Energy-saving intelligent control method and system for variable frequency drive type egg roll production line

Abstract

This invention relates to the field of intelligent egg roll production, providing an energy-saving intelligent control method and system for a frequency converter-driven egg roll production line. The method includes the following steps: acquiring real-time electricity price data and target output data; calculating a set of process parameters using a preset baking energy consumption dynamic model; generating corresponding instructions based on the process parameter set to control the baking equipment to switch modes on the time axis, and obtaining product batch data including two characteristic identifiers: slightly under-progressive and slightly over-progressive; generating global scheduling instructions for egg rolls with different characteristic identifiers based on the product batch data, status parameters, and preset target quality parameters; acquiring cycle power consumption and output data and calculating the comprehensive energy cost, generating deviation data by comparing it with the prediction results of the baking energy consumption dynamic model. This invention utilizes the unique heat transfer properties of egg roll production to transfer energy utilization, effectively reducing comprehensive energy consumption while ensuring stable production.

Description

Technical Field

[0001] This invention relates to the field of intelligent egg roll production, specifically to an energy-saving intelligent control method and system for a frequency conversion driven egg roll production line. Background Technology

[0002] The variable frequency drive (VFD) egg roll production line is an automated food production line that utilizes modern transmission and control technologies such as VFDs and AC motors. It uses VFDs to flexibly and precisely control the speed of motors in each stage of the production line, thereby achieving precise adjustment of process parameters such as production speed, temperature, and tension. Compared to traditional fixed-speed or simple speed-adjustable production lines, it has advantages such as high automation, flexible adjustment, and significant energy-saving potential.

[0003] Generally, an egg roll production line consists of a mixing system, a baking machine, a rolling and cutting system, a cooling conveyor line, and a packaging machine. Variable frequency drive (VFD) is used to coordinate all processes via a PLC or industrial computer, synchronizing the speeds of each component. Energy saving is a crucial consideration in production. Conventional energy-saving methods involve controlling the power of one or more devices based on actual production conditions; for example, using VFD control to adjust the mixing speed of a mixing motor to accommodate different batter mixing speeds. However, this approach has limitations because existing equipment is already quite sophisticated in terms of functionality.

[0004] In existing technologies, there are strategies that adjust power generation in real time based on electricity prices, i.e., reducing speed during peak hours and increasing speed during off-peak hours while maintaining a constant total output. This strategy is particularly suitable for purely mechanical processing or assembly lines where energy consumption and speed are basically linearly related. However, egg roll production lines have unique characteristics; their core energy consumption is in the heating stage, and simply reducing speed has limited energy-saving effects because the oven is still running at high temperatures, and there is also the issue of reducing production during peak hours, which may not be feasible in the face of urgent orders. Therefore, a variable frequency drive-driven intelligent energy-saving control method and system for egg roll production lines is proposed to solve the above problems. Summary of the Invention

[0005] In view of the shortcomings of the existing technology, the purpose of this invention is to provide an energy-saving intelligent control method and system for a variable frequency drive egg roll production line, so as to solve the problems existing in the above-mentioned background technology.

[0006] This invention is implemented as follows: an energy-saving intelligent control method for a frequency conversion driven egg roll production line, the method comprising the following steps: Real-time electricity price data and target output data are obtained, and a set of process parameters is calculated through a preset baking energy consumption dynamic model. The set of process parameters includes high-speed low-temperature parameters and low-speed high-temperature parameters. The set of process parameters is used to control the speed and temperature of the baking equipment in a future set time period. Based on the process parameter set, corresponding instructions are generated to control the baking equipment to switch modes on the time axis and obtain product batch data containing two feature identifiers: slightly under-state and slightly over-state. Based on product batch data, status parameters, and preset target quality parameters, global scheduling instructions are generated for egg rolls with different characteristic identifiers. These instructions are used to adjust the conveying speed and air volume of each section of the cooling conveyor line. The status parameters are obtained through data acquisition equipment deployed at the entrance of the cooling conveyor line. When a production cycle is completed, the cycle power consumption and output data are obtained and the comprehensive energy consumption cost is calculated. The deviation data is generated by comparing it with the prediction results of the baking energy consumption dynamic model, which is used to calibrate the baking energy consumption dynamic model.

[0007] As a further aspect of the present invention: the step of obtaining real-time electricity price data and target output data, and calculating the process parameter set through a preset baking energy consumption dynamic model, specifically includes: The baking energy consumption dynamic model is established based on historical data from the production line, including baking speed data, baking roller temperature data, and moisture content data of the egg rolls after baking. When acquiring real-time electricity price data and target output data, the flowability data of the current batch of batter is collected by sensors deployed on the batter delivery pipeline; Real-time electricity price data, target output data, and liquidity data are input into the baking energy consumption dynamic model. The goal is to minimize the overall energy consumption cost to obtain the high-speed low-temperature parameters and low-speed high-temperature parameters corresponding to different electricity price periods. Based on the obtained high-speed low-temperature parameters and low-speed high-temperature parameters, the process parameter set is generated by arranging them in time sequence according to their corresponding electricity price periods.

