A temperature control system of a sea cucumber low-temperature curing digital workshop

Abstract

The present application relates to the technical field of aquatic processing control, and in particular to a temperature control system of a sea cucumber low-temperature curing digital workshop. By obtaining the water temperature sequence at the entrance of the curing tank and determining all disturbance buffer zones, the sensible heat load of the material and the latent heat characteristics of the ice core phase change are separated; the energy deficit of each batch of water is calculated according to the temperature change of each disturbance buffer zone, the expected temperature sequence is constructed according to the temperature difference distribution, the temperature return hysteresis area is determined according to the discrete deviation of the expected sequence and the measured sequence, and the energy deficit and the hysteresis area are coupled and analyzed to obtain the skin overheating factor of each disturbance buffer zone; according to the difference distribution of the skin overheating factors of the buffer zones, the corresponding conveying belt running speed is determined, the accurate identification and adaptive speed reduction compensation control of the ice-containing raw materials are realized, and the quality problem of external rotting and internal generation in the processing of frozen materials is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of aquatic product processing control technology, specifically to a temperature control system for a digital workshop for low-temperature cooking of sea cucumbers. Background Technology

[0002] Continuous low-temperature cooking of sea cucumbers is a crucial step in modern pre-prepared seafood production. Its core technology involves using constant-temperature hot water to denature the collagen in the sea cucumber's body wall to fix its texture. This process demands extremely strict temperature control: excessively high water temperatures or prolonged heating can lead to over-hydrolysis of collagen, causing skin ulceration (commonly known as "skin rot"); insufficient water temperatures or heating will result in undenatured internal proteins, leading to undercooked sea cucumbers. In actual production, the variation in the state of the raw materials is a major factor causing inconsistent quality, especially the difference in the degree of thawing. Fully thawed fresh sea cucumbers, upon entering the cooking tank, exhibit a rapid increase in sensible heat and a quick rise in water temperature. However, frozen sea cucumbers containing unthawed ice cores undergo a prolonged solid-liquid phase transition in the early stages of cooking, continuously absorbing significant latent heat while maintaining their own temperature near freezing, resulting in a significant plateau in the temperature rise of the surrounding water.

[0003] Existing control methods primarily rely on PID controllers to adjust steam valves to maintain water temperature, but the production line conveyor belt always operates at a fixed speed. In continuous production scenarios with intermittent feeding (such as cage-type or conveyor belts with large batch intervals), when a large amount of heat-absorbing material (frozen material) enters, the ice nuclei require additional time to melt. However, the fixed conveyor belt speed cannot extend the residence time of the material in the water, leading to a significant drop in water temperature. Traditional PID controllers cannot physically distinguish between sensible heat absorption (large material quantity) and latent heat phase change (material containing ice). They mistakenly interpret the low-temperature lag caused by ice nuclei as insufficient heating power, incorrectly increasing the steam supply. Meanwhile, the production line conveyor belt speed remains unchanged, resulting in overheating and rotting of the outer layer. The ice nuclei, due to insufficient time, remain unmelted, forming defective products with "outer rot and inner defects," thus reducing product quality. Summary of the Invention

[0004] To address the technical problem that existing control methods struggle to dynamically adjust the conveyor belt speed on production lines, leading to overheating and skin rot of the product's surface while the ice core remains unmelted due to insufficient time, thus reducing product quality, this invention aims to provide a temperature control system for a digital workshop for the low-temperature cooking of sea cucumbers. The specific technical solution adopted is as follows: This invention proposes a temperature control system for a digital workshop for low-temperature cooking of sea cucumbers, the system comprising: The data processing module is used to acquire the inlet water temperature sequence of the maturation tank and determine all disturbance buffers based on the temperature time-series changes of the inlet water temperature sequence of the maturation tank. The heat load quantification module is used to determine the energy deficit of a single batch of water based on the temperature change of each disturbance buffer; determine the expected temperature sequence based on the temperature difference distribution in each disturbance buffer; determine the reheating hysteresis area based on the discrete deviation between the expected temperature sequence and the inlet water temperature sequence of the maturation tank; and determine the skin superheating factor of each disturbance buffer based on the coupled analysis of the energy deficit of the single batch of water and the reheating hysteresis area. The decision execution module is used to determine the corresponding conveyor belt running speed based on the differential distribution of the overheating factor on the surface of each disturbance buffer.

[0005] Furthermore, the method for obtaining the perturbation buffer includes: For each sampling time in the inlet water temperature sequence of the maturation tank, the absolute difference between the temperature value at each sampling time and the temperature value at the previous sampling time is calculated as the temperature change rate at each sampling time. The sampling time corresponding to the temperature value that is greater than the preset process target constant temperature value is taken as the reference end time; the inlet water temperature sequence of the maturation tank is divided into all reference disturbance time intervals with the reference end time as the interval; In each reference perturbation time interval, the sampling time corresponding to the temperature change rate that is greater than the preset temperature change threshold is taken as the corresponding reference start time. The first reference start time in the time sequence of each reference disturbance time interval is taken as the disturbance start time; the disturbance buffer is determined based on each disturbance start time and its closest subsequent reference end time.

[0006] Furthermore, the method for calculating the energy deficit of a single batch of water includes: The difference between the temperature value at each sampling moment in the disturbance buffer and the preset process target constant temperature value is calculated as the instantaneous temperature difference; the product of the instantaneous temperature difference and the preset sampling interval is taken as the instantaneous heat loss; the instantaneous heat loss at all sampling moments in the disturbance buffer is accumulated to determine the heat loss of a single batch; the product of the heat loss of a single batch and the preset water constant is taken as the energy deficit of a single batch of water.

