A sensor network-based automated heat treatment equipment energy consumption optimization method
Patent Information
- Application Number
- CN202611218088.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-08-12
- Publication Date
- 2026-10-27
Smart Images
Figure CN122981901A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of equipment energy consumption optimization technology, and specifically to an energy consumption optimization method for automated heat treatment equipment based on sensor networks. Background Technology
[0002] Automated thermochemical heat treatment equipment such as carburizing furnaces and nitriding furnaces are core process equipment in the equipment manufacturing field. They are also typical high-energy-consuming and long-cycle operation equipment in the industrial field, and their energy efficiency level directly affects the green and low-carbon transformation process of the heat treatment industry.
[0003] Currently, there are significant shortcomings in the waste heat recovery and utilization of heat treatment equipment in the industry: the application rate of waste heat recovery systems for carburizing and nitriding furnace exhaust gas and furnace wall heat dissipation is extremely low, and a large amount of medium and high temperature waste heat is directly emitted without being recovered, resulting in significant energy waste; and the equipment that has deployed waste heat recovery devices generally suffers from technical defects such as low operating condition matching, insufficient actual heat recovery efficiency, far below the design nominal value, and insufficient quality and stability of recovered heat, making it unable to be effectively applied to scenarios such as workpiece preheating, process gas preheating, or plant heating, and the energy-saving potential of the equipment has not been fully released. Summary of the Invention
[0004] The purpose of this invention is to provide an energy consumption optimization method for automated heat treatment equipment based on sensor networks, and to solve the following technical problems.
[0005] The objective of this invention can be achieved through the following technical solutions: A method for optimizing energy consumption in automated heat treatment equipment based on sensor networks includes the following steps: Step S1: Establish a temperature sensing network between various heat treatment devices. The temperature sensing network acquires the furnace temperature and exhaust gas temperature of each heat treatment device in real time to obtain device temperature data. Step S2: Obtain all processes of the workpiece to be processed, and obtain the temperature range required for each process. Record several processes whose temperature ranges overlap more than a preset overlap threshold as a group of temperature level processes, and establish a process temperature mapping table. Based on the process temperature mapping table, generate an initial equipment scheduling plan. Step S3: Each heat treatment equipment runs the initial equipment scheduling plan, obtains the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index in real time based on the equipment temperature data, compares the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index with the preset furnace temperature fluctuation threshold and the exhaust gas temperature fluctuation threshold, and generates a corrected equipment scheduling plan based on the comparison results. Step S4: Based on the equipment temperature data, generate waste heat recovery control parameters. Each heat treatment device executes the waste heat recovery control parameters and equipment scheduling plan to complete waste heat recovery.
[0006] As a further aspect of the present invention: the heat treatment equipment includes a carburizing furnace, a nitriding furnace and a high-temperature tempering furnace, and the workpiece to be treated is a workpiece that needs to be heated by the heat treatment equipment.
[0007] As a further aspect of the present invention: the process of obtaining the overlap between the two temperature ranges includes: For any two temperature intervals, let the two temperature intervals be denoted as [T1], [T2], [T3], [T4], [T5], [T6], [T7], [T8], [T9], [T1 ... min T1 max ] and [T2 min T2 max ], get T1 min and T2 min The larger of the two values is used as the lower bound of overlap, and T1 is obtained. max and T2 max The smaller of the two intervals is taken as the upper limit of overlap; when the upper limit of overlap is greater than the lower limit of overlap, the difference between the upper limit and the lower limit of overlap is obtained, and the difference is divided by the smaller interval span to obtain a ratio. The ratio is recorded as the degree of overlap between the two temperature intervals, where the smaller interval span is |T1|. min -T1 max | and | T2 min -T2 max The smaller of the two; when the upper limit of overlap is less than or equal to the lower limit of overlap, the overlap between the two temperature ranges is directly set to 0.
[0008] As a further aspect of the present invention: the process of establishing the process temperature mapping table includes: Create a blank process temperature mapping table. Iterate through all processes of the workpiece to be processed. For any process iterates through, determine whether the process is marked as belonging to any temperature level process group. If the process is marked as belonging to any temperature level process group, associate the process with its temperature level process group. If the process is not marked as belonging to any temperature level process group, create a new temperature level process group, add the process to the new temperature level process group, and associate the process with the new temperature level process group. The process temperature mapping table is obtained from each process and its associated temperature level process group.
