An intelligent collaborative control system for processing goat milk products

Abstract

The present application relates to the technical field of dairy product processing control, and discloses an intelligent collaborative control system for goat milk product processing, which comprises a conveying module, a homogenizing module, a heat exchange module and a control unit. The homogenizing module is located downstream of the conveying module and is provided with a high-pressure homogenizer and a pressure transmitter. The heat exchange module is located downstream of the homogenizing module and is provided with a heat exchanger, a temperature transmitter and a proportional regulating valve. The control unit is configured to calculate the pure lag time of fluid micro-aggregates according to the collected instantaneous mass flow to establish a time window, align the pressure parameter of the same fluid micro-aggregate in the homogenizing module with the temperature parameter in the heat exchange module, and generate a dynamic micro-aggregate level shear-thermal stress coupling index accordingly. When the index reaches a critical threshold, the opening of the proportional regulating valve is locked and the working pressure of the high-pressure homogenizer is simultaneously reduced. The present application avoids control overshoot caused by single temperature adjustment and reduces the risk of thermal denaturation of goat milk protein.

Description

Technical Field

[0001] This invention relates to the field of dairy product processing control technology, specifically to an intelligent collaborative control system for goat milk product processing. Background Technology

[0002] In the industrial processing of goat milk products, the materials need to undergo high-pressure homogenization to refine the fat globules, and then enter the heat exchange equipment for heating and sterilization. The milk proteins inside goat milk are quite sensitive to heat load and mechanical shear. The current processing control system controls the homogenization process and the sterilization process as independent control nodes. That is, the homogenizer maintains the set mechanical shear intensity by adjusting the working pressure, while the sterilization heat exchanger maintains the set sterilization temperature by adjusting the opening of the heat medium valve.

[0003] However, there is a significant spatial distance and time lag in the transfer of fluid from homogenizing equipment to heat exchange equipment in the processing pipeline. When the operating conditions fluctuate, the existing system cannot correlate and evaluate the mechanical and thermal stresses borne by the same batch of materials at different processing stages. Once the outlet temperature of the heat exchange equipment deviates from the process set value, the traditional control logic can only adjust the heat medium proportional valve of the heat exchanger. Due to the inherent physical inertia of the heat conduction process, coupled with the lag effect of pipeline transmission; This one-sided temperature regulation can cause system control oscillations and temperature overshoot. The goat milk material has already absorbed a high amount of mechanical energy when passing through the high-pressure homogenizer. If it is subjected to excessive heat load due to temperature overshoot in the subsequent sterilization stage, the combined stress will exceed the stability limit of the protein, leading to thermal denaturation of the goat milk protein and affecting product quality. In addition, when dealing with fluctuations in operating conditions, some conventional control schemes will try to adjust the sterilization intensity by changing the material delivery flow rate. However, simply reducing the flow rate will cause the fluid velocity inside the pipeline to decrease. When the fluid inside the pipeline deviates from the turbulent state, the material close to the pipe wall will have protein adhesion due to insufficient kinetic energy and uneven heating, causing pipeline scaling problems and shortening the continuous operation cycle of the processing equipment. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an intelligent collaborative control system for goat milk product processing. This system solves the problem that in existing goat milk processing, the pressure control in the homogenization stage and the temperature control in the sterilization stage are independent, making it impossible for the system to accurately align and assess the mechanical shear and thermal stress experienced by the same fluid, and thus failing to achieve coordinated response between equipment. This can lead to heat denaturation of goat milk proteins or scaling in pipelines.

[0005] To achieve the above objectives, the present invention provides the following technical solution: This invention provides an intelligent collaborative control system for goat milk product processing, comprising: The conveying module is equipped with a centrifugal material conveying pump connected to a frequency converter and a Coriolis mass flow meter for collecting instantaneous mass flow rate. The homogenization module, located downstream of the conveying module, is equipped with a high-pressure homogenizer with a hydraulic power unit and a diaphragm pressure transmitter for collecting pressure parameters. The heat exchange module, located downstream of the homogenization module, is equipped with a plate heat exchanger. The plate heat exchanger is equipped with a multi-point thin-film temperature transmitter that collects multi-point measured temperatures as temperature parameters and a proportional regulating valve. At the end, a pneumatic sterile diversion valve is provided. The control unit, connected to the aforementioned components, is configured to execute the following logic: calculate the pure time lag of the fluid micro-particle based on the instantaneous mass flow rate and physical volume parameters; A time window is established based on the pure lag time to align the pressure parameters of the same fluid micro-particle in the homogenizing module with the temperature parameters in the heat exchange module. Dynamic micro-group-level shear-thermal stress coupling index is generated based on the aligned pressure and temperature parameters. When the dynamic micro-cluster level shear-thermal stress coupling index reaches the critical threshold, the opening of the proportional regulating valve is locked and a pressure reduction command is sent to the hydraulic power unit.

