: The current value of each heat generating unit at the current sampling moment and the temperature average value in the corresponding block are combined to form the characteristic vector of each heat generating unit at the current sampling moment. According to the similarity between each heat generating unit and the adjacent heat generating unit about the characteristic vector at the current sampling moment, combined with the synchronization deviation, the radiation coupling influence degree of each heat generating unit at the current sampling moment is obtained.

[0051] At the same time, the heat generating units are evenly distributed on the heat-conducting components, and the heat generated by a single heat generating unit will often radiate to the surroundings, thereby affecting the temperature conditions on the adjacent input units. Therefore, part of the heat of the block corresponding to a single heat generating unit comes from the heat generated by its own electrothermal conversion, and the other part comes from the heat radiated from the adjacent block. Therefore, if the current heat generating unit is subjected to more radiation, the current of the heat generating unit will be lower, and the temperature of the block corresponding to the heat generating unit will be higher. Therefore, based on a single heat generating unit, a feature vector is constructed with the current value of each heat generating unit at the current sampling moment and the temperature value of the corresponding block, and the current of each heat generating unit at the current sampling moment and the average temperature in the corresponding block form the feature vector of each heat generating unit at the current sampling moment. Specifically, represents the characteristic vector of the kth heat generating unit at the current sampling time, where and It represents the current value of the kth heat generating unit and the average temperature of the block corresponding to the kth heat generating unit at the current sampling moment.

[0052] Based on the above analysis, according to the similarity between the heat generating unit and the adjacent heat generating unit about the characteristic vector at the current sampling moment, combined with the synchronization deviation, the radiation coupling influence of the heat generating unit at the current sampling moment is obtained. In this embodiment, the specific calculation formula is:

[0053] ; In the formula, B and A represent the radiation coupling influence and synchronization deviation of the heat generating unit at the current sampling time, respectively, M represents the number of adjacent heat generating units of the heat generating unit, and cos() represents the cosine similarity. and They respectively represent the characteristic vectors of the heat producing unit and its adjacent i-th heat producing unit at the current sampling moment.

[0054] If the current heat-generating unit is more seriously affected by the heat radiation of other heat-generating units, the contribution of the heat-generating unit itself to the electrothermal conversion will be lower, thereby making the current value of the heat-generating unit lower, and the temperature value of the corresponding block higher, the difference with the adjacent block is greater, so the difference between the heat-generating unit and the adjacent heat-generating unit is greater, the cosine similarity is lower, and thus the radiation coupling influence value of the heat-generating unit is greater.

[0055] Step 4: Based on the current difference between each heat generating unit and its adjacent heat generating unit at the current sampling moment, and the temperature extreme difference within the corresponding block of each heat generating unit, the transfer deviation value of each heat generating unit at the current sampling moment is obtained.

[0056] Generally speaking, the back of the heat generating unit and the bottom of the heat conducting component are both smooth planes, but from a microscopic perspective, the two planes are not completely fitted together, and there is a certain air gap. The specific diagram of the gap between the fitting surfaces is as follows: Figure 3 As shown, Figure 3 In the figure, number 3 represents the microstructure of the bottom plane of the heat-conducting component, number 4 represents the air gap between the heat-conducting component and the plane of the heat-generating unit, and number 5 represents the microstructure of the top plane of the heat-generating unit.

[0057] Since air is a poor conductor of thermal energy, the heat of the heat generating unit may accumulate in the gap, resulting in a lag between the heat of the heat generating unit and the temperature of the corresponding heat conducting component block. At this time, when the current of the heat generating unit is small, the temperature value of the corresponding block is also low. Therefore, there may be misjudgment when judging only by the composite coupling influence, and further analysis of the current and temperature conditions is required.

[0058] Since the back of the heat generating unit and the bottom of the heat conducting component have a certain area, there are air gaps and direct contact areas on the connection surface of the two, which makes the temperature distribution of the block corresponding to the heat generating unit uneven, that is, in the direct contact area, since the two planes are directly connected, the heat can be transferred quickly and the temperature is often higher, while in the air gap area, due to the poor thermal conductivity of the air, the heat transfer is slow and the temperature is often lower.

[0059] Based on the above analysis, according to the current situation of the heat generating unit and the temperature distribution in the corresponding block, the transfer deviation value C is obtained. In this embodiment, the specific calculation formula is:

[0060] ; In the formula, C represents the transfer deviation value of the heat generating unit at the current sampling time, Indicates the extreme value of the temperature in the block corresponding to the heat generating unit at the current sampling moment. It represents the average absolute deviation between the current of the heat generating unit and the current of all its adjacent heat generating units at the current sampling moment, wherein the calculation of the average absolute deviation is a prior art and will not be elaborated here.