[0008] As a further aspect of the present invention: the step of generating corresponding instructions based on the process parameter set to control the baking equipment to switch modes on the time axis specifically includes: The high-speed low-temperature parameters and the low-speed high-temperature parameters are used to generate timing control commands according to the corresponding time periods, and these commands are sent to the baking roller drive frequency converter and the heating temperature control component. Egg rolls produced at high speed and low temperature are defined as feature markers of the slightly under-produced state, and egg rolls produced at low speed and high temperature are defined as feature markers of the slightly over-produced state. The corresponding moisture content data of the two are integrated to obtain a feature reference set. The real-time moisture content data of the baked egg rolls is obtained by the detection equipment deployed at the outlet of the baking equipment, and compared with the feature reference set. Product batch data is generated based on the comparison results and the current order of the freshly baked egg rolls.

[0009] As a further aspect of the present invention: the step of generating global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters, and preset target quality parameters specifically includes: Receive product batch data with slightly under and slightly over states as identifiers, and simultaneously acquire egg roll state parameters detected in real time by data acquisition equipment, including surface temperature and current moisture content data. The target quality parameters for the current batch of egg rolls are determined based on the feature identifiers, and the theoretical cooling load is calculated based on the current moisture content data. Based on the theoretical cooling load and the inventory on the cooling conveyor line, a global scheduling instruction is generated for each batch of egg rolls. The global scheduling instruction includes the conveying speed and air volume corresponding to each segment of the cooling conveyor line when the egg rolls pass through it. The global scheduling command is issued and executed, and the parameters are corrected using real-time moisture content data obtained from various detection points deployed on the cooling conveyor line.

[0010] As a further aspect of the present invention: the step of generating a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line specifically includes: Obtain real-time order data and create a list of manageable inventory based on the egg roll's stock level; Calculate the outbound priority for each batch of egg rolls in the processable inventory list; Cooling strategy decisions are made based on the theoretical cooling load, characteristic identifiers, and outbound priority of each batch of egg rolls; The decision results are combined into a global scheduling command, which is then sent to each segment of the cooling conveyor line for execution.

[0011] As a further aspect of the present invention, the cooling strategy specifically includes: When the egg roll batch is in a slightly over-processed state and has a high priority, generate a first-class cooling instruction that can complete the cooling process in the shortest time. When the egg roll batch is in a slightly overloaded state and has a low priority, generate a second type of cooling instruction that can ensure minimal energy consumption. When the egg roll batch is in a slightly under-cooled state and has a high priority, the wind speed adjustment coefficient is obtained through a preset mapping table based on its outbound priority and theoretical cooling load, and a third type of cooling instruction that can increase the air volume is generated. When the egg roll batch is in a slightly deficient state and has a low priority, a fourth type of cooling instruction is generated that allows it to remain on the cooling conveyor line with the lowest airflow and the longest duration.

[0012] Another object of the present invention is to provide an energy-saving intelligent control system for a frequency conversion drive egg roll production line, the system comprising: The parameter calculation module is used to acquire real-time electricity price data and target output data, and calculate the process parameter set through a preset baking energy consumption dynamic model. The process parameter set includes high-speed low temperature parameters and low-speed high temperature parameters. The process parameter set is used to control the speed and temperature of the baking equipment in a future set period. The mode switching module is used to generate corresponding instructions based on the process parameter set, which are used to control the baking equipment to switch modes on the time axis and obtain product batch data containing two feature identifiers: slightly under-state and slightly over-state. The scheduling generation module is used to generate global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters and preset target quality parameters. It is used to adjust the conveying speed and air volume of each section of the cooling conveyor line. The status parameters are obtained through data acquisition equipment deployed at the entrance of the cooling conveyor line. The model calibration module is used to acquire cycle power consumption and output data and calculate the comprehensive energy cost when a production cycle is completed. It generates deviation data by comparing the prediction results with the baking energy consumption dynamic model, which is used to calibrate the baking energy consumption dynamic model.

[0013] As a further aspect of the present invention: the parameter calculation module includes: The model building unit is used to build the baking energy consumption dynamic model based on the historical data of the production line. The historical data includes baking speed data, baking roller temperature data, and moisture content data of the egg rolls after baking. The data acquisition unit is used to collect flow data of the current batch of batter by means of sensors deployed on the batter delivery pipeline when acquiring real-time electricity price data and target output data; The optimization solution unit is used to input real-time electricity price data, target output data and liquidity data into the baking energy consumption dynamic model, and solves the high-speed low temperature parameters and low-speed high temperature parameters corresponding to different electricity price periods with the goal of minimizing the overall energy consumption cost; The parameter arrangement unit is used to generate the process parameter set by arranging the obtained high-speed low-temperature parameters and low-speed high-temperature parameters in a time sequence according to their corresponding electricity price periods.