[0006] This invention discretizes continuous fluid into fluid micro-elements and utilizes pure time lag and time window mechanisms to achieve spatiotemporal alignment of fluid state parameters between the homogenization module and the heat exchange module. Based on this, the system can quantitatively evaluate the comprehensive stress on the fluid. When the coupling index reaches a threshold, the system actively locks the heat exchange control and reduces the upstream homogenization pressure. By reducing the total load input, the system avoids temperature overshoot caused by simply adjusting the heat exchanger, thereby reducing the risk of protein thermal denaturation.

[0007] Furthermore, the control unit aligns the pressure and temperature parameters of the same fluid micro-particle in the following manner: A time window containing Gaussian distribution weights is generated by extending a preset width forward and backward from the theoretical timestamp of the fluid micro-particle arriving at the heat exchange module; Gaussian distribution weights are calculated for historical sampling points within the time window, and the historical mechanical shear pressure differences recorded by the homogenizing module within the time window are weighted and summed to obtain the equivalent mechanical shear parameter; the equivalent mechanical shear parameter is associated with the temperature parameter collected by the heat exchange module at the current moment and stored in a spatiotemporal matrix.

[0008] To address the axial back-mixing phenomenon of fluids within pipelines, this solution uses a Gaussian distribution model to weight historical sampling data, compensating for positional deviations caused by fluid diffusion and improving the accuracy of pressure and temperature parameter alignment.

[0009] Furthermore, the temperature parameter is the reconstructed temperature; the process by which the control unit obtains the reconstructed temperature includes: performing data aggregation processing on the multi-point measured temperatures using an internal arithmetic averaging algorithm to generate a global average measured temperature; and using a first-order differential compensation algorithm to process the global average measured temperature to eliminate thermal response hysteresis, thereby generating the reconstructed temperature.

[0010] Due to the influence of the thermal capacity and thermal resistance of the temperature sensor hardware structure, the measured temperature exhibits a thermal response hysteresis phenomenon. This solution uses a first-order differential compensation algorithm to perform phase lead correction on the measured temperature, compensating for thermal delay error, thereby more accurately reflecting the transient temperature of the fluid in the pipeline.

[0011] Furthermore, the process by which the control unit generates the dynamic micro-cluster level shear-thermal stress coupling index includes: extracting the equivalent mechanical shear parameters and the transient temperature gradient corresponding to the reconstructed temperature of the fluid micro-cluster in the spatiotemporal matrix, and performing dimensionless processing based on the reference working pressure and the reference heating gradient, respectively; establishing a historical sliding window in the time dimension, and performing integral weighted calculation on the dimensionless equivalent mechanical shear parameters and the transient temperature gradient to generate the dynamic micro-cluster level shear-thermal stress coupling index.

[0012] The dimensionless processing eliminates the dimensional differences between pressure and temperature gradients, and the integration calculation is combined with historical sliding window to quantitatively reflect the mechanical and thermal loads accumulated by the fluid during the processing.

[0013] Furthermore, the control unit is also configured to: simultaneously monitor the working pressure baseline of the high-pressure homogenizer during the continuous issuance of the pressure reduction command; when the working pressure of the high-pressure homogenizer drops to the preset minimum homogenization pressure limit, and the dynamic micro-cluster level shear-thermal stress coupling index remains higher than the critical threshold within a preset delay period, output a rework switching command to the pneumatic sterile diversion valve, so that the current material enters the rework module.

[0014] Setting a lower limit for homogenization pressure is used to maintain basic process homogenization. When continuous pressure reduction fails to restore the coupling index to normal, the system determines that the current regulation has failed and controls the diversion valve to switch, importing unqualified materials into the rework module to prevent defective materials from entering downstream processes.

[0015] Furthermore, the control unit is also configured to: within the same issuance cycle of the pressure reduction command, activate the feedforward loop to issue a frequency reduction command to the frequency converter to reduce the instantaneous mass flow rate; calculate the Reynolds number at the current internal flow velocity of the pipeline in real time, and when the Reynolds number reaches a preset critical turbulent Reynolds number baseline, cut off the frequency reduction command to maintain the current instantaneous mass flow rate.