[0007] Furthermore, the method for obtaining the expected temperature sequence includes: Obtain the expected temperature start time, expected temperature end time, and expected total melt response rate for each perturbation buffer. Each sampling moment between the expected temperature start time and the expected temperature end time is sequentially taken as the target time. The difference between the temperature value at the expected temperature start time and the preset process target isothermal value is taken as the expected instantaneous temperature difference. The time interval between the target time and the expected temperature start time is taken as the numerator, and the expected full melt response rate is taken as the denominator. The temperature decay factor is determined by ratio calculation and negative correlation mapping. The product of the expected instantaneous temperature difference and the temperature decay factor is taken as the remaining temperature difference. The difference between the remaining temperature difference and the preset process target isothermal value is taken as the expected temperature value at the target time. Arrange the expected temperature values ​​for all target times in chronological order to determine the expected temperature sequence.

[0008] Furthermore, the method for obtaining the expected temperature start time includes: For each disturbance buffer, the sampling time corresponding to the minimum temperature in the disturbance buffer is selected as the expected temperature start time.

[0009] Furthermore, the method for obtaining the expected temperature end time includes: Obtain all reference expected temperature end times for each disturbance buffer; the temperature values ​​at the end times of the reference expected temperatures are all greater than the preset process target isothermal value; The first reference expected temperature end time in the temporal sequence of each perturbation buffer is taken as the expected temperature end time.

[0010] Furthermore, the method for calculating the expected full-melting response speed includes: The standardized value of the energy deficit of the single batch of water body is multiplied by the preset heat capacity correction coefficient as the load factor; the preset empty tank heating response benchmark is weighted and analyzed based on the load factor to determine the expected response speed of full melting.

[0011] Furthermore, the method for calculating the reheat hysteresis area includes: Each sampling moment in the expected temperature sequence is taken as the target moment. The absolute difference between the expected temperature value at the target moment and the temperature value corresponding to the water temperature sequence at the inlet of the maturation tank at the target moment is calculated as the instantaneous temperature difference at the target moment. All instantaneous temperature differences greater than the preset noise threshold are selected as the theoretical instantaneous temperature difference. The product of the theoretical instantaneous temperature difference and the time interval between two adjacent sampling moments is taken as the instantaneous deviation heat. The instantaneous deviation heat of all target moments in the disturbance buffer is accumulated to determine the reheat hysteresis area.

[0012] Furthermore, the method for obtaining the epidermal overheating factor includes: Using the heat recovery lag area as the numerator and the energy deficit of a single batch of water as the denominator, the ice core heat absorption ratio coefficient is determined by ratio calculation and normalization. The base load rate is determined by using the energy deficit of a single batch of water as the numerator and the preset single batch heat load benchmark as the denominator through ratio calculation; the sum of the ice core heat absorption ratio coefficient and the preset base value is used as the impedance correction factor; and the product of the base load rate and the impedance correction factor is used as the skin overheating factor.

[0013] Furthermore, the method for calculating the conveyor belt speed includes: For each disturbance buffer zone, the preset standard conveyor belt running speed is used as the numerator, and the maximum value of the skin overheating factor and the preset benchmark value is used as the denominator. The corresponding conveyor belt running speed is determined by ratio calculation.

[0014] The present invention has the following beneficial effects: This invention acquires the inlet water temperature sequence of the curing tank and determines the disturbance buffer zone based on the temperature time sequence change. This allows for precise extraction of the thermal response segment of each batch of material during continuous production, providing a data foundation for subsequent targeted control and solving the problem of existing technologies being unable to identify the state of a single batch of material online. By determining the expected temperature sequence and the discrete deviation between the expected temperature sequence and the inlet water temperature sequence of the curing tank, the reheat hysteresis area is determined, achieving physical-level decoupling of sensible heat load and latent heat phase change. This enables accurate quantification of the ice content inside the material, solving the problem of misjudgment caused by the inability of existing PID control to distinguish the material state. By determining the skin overheating factor, the total amount of material and ice content are uniformly quantified as risk indicators, solving the technical defect of existing control that cannot comprehensively assess the difficulty of freezing process. By dynamically adjusting the conveyor belt speed according to the differential distribution of the skin overheating factor in each disturbance buffer zone, the material residence time is automatically adjusted when ice-containing freezing parameters are detected, allowing the ice nuclei to fully melt in a low-temperature environment. This avoids accidents caused by skin overheating and rotting due to accelerating ice melting by increasing water temperature, fundamentally solving the quality problem of "outer rotting and inner growth". Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a structural diagram of a temperature control system for a digital workshop for low-temperature cooking of sea cucumbers, provided as an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a temperature control system for a digital workshop for low-temperature cooking of sea cucumbers proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The specific solution of a temperature control system for a digital workshop for low-temperature cooking of sea cucumbers provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0020] Please see Figure 1 The diagram illustrates a temperature control system structure for a digital workshop for low-temperature cooking of sea cucumbers, according to an embodiment of the present invention. The system includes: The data processing module 101 is used to acquire the inlet water temperature sequence of the maturation tank and determine all disturbance buffers based on the temperature time-series changes of the inlet water temperature sequence of the maturation tank.

[0021] In continuous feeding production, different batches of materials enter the curing tank sequentially, and their thermal response signals are continuously superimposed on the time axis. Directly analyzing the entire temperature sequence makes it impossible to isolate the temperature changes caused by a specific batch, resulting in a lack of benchmark for subsequent calculations of individual batch states. Therefore, it is necessary to first extract independent temperature change segments corresponding to each feeding event from the continuous temperature monitoring data. Because the low-temperature curing production line uses intermittent feeding, the moment low-temperature raw materials enter the curing tank, it disrupts the thermal balance of the inlet area, causing a characteristic drop in water temperature. Therefore, this invention obtains the inlet water temperature sequence of the curing tank and, based on the temporal temperature changes of this sequence, determines all disturbance buffer zones.

[0022] In one specific implementation of this invention, the system activates a high-frequency temperature sensor located in the inlet area of ​​the curing tank to continuously collect the measured water temperature value at the inlet of the curing tank. To eliminate high-frequency electromagnetic interference in the industrial environment, the system performs a moving average filtering process on the raw collected data. In this embodiment of the invention, the preset sampling interval is set to 1 second, that is, the arithmetic mean of the measured water temperature within the most recent 1 second is selected as the temperature value at the current sampling time, and the temperature values ​​at all sampling times are arranged in chronological order to determine the curing tank inlet water temperature sequence.