[0014] As a further aspect of the present invention: the mode switching module includes: The instruction issuing unit is used to generate timing control instructions for the high-speed low-temperature parameters and low-speed high-temperature parameters according to the corresponding time periods, and to issue them to the baking roller drive frequency converter and heating temperature control components. The feature definition unit is used to define the feature identifier of egg rolls produced at high speed and low temperature as slightly under-produced, and the feature identifier of egg rolls produced at low speed and high temperature as slightly over-produced, and integrate the corresponding moisture content data to obtain the feature reference set. The data comparison unit is used to obtain the real-time moisture content data of the baked egg rolls through the detection equipment deployed at the outlet of the baking equipment, and compare it with the feature reference set; The batch generation unit is used to generate product batch data based on the comparison results and the current order of the freshly baked egg rolls.

[0015] As a further aspect of the present invention: the scheduling generation module includes: The data receiving unit is used to receive product batch data with slight understate and slight overstate characteristics, and simultaneously acquire egg roll status parameters detected in real time by the data acquisition device. The status parameters include surface temperature and current moisture content data. The load calculation unit is used to determine the target quality parameters of the current batch of egg rolls based on the feature identifier, and to calculate the theoretical cooling load based on the current moisture content data. The instruction generation unit is used to generate a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line. The global scheduling instruction includes the conveying speed and air volume corresponding to each segment of the cooling conveyor line when the egg rolls pass through it. The execution correction unit is used to issue and execute the global scheduling instructions, and to correct parameters using real-time moisture content data obtained from various detection points deployed on the cooling conveyor line.

[0016] Compared with the prior art, the beneficial effects of the present invention are: This invention primarily addresses the problem that simply adjusting the production speed cannot reduce core heating energy consumption and would disrupt production continuity. Firstly, it employs two different heating methods for egg rolls. Responding to peak and off-peak electricity prices, it alters the energy injection method in the baking process, transferring some of the product's inherent heat to the cooling line for reuse, thereby reducing overall energy consumption, rather than simply changing the electricity usage time. Regarding production continuity, this invention utilizes the long cooling conveyor line characteristic of egg roll production. Both states of egg rolls are stored on the cooling conveyor line, forming a dynamic storage system. The baking process can flexibly adjust the temperature according to electricity prices, while the cooling process maintains production stability through this buffering mechanism. This is because egg rolls, whether slightly over- or slightly under-processed, ultimately reach a consistent quality standard on the cooling conveyor line. In summary, this invention differs from existing technologies that only focus on external electricity prices and adjusting production speed. By utilizing the unique heat transfer properties of egg roll production, it transfers energy utilization, effectively reducing overall energy consumption while ensuring stable production. Attached Figure Description

[0017] Figure 1 A flowchart illustrating an energy-saving intelligent control method for a frequency converter-driven egg roll production line.

[0018] Figure 2 This is a flowchart illustrating the process parameter set obtained in the energy-saving intelligent control method for a frequency-driven egg roll production line.

[0019] Figure 3 This is a flowchart illustrating the mode switching of the baking equipment on the time axis in the energy-saving intelligent control method for a frequency-driven egg roll production line.

[0020] Figure 4 This is a flowchart illustrating the generation of global scheduling instructions in the energy-saving intelligent control method for a frequency-driven egg roll production line.

[0021] Figure 5 This is a flowchart illustrating the generation of global scheduling instructions for each batch of egg rolls in the energy-saving intelligent control method for a frequency-driven egg roll production line.

[0022] Figure 6 This is a schematic diagram of the energy-saving intelligent control system for a frequency conversion drive egg roll production line.

[0023] Figure 7 This is a schematic diagram of the parameter calculation module in the energy-saving intelligent control system of a frequency-driven egg roll production line.

[0024] Figure 8 This is a schematic diagram of the mode switching module in the energy-saving intelligent control system of a frequency-driven egg roll production line.

[0025] Figure 9 This is a schematic diagram of the scheduling and generation module in the energy-saving intelligent control system of a frequency-driven egg roll production line. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0027] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0028] like Figure 1 As shown in the figure, this invention provides an energy-saving intelligent control method for a frequency converter-driven egg roll production line, the method comprising the following steps: S100: Obtain real-time electricity price data and target output data, and calculate the process parameter set through the preset baking energy consumption dynamic model. The process parameter set includes high-speed low-temperature parameters and low-speed high-temperature parameters. The process parameter set is used to control the speed and temperature of the baking equipment in a future set time period. S200 generates corresponding instructions based on the process parameter set to control the baking equipment to switch modes on the time axis and obtain product batch data containing two feature identifiers: slightly under-state and slightly over-state. S300 generates global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters, and preset target quality parameters. These instructions are used to adjust the conveying speed and air volume of each section of the cooling conveyor line. The status parameters are obtained through data acquisition devices deployed at the entrance of the cooling conveyor line. When a production cycle is completed, the S400 acquires the cycle power consumption and output data and calculates the comprehensive energy consumption cost. By comparing the results with the prediction results of the baking energy consumption dynamic model, deviation data is generated and used to calibrate the baking energy consumption dynamic model.