[0016] By reducing the homogenization pressure and the material flow rate, the residence time of the material in the sterilization section can be extended to ensure the sterilization effect. At the same time, the Reynolds number is introduced to control the lower limit of the flow rate, ensuring that the fluid in the pipeline is in a turbulent state and avoiding the adhesion and scaling of protein on the pipe wall due to excessively low flow rate.

[0017] Furthermore, the process by which the control unit obtains the Reynolds number includes: calling the built-in viscosity compensation curve to dynamically correct the current rheological properties of the material and obtaining the corrected dynamic viscosity; and calculating the Reynolds number based on the corrected dynamic viscosity, the instantaneous mass flow rate, the equivalent hydraulic diameter of the heat exchange pipeline, and the multi-point measured temperature.

[0018] Since the dynamic viscosity of goat milk exhibits a nonlinear characteristic with temperature, this scheme uses measured temperature to dynamically correct the dynamic viscosity, thereby improving the accuracy of Reynolds number calculation.

[0019] Furthermore, the control unit is also configured to: construct a thermodynamic lethality integral model using the temperature parameters combined with preset microbial heat resistance parameters; calculate the instantaneous lethality of the fluid microparticles in the sterilization and heat preservation section, and perform online integration calculation on the instantaneous lethality during the physical residence time of the fluid microparticles flowing through the sterilization and heat preservation section to generate a global cumulative lethality; when the global cumulative lethality is lower than the target lethality threshold, output a valve position switching command to the pneumatic aseptic diversion valve to connect the rework module.

[0020] During the process of adjusting the flow rate and pressure of the system, the cumulative lethality of the fluid is calculated online simultaneously, and material rework is performed when the value does not meet the standard to prevent insufficient sterilization intensity caused by the parameter adjustment process.

[0021] Furthermore, the control unit is also configured to: continuously monitor the dynamic micro-cluster level shear-thermal stress coupling index; when it is determined that the dynamic micro-cluster level shear-thermal stress coupling index falls back to the safe dead zone range, the global cumulative lethality reaches the target lethality threshold, the temperature parameter does not exceed the maximum temperature protection value, and is continuously maintained for no less than a preset confirmation period, cancel the locking command for the opening of the proportional regulating valve, and release the reverse pressure reduction constraint for the high-pressure homogenizer.

[0022] Setting a safety dead zone and confirmation cycle prevents the system from frequently triggering adjustment commands at critical points in the state, ensuring that control intervention can only be lifted after the equipment has stabilized in its operating condition.

[0023] Furthermore, the control unit is also configured to: after confirming that the valve position feedback signal of the pneumatic aseptic diverter valve is in a positive flow state, call a first-order inertial filtering algorithm to calculate a smooth recovery setpoint; and control the operating frequency of the frequency converter and the working pressure of the high-pressure homogenizer to gradually recover to the initial process setpoint according to the smooth recovery setpoint.

[0024] When the system restores its initial setting state, it uses a first-order inertial filtering algorithm to smooth the setting parameters, avoiding signal step abrupt changes caused by direct parameter switching and reducing the impact on the mechanical actuator.

[0025] This invention provides an intelligent collaborative control system for goat milk product processing. It has the following beneficial effects: 1. This invention reduces the risk of thermal denaturation of goat milk proteins. By calculating pure lag time and establishing a time window, this invention aligns the pressure parameters of fluid micro-elements in the homogenization module with the temperature parameters of the heat exchange module in time and space, thereby generating a dynamic micro-element-level shear-thermal stress coupling index. When this index exceeds the limit, the system actively locks the opening of the proportional regulating valve of the heat exchanger and simultaneously lowers the working pressure of the upstream high-pressure homogenizer. This control logic overcomes the control lag caused by long-distance pipeline transmission and avoids temperature overshoot caused by simply adjusting the heat source when the operating conditions are abnormal. Through linkage, the overall physical load on the material is reduced, ensuring the physical and chemical stability of the product.

[0026] 2. This invention prevents material scaling inside the heat exchange pipeline. While reducing the homogenization pressure, this invention simultaneously reduces the operating frequency of the frequency converter through the feedforward loop to reduce the instantaneous mass flow rate. In this process, a Reynolds number based on the measured temperature and dynamically corrected viscosity is introduced for bottom-level constraint. When the Reynolds number reaches the critical turbulence threshold, the flow reduction command is directly cut off. This allows the system to extend the material sterilization residence time to compensate for the reduction in heat input while forcibly maintaining the turbulent state of the fluid inside the pipe, avoiding protein adhesion and scaling on the pipe wall caused by excessively low local flow velocity.