[0023] It should be noted that the implementation scenario of this invention is a low-temperature cooking process for sea cucumbers. For the convenience of subsequent analysis, sea cucumbers will be used as the material in the description of the following specific implementation methods.

[0024] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the perturbation buffer includes: In continuous production, the moment material enters the curing tank, it causes a characteristic drop in the inlet water temperature, which is the most direct physical signal for identifying feeding events. However, industrial sites are subject to high-frequency interference such as water turbulence and sensor noise. If feeding is determined solely by a single temperature drop, false triggering is highly likely. Therefore, this invention calculates the absolute difference between the temperature value at each sampling moment and the temperature value at the previous sampling moment in the curing tank inlet water temperature sequence, using this as the temperature change rate at each sampling moment. The sampling moment corresponding to the temperature value greater than the preset process target constant temperature value is used as the reference end moment. The curing tank inlet water temperature sequence is divided into all reference disturbance time intervals with the reference end moments as the intervals. This indicates that the heat absorption process of this batch of material on the water body has basically ended and the system thermal balance has been restored. The current sampling moment is then marked as the disturbance end moment, thus completely covering the entire process of this batch of material from entry to thermal balance.

[0025] In each reference disturbance time interval, the sampling time corresponding to the temperature change rate greater than the preset temperature change threshold is taken as the corresponding reference start time. This situation means that a significant cooling event has occurred, which is usually caused by thermal shock caused by cold materials entering the water body.

[0026] The first reference start time in the time sequence within each reference disturbance time series interval is taken as the disturbance start time, representing the first time the cold material is added in the current disturbance time series interval. Using this as the disturbance start time allows for immediate identification of the point where the material is added. Based on each disturbance start time and its closest subsequent reference end time, a disturbance buffer is determined. This not only preserves the complete thermal response trajectory of the batch of material but also eliminates invalid data that interferes with each batch. Each disturbance buffer corresponds to a batch of material added in the working scenario, providing a clean and accurate data foundation for subsequent calculations of the heat load and analysis of the ice-containing state of a single batch of material.

[0027] It should be noted that, in order to prevent the defined reference disturbance time series interval from exceeding the data (i.e., the inlet water temperature sequence of the curing tank), in this embodiment of the invention, the last sampling time of the inlet water temperature sequence of the curing tank is also used as the reference end time; if there is no reference start time in the reference disturbance time series interval, that is, the temperature change rate of all sampling times in the interval is less than or equal to the preset temperature change threshold, then the reference disturbance time series interval is marked as "conveyor belt empty" and will not participate in the subsequent analysis.

[0028] In one specific implementation of this invention, to reduce the impact of temperature changes on material quality, the preset temperature change threshold is set to 0.2. It can be adjusted according to the specific implementation scenario; the preset process target is set to 90. It can be adjusted according to the production formula of the production line.

[0029] The heat load quantification module 102 is used to determine the energy deficit of a single batch of water based on the temperature change of each disturbance buffer; determine the expected temperature sequence based on the temperature difference distribution in each disturbance buffer; determine the reheating hysteresis area based on the discrete deviation between the expected temperature sequence and the inlet water temperature sequence of the maturation tank; and determine the skin superheating factor of each disturbance buffer based on the coupled analysis of the energy deficit of the single batch of water and the reheating hysteresis area.

[0030] Considering that frozen sea cucumbers may thaw on the surface but contain ice cores in the center, traditional surface infrared thermometry methods cannot identify this. However, during the low-temperature cooking process, the sea cucumber raw material's entry into the high-temperature water body instantly disrupts the thermal equilibrium, causing a drop in water temperature. Due to the different degrees of thawing of the raw material (completely thawed versus containing ice internally), the disturbances to water temperature caused by the raw material have fundamentally different physical mechanisms. Completely thawed material absorbs heat in the form of sensible heat, resulting in a rapid rise in water temperature; while material containing ice needs to absorb a large amount of latent heat due to the melting of the ice core, which will hinder the rise in water temperature for a longer period of time. However, traditional control methods can only sense instantaneous temperature differences and cannot distinguish between these two forms of heat absorption. If compensation is based solely on the magnitude of the temperature drop, it is very easy to misjudge the heat of the ice-containing raw material. Therefore, this invention determines the energy deficit of a single batch of water body based on the temperature change of each disturbance buffer zone, converting temperature changes into a quantifiable heat load index, providing a unified energy benchmark for all subsequent analyses.

[0031] However, knowing only the total heat absorbed by the material is insufficient to distinguish whether that heat is used for heating the material (fresh sea cucumber) or melting ice nuclei (frozen sea cucumber). Considering the different impacts of the two on processing time, heating the material only requires heating, while melting ice nuclei requires additional time for the ice nuclei to slowly melt. To separate the two, a reference system in an ice-free state needs to be established. Therefore, this invention determines the expected temperature sequence based on the differential distribution of each disturbance buffer zone. Considering the difference between the measured temperature in the ripening tank inlet water temperature sequence and the predicted temperature in the expected temperature sequence, the thermal hysteresis effect caused by the ice nucleus phase transition is directly quantified. However, temperature measurement data in industrial settings are often superimposed with high-frequency noise such as water flow turbulence and steam valve operation, resulting in drastic instantaneous temperature fluctuations. If the instantaneous deviation value is used directly for judgment, it is easy to make misjudgments due to noise interference, and it is impossible to reliably identify weak but continuous phase transition characteristics. To solve this detection robustness problem, this invention abandons the dependence on instantaneous fluctuations and determines the reheat hysteresis area based on the discrete deviation between the expected temperature sequence and the ripening tank inlet water temperature sequence.