[0029] In this invention, the main focus is on the problem that simply adjusting the production speed cannot reduce core heating energy consumption and would disrupt production continuity. Firstly, two different methods are used to heat the egg rolls. While responding to peak and off-peak electricity prices, the energy injection method of the baking process is changed, transferring some of the product's inherent heat to the cooling line for reuse, thereby reducing total energy consumption, rather than simply changing the electricity usage time. Regarding production continuity, this invention utilizes the long cooling conveyor line characteristic of egg roll production. Both states of egg rolls are stored on the cooling conveyor line, forming a dynamic storage system. The baking process can flexibly adjust the temperature according to electricity prices, while the cooling process maintains production stability through this buffering method. This is because egg rolls, whether slightly over- or slightly under-processed, ultimately reach a consistent quality standard on the cooling conveyor line. In summary, this invention differs from existing technologies that only focus on external electricity prices and adjusting production speed. By utilizing the unique heat transfer properties of egg roll production, energy is transferred for utilization, effectively reducing overall energy consumption while ensuring stable production. In addition, the dynamic baking energy consumption model in this invention is also an important component. Through data-driven continuous optimization, the model can be continuously improved and will continue to approach the optimal efficiency as production continues.

[0030] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of obtaining real-time electricity price data and target output data, and calculating the process parameter set through a preset baking energy consumption dynamic model, specifically includes: S101, Establish the baking energy consumption dynamic model based on the historical data of the production line, wherein the historical data includes baking speed data, baking roller temperature data and moisture content data of the egg rolls after baking; S102, when acquiring real-time electricity price data and target output data, the flowability data of the current batch of batter is collected by sensors deployed on the batter conveying pipeline; S103, input real-time electricity price data, target output data and liquidity data into the baking energy consumption dynamic model, and solve for the comprehensive energy consumption cost minimization to obtain the high-speed low temperature parameters and low-speed high temperature parameters corresponding to different electricity price periods; S104, Based on the obtained high-speed low-temperature parameters and low-speed high-temperature parameters, the process parameter set is generated by arranging them in time sequence according to their corresponding electricity price periods.

[0031] This invention describes in detail how the process parameter set is obtained. Firstly, historical data can be collected from previous production or obtained from experiments, mainly including baking speed, baking temperature, oven moisture content, and their corresponding relationships. The established baking energy consumption model can better describe the mathematical relationship between baking speed, roller temperature, and initial moisture content of the egg rolls. To ensure the accuracy of the model, this embodiment also introduces batter data, i.e., the fluidity data, because the state of the batter also affects baking in actual production. Then, optimization algorithms (such as linear programming) are used to back-calculate the precise combination of process parameters to be used during different electricity price periods in the future. For example, during peak electricity price periods, a high-speed, low-temperature parameter of "50 meters per minute, roller temperature 185°C" is used, while during off-peak electricity price periods, a low-speed, high-temperature parameter of "40 meters per minute, roller temperature 195°C" is used. Finally, these solved parameters are arranged and packaged according to their corresponding future time windows to generate a process parameter set that can directly drive the production line.

[0032] like Figure 3 As shown, in a preferred embodiment of the present invention, the step of generating corresponding instructions based on the process parameter set to control the baking equipment to switch modes on the time axis specifically includes: S201, the high-speed low-temperature parameters and the low-speed high-temperature parameters are used to generate timing control commands according to the corresponding time periods, and the commands are sent to the baking roller drive frequency converter and the heating temperature control component. S202 defines egg rolls produced at high speed and low temperature as feature identifiers of the slightly under-state and egg rolls produced at low speed and high temperature as feature identifiers of the slightly over-state, and integrates the moisture content data corresponding to the two to obtain a feature reference set. S203: The real-time moisture content data of the baked egg rolls is obtained by the detection equipment deployed at the outlet of the baking equipment, and compared with the feature reference set; S204, Generate product batch data based on the comparison results and the current order of freshly baked egg rolls.

[0033] In this embodiment of the invention, after obtaining the set of process parameters, two different states of egg rolls are produced. The main difference lies in the moisture content. For ease of explanation, the parameters from the previous embodiment are used. During peak electricity price periods, high-speed, low-temperature parameters of "speed 50 meters per minute, roller temperature 185°C" are sent to the frequency converter controlling the rotation of the baking rollers and the heating temperature control components. This switches the production line to a high-speed, low-temperature mode, resulting in egg rolls in a slightly under-moisturized state. Similarly, during off-peak electricity price periods, the production line switches to a low-speed, high-temperature mode, resulting in egg rolls in a slightly over-moisturized state. It should be noted that these egg rolls are not individual units but exist in batches. The two different states of egg rolls are defined based on moisture content; that is, different baking modes will result in egg rolls with different moisture contents. To ensure consistency between theoretical design and actual output and to assign a precise identity to each batch of products, a near-infrared moisture meter (detection device) at the baking roller outlet will detect the real-time moisture content of each batch of egg rolls coming out of the oven. Then, the measured data will be automatically compared, and the batch of egg rolls will be marked with features based on the comparison results. For example, when a batch of egg rolls is marked as slightly deficient, its baking time, baking mode, and other information will be combined to generate a structured product batch data.