[0027] 3. This invention ensures the sterilization quality of products during dynamic adjustment of operating conditions. This invention utilizes reconstructed temperature and microbial heat resistance parameters to construct a thermodynamic lethality integral model. During the cross-domain coordinated adjustment of pressure and flow rate in the system, the instantaneous lethality of fluid microparticles in the sterilization and heat preservation section is calculated online simultaneously. Once the calculated global cumulative lethality is lower than the target threshold, the system directly triggers the terminal pneumatic aseptic diversion valve to switch the valve position and guide the current fluid into the rework module, thus preventing unqualified materials with insufficient sterilization intensity caused by changes in control parameters from flowing into downstream processes from the physical channel. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the intelligent collaborative control system architecture of the present invention; Figure 2 This is a flowchart of the intelligent collaborative control method of the present invention; Figure 3 This is a schematic diagram of the topology and data interaction principle of the conveying module of the present invention; Figure 4 This is a schematic diagram of the homogeneous module structure topology and pressure control principle of the present invention; Figure 5 This is a schematic diagram of the physical architecture and control element arrangement of the heat exchange module of the present invention; Figure 6 This is a schematic diagram illustrating the principle of spatiotemporal mapping and data alignment of fluid micro-clusters in this invention. Figure 7 This is the logic diagram of the multi-point measured temperature dynamic compensation and stress coupling calculation of the present invention; Figure 8 This is a timing diagram of the cross-domain collaborative constraint and reverse pressure regulation of the present invention; Figure 9 This is the logic diagram of the pipeline anti-scaling feedforward control and frequency conversion cutoff of the present invention; Figure 10 This is a schematic diagram illustrating the working condition recovery path calculation and smooth adjustment principle of the present invention; Figure 11 This is a comparison curve of the sterilization temperature response under flow disturbance according to the present invention. Detailed Implementation

[0029] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] See attached document Figure 1 This invention provides an intelligent collaborative control system for processing goat milk products, the system comprising the following components: The conveying module is equipped with a centrifugal material conveying pump and a Coriolis mass flow meter. The frequency converter adjusts the speed of the centrifugal material conveying pump according to the frequency command issued by the system controller to control the basic flow rate. A pressure stabilizing buffer section and a bypass return branch are set between the centrifugal material conveying pump and the high-pressure homogenizer to keep the inlet of the high-pressure homogenizer in a continuous full-pipe feeding state. The control unit changes the actual mass flow rate entering the high-pressure homogenizer by adjusting the operating frequency of the centrifugal material conveying pump and cooperating with the flow constraint of the bypass return branch. The Coriolis mass flow meter collects the instantaneous mass flow rate in real time.

[0031] The homogenization module, downstream of the conveying module, is equipped with a high-pressure homogenizer. The high-pressure homogenizer is equipped with a hydraulic power unit. Diaphragm pressure transmitters are installed at both ends of the mechanical valve head of the high-pressure homogenizer to collect the homogenizer inlet pressure and homogenizer outlet pressure. The hydraulic power unit receives analog signals from the system controller and adjusts the proportional relief valve to change the working pressure of the high-pressure homogenizer.

[0032] The heat exchange module, downstream of the homogenization module, is equipped with a plate heat exchanger. The sterilization and heat preservation section of the plate heat exchanger is equipped with multiple thin-film temperature transmitters along the fluid flow direction to collect multiple measured temperatures. The heat medium module of the plate heat exchanger is equipped with a proportional regulating valve controlled by a PID loop. A pneumatic sterile diversion valve is connected to the end of the heat exchange module.

[0033] The control unit establishes hardware communication with frequency converters, Coriolis mass flow meters, hydraulic power units, diaphragm pressure transmitters, thin-film temperature transmitters, proportional control valves, and pneumatic aseptic diverter valves via an industrial fieldbus, so as to synchronously collect data and issue control commands at fixed intervals.

[0034] See attached document Figure 2 This invention provides an intelligent collaborative control method for processing goat milk products, the method comprising the following steps: Read the instantaneous mass flow rate, discretize the continuous fluid flowing into the high-pressure homogenizer into a sequence of fluid micro-elements containing timestamps, call the physical volume parameters between the high-pressure homogenizer and the plate heat exchanger, calculate the pure lag time of the fluid micro-elements, establish a time window containing Gaussian distribution weights based on the pure lag time and the preset axial back-mixing diffusion coefficient, and align the pressure parameters obtained by the same fluid micro-element in the homogenization module with the temperature parameters obtained by the heat exchange module on the spatiotemporal matrix through the time window.