[0009] As a further aspect of the present invention: the process of generating the initial equipment scheduling plan includes: Several workpieces belonging to the same temperature level process are assigned to the same production batch, and the temperature range of each workpiece belonging to the same temperature level process is obtained. The intersection of all temperature ranges is used as the operating temperature range of the production batch. Then, within the production batch, the workpieces put into each heat treatment equipment belong to the same temperature level process, and the furnace temperature of each heat treatment equipment is maintained within the operating temperature range.
[0010] As a further aspect of the present invention: the process of obtaining the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index includes: A time period threshold is set, and the furnace temperature sequence and exhaust gas emission temperature sequence within the time period threshold are obtained based on the equipment temperature data. The standard deviations of the furnace temperature sequence and exhaust gas emission temperature sequence are obtained respectively and recorded as the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index.
[0011] As a further aspect of the present invention: the process of generating the modified equipment scheduling plan includes: When the furnace temperature fluctuation index exceeds a preset furnace temperature fluctuation threshold, or the exhaust gas temperature fluctuation index exceeds a preset exhaust gas temperature fluctuation threshold, the temperature level process currently operating in the heat treatment equipment is determined and recorded as the current operating temperature level. Workpieces not yet loaded into the furnace are extracted from the initial equipment scheduling plan, and the loading order of each workpiece is obtained according to the initial equipment scheduling plan, resulting in a workpiece sequence to be loaded into the furnace. A search is performed within the workpiece sequence to be loaded into the furnace to determine if any workpieces belonging to the current operating temperature level exist. If so, the workpiece is recorded as a workpiece to be loaded into the furnace ahead of schedule, and its loading time is advanced to the current time. The workpiece to be loaded into the furnace ahead of schedule is then inserted into the initial equipment scheduling plan, and the loading time of subsequent workpieces is correspondingly postponed to obtain a revised equipment scheduling plan. If no workpieces are loaded into the furnace ahead of schedule, the current furnace temperature remains unchanged.
[0012] As a further aspect of the present invention: the process of generating the waste heat recovery control parameters includes: From the equipment temperature data, extract the furnace temperature value and exhaust gas emission temperature value corresponding to the temperature level process of each heat treatment equipment in operation, and record the furnace temperature value and exhaust gas emission temperature value as the current waste heat characterization parameters; based on the current waste heat characterization parameters, obtain the target flow rate of the heat exchange medium and the target operating frequency of the heat exchanger, and record the target flow rate of the heat exchange medium and the target operating frequency of the heat exchanger as waste heat recovery control parameters.
[0013] The beneficial effects of this invention are: Addressing the industry pain points of low waste heat recovery coverage, poor operating condition matching, and insufficient actual recovery efficiency in existing heat treatment furnace groups, this invention reduces the significant temperature rise and fall processes caused by process switching in the furnace body by centralizing the production of processes at the same temperature level, significantly reducing ineffective heat loss during the temperature rise and fall stages. Simultaneously, it maintains the furnace temperature within a stable temperature window for a long period, providing a constant heat source foundation for waste heat recovery and fundamentally improving the operating condition adaptability of waste heat recovery. Furthermore, this invention utilizes a temperature sensor network to achieve real-time sensing of the thermal status of the entire furnace group, combined with dynamic monitoring of furnace temperature and exhaust gas temperature fluctuation indices. Through dynamic correction of the scheduling plan, it suppresses temperature trend drift, ensuring process temperature stability and reducing the risk of product quality fluctuations. Furthermore, it maintains a stable waste heat output, avoiding heat exchange efficiency degradation caused by large fluctuations in waste heat parameters; based on real-time temperature data, it adjusts the operating parameters of the waste heat recovery system to accurately match the heat exchange operating point with the current waste heat grade, effectively improving the actual operating efficiency of the waste heat recovery system; the recovered heat can be directly used for workpiece preheating, process gas preheating, and plant heating, realizing energy cascade utilization and significantly reducing the overall energy consumption of the furnace group and production energy costs; in addition, the solution of this invention does not require hardware upgrades to the equipment body and waste heat recovery device, and can be implemented simply through scheduling optimization and control logic linkage, with low modification costs and strong adaptability, and can be widely applied to heat treatment production lines composed of carburizing furnaces, nitriding furnaces, and high-temperature tempering furnaces. Attached Figure Description
[0014] The invention will now be further described with reference to the accompanying drawings.