[0034] like Figure 4 As shown, in a preferred embodiment of the present invention, the step of generating global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters, and preset target quality parameters specifically includes: S301, Receive product batch data with slight understate and slight overstate characteristics, and simultaneously acquire egg roll status parameters detected in real time by data acquisition equipment, the status parameters including surface temperature and current moisture content data. S302, determine the target quality parameters of the current batch of egg rolls based on the feature identifier, and calculate the theoretical cooling load based on the current moisture content data; S303, generate a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line. The global scheduling instruction includes the conveying speed and air volume corresponding to each segment of the cooling conveyor line when the egg rolls pass through it. S304, issue and execute the global scheduling instruction, and correct the parameters using real-time moisture content data obtained from various detection points deployed on the cooling conveyor line.

[0035] In this embodiment of the invention, for ease of explanation of the production control process, it is assumed that specific product batch data (characterized by a slightly insufficient state) has been obtained. Then, the state parameters of this batch of egg rolls are captured in real time by a high-resolution thermal imager and an online moisture sensor deployed at the cooling line inlet, obtaining the surface temperature and current moisture content data. At this point, the target quality parameter (the final moisture content that the egg rolls should achieve) is retrieved for calculation. The theoretical cooling load required to uniformly cool this batch of egg rolls to the target level can be calculated using a built-in heat and mass transfer model. The theoretical cooling load is calculated using the following formula: ; in, For the quality of egg roll batches, For the specific heat capacity of egg rolls, and These are the furnace exit temperature and the target temperature, respectively. and These are the moisture content at the furnace exit and the target moisture content, respectively. This refers to the latent heat of vaporization of water. In practical applications, this parameter can be acquired in real time through production line sensors and combined with historical data. Dynamic calibration is performed on physical property parameters.

[0036] Then, taking into account the urgency of the theoretical cooling load, the existing stock of egg roll batches on each segment of the cooling conveyor line, their locations, and their own cooling progress, operations research calculations are performed based on the principles of optimal overall energy efficiency and minimum queuing time. A targeted global scheduling instruction can be generated for different batches of egg rolls. This instruction is not a single speed value, but a detailed spatiotemporal function that explicitly specifies the speed and airflow of each segment of the cooling line for that batch of egg rolls. After the instruction is issued, the moisture content of the batch of egg rolls is continuously tracked by several moisture monitoring points set up in the middle and end of the cooling line. When the moisture content of the batch of egg rolls changes abnormally, the operating parameters of subsequent segments of the cooling conveyor line are automatically adjusted. This ensures that regardless of the initial state, all egg rolls can accurately reach the preset quality target when exiting the cooling line, while simultaneously optimizing the overall energy consumption and processing efficiency of the entire cooling system.

[0037] like Figure 5 As shown, in a preferred embodiment of the present invention, the step of generating a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line specifically includes: S313, obtain real-time order data and create a list of manageable inventory based on the egg roll's inventory level; S323 calculates the outbound priority for each batch of egg rolls in the processable inventory list; S333, the cooling strategy is decided based on the theoretical cooling load, characteristic identifiers and outbound priority of each batch of egg rolls; S343 combines the decision results into a global scheduling instruction and sends it to each segment of the cooling conveyor line for execution.

[0038] It should be noted that the outbound priority is determined based on at least one of the following: order urgency, delivery time, and customer level. The cooling strategy specifically includes: for egg roll batches in a slightly overloaded state with high priority, generating a first-type cooling instruction that can complete the cooling process in the shortest time; for egg roll batches in a slightly overloaded state with low priority, generating a second-type cooling instruction that ensures minimal energy consumption; for egg roll batches in a slightly underloaded state with high priority, based on their outbound priority and theoretical cooling load, obtaining the wind speed adjustment coefficient through a preset mapping table, generating a third-type cooling instruction that can increase airflow; and for egg roll batches in a slightly underloaded state with low priority, generating a fourth-type cooling instruction that allows them to remain on the cooling conveyor line with the lowest airflow and the longest possible duration.