[0032] After identifying the presence of ice in the material (i.e., a large lag area), the system faces a core physical contradiction: the sea cucumber's skin is extremely heat-sensitive, and raising the water temperature will immediately cause skin damage (skin rot); however, melting the ice core requires a large amount of heat and time. Traditional heating compensation strategies attempt to exacerbate skin thermal damage in exchange for the melting of the internal ice core, which is the root cause of "external rot and internal defects." To resolve this contradiction, this invention uses a coupled analysis of the single-batch water energy deficit and the reheat lag area to determine the skin overheating factor for each disturbance buffer zone. This factor comprehensively assesses the thermal burden that the sea cucumber's skin must withstand under current operating conditions to ensure the sea cucumber's central maturation (especially the melting of the ice core).

[0033] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the energy deficit of a single batch of water includes: Since heat transfer is a power integral over time, simply monitoring the temperature difference (i.e., heat flux density) at a single moment is like judging the length of a journey using only "instantaneous velocity," which is too simplistic. Therefore, this invention calculates the difference between the temperature value at each sampling moment in the disturbance buffer and the preset process target constant temperature value as the instantaneous temperature difference; the product of the instantaneous temperature difference and the preset sampling interval is taken as the instantaneous heat deficit, linking the temperature difference with the action time, so that the contribution of each sampling point to the total heat loss is accurately quantified; by accumulating the instantaneous heat deficit at all sampling moments in the disturbance buffer, the heat deficit of a single batch is determined, which is used to characterize the total amount of heat absorbed by the batch of material from the water body during the entire process from entering to thermal equilibrium; considering that although the heat deficit of a single batch can reflect the relative magnitude of heat exchange, it is not a strict physical energy value and cannot be directly compared with physical parameters such as system heat capacity and rated load in subsequent calculations, this invention takes the product of the heat deficit of a single batch and the preset water body constant as the energy deficit of a single batch of water body.

[0034] In one specific implementation of this invention, the instantaneous temperature difference at each sampling moment is obtained by subtracting the temperature value at each sampling moment from the preset process target constant temperature value; the preset water constant integrates the inherent physical properties of the water in the curing tank, such as density, specific heat capacity, and circulation flow rate, and can be obtained through on-site calibration experiments during the equipment commissioning phase.

[0035] It should be noted that, in order to prevent the subsequent algorithm from overflowing or misjudging due to small single-batch water energy deficits calculated by sensor drift, minor fluctuations in water flow, or non-productive micro-feeding, the system introduces a minimum effective load threshold. Each disturbance buffer is analyzed: if the single-batch water energy deficit is less than or equal to the minimum effective load threshold, the system determines the current disturbance as invalid noise, directly terminates the subsequent calculation process for the current batch, maintains the existing control state, and waits for the next feeding event; if the single-batch water energy deficit is greater than the minimum effective load threshold, the system confirms that the batch is a valid production batch and continues to execute subsequent steps.

[0036] In one specific implementation of this invention, to eliminate interference from sensor drift, minor fluctuations in water flow, or non-productive micro-feeding, the minimum effective load threshold is set to 10% of a preset single-batch heat load benchmark. The calibration process for the preset single-batch heat load benchmark is as follows: At a standard conveying speed, the system feeds in a batch of fully thawed standard fresh sea cucumbers (ice-free) of known mass. The system records the water temperature drop and recovery process caused by this batch, calculates its total heat absorption, and stores it as the preset single-batch heat load benchmark.

[0037] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the expected temperature sequence includes: The purpose of the expected temperature sequence is to compare it point-by-point with the inlet water temperature sequence of the maturation tank; therefore, both must have the same start and end points in the time domain. Thus, this invention obtains the expected temperature start time, expected temperature end time, and expected response speed of complete melting for each disturbance buffer zone. Since the process of water temperature rising from its lowest point to the target value is essentially a first-order inertial process of heat energy being input through the heater and diffused into the water, according to the principles of heat transfer, this process is typically characterized by approaching the set value exponentially, rather than rising nonlinearly. Using simple linear interpolation or a fixed slope as the expected benchmark will significantly deviate from the actual physical process, leading to systematic biases when extracting phase change characteristics. Therefore, this invention performs energy correction by obtaining the expected full melt response rate, which includes the influence of the current feed rate on thermal inertia. Each sampling time between the expected temperature start time and the expected temperature end time is taken as the target time, and the difference between the expected temperature start time and the preset process target isothermal value is taken as the expected instantaneous temperature difference. Considering that during the thermal equilibrium recovery process, the difference between the current temperature and the target temperature (i.e., the remaining temperature difference) is not constant but negatively correlated over time, the time interval between each target time and the expected temperature start time is used as the numerator, and the expected full melt response rate is used as the denominator. Through ratio calculation and negative correlation mapping, a temperature decay factor is determined. This factor quantifies the proportion of the initial temperature difference that has not been offset by thermal inertia and heating after a certain time from the starting point. This demonstrates that by using a dynamic expected full melt response rate as a time constant specific to this batch, this invention eliminates the physical extension of the recovery time caused by the use of a fixed time constant in traditional methods, which leads to an increase in feed rate. The product of the expected instantaneous temperature difference and the temperature decay factor is taken as the residual temperature difference, which represents the difference between the water temperature and the preset process target constant temperature value at the current moment. Finally, the difference between the residual temperature difference and the preset process target constant temperature value is taken as the expected temperature value at the target moment, which represents the instantaneous value that the water temperature in the inlet area of ​​the maturation tank should ideally reach under the assumption that there are no ice nuclei inside the material (i.e., all of it is sensible heat and endothermic heat). In order to facilitate subsequent point-by-point comparison with the maturation tank inlet water temperature sequence, all the expected temperature values ​​at the target moment are arranged in chronological order to determine the expected temperature sequence.

[0038] In one specific implementation of this invention, the expected instantaneous temperature difference at each target time is obtained by subtracting the temperature value at each target time from the preset process target constant temperature value.

[0039] As an example, the first Expected temperature value at each target time The calculation formula can be expressed as: in, This indicates the preset target isothermal value; This indicates the temperature value at the initial moment of the expected temperature. Indicates the target time The time interval between the expected temperature start time and the time interval between the start time of the expected temperature. Indicates the expected response speed of full melting; This represents the expected instantaneous temperature difference; considering that the temperature difference decays exponentially over time during the thermal equilibrium recovery process, this invention will... As a temperature decay factor; This indicates the remaining temperature difference.