[0015] Figure 1 This is a schematic diagram illustrating the steps of an automated heat treatment equipment energy consumption optimization method based on sensor networks according to the present invention. Figure 2 This is a schematic diagram of the structure of an automated heat treatment equipment energy consumption optimization method based on sensor networks according to the present invention. Detailed Implementation
[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0017] Please see Figure 1 As shown, this invention is an energy consumption optimization method for automated heat treatment equipment based on sensor networks, comprising the following steps: Step S1: Establish a temperature sensing network between various heat treatment devices. The temperature sensing network acquires the furnace temperature and exhaust gas temperature of each heat treatment device in real time to obtain device temperature data. In a preferred embodiment of the present invention, the heat treatment equipment includes a carburizing furnace, a nitriding furnace and a high-temperature tempering furnace, and the workpiece to be treated is a workpiece that needs to be heated by the heat treatment equipment. In a preferred embodiment of the present invention, furnace temperature sensors are installed inside the furnace of each heat treatment equipment, and exhaust gas temperature sensors are installed in the exhaust gas discharge pipes of each heat treatment equipment. Each sensor is connected to a data acquisition terminal via an industrial fieldbus, and the data acquisition terminal establishes a communication link with a computing device executing the method of the present invention via an Ethernet, thereby forming a temperature sensing network covering the entire heat treatment furnace group. The temperature sensing network synchronously collects the furnace temperature and exhaust gas temperature of each heat treatment device at the current moment according to a preset sampling period; it associates each collected temperature value with the device identifier of the heat treatment device from which it originates and the timestamp of the collection time to form a device temperature data record; it packages the device temperature data records of all heat treatment devices in the same sampling period to generate the device temperature data frame corresponding to that sampling period, and it aggregates the device temperature data frames corresponding to each sampling period in chronological order to form device temperature data; Step S2: Obtain all processes of the workpiece to be processed, and obtain the temperature range required for each process. Record several processes whose temperature ranges overlap more than a preset overlap threshold as a group of temperature level processes, and establish a process temperature mapping table. Based on the process temperature mapping table, generate an initial equipment scheduling plan. Understandably, based on the degree of overlap in the temperature ranges of each process, processes that originally had similar temperature requirements but were scheduled separately are grouped into processes of the same temperature level and scheduled together. This ensures that all heat treatment equipment within the same production batch operates at similar furnace temperatures, thereby reducing the range and frequency of furnace temperature rises and falls caused by process switching from the source of production scheduling. In a preferred embodiment of the present invention, the process of obtaining the overlap between the two temperature ranges includes: For any two temperature intervals, let the two temperature intervals be denoted as [T1], [T2], [T3], [T4], [T5], [T6], [T7], [T8], [T9], [T1 ... min T1 max ] and [T2 min T2 max ], get T1 min and T2 min The larger of the two values is used as the lower bound of overlap, and T1 is obtained. max and T2 max The smaller of the two intervals is taken as the upper limit of overlap; when the upper limit of overlap is greater than the lower limit of overlap, the difference between the upper limit and the lower limit of overlap is obtained, and the difference is divided by the smaller interval span to obtain a ratio. The ratio is recorded as the degree of overlap between the two temperature intervals, where the smaller interval span is |T1|. min -T1max | and | T2 min -T2 max The smaller of the two; when the upper limit of overlap is less than or equal to the lower limit of overlap, the overlap between the two temperature ranges is directly set to 0; The process of establishing the process temperature mapping table includes: Create a blank process temperature mapping table. Iterate through all processes of the workpiece to be processed. For any process iterates through, determine whether the process is marked as belonging to any temperature level process group. If the process is marked as belonging to any temperature level process group, associate the process with its corresponding temperature level process group. If the process is not marked as belonging to any temperature level process group, create a new temperature level process group, add the process to the new temperature level process group, and associate the process with the new temperature level process group. The process temperature mapping table is obtained from each process and its associated temperature level process group. It should be noted that all processes are paired up in pairs. For each pair of processes, the following temperature range overlap calculation is performed: the lower and upper limits of the process temperature range for the first process and the second process are taken; the larger of the two lower limits is taken as the lower overlap limit, and the smaller of the two upper limits is taken as the upper overlap limit; when the upper overlap limit is greater than the lower overlap limit, the difference between the upper and lower overlap limits