[0035] Multiple measured temperatures are collected, and the measured temperatures are processed by a first-order differential compensation algorithm to eliminate thermal response hysteresis and generate reconstructed temperatures. The pressure parameters of the corresponding fluid micro-elements and the transient temperature gradients corresponding to the reconstructed temperatures are extracted from the spatiotemporal matrix, and the dynamic micro-element-level shear-thermal stress coupling index is generated by integral weighting calculation in the time dimension.

[0036] The shear-thermal stress coupling index is compared with a preset critical threshold. When the shear-thermal stress coupling index reaches the critical threshold, a control command is output to lock the current valve opening of the proportional regulating valve of the heat medium module. A pressure reduction command is sent to the hydraulic power unit to control the hydraulic power unit to reduce the current working pressure setting value. When the current working pressure of the high-pressure homogenizer has been reduced to the preset minimum homogenization pressure limit, and the shear-thermal stress coupling index continues to be higher than the critical threshold within the preset delay period, the control unit generates an extreme value over-limit flag and directly outputs a rework switching command to the pneumatic aseptic diversion valve, so that the current material enters the rework module.

[0037] Within the same issuance cycle of the pressure reduction command, the feedforward loop is activated to send a frequency reduction command to the frequency converter to reduce the instantaneous mass flow rate. The frequency reduction is used to reduce the material throughput entering the high shear zone and high heat load zone per unit time, and to extend the effective residence time of fluid particles in the sterilization and heat preservation section, so that the system can maintain the necessary sterilization intensity while reducing mechanical shear work. The Reynolds number under the current internal flow velocity is calculated in real time. When the Reynolds number reaches the critical turbulent Reynolds number threshold, the frequency reduction command is cut off to maintain the current instantaneous mass flow rate. At the same time, the microbial lethality rate is calculated online by integration. When the microbial lethality rate is lower than the target lethality rate threshold, a valve position switching command is output to the pneumatic aseptic diversion valve to connect the rework module.

[0038] The shear-thermal stress coupling index is continuously monitored. When the index falls back to the safe dead zone, the cumulative microbial mortality rate reaches the target mortality rate threshold, the reconstruction temperature does not exceed the maximum temperature protection value, and the above conditions are met within a preset number of sampling periods, the control unit releases the rework interlock and restores the positive holding signal of the pneumatic aseptic diversion valve. After confirming that the valve position feedback signal of the pneumatic aseptic diversion valve is in a positive flow state, the first-order inertial filtering algorithm is called to calculate the recovery path parameters. According to the recovery path parameters, the inverter operating frequency and the high-pressure homogenizer working pressure are gradually restored to the initial process setting value.

[0039] See attached document Figure 3 In this embodiment, the main physical actuator of the conveying module is a centrifugal material conveying pump. The frequency converter, as an electrical drive unit, changes the frequency of the output three-phase AC power supply to adjust the actual operating speed of the motor inside the centrifugal material conveying pump. The change in motor speed drives the pump impeller to change the working head and discharge to achieve control of the basic flow rate.

[0040] The basic flow rate is the continuous feed flow rate entering the pressure stabilizing buffer section at the front end of the high-pressure homogenizer. The pressure stabilizing buffer section is used to absorb the transient pulsations caused by the periodic intake of the high-pressure homogenizer. The bypass return branch is used to return part of the material to the front balance cylinder when the inlet pressure of the high-pressure homogenizer exceeds the set range. Thus, the instantaneous mass flow rate collected by the Coriolis mass flow meter can characterize the effective material flow rate entering the homogenization process path. The voltage-frequency ratio control or space vector pulse width modulation drive link executed at the bottom layer inside the frequency converter is based on the existing motor frequency conversion control methods.

[0041] As a preferred method, the Coriolis mass flow meter is arranged in series in the pipeline downstream of the centrifugal material conveying pump. The Coriolis mass flow meter drives the measuring tube to generate high-frequency micro-vibration through the internal excitation coil and uses the Coriolis force effect to detect the phase difference signal generated when the fluid flows through the measuring tube. This detection mechanism directly reflects the true mass characteristics of the fluid and will not produce perception deviation due to changes in fluid density caused by temperature or pressure fluctuations during goat milk processing. The digital signal processing unit integrated inside the Coriolis mass flow meter converts the analog vibration signal into a digital quantity and stores it in the internal data register.

[0042] The control unit establishes a data interaction link with the transmission module through a communication network that supports the industrial fieldbus protocol. Both the frequency converter and the Coriolis mass flow meter are connected to the fieldbus network as slave nodes. The system controller cyclically sends the target operating frequency command to the frequency converter and reads the instantaneous mass flow data in the Coriolis mass flow meter register at a preset fixed sampling period. The fixed sampling period is determined based on the response limit of the frequency converter communication interface and the scanning period of the control system. The typical value range is 10 milliseconds to 50 milliseconds. The synchronization mechanism based on digital bus communication ensures that the flow sensing timestamp and the actuator command issuance timestamp are within the same command cycle at the system clock level.