[0040] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the expected temperature start time includes: Within the disturbance buffer zone, the water temperature change can be divided into two distinct phases: the first phase is a continuous temperature decrease after the material enters, during which the heat absorption power of the material exceeds the heating power, and the system is in a period of unsteady energy deficit accumulation; the second phase is a temperature rebound after the water temperature reaches its lowest point, during which the heating power begins to dominate, and the system enters a natural temperature recovery period aimed at restoring equilibrium. The mathematical description of the first-order inertial response model presupposes that the system converges towards the target value from a certain initial steady state or extreme point. Therefore, for each disturbance buffer zone, this invention selects the sampling time corresponding to the minimum temperature within the disturbance buffer zone as the expected temperature starting time.

[0041] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the expected temperature end time includes: Once the water temperature rises and reaches the preset process target constant temperature value again, the system has returned to thermal equilibrium. At this time, subsequent temperature data points fluctuate slightly in the vicinity, belonging to the steady-state adjustment phase. During the steady-state adjustment phase, the actual temperature may be slightly higher than the process target constant temperature value due to a slight overshoot of the controller. If a first-order exponential model is forcibly used to fit the part higher than the target value, a mathematical contradiction will occur (the exponential model can only asymptotically approach the target value, but cannot exceed it). Therefore, this invention obtains all reference expected temperature end times for each disturbance buffer; the temperature values ​​of the reference expected temperature end times are all greater than the preset process target constant temperature value; considering that there will be multiple sampling times in the disturbance buffer where the temperature value is greater than the preset process target constant temperature value, that is, multiple reference expected temperature end times will occur; the first reference expected temperature end time in the temporal sequence in each disturbance buffer is taken as the expected temperature end time.

[0042] In one specific implementation of this invention, for each disturbance buffer, the system acquires the temperature value of each sampling time after the expected temperature start time, selects the sampling time with a temperature value greater than the preset process target constant temperature value as the reference expected temperature end time, and takes the first reference expected temperature end time in the temporal sequence of each disturbance buffer as the expected temperature end time.

[0043] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the expected full-melting response rate includes: Considering that the increase in system thermal inertia depends not only on the mass of the material but also on the inherent properties such as the heat exchange efficiency between the material and the water, and the specific heat capacity of the material, and to eliminate dimensional differences between different equipment, this invention uses the product of the standardized value of the single-batch water energy deficit and the preset heat capacity correction coefficient as the load factor. Since the preset empty tank heating response benchmark characterizes the inherent heating rate of the maturation tank under no-load conditions, the addition of material increases the total heat capacity of the system, inevitably resulting in a slower actual response speed than under no-load conditions. Therefore, this invention performs a weighted analysis on the preset empty tank heating response benchmark based on the load factor to determine the expected full-melting response speed. This parameter is a dynamically adjusted time constant, and its value is positively correlated with the current batch feed amount. The larger the feed amount, the larger the expected full-melting response speed, meaning a flatter expected recovery curve. Substituting this time constant into the subsequent exponential model, the generated expected temperature sequence naturally includes the physical law that "a large feed amount leads to a slow recovery." When the measured curve is compared with the expected curve, the deviation between the two will be mainly attributed to the ice nucleus phase transition, rather than the influence of the feed scale, thus achieving physical-level decoupling of sensible heat load and latent heat load.

[0044] In one specific implementation of this invention, since different specifications of curing equipment have different design capacity, water volume, and heating power, directly using the absolute value of the energy deficit of a single batch of water to standardize it would result in a lack of portability of the control model between different devices. Therefore, this embodiment of the invention uses the energy deficit of a single batch of water as the numerator and a preset single batch heat load benchmark as the denominator, and determines the standardized value of the energy deficit of a single batch of water through ratio calculation. The preset single batch heat load benchmark has been obtained through calibration during the single batch water energy deficit acquisition stage.

[0045] Considering that the energy deficit of a single batch of water is zero when no material passes through the curing tank, this embodiment of the invention introduces a constant 1. The sum of the standardized value of the energy deficit of a single batch of water and 1 is used as a correction factor to avoid violating physical common sense, as the water's response to the heating command still has an inherent time delay even without load. When material enters the curing tank, the total heat capacity of the system consists of the water's own heat capacity and the material's additional heat capacity. Correspondingly, the system's response time constant should also be the superposition of the no-load basic thermal inertia and the load-added thermal inertia. Therefore, this embodiment of the invention uses the product of the correction factor and the preset empty tank heating response benchmark as the expected response speed for full melting. The calibration process of the preset empty tank heating response benchmark is as follows: the system controls the steam valve opening to perform a step change (in this embodiment, it is set from 0% to 50%), and the sensor records the water temperature rise curve. The curve was fitted with a first-order inertial element using the least squares method, and the time constant was extracted and stored as a preset empty tank heating response benchmark. This parameter characterizes the inherent response rate of the water temperature to the heating command when no sea cucumber raw material passes through the current maturation tank.

[0046] It should be noted that the least squares method and first-order inertial element fitting are both techniques well known to those skilled in the art, and will not be limited or elaborated upon here.

[0047] To ensure that the expected response speed of full melting accurately reflects the impact of feed rate on thermal inertia in subsequent online calculations, a preset heat capacity correction coefficient must be pre-calibrated. This coefficient characterizes the relative rate of change of the time constant caused by a unit standardized load increment. The calibration process is based on a control experiment with a known load, and the specific steps are as follows: The system feeds a batch of fully thawed standard fresh ginseng (without ice cores) of known mass at a standard conveying speed, records the actual warming process caused by this batch, and extracts its warming time constant. Since this batch of material is ice-free, its actual warming time constant is the theoretical warming rate that should be expected under this load. Substituting this measured value and the corresponding rated load value of this batch into the formula for calculating the expected full-thaw response rate, a preset heat capacity correction coefficient is obtained. This coefficient quantifies the increase in system thermal inertia caused by the increase in unit feed volume and is solidified for use in subsequent online production to dynamically estimate the expected full-thaw response rate based on the real-time detected load value.