[0039] In this embodiment of the invention, the real-time order data can come from Enterprise Resource Planning (ERP) or Manufacturing Execution System (MES). Based on the current inventory, location, and respective characteristic identifiers and moisture status of all egg roll batches on the cooling conveyor line, products whose moisture content has met the standard or can meet the standard in subsequent cooling are selected, forming a dynamic and processable inventory list, which is equivalent to establishing a real-time updated "callable resource map". When calculating priorities, it is not simply processed according to the first-in, first-out rule, but rather a dynamic and quantitative outbound priority is calculated for each batch in the list based on multiple factors such as the urgency of the order (e.g., delivery date), customer level, and order value. The introduction of priority makes controlling the cooling conveyor line more complex. This will be explained in detail using four cooling strategies. When a batch of egg rolls is marked as slightly over-cooled and associated with an urgent export order, all fans in the cooling path will run at full speed, and the conveyor belt speed will be adjusted to maximum to complete cooling in the shortest possible time—this is the first type of cooling instruction. For batches also in a slightly over-cooled state but with a lower outbound priority, the goal becomes minimizing energy consumption. The system will calculate an energy-optimal cooling path, such as using a lower, segmented, variable-speed airflow to ensure moisture content meets standards while minimizing total fan power consumption. Crucially, for batches marked as slightly under-cooled but with a high outbound priority, it is necessary to utilize waste heat for energy saving. To achieve a balance between accelerating cooling to meet delivery requirements, a pre-defined "priority-load-wind speed coefficient" mapping table is consulted based on the specific outbound priority value and theoretical cooling load of the batch. This yields a wind speed adjustment coefficient k greater than 1. Subsequently, based on the calculated baseline slow cooling wind speed, the airflow of each segment is multiplied by the coefficient k, generating an accelerated third-type cooling command. For batches in a slightly under-cooled state with low outbound priority, the decision objective is to maximize waste heat utilization for deep energy saving. A fourth-type cooling command can then be used to allow the batch to move at the lowest permissible transport speed and allocate the minimum necessary airflow (even relying solely on natural convection in some sections), allowing it to remain on the cooling line for an extended period, fully utilizing its own waste heat to evaporate moisture. Finally, these commands are arranged in spatiotemporal order to form a global scheduling command set that coordinates the collaborative operation of all segments of the cooling line, and then distributed to each frequency converter for execution.

[0040] like Figure 6 As shown in the figure, this embodiment of the invention also provides an energy-saving intelligent control system for a frequency conversion driven egg roll production line, the system comprising: The parameter calculation module 100 is used to acquire real-time electricity price data and target output data, and calculate the process parameter set through a preset baking energy consumption dynamic model. The process parameter set includes high-speed low-temperature parameters and low-speed high-temperature parameters. The process parameter set is used to control the speed and temperature of the baking equipment in a future set period. The mode switching module 200 is used to generate corresponding instructions based on the process parameter set, to control the baking equipment to switch modes on the time axis, and to obtain product batch data containing two feature identifiers: slightly under-state and slightly over-state. The scheduling generation module 300 is used to generate global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters and preset target quality parameters. It is used to adjust the conveying speed and air volume of each section of the cooling conveyor line. The status parameters are obtained by data acquisition equipment deployed at the entrance of the cooling conveyor line. The model calibration module 400 is used to acquire cycle power consumption and output data and calculate the comprehensive energy consumption cost when a production cycle is completed. It generates deviation data by comparing the prediction results with the baking energy consumption dynamic model, which is used to calibrate the baking energy consumption dynamic model.

[0041] like Figure 7 As shown, in a preferred embodiment of the present invention, the parameter calculation module 100 includes: The model building unit 101 is used to build the baking energy consumption dynamic model based on the historical data of the production line. The historical data includes baking speed data, baking roller temperature data, and moisture content data of the egg rolls after baking. The data acquisition unit 102 is used to collect the flowability data of the current batch of batter by means of sensors deployed on the batter conveying pipeline when acquiring real-time electricity price data and target output data; The optimization and solution unit 103 is used to input real-time electricity price data, target output data and liquidity data into the baking energy consumption dynamic model, and solve for the comprehensive energy consumption cost minimization to obtain high-speed low-temperature parameters and low-speed high-temperature parameters corresponding to different electricity price periods. The parameter arrangement unit 104 is used to generate the process parameter set by arranging the obtained high-speed low-temperature parameters and low-speed high-temperature parameters in a time sequence according to their corresponding electricity price periods.

[0042] like Figure 8 As shown, in a preferred embodiment of the present invention, the mode switching module 200 includes: The instruction issuing unit 201 is used to generate timing control instructions for the high-speed low-temperature parameters and the low-speed high-temperature parameters according to the corresponding time periods, and to issue them to the baking roller drive frequency converter and the heating temperature control component. The feature definition unit 202 is used to define the feature identifier of egg rolls produced at high speed and low temperature as slightly under-produced, and the feature identifier of egg rolls produced at low speed and high temperature as slightly over-produced, and integrate the moisture content data of the two to obtain the feature reference set. The data comparison unit 203 is used to obtain the real-time moisture content data of the baked egg rolls through the detection equipment deployed at the outlet of the baking equipment, and compare it with the feature reference set; Batch generation unit 204 is used to generate product batch data based on the comparison results and the current order of the baked egg rolls.