[0043] After receiving the instantaneous mass flow rate, the system controller executes conversion logic to obtain the average flow velocity of the fluid inside the pipeline. The calculation logic for the average flow velocity is as follows: ; In the formula, This is the average flow velocity parameter on the cross-section of the fluid inside the pipe at the current sampling time; The parameter at the current discrete sampling time; This represents the instantaneous mass flow rate actually passing through the pipe at the current sampling moment; Pi is a mathematical constant. This is a physical dimensional constant representing the inner diameter of the flow pipe. Let be the fluid density constant of the material under operating conditions.

[0044] See attached document Figure 4 In this embodiment, the homogenization module is connected downstream of the conveying module and uses a high-pressure homogenizer as the core execution device. Diaphragm pressure transmitters are installed at both ends of the mechanical valve head of the high-pressure homogenizer. The diaphragm pressure transmitters adopt a flush diaphragm structure and are attached to the inner wall of the inlet and outlet pipelines of the high-pressure homogenizer with sanitary clamps. The front-end diaphragm pressure transmitter collects the homogenization inlet pressure in real time before the fluid is forced to compress, and the rear-end diaphragm pressure transmitter collects the homogenization outlet pressure after the fluid passes through the gap of the homogenization valve and undergoes pressure relief and expansion. The two diaphragm pressure transmitters continuously convert the sensed physical pressure into standard electrical signals and transmit them to the control unit.

[0045] As a preferred approach, the control unit receives the homogenizer inlet pressure and homogenizer outlet pressure and constructs a mechanical shear pressure difference model in its internal computational domain. The mechanical shear pressure difference characterizes the intensity of mechanical work applied by the high-pressure homogenizer to the internal fluid micro-elements. The specific calculation logic for the shear pressure difference is as follows: ; In the formula, The instantaneous pressure difference parameter generated when fluid micro-particles pass through the core execution section; The parameter at the current discrete sampling time; This refers to the transient pressure parameter at the segment inlet obtained at the current sampling time. This refers to the transient pressure parameter at the outlet end of the section obtained at the current sampling time.

[0046] The high-pressure homogenizer is equipped with a hydraulic power unit that provides the actuation power to adjust the gap of the homogenizing valve body. The control unit continuously sends electrical analog signals to the hydraulic power unit based on the output results of the upper-level collaborative control algorithm. These electrical analog signals adopt the industry standard 4 to 20 mA current signals. The electro-hydraulic proportional amplifier board built into the hydraulic power unit analyzes and amplifies the received electrical analog signals into corresponding drive currents. This drive current acts on the proportional electromagnet of the proportional relief valve. The proportional electromagnet generates a mechanical thrust proportional to the drive current based on the principle of electromagnetic induction and presses the main valve core of the proportional relief valve. The displacement of the main valve core changes the overflow cross-sectional area of ​​the hydraulic oil circuit, thereby dynamically adjusting the working pressure of the high-pressure homogenizer. The drive of the gear pump inside the hydraulic power unit and the pressure building of the basic hydraulic oil circuit are carried out according to existing conventional hydraulic transmission methods.

[0047] The electrical analog signal output by the control unit follows a defined physical mapping relationship with the actual working pressure of the high-pressure homogenizer. This mapping process transforms digital domain commands into mechanical constraints in the fluid dynamics domain. The specific physical mapping model is as follows: ; In the formula, The actual setpoint pressure value issued to the actuator; The parameter at the current discrete control cycle time; The proportional conversion gain coefficient characterizes the mapping relationship between electrical signals and mechanical pressure; The analog current parameter corresponding to the target control command output in the current control cycle; This is the pressure basis offset compensation constant used to calibrate the static zero-point deviation of the system.

[0048] See attached document Figure 5In this embodiment, the heat exchange module is connected downstream of the homogenization module and includes a plate heat exchanger and a matching flow direction control component. The sterilization and heat preservation section of the plate heat exchanger is arranged with multiple thin-film temperature transmitters in an array distribution strategy along the fluid flow direction. This distribution method can capture the heat gradient change characteristics of the fluid in the pipeline during the axial advancement process. The thin-film temperature transmitters are attached to the outer wall of the heat preservation pipeline at preset physical intervals to continuously collect the local node temperature analog values.