[0048] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the reheat hysteresis area includes: In industrial settings, measured temperature curves are often superimposed with high-frequency noise such as water flow turbulence and steam valve operation. Directly using instantaneous deviations for judgment can easily lead to misjudgments due to noise interference, making it impossible to reliably identify weak but continuous phase transition characteristics. Therefore, this invention sequentially uses each sampling moment in the expected temperature sequence as the target moment, calculating the absolute difference between the expected temperature value at the target moment and the corresponding temperature value in the ripening tank inlet water temperature sequence at the target moment. This is taken as the instantaneous temperature difference at the target moment. This index quantifies the lag of the actual warming process relative to the "ice-free ideal state" at each time segment. When the material is fresh ginseng, the actual curve closely follows the expected curve, with the difference fluctuating around zero. When the material is frozen ginseng, the actual curve remains consistently lower than the expected curve due to ice nucleus heat absorption, forming a continuous positive deviation. Then, all instantaneous temperature differences greater than a preset noise threshold are selected as theoretical instantaneous temperature differences, ensuring that only deviations significantly exceeding the normal fluctuation range are considered deterministic signals caused by ice nucleus phase transitions; while minute fluctuations filtered out by the threshold are considered noise and disregarded.

[0049] Since the temperature deviation at a single moment only characterizes the hysteresis intensity at that instant and cannot reflect the persistence of the phase change process, the time dimension must be taken into account in order to quantify the total impact of ice nucleus heat absorption throughout the entire recovery cycle. Therefore, this invention uses the product of the theoretical instantaneous temperature difference and the time interval between two adjacent sampling moments as the instantaneous deviation heat; by accumulating the instantaneous deviation heat of all target moments in the perturbation buffer, the recovery hysteresis area is determined. This index quantifies the total delay in water temperature recovery caused by phase change behavior (ice nucleus melting) in a two-dimensional plane of time and temperature domains for this batch of materials.

[0050] In one specific implementation of this invention, the preset noise threshold is set to 0.2. Its acquisition principle is the same as the preset temperature change threshold setting principle in the disturbance buffer, and can be adjusted according to the specific implementation scenario.

[0051] Preferably, in some possible implementations of the embodiments of the present invention, the method for obtaining the epidermal overheating factor includes: Since the hysteresis area is essentially the projection of the additional heat absorption caused by ice core melting onto the temperature-time plane, its dimensions are... The energy deficit of a single batch of water represents the total heat absorbed by that batch of material from the water, with dimensions of [missing value]. (Joules) have different dimensions. Therefore, this invention uses the hysteresis area of ​​the reheating as the numerator and the energy deficit of the single batch of water as the denominator. By performing ratio calculations and normalization, the influence of dimensions is eliminated, and the ice core heat absorption ratio coefficient is finally determined.

[0052] In one specific implementation of this invention, a gain coefficient is introduced, wherein the dimensions of the gain coefficient are... The value is 1. By calculating the product of the gain coefficient and the above ratio, the ice core heat absorption ratio coefficient is ensured to be a dimensionless constant. Based on the ice core heat absorption ratio coefficients corresponding to historical disturbance buffers, the Min-Max normalization algorithm is used to map each ice core heat absorption ratio coefficient to the range [0,1]. The minimum and maximum values ​​in the Min-Max normalization algorithm can be obtained by statistically analyzing the minimum and maximum values ​​of the ice core heat absorption ratio coefficients of all historical disturbance buffers. The ice core heat absorption ratio coefficient measures the phase change retardation component in a unit heat load. The closer the ice core heat absorption ratio coefficient is to 0, the more it indicates that the material's thermal response conforms to the sensible heat model, and it is judged as fully thawed fresh ginseng. If the ice core heat absorption ratio coefficient is significantly greater than 0 (e.g., greater than 0.8), it indicates that the material has significant phase change retardation, and it is judged as containing frozen ginseng.

[0053] It should be noted that other normalization methods, such as mean normalization, may also be used in other implementations of the embodiments of the present invention, which are not limited or elaborated here.

[0054] Since the preset single-batch heat load benchmark represents the nominal heat load that the equipment can efficiently handle under its designed capacity, it is the matching point between the equipment's heat exchange capacity and the designed processing speed. Therefore, this invention uses the single-batch water energy deficit as the numerator and the preset single-batch heat load benchmark as the denominator, and determines the base load rate through ratio calculation. This base load rate is used to characterize the total amount of material in the current batch, relative to the equipment's designed capacity. The larger the base load rate, the longer the heating time required to complete heat exchange for this batch of material at the same transfer speed. This indicator eliminates the influence of ice-containing factors and quantifies the benchmark requirement for heating time purely from the dimension of the total amount of material. Considering that even if the material is completely ice-free, i.e., the ice nucleus heat absorption ratio is 0, heat transfer from the water to the center of the material still needs to overcome inherent thermal resistance and consume a certain amount of time. The ice nucleus heat absorption ratio quantifies the additional heat transfer resistance caused by the presence of ice nuclei: the melting of ice nuclei requires the absorption of a large amount of latent heat, but in a constant temperature environment, the driving force of heat conduction (the temperature difference between the water temperature and the ice nucleus) is fixed. Therefore, ice-containing materials require a longer heat conduction time to complete the phase change. Therefore, this invention uses the sum of the ice core heat absorption ratio coefficient and the preset baseline value as the impedance correction factor; at the same time, the actual heating time required is determined by both the total demand and the impedance, and the two are multiplicative rather than additive. If the material quantity is large and the ice content is high, the extension of the heating demand is an amplification of both. Therefore, this invention uses the product of the baseline load rate and the impedance correction factor as the skin overheating factor.

[0055] It should be noted that the skin overheating factor directly determines the speed control of the subsequent conveyor belt. The larger the skin overheating factor, the longer the heating time required. If the original speed is maintained, the risk of skin overheating is higher. Therefore, the conveying speed must be reduced accordingly to prolong the residence time of the material in the water and realize the risk avoidance strategy of trading space for time.