[0043] like Figure 9 As shown, in a preferred embodiment of the present invention, the scheduling generation module 300 includes: The data receiving unit 301 is used to receive product batch data with slight understate and slight overstate feature identifiers, and simultaneously acquire egg roll status parameters detected in real time by the data acquisition device. The status parameters include surface temperature and current moisture content data. The load calculation unit 302 is used to determine the target quality parameters of the current batch of egg rolls based on the feature identifier, and to calculate the theoretical cooling load based on the current moisture content data. The instruction generation unit 303 is used to generate a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line. The global scheduling instruction includes the conveying speed and air volume corresponding to each segment of the cooling conveyor line when the egg rolls pass through each segment. The execution correction unit 304 is used to issue and execute the global scheduling command, and to correct the parameters using real-time moisture content data obtained from various detection points deployed on the cooling conveyor line.

[0044] The above description only details the preferred embodiments of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0045] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0046] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0047] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the disclosure in the specification and embodiments. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. An energy-saving intelligent control method for a variable frequency drive egg roll production line, characterized in that, The method includes the following steps: Real-time electricity price data and target output data are obtained, and a set of process parameters is calculated through a preset baking energy consumption dynamic model. The set of process parameters includes high-speed low-temperature parameters and low-speed high-temperature parameters. The set of process parameters is used to control the speed and temperature of the baking equipment in a future set time period. Based on the process parameter set, corresponding instructions are generated to control the baking equipment to switch modes on the time axis and obtain product batch data containing two feature identifiers: slightly under-state and slightly over-state. Based on product batch data, status parameters, and preset target quality parameters, global scheduling instructions are generated for egg rolls with different characteristic identifiers. These instructions are used to adjust the conveying speed and air volume of each section of the cooling conveyor line. The status parameters are obtained through data acquisition equipment deployed at the entrance of the cooling conveyor line. When a production cycle is completed, the cycle power consumption and output data are obtained and the comprehensive energy consumption cost is calculated. The deviation data is generated by comparing it with the prediction results of the baking energy consumption dynamic model, which is used to calibrate the baking energy consumption dynamic model.

2. The energy-saving intelligent control method for a variable frequency drive egg roll production line according to claim 1, characterized in that, The steps of acquiring real-time electricity price data and target output data, and calculating the process parameter set through a preset baking energy consumption dynamic model, specifically include: The baking energy consumption dynamic model is established based on historical data from the production line, including baking speed data, baking roller temperature data, and moisture content data of the egg rolls after baking. When acquiring real-time electricity price data and target output data, the flowability data of the current batch of batter is collected by sensors deployed on the batter delivery pipeline; Real-time electricity price data, target output data, and liquidity data are input into the baking energy consumption dynamic model. The goal is to minimize the overall energy consumption cost to obtain the high-speed low-temperature parameters and low-speed high-temperature parameters corresponding to different electricity price periods. Based on the obtained high-speed low-temperature parameters and low-speed high-temperature parameters, the process parameter set is generated by arranging them in time sequence according to their corresponding electricity price periods.

3. The energy-saving intelligent control method for a variable frequency drive egg roll production line according to claim 1, characterized in that, The step of generating corresponding instructions based on the process parameter set to control the baking equipment to switch modes on the time axis specifically includes: The high-speed low-temperature parameters and the low-speed high-temperature parameters are used to generate timing control commands according to the corresponding time periods, and these commands are sent to the baking roller drive frequency converter and the heating temperature control component. Egg rolls produced at high speed and low temperature are defined as feature markers of the slightly under-produced state, and egg rolls produced at low speed and high temperature are defined as feature markers of the slightly over-produced state. The corresponding moisture content data of the two are integrated to obtain a feature reference set. The real-time moisture content data of the baked egg rolls is obtained by the detection equipment deployed at the outlet of the baking equipment, and compared with the feature reference set. Product batch data is generated based on the comparison results and the current order of the freshly baked egg rolls.

4. The energy-saving intelligent control method for a variable frequency drive egg roll production line according to claim 1, characterized in that, The step of generating global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters, and preset target quality parameters specifically includes: Receive product batch data with slightly under and slightly over states as identifiers, and simultaneously acquire egg roll state parameters detected in real time by data acquisition equipment, including surface temperature and current moisture content data. The target quality parameters for the current batch of egg rolls are determined based on the feature identifiers, and the theoretical cooling load is calculated based on the current moisture content data. Based on the theoretical cooling load and the inventory on the cooling conveyor line, a global scheduling instruction is generated for each batch of egg rolls. The global scheduling instruction includes the conveying speed and air volume corresponding to each segment of the cooling conveyor line when the egg rolls pass through it. The global scheduling command is issued and executed, and the parameters are corrected using real-time moisture content data obtained from various detection points deployed on the cooling conveyor line.

5. The energy-saving intelligent control method for a variable frequency drive egg roll production line according to claim 4, characterized in that, The step of generating a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line specifically includes: Obtain real-time order data and create a list of manageable inventory based on the egg roll's stock level; Calculate the outbound priority for each batch of egg rolls in the processable inventory list; Cooling strategy decisions are made based on the theoretical cooling load, characteristic identifiers, and outbound priority of each batch of egg rolls; The decision results are combined into a global scheduling command, which is then sent to each segment of the cooling conveyor line for execution.