[0061] If the top of the current heat generating unit is not tightly connected to the base of the heat conducting component and there is a gap, this will cause a difference in the temperature distribution in the corresponding block of the current heat generating unit. The temperature of the heat generating unit at the connection position can be transferred, making the temperature at the connection lower, while the temperature at the gap is lower due to the poor thermal conductivity of the air and slow transfer, thereby making the temperature extreme difference at the corresponding block of the heat generating unit greater; the greater the deviation between the current value of the current heat generating unit and the current value of the adjacent heat generating unit, the greater the transfer deviation of the heat generating unit.

[0062] Step 5: Determine the current adjustment degree of each heat generating unit at the current sampling moment in combination with the radiation coupling influence degree and the transfer deviation value.

[0063] After comprehensively considering the thermal radiation coupling between the heat generating units and the influence of the gap between the heat generating units and the heat conducting components, the corresponding radiation coupling influence and transfer deviation values ​​are obtained respectively. Thus, the current adjustment degree of the heat generating unit at the current sampling moment is calculated. The specific acquisition method is to calculate the mean of the radiation coupling influence and transfer deviation value of the heat generating unit at the current sampling moment, and the normalized result is used as the current adjustment degree. It should be noted that there are many normalization methods. This embodiment adopts the ‌‌Z-Score normalization method. The specific normalization process is the prior art and will not be repeated in this embodiment. In specific practical application scenarios, the implementer also adopts other existing normalization methods. This embodiment does not make special restrictions.

[0064] The larger the current adjustment value, the worse the coordination between the current value of the heat generating unit and the temperature value of the corresponding block. At this time, it is necessary to increase the current adjustment to improve the electrothermal conversion efficiency and the temperature uniformity of the heat conducting components. The smaller the current adjustment value, the closer the current value of the heat generating unit is to the temperature of the corresponding block. At this time, there is no need to specially adjust the current of the heat generating unit.

[0065] Step 6: Based on the current adjustment degree of each heat generating unit at the current sampling moment, the current of each heat generating unit at the next moment is adjusted.

[0066] Through the above process, the corresponding current adjustment degree of each heat generating unit at each sampling moment can be obtained, and by adjusting the current value of each heat generating unit, the temperature uniformity and transfer efficiency of the heat conducting component can be improved. The specific process is:

[0067] At the current sampling time, the current and current adjustment of all heat generating units and the temperature mean of the corresponding blocks are used as the input of the particle swarm optimization algorithm, where the population size is set to 100 and the individual learning factor is and social learning factors They are set to 1.5 and 2.2 respectively, the inertia weight is set to 1.2, and gradually decreases with the increase of the number of iterations, that is, when the number of iterations is 100, the inertia weight reaches 0.4, and no longer decreases with the increase of the number of iterations, the maximum number of iterations is set to 200, the convergence threshold is set to 0.1, and the fitness function is based on the minimum temperature variance of each block of the heat-conducting component. The algorithm outputs the current of each heat-generating unit that wants to achieve the temperature uniformity of the heat-conducting component, and adjusts the current value of each heat-generating unit at the next moment based on this.

[0068] It should be noted that the role of the current adjustment degree is to measure the attention paid to each heat-generating unit during optimization and adjustment. The reason is that the heat-generating unit with a larger current adjustment degree has a more complex relationship between the corresponding current and temperature distribution, and has a more important impact on the temperature uniformity of the final heat-conducting component. Therefore, more attention is paid to the regulation of the heat-generating units with a larger current adjustment degree during the optimization process, which can improve the convergence speed and the temperature uniformity of the final heat-conducting component.

[0069] Based on the same inventive concept as the above method, an embodiment of the present application also provides an intelligent monitoring system for electrothermal conversion thermal conductive components, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned methods for intelligent monitoring of electrothermal conversion thermal conductive components are implemented.

[0070] In summary, the above-mentioned embodiment of the present application obtains the synchronization deviation based on the coordination between the current value of a single heat generating unit and the temperature of the corresponding block, measures the degree of coordination between the current transformation and the temperature fluctuation of the heat generating unit, and obtains the radiation coupling influence degree in combination with the difference in the characteristic vectors of adjacent heat generating units, measures the influence of the heat radiation of the adjacent heat generating unit on the heat generating unit, and at the same time, combined with the situation in actual conditions where the heat generating unit and the heat conducting component are not tightly coupled, based on the difference in temperature distribution in the corresponding block of the heat generating unit, obtains the transfer deviation value of a single heat generating unit, and obtains the current adjustment degree in combination with the radiation coupling influence degree, and finally uses the particle swarm optimization algorithm to obtain the current adjustment amount of each heat generating unit at each sampling moment to achieve the uniformity of thermal conductivity of the heat conducting component. Unlike traditional electrothermal conversion devices, in which the current size is directly adjusted based on the relationship between the current size and the heat generation situation, the mutual interference of the heat radiation between adjacent heat generating units and the interference to the heat transfer when there is a gap between the heat generating unit and the heat-conducting component are not taken into account. The current adjustment degree of each heat generating unit is obtained as the attention level of each heat generating unit in the particle swarm optimization algorithm, so as to adjust the current of each heat generating unit at the next moment, thereby improving the temperature uniformity and heat conduction efficiency of the heat-conducting component, realizing efficient and stable precise monitoring of the intelligent heat-conducting component, and improving the application effect of the electrothermal conversion heat-conducting component of the present application in equipment such as vulcanizers.