[0049] The control unit establishes an equivalent temperature compensation relationship between the measured value of the outer wall of the thin-film temperature transmitter, the thermal resistance of the pipe wall, the inner diameter of the pipe, the current flow rate, and the reference fluid temperature inside the pipe through calibration tests. The temperature analog quantity output by the thin-film temperature transmitter is compensated and used as the equivalent fluid temperature at the corresponding location for subsequent calculations. The multi-point thin-film temperature transmitter synchronously transmits the acquired analog quantity to the input module inside the control unit. The input module converts the continuous electrical signal into a digital quantity for the control unit to summarize and process to generate a representative measured temperature that reflects the overall thermodynamic state of the sterilization and heat preservation section.

[0050] As a preferred approach, the control unit internally performs data aggregation processing on multi-point measured temperatures using an arithmetic averaging algorithm. This averaging process effectively smooths out measurement noise and local hotspot deviations present in a single sensor in a physical sense. When multi-point measured temperatures are used for spatiotemporal alignment at the fluid micro-cluster level, the control unit does not directly average all temperature nodes at once, but rather, based on the... The transmission lag time is calculated for the actual physical volume between each temperature sensor node and the homogenization module, and an alignment relationship between pressure and temperature parameters is established for each temperature node. After node-level alignment is completed, the control unit generates a representative reconstructed temperature based on the position weight of each temperature node within the sterilization and insulation section. The specific convergence calculation model is as follows: ; In the formula, The global average measured temperature is synthesized from multiple data acquisitions at the heat exchange module. The parameter at the current discrete sampling time; The constant representing the total number of temperature sensor nodes deployed on the heat exchange pipeline; An index variable is added to the sequence representing a single sensor node; For the first The raw measured temperature value output by each sensor node at the current sampling time.

[0051] The heat medium module of the plate heat exchanger is equipped with a proportional regulating valve connected to the steam or hot water pipeline. The control unit has a built-in temperature PID control loop that continuously reads the global average measured temperature. It compares the global average measured temperature with the target process temperature preset and issued by the host computer system. Based on the deviation, the control unit performs calculations and outputs basic valve opening commands. The specific valve opening command calculation logic is as follows: ; In the formula, These are the servo adjustment command parameters output by the continuous-time model controller. For continuous physical time parameters; The proportional gain coefficient is set internally to control the algorithm; The instantaneous deviation parameter between the system setpoint and the feedback value at the current moment; To control the integral gain coefficient set internally within the algorithm; The differential feedforward gain coefficient is set internally to control the algorithm.

[0052] At the end of the heat exchange module, a pneumatic sterile diversion valve driven by a pneumatic actuator is arranged. Under normal processing conditions, the pneumatic sterile diversion valve maintains the cylinder pressurization state and guides the fluid to the forward flow pipeline to enter the next processing step. The pneumatic sterile diversion valve adopts a fail-safe structure that allows rework after power failure. During normal processing, the control unit outputs a holding signal to the matching control solenoid valve, so that the control solenoid valve is energized and maintains the cylinder pressurization.

[0053] When the control unit determines that the current operating condition triggers the interlock condition, the control system loses power, or the holding signal is revoked, the control solenoid valve loses power and reverses, cutting off the compressed air source of the pneumatic aseptic diverter valve and connecting the exhaust port to release the internal pressure of the cylinder. The reset spring inside the pneumatic aseptic diverter valve releases mechanical potential energy to push the internal main valve stem to move downward quickly. This mechanical displacement cuts off the physical channel for materials to flow to the forward flow pipeline and simultaneously opens the bypass interface of the reprocessing module. The goat milk products flowing through the end of the heat exchange module are diverted by the valve body and flow back to the front balance cylinder for secondary circulation processing.

[0054] See attached document Figure 6 In this embodiment, the control unit reads the instantaneous mass flow rate obtained by the delivery module and discretizes the continuous fluid flowing into the homogenization module into a set of fluid micro-clusters containing sequence timestamps in the internal computing area. Considering the migration characteristics of the continuous fluid in the processing pipeline in terms of time and space dimensions, the control unit extracts the physical position of the homogenization module performing the shearing action as the starting coordinate and extracts the physical position of the heat exchange module collecting multiple measured temperatures as the ending coordinate. By extracting the physical parameters between these starting and ending coordinates, a precise parameter basis is established for the subsequent reconstruction of the physical field boundary conditions.