is divided by the smaller span of the respective process temperature ranges for the first and second processes, and the resulting ratio is the temperature range overlap for this pair of processes; when the upper overlap limit is less than or equal to the lower overlap limit, the temperature range overlap for this pair of processes is zero. Pairs of processes with temperature range overlap greater than a preset overlap threshold are grouped into the same group. All processes within the group are recorded as a temperature level process, and a temperature level identifier is assigned to each temperature level process. A process temperature mapping table is established, and each record in the process temperature mapping table contains the correspondence between the process identifier and the temperature level identifier of the temperature level process to which the process belongs. The process of generating the initial equipment scheduling plan includes: Several workpieces belonging to the same temperature level process are assigned to the same production batch, and the temperature range of each workpiece belonging to the same temperature level process is obtained. The intersection of all temperature ranges is used as the operating temperature range of the production batch. Then, within the production batch, the workpieces put into each heat treatment equipment belong to the same temperature level process, and the furnace temperature of each heat treatment equipment is maintained within the operating temperature range. Understandably, based on the process temperature mapping table, production scheduling calculations are performed on the workpieces to be processed. Workpieces belonging to the same temperature level process are assigned to the same production batch. A temperature maintenance range matching the common process temperature range of the temperature level process is set for this production batch. The execution order of each production batch is arranged in descending order of the temperature maintenance range of each production batch, generating an initial equipment scheduling plan. The initial equipment scheduling plan specifies the furnace entry sequence of the workpieces in each production batch on each heat treatment equipment and the corresponding furnace temperature maintenance range. Step S3: Each heat treatment equipment runs the initial equipment scheduling plan, obtains the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index in real time based on the equipment temperature data, compares the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index with the preset furnace temperature fluctuation threshold and the exhaust gas temperature fluctuation threshold, and generates a corrected equipment scheduling plan based on the comparison results. In a preferred embodiment of the present invention, the process of obtaining the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index includes: A time period threshold is set, and the furnace temperature sequence and exhaust gas emission temperature sequence within the time period threshold are obtained based on the equipment temperature data; the standard deviations of the furnace temperature sequence and exhaust gas emission temperature sequence are obtained respectively, and are denoted as furnace temperature fluctuation index and exhaust gas temperature fluctuation index respectively. It is worth noting that the standard deviation of its furnace temperature series is calculated and used as the furnace temperature fluctuation index of the equipment; the standard deviation of its exhaust gas temperature series is calculated and used as the exhaust gas temperature fluctuation index of the equipment; the maximum value of the furnace temperature fluctuation index of all heat treatment equipment is taken as the furnace temperature fluctuation index of the furnace group, and the maximum value of the exhaust gas temperature fluctuation index of all heat treatment equipment is taken as the exhaust gas temperature fluctuation index of the furnace group. The process of generating the revised equipment scheduling plan includes: When the furnace temperature fluctuation index exceeds a preset furnace temperature fluctuation threshold, or the exhaust gas temperature fluctuation index exceeds a preset exhaust gas temperature fluctuation threshold, the temperature level process currently operating in the heat treatment equipment is determined and recorded as the current operating temperature level. Workpieces not yet loaded into the furnace are extracted from the initial equipment scheduling plan, and the loading order of each workpiece is obtained according to the initial equipment scheduling plan, resulting in a workpiece sequence to be loaded into the furnace. Within the workpiece sequence, it is checked whether a workpiece belonging to the current operating temperature level exists. If so, the workpiece is recorded as a workpiece to be loaded early, and its loading time is advanced to the current time. The workpiece to be loaded early is then inserted into the initial equipment scheduling plan, and the loading time of subsequent workpieces is correspondingly postponed, resulting in a revised equipment scheduling plan. If no workpiece is loaded early, the current furnace temperature remains unchanged. Understandably, the process involves determining the temperature level process currently running for each heat treatment equipment, extracting workpieces yet to be processed from the initial equipment scheduling plan, and sorting them according to their loading times as specified in the initial equipment scheduling plan to form a sequence of workpieces to be loaded. Workpieces belonging to the currently running temperature level process are then retrieved from this sequence. If a workpiece is found, its loading time is modified to the current time, generating a revised equipment scheduling plan. If no workpiece is found, a