[0071] It is to be understood that the sequence of the embodiments of the present application described above is for description only and does not represent the advantages and disadvantages of the embodiments. The above describes specific embodiments of the present specification. In addition, 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.

[0072] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0073] The above content is only an implementation method of the present application and is not intended to limit the scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the protection scope of the present application.

Claims

1. An intelligent monitoring method for an electrothermal conversion heat-conducting component, characterized in that: The following steps are involved: Obtaining the current of each heat generating unit in the electrothermal conversion device and the temperature data of each position of the heat conducting component in the electrothermal conversion device, and obtaining each block corresponding to each heat generating unit on the heat conducting component; Based on the differences between the temperature data and the current data of each heat generating unit at multiple sampling moments before the current sampling moment, and the change trends of the temperature data and the current data, the synchronization deviation of each heat generating unit at the current sampling moment is obtained; The characteristic vector of each heat-generating unit at the current sampling moment is constructed by the current of each heat-generating unit and the temperature in the corresponding block at the current sampling moment, and the radiation coupling influence of each heat-generating unit at the current sampling moment is obtained according to the similarity between each heat-generating unit and the adjacent heat-generating unit about the characteristic vector at the current sampling moment and the synchronization deviation; Based on the current difference between each heat-generating unit and its adjacent heat-generating unit at the current sampling moment, and the temperature extreme difference within the corresponding block of each heat-generating unit, the transfer deviation value of each heat-generating unit at the current sampling moment is obtained; Determine the current adjustment degree of each heat generating unit at the current sampling moment in combination with the radiation coupling influence degree and the transfer deviation value; Based on the current adjustment degree of each heat generating unit at the current sampling moment, the current of each heat generating unit at the next moment is adjusted.

2. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The acquisition of each block corresponding to each heat generating unit on the heat conducting component includes: Based on the position of each heat generating unit on the heat conducting component, the heat conducting component is divided into blocks, wherein each heat generating unit corresponds to a block on the heat conducting component.

3. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The expression of the synchronization deviation of each heat generating unit at the current sampling moment is: ; Wherein, A represents the synchronization deviation of the heat generating unit at the current sampling time, L and W represent the current data sequence and temperature data sequence of the heat generating unit at the current sampling time, respectively, DTW() represents the DTW distance, and They respectively represent the trend strength of the current data series and the temperature data series of the heat generating unit at the current sampling moment.

4. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 3, characterized in that: The current data sequence and the temperature data sequence are composed of the current and the temperature of the heat generating unit at multiple sampling moments before the current sampling moment, respectively arranged in time sequence.

5. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The characteristic vector of each heat generating unit at the current sampling moment is composed of the current of each heat generating unit at the current sampling moment and the average temperature in the corresponding block.

6. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The expression of the radiation coupling influence of each heat generating unit at the current sampling moment is: ; In the formula, B and A represent the radiation coupling influence and synchronization deviation of the heat generating unit at the current sampling time, respectively, M represents the number of adjacent heat generating units of the heat generating unit, and cos() represents the cosine similarity. and They respectively represent the characteristic vectors of the heat producing unit and its adjacent i-th heat producing unit at the current sampling moment.

7. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The expression of the transfer deviation value of each heat generating unit at the current sampling time is: ; In the formula, C represents the transfer deviation value of the heat generating unit at the current sampling time, Indicates the extreme value of the temperature in the block corresponding to the heat generating unit at the current sampling moment. It represents the average absolute deviation between the current of the heat generating unit and the current of all its adjacent heat generating units at the current sampling moment.

8. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The current adjustment degree of each heat generating unit at the current sampling moment is the result of normalizing the average of the radiation coupling influence degree and the transfer deviation value of each heat generating unit at the current sampling moment.

9. The intelligent monitoring method for electric heat conversion heat conducting components according to claim 1, characterized in that: The adjusting of the current of each heat generating unit at the next moment further includes: The current and current adjustment degree of all heat generating units at the current sampling moment and the average temperature of the corresponding block are used as the input of the optimization algorithm to obtain the current of each heat generating unit on the heat conducting component through the optimization algorithm as the current value of each heat generating unit at the next moment.

10. An intelligent monitoring system for electric heat conversion heat conducting components, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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