[0056] The decision execution module 103 is used to determine the corresponding conveyor belt running speed based on the differential distribution of the overheating factor of each disturbance buffer skin.

[0057] The surface overheating factor, acquired by the heat load quantification module 102, is a comprehensive indicator of the heating difficulty and risk level of the current batch of materials. However, this indicator itself does not directly produce a control effect; the system must convert it into executable process parameter adjustment instructions to truly achieve optimized intervention in the production process. Among many adjustable parameters, the conveyor belt speed is the most direct and effective control method because it determines the physical residence time of the material in the water. The surface overheating factor directly characterizes the heating time required for the current batch of materials (i.e., the current disturbance buffer) to achieve complete curing, relative to standard operating conditions. Therefore, this invention determines the corresponding conveyor belt speed based on the differential distribution of the surface overheating factor in each disturbance buffer.

[0058] Preferably, in some possible implementations of the embodiments of the present invention, the method for calculating the conveyor belt running speed includes: For each disturbance buffer, the preset standard conveyor operating frequency is used as the numerator, and the maximum value of the skin overheating factor and the preset benchmark value is used as the denominator. The corresponding conveyor belt operating speed is determined by ratio calculation.

[0059] The skin overheat factor is physically defined as the multiple of the heating time required for the current batch of material to achieve complete curing relative to standard operating conditions. Based on fundamental kinematics, with a fixed heating path length, the conveyor belt speed is inversely proportional to the material residence time, and correspondingly, the conveyor belt speed is also inversely proportional to the skin overheat factor. To prevent uneven curing caused by conveyor belt overspeed operation under low-risk conditions, the system calculates the requested conveyor belt speed command for the current batch based on an inverse proportional control law with a lower limit constraint.

[0060] Specifically, for each disturbance buffer zone, the preset standard conveyor belt running speed is used as the numerator, and the maximum value of the skin overheating factor and the preset benchmark value is used as the denominator. The corresponding conveyor belt running speed is determined by ratio calculation.

[0061] In one specific implementation of this invention, the preset standard conveyor belt speed is set to 0.02. The parameters are obtained from the equipment's design capacity and can be adjusted according to the specific implementation scenario. Setting the preset benchmark value to 1 means that when the skin overheat factor is less than or equal to 1, it indicates that the current batch of materials consists of fully thawed fresh ginseng, and the denominator is 1. At this time, the conveyor belt speed maintains the preset standard conveyor belt speed to ensure capacity. When the skin overheat factor is greater than 1, it indicates that the current batch of materials contains frozen ginseng. The larger the skin overheat factor, the higher the content of frozen ginseng, which poses a risk of overload or ice core blockage. The requested speed is reduced by the reciprocal of the skin overheat factor, which prolongs the heating time of this batch of materials in water, thereby avoiding the situation of undercooked ginseng.

[0062] It should be noted that on a continuous production line with intermittent feeding, multiple batches may be at different stages of maturation simultaneously (e.g., batch A is in the middle of the tank, while batch B has just passed the inlet). To resolve the conflicting speed requirements of different batches and ensure food safety, the system implements a fallback control strategy that prioritizes lower speeds.

[0063] Specifically, the system selects the minimum conveyor belt speed of all currently online batches (i.e., batches that have not yet left the ripening tank) as the real-time speed of the current conveyor belt. Simultaneously, the system continuously tracks the position of each batch. When a batch requesting lower speed (such as a frozen sea cucumber batch) leaves the ripening tank, the system automatically re-acquires all currently online batches, thus dynamically updating the conveyor belt speed. This speed adjustment strategy ensures that if any batch on the line is a difficult-to-cook frozen sea cucumber (requesting lower speed), the entire line must slow down to ensure that the frozen sea cucumber batch is fully cooked. For easily cooked fresh sea cucumber batches on the same line, although they will undergo a longer hot water soaking time due to the reduced speed (potentially slightly overcooked), in the sea cucumber processing process, "thorough cooking and sterilization" takes precedence over "perfect taste." Furthermore, since the water temperature is always strictly controlled at the target constant temperature value, slight over-soaking will not lead to catastrophic "skin rot" accidents, which is an acceptable process compromise.

[0064] It should be noted that in the actual engineering application of the low-temperature cooking process for sea cucumbers, the cooking tank is usually composed of multiple heating process sections connected in series. The production line is typically configured as follows: an inlet section (equipped with temperature sensors for material characteristic identification), a main cooking section (completing the denaturation of the core collagen), and a heat preservation section (ensuring uniform core temperature). This multi-segment process design provides a natural timing matching basis for the spatiotemporal conversion control of this invention. This invention fully utilizes this process feature to construct a control logic of "identification in the initial stage and compensation in the subsequent stage." Specifically, when the system completes the calculation of the skin overheating factor of the current batch of material in the inlet section, the material of that batch has not yet left the inlet section and has not yet entered the subsequent main cooking section or heat preservation section. The system then issues the conveyor belt running speed. Due to the synchronous change of the overall line speed, the current batch will obtain an extended residence time matching the skin overheating factor after entering the subsequent process section.

[0065] In summary, this invention, by acquiring the inlet water temperature sequence of the curing tank and determining the disturbance buffer zone based on the temperature time sequence changes, can accurately extract the thermal response segment of each batch of material during continuous production, providing a data foundation for subsequent targeted control and solving the problem of existing technologies being unable to identify the state of a single batch of material online. By determining the expected temperature sequence and determining the reheat hysteresis area based on the discrete deviation between the expected temperature sequence and the inlet water temperature sequence of the curing tank, the physical level decoupling of sensible heat load and latent heat phase change is achieved, which can accurately quantify the ice content inside the material and solve the problem of misjudgment caused by the inability of existing PID control to distinguish the material state. By determining the skin overheating factor, the total amount of material and the ice content are uniformly quantified as risk indicators, solving the technical defect of existing control that cannot comprehensively assess the difficulty of freezing process. By dynamically adjusting the conveyor belt running speed according to the difference distribution of the skin overheating factor in each disturbance buffer zone, the material residence time is automatically adjusted when ice-containing freezing parameters are detected, so that the ice nuclei can fully melt in the low temperature environment, avoiding the accident of skin overheating and rotting caused by accelerating ice melting by increasing the water temperature, fundamentally solving the quality problem of "outer rotting and inner growth".