6. The energy-saving intelligent control method for a variable frequency drive egg roll production line according to claim 5, characterized in that, The cooling strategy specifically includes: When the egg roll batch is in a slightly over-processed state and has a high priority, generate a first-class cooling instruction that can complete the cooling process in the shortest time. When the egg roll batch is in a slightly overloaded state and has a low priority, generate a second type of cooling instruction that can ensure minimal energy consumption. When the egg roll batch is in a slightly under-cooled state and has a high priority, the wind speed adjustment coefficient is obtained through a preset mapping table based on its outbound priority and theoretical cooling load, and a third type of cooling instruction that can increase the air volume is generated. When the egg roll batch is in a slightly deficient state and has a low priority, a fourth type of cooling instruction is generated that allows it to remain on the cooling conveyor line with the lowest airflow and the longest duration.

7. An energy-saving intelligent control system for a frequency conversion drive egg roll production line, characterized in that: The system includes: The parameter calculation module is used to acquire real-time electricity price data and target output data, and calculate the process parameter set through a preset baking energy consumption dynamic model. The process parameter set includes high-speed low temperature parameters and low-speed high temperature parameters. The process parameter set is used to control the speed and temperature of the baking equipment in a future set period. The mode switching module is used to generate corresponding instructions based on the process parameter set, which are used to control the baking equipment to switch modes on the time axis and obtain product batch data containing two feature identifiers: slightly under-state and slightly over-state. The scheduling generation module is used to generate global scheduling instructions for egg rolls with different feature identifiers based on product batch data, status parameters and preset target quality parameters. It is used to adjust the conveying speed and air volume of each section of the cooling conveyor line. The status parameters are obtained through data acquisition equipment deployed at the entrance of the cooling conveyor line. The model calibration module is used to acquire cycle power consumption and output data and calculate the comprehensive energy cost when a production cycle is completed. It generates deviation data by comparing the prediction results with the baking energy consumption dynamic model, which is used to calibrate the baking energy consumption dynamic model.

8. The energy-saving intelligent control system for the variable frequency drive egg roll production line according to claim 7, characterized in that, The parameter calculation module includes: The model building unit is used to build the baking energy consumption dynamic model based on the historical data of the production line. The historical data includes baking speed data, baking roller temperature data, and moisture content data of the egg rolls after baking. The data acquisition unit is used to collect flow data of the current batch of batter by means of sensors deployed on the batter delivery pipeline when acquiring real-time electricity price data and target output data; The optimization solution unit is used to input real-time electricity price data, target output data and liquidity data into the baking energy consumption dynamic model, and solves the high-speed low temperature parameters and low-speed high temperature parameters corresponding to different electricity price periods with the goal of minimizing the overall energy consumption cost; The parameter arrangement unit is used to generate the process parameter set by arranging the obtained high-speed low-temperature parameters and low-speed high-temperature parameters in a time sequence according to their corresponding electricity price periods.

9. The energy-saving intelligent control system for a variable frequency drive egg roll production line according to claim 7, characterized in that, The mode switching module includes: The instruction issuing unit is used to generate timing control instructions for the high-speed low-temperature parameters and the low-speed high-temperature parameters according to the corresponding time periods, and to issue them to the baking roller drive frequency converter and the heating temperature control component. The feature definition unit is used to define the feature identifier of egg rolls produced at high speed and low temperature as slightly under-produced, and the feature identifier of egg rolls produced at low speed and high temperature as slightly over-produced, and integrate the corresponding moisture content data to obtain the feature reference set. The data comparison unit is used to obtain the real-time moisture content data of the baked egg rolls through the detection equipment deployed at the outlet of the baking equipment, and compare it with the feature reference set; The batch generation unit is used to generate product batch data based on the comparison results and the current order of the freshly baked egg rolls.

10. The energy-saving intelligent control system for a variable frequency drive egg roll production line according to claim 7, characterized in that, The scheduling generation module includes: The data receiving unit is used to receive product batch data with slight understate and slight overstate characteristics, and simultaneously acquire egg roll status parameters detected in real time by the data acquisition device. The status parameters include surface temperature and current moisture content data. The load calculation unit is used to determine the target quality parameters of the current batch of egg rolls based on the feature identifier, and to calculate the theoretical cooling load based on the current moisture content data. The instruction generation unit is used to generate a global scheduling instruction for each batch of egg rolls based on the theoretical cooling load and the inventory on the cooling conveyor line. The global scheduling instruction includes the conveying speed and air volume corresponding to each segment of the cooling conveyor line when the egg rolls pass through it. The execution correction unit is used to issue and execute the global scheduling instructions, and to correct parameters using real-time moisture content data obtained from various detection points deployed on the cooling conveyor line.

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