heat preservation waiting instruction is generated, instructing each heat treatment equipment to maintain its current furnace temperature and suspending the reading of new loading tasks from the sequence of workpieces to be loaded until both the furnace group temperature fluctuation index and the furnace group exhaust gas temperature fluctuation index fall back to their respective threshold ranges. Step S4: Based on the equipment temperature data, generate waste heat recovery control parameters, and each heat treatment device executes the waste heat recovery control parameters and equipment scheduling plan to complete waste heat recovery; In a preferred embodiment of the present invention, the process of generating the waste heat recovery control parameters includes: From the equipment temperature data, extract the furnace temperature value and exhaust gas temperature value corresponding to the temperature level process of each heat treatment equipment in operation, and record the furnace temperature value and exhaust gas temperature value as the current waste heat characterization parameters; based on the current waste heat characterization parameters, obtain the target flow rate of the heat exchange medium and the target operating frequency of the heat exchanger, and record the target flow rate of the heat exchange medium and the target operating frequency of the heat exchanger as waste heat recovery control parameters; It is understandable that the furnace temperature and exhaust gas temperature of each heat treatment device under stable operating conditions at the current moment are extracted; and the extracted furnace temperature and exhaust gas temperature are used as input parameters to characterize the current waste heat grade. Based on the input parameters, according to the temperature level of the current waste heat grade, the heat exchange medium flow rate setting value and the heat exchanger operating frequency setting value corresponding to the temperature level are found from the pre-calibrated waste heat grade-heat exchange parameter mapping relationship; wherein, the waste heat grade-heat exchange parameter mapping relationship is obtained by testing under different steady-state temperature conditions, and the combination value of heat exchange medium flow rate and heat exchanger operating frequency that makes the heat exchange efficiency reach the preset high efficiency range is recorded; The found heat exchange medium flow rate setpoint is used to generate a heat exchange medium flow rate control command, and the found heat exchanger operating frequency setpoint is used to generate a heat exchanger operating frequency control command; the heat exchange medium flow rate control command and the heat exchanger operating frequency control command together constitute the waste heat recovery control parameters under the current operating conditions. The waste heat recovery control parameters are output to the execution end of the waste heat recovery process to control the flow rate of the heat exchange medium flowing through the heat exchanger and the operating frequency of the heat exchanger, so that the operating point of the heat exchanger matches the current waste heat grade in real time, thereby transferring the heat in the exhaust gas to the heat exchange medium through the heat exchanger; the heat carried by the heat exchange medium is transported to the preheating stage of the workpiece to be processed, and the workpiece is preheated before entering the heat treatment equipment. Understandably, by taking advantage of the stable waste heat grade resulting from the stable thermal state of the furnace group, and using the furnace temperature and exhaust gas temperature as inputs, heat exchange control parameters that precisely match the current waste heat grade are generated and output for execution. This ensures that the waste heat recovery process always operates within the designed high-efficiency range, solving the problem in existing technologies where furnace temperature fluctuations lead to low matching of heat exchange system operating conditions and actual heat recovery efficiency far below the design value. At the same time, the recovered heat is effectively used for workpiece preheating, reducing the overall process energy consumption of the heat treatment equipment.
[0018] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.
Claims
1. A method for optimizing energy consumption in automated heat treatment equipment based on sensor networks, characterized in that, Includes the following steps: Step S1: Establish a temperature sensing network between various heat treatment devices. The temperature sensing network acquires the furnace temperature and exhaust gas temperature of each heat treatment device in real time to obtain device temperature data. Step S2: Obtain all processes of the workpiece to be processed, and obtain the temperature range required for each process. Record several processes whose temperature ranges overlap more than a preset overlap threshold as a group of temperature level processes, and establish a process temperature mapping table. Based on the process temperature mapping table, generate an initial equipment scheduling plan. Step S3: Each heat treatment equipment runs the initial equipment scheduling plan, obtains the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index in real time based on the equipment temperature data, compares the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index with the preset furnace temperature fluctuation threshold and the exhaust gas temperature fluctuation threshold, and generates a corrected equipment scheduling plan based on the comparison results. Step S4: Based on the equipment temperature data, generate waste heat recovery control parameters. Each heat treatment device executes the waste heat recovery control parameters and equipment scheduling plan to complete waste heat recovery.
2. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S1, the heat treatment equipment includes a carburizing furnace, a nitriding furnace, and a high-temperature tempering furnace, and the workpiece to be treated is the workpiece that needs to be heated by the heat treatment equipment.
3. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S2, the process of obtaining the overlap between the two temperature ranges includes: For any two temperature intervals, let the two temperature intervals be denoted as [T1], [T2], [T3], [T4], [T5], [T6], [T7], [T8], [T9], [T1 ... min T1 max ] and [T2 min T2 max ], get T1 min and T2 min The larger of the two values is used as the lower bound of overlap, and T1 is obtained. max and T2 max The smaller of the two intervals is taken as the upper limit of overlap; when the upper limit of overlap is greater than the lower limit of overlap, the difference between the upper limit and the lower limit of overlap is obtained, and the difference is divided by the smaller interval span to obtain a ratio. The ratio is recorded as the degree of overlap between the two temperature intervals, where the smaller interval span is |T1|. min -T1 max | and | T2 min -T2 max The smaller of the two; when the upper limit of overlap is less than or equal to the lower limit of overlap, the overlap between the two temperature ranges is directly set to 0.
4. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S2, the process of establishing the process temperature mapping table includes: Create a blank process temperature mapping table. Iterate through all processes of the workpiece to be processed. For any process iterates through, determine whether the process is marked as belonging to any temperature level process group. If the process is marked as belonging to any temperature level process group, associate the process with its temperature level process group. If the process is not marked as belonging to any temperature level process group, create a new temperature level process group, add the process to the new temperature level process group, and associate the process with the new temperature level process group. The process temperature mapping table is obtained from each process and its associated temperature level process group.
5. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S2, the process of generating the initial equipment scheduling plan includes: Several workpieces belonging to the same temperature level process are assigned to the same production batch, and the temperature range of each workpiece belonging to the same temperature level process is obtained. The intersection of all temperature ranges is used as the operating temperature range of the production batch. Then, within the production batch, the workpieces put into each heat treatment equipment belong to the same temperature level process, and the furnace temperature of each heat treatment equipment is maintained within the operating temperature range.
6. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S3, the process of obtaining the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index includes: A time period threshold is set, and the furnace temperature sequence and exhaust gas emission temperature sequence within the time period threshold are obtained based on the equipment temperature data. The standard deviations of the furnace temperature sequence and exhaust gas emission temperature sequence are obtained respectively and recorded as the furnace temperature fluctuation index and the exhaust gas temperature fluctuation index.
7. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S3, the process of generating the revised equipment scheduling plan includes: When the furnace temperature fluctuation index exceeds a preset furnace temperature fluctuation threshold, or the exhaust gas temperature fluctuation index exceeds a preset exhaust gas temperature fluctuation threshold, the temperature level process currently operating in the heat treatment equipment is determined and recorded as the current operating temperature level. Workpieces not yet loaded into the furnace are extracted from the initial equipment scheduling plan, and the loading order of each workpiece is obtained according to the initial equipment scheduling plan, resulting in a workpiece sequence to be loaded into the furnace. A search is performed within the workpiece sequence to be loaded into the furnace to determine if any workpieces belonging to the current operating temperature level exist. If so, the workpiece is recorded as a workpiece to be loaded into the furnace ahead of schedule, and its loading time is advanced to the current time. The workpiece to be loaded into the furnace ahead of schedule is then inserted into the initial equipment scheduling plan, and the loading time of subsequent workpieces is correspondingly postponed to obtain a revised equipment scheduling plan. If no workpieces are loaded into the furnace ahead of schedule, the current furnace temperature remains unchanged.
8. The energy consumption optimization method for automated heat treatment equipment based on sensor networks according to claim 1, characterized in that, In step S4, the process of generating the waste heat recovery control parameters includes: From the equipment temperature data, extract the furnace temperature value and exhaust gas emission temperature value corresponding to the temperature level process of each heat treatment equipment in operation, and record the furnace temperature value and exhaust gas emission temperature value as the current waste heat characterization parameters; based on the current waste heat characterization parameters, obtain the target flow rate of the heat exchange medium and the target operating frequency of the heat exchanger, and record the target flow rate of the heat exchange medium and the target operating frequency of the heat exchanger as waste heat recovery control parameters.