[0066] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A temperature control system for a digital workshop for low-temperature cooking of sea cucumbers, characterized in that, The system includes: The data processing module is used to acquire the inlet water temperature sequence of the maturation tank and determine all disturbance buffers based on the temperature time-series changes of the inlet water temperature sequence of the maturation tank. The heat load quantification module is used to determine the energy deficit of a single batch of water based on the temperature change of each disturbance buffer; determine the expected temperature sequence based on the temperature difference distribution in each disturbance buffer; determine the reheating hysteresis area based on the discrete deviation between the expected temperature sequence and the inlet water temperature sequence of the maturation tank; and determine the skin superheating factor of each disturbance buffer based on the coupled analysis of the energy deficit of the single batch of water and the reheating hysteresis area. The decision execution module is used to determine the corresponding conveyor belt running speed based on the differential distribution of the overheating factor on the surface of each disturbance buffer.

2. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 1, characterized in that, The method for obtaining the disturbance buffer includes: For each sampling time in the inlet water temperature sequence of the maturation tank, the absolute difference between the temperature value at each sampling time and the temperature value at the previous sampling time is calculated as the temperature change rate at each sampling time. The sampling time corresponding to the temperature value that is greater than the preset process target constant temperature value is taken as the reference end time; the inlet water temperature sequence of the maturation tank is divided into all reference disturbance time intervals with the reference end time as the interval; In each reference perturbation time interval, the sampling time corresponding to the temperature change rate that is greater than the preset temperature change threshold is taken as the corresponding reference start time. The first reference start time in the time sequence of each reference disturbance time interval is taken as the disturbance start time; the disturbance buffer is determined based on each disturbance start time and its closest subsequent reference end time.

3. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 1, characterized in that, The method for calculating the energy deficit of a single batch of water bodies includes: The difference between the temperature value at each sampling moment in the disturbance buffer and the preset process target constant temperature value is calculated as the instantaneous temperature difference; the product of the instantaneous temperature difference and the preset sampling interval is taken as the instantaneous heat loss; the instantaneous heat loss at all sampling moments in the disturbance buffer is accumulated to determine the heat loss of a single batch; the product of the heat loss of a single batch and the preset water constant is taken as the energy deficit of a single batch of water.

4. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 1, characterized in that, The method for obtaining the expected temperature sequence includes: Obtain the expected temperature start time, expected temperature end time, and expected total melt response rate for each perturbation buffer. Each sampling moment between the expected temperature start time and the expected temperature end time is sequentially taken as the target time. The difference between the temperature value at the expected temperature start time and the preset process target isothermal value is taken as the expected instantaneous temperature difference. The time interval between the target time and the expected temperature start time is taken as the numerator, and the expected full melt response rate is taken as the denominator. The temperature decay factor is determined by ratio calculation and negative correlation mapping. The product of the expected instantaneous temperature difference and the temperature decay factor is taken as the remaining temperature difference. The difference between the remaining temperature difference and the preset process target isothermal value is taken as the expected temperature value at the target time. Arrange the expected temperature values ​​for all target times in chronological order to determine the expected temperature sequence.

5. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 4, characterized in that, The method for obtaining the expected temperature start time includes: For each disturbance buffer, the sampling time corresponding to the minimum temperature in the disturbance buffer is selected as the expected temperature start time.

6. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 5, characterized in that, The method for obtaining the expected temperature end time includes: Obtain all reference expected temperature end times for each disturbance buffer; the temperature values ​​at the end times of the reference expected temperatures are all greater than the preset process target isothermal value; The first reference expected temperature end time in the temporal sequence of each perturbation buffer is taken as the expected temperature end time.

7. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 4, characterized in that, The method for calculating the expected response speed of the full melting includes: The standardized value of the energy deficit of the single batch of water body is multiplied by the preset heat capacity correction coefficient as the load factor; the preset empty tank heating response benchmark is weighted and analyzed based on the load factor to determine the expected response speed of full melting.

8. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 1, characterized in that, The method for calculating the reheat hysteresis area includes: Each sampling moment in the expected temperature sequence is taken as the target moment. The absolute difference between the expected temperature value at the target moment and the temperature value corresponding to the water temperature sequence at the inlet of the maturation tank at the target moment is calculated as the instantaneous temperature difference at the target moment. All instantaneous temperature differences greater than the preset noise threshold are selected as the theoretical instantaneous temperature difference. The product of the theoretical instantaneous temperature difference and the time interval between two adjacent sampling moments is taken as the instantaneous deviation heat. The instantaneous deviation heat of all target moments in the disturbance buffer is accumulated to determine the reheat hysteresis area.

9. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 1, characterized in that, The method for obtaining the epidermal overheating factor includes: Using the heat recovery lag area as the numerator and the energy deficit of a single batch of water as the denominator, the ice core heat absorption ratio coefficient is determined by ratio calculation and normalization. The base load rate is determined by using the energy deficit of a single batch of water as the numerator and the preset single batch heat load benchmark as the denominator through ratio calculation; the sum of the ice core heat absorption ratio coefficient and the preset base value is used as the impedance correction factor; and the product of the base load rate and the impedance correction factor is used as the skin overheating factor.

10. The temperature control system for a digital workshop for low-temperature cooking of sea cucumbers according to claim 1, characterized in that, The method for calculating the conveyor belt speed includes: For each disturbance buffer zone, the preset standard conveyor belt running speed is used as the numerator, and the maximum value of the skin overheating factor and the preset benchmark value is used as the denominator. The corresponding conveyor belt running speed is determined by ratio calculation.

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