[0055] As a preferred method, the control unit uses the physical volume parameters between the start and end coordinates to calculate the pure time delay of the fluid particle as it flows through that section of the pipeline. When the instantaneous mass flow rate is within a stable fluctuation range, the control unit uses the current instantaneous mass flow rate to calculate the pure time delay. When the frequency converter frequency decreases or increases, or the pipeline flow rate undergoes significant dynamic changes, the control unit uses the cumulative mass flow rate integration method to determine the actual arrival time of the fluid particle. That is, from the moment the fluid particle enters the starting coordinate, the mass flow rate collected by the Coriolis mass flow meter is integrated over time. When the cumulative equivalent volume converted by mass reaches the physical volume between the start and end coordinates, it is determined that the fluid particle has reached the end coordinate. The specific pure time delay calculation logic is as follows: ; In the formula, The mapping lag time for the fluid particle to migrate from the pressure acquisition position of the homogenizing module to the temperature acquisition position of the heat exchange module, as evaluated at the current sampling moment; The parameter at the current discrete sampling time; A fixed physical volume constant measured between pipeline sections; Let be the fluid density constant of the material under operating conditions; This represents the instantaneous mass flow rate actually passing through the pipe at the current sampling moment.

[0056] In actual processing environments, when fluid particles advance along pipelines, there are axial velocity differences and material exchanges. The control unit introduces a preset axial backmixing diffusion coefficient to construct a time window with Gaussian distribution weights to correct the pure lag time reference. The axial backmixing diffusion coefficient characterizes the microscopic diffusion intensity of fluid particles in the macroscopic flow direction. This coefficient is obtained by dynamically checking a preset empirical experimental mapping table based on the Reynolds number of the current pipeline.

[0057] The empirical mapping table is obtained through pipeline tracer calibration tests before commissioning. Specifically, a pulsed or step tracer signal is applied to the pipeline inlet, and the tracer response curve is recorded at the temperature acquisition location or equivalent detection location of the heat exchange module.

[0058] The residence time distribution width under different Reynolds number intervals is obtained by fitting the response curve, and the residence time distribution width is converted into the corresponding axial backmixing diffusion coefficient or Gaussian distribution variance parameter. The control unit uses this axial backmixing diffusion coefficient as the variance benchmark factor of the Gaussian distribution model. Then, a discrete time window is generated by extending a fixed width of sampling period forward and backward with the theoretical timestamp of the fluid micro-particle reaching the endpoint coordinate as the center. The width range of this time window is limited to 10% to 20% of the pure lag time to cover the actual backmixing interval of the fluid.

[0059] Based on the constructed discrete-time window, the control unit calculates Gaussian distribution weights for each historical sampling point. The specific weight allocation and alignment calculation logic is as follows: ; In the formula, For the discrete time window, the first Gaussian distribution weight parameters corresponding to each historical sampling point; A discrete integer index variable representing the sequence of historical sampling points; Pi is a mathematical constant. The diffusion variance parameter is determined by the axial backmixing diffusion coefficient mapping; For the first The actual time interval between each historical sampling point and the current calculation reference time; The first-order equivalent thermal response time constant corresponding to both the temperature sensor and the heat transfer path of the pipe wall, obtained from the calibration test; This is the parameter at the current global evaluation baseline time.

[0060] The control unit uses the calculated Gaussian weighted matrix to perform a weighted summation of the historical mechanical shear pressure difference recorded by the homogenizing module within the time window. The weighted equivalent mechanical shear parameter and the measured temperature collected by the heat exchange module at the current moment are stored as a correlation key pair in the controller's two-dimensional array buffer. The two-dimensional array buffer includes at least the fluid micro-particle number, the homogenizing module inlet timestamp, the homogenizing inlet pressure, the homogenizing outlet pressure, the equivalent mechanical shear pressure difference, the temperature sensor node number, the node physical location, the reconstructed temperature, the transient temperature gradient, the cumulative lethality, the diversion valve status flag, and the interlock status flag. In this way, the data alignment operation of multi-domain heterogeneous parameters is completed on the spatiotemporal matrix in the system memory.

[0061] See attached document Figure 7 In this embodiment, the control unit reads the global average measured temperature collected by the heat exchange module. Considering the inherent physical heat capacity and thermal resistance of the protective sleeve and internal thermistor of the thin-film temperature transmitter, the sensor inevitably produces a measurement delay when facing the temperature fluctuation of the fluid in the pipeline. This hardware-level thermal response lag causes the temperature curve obtained by the control unit to lag in phase and attenuate in amplitude. The control unit internally constructs a preprocessing stage based on the hardware dynamic characteristics and introduces a first-order differential compensation algorithm to perform phase lead correction on the measured temperature, thereby eliminating the thermal response lag and generating a reconstructed temperature that truly reflects the transient thermodynamic state of the fluid.

[0062] As a preferred approach, the first-order differential compensation algorithm executed by the control unit in the digital domain adopts a backward differential discretization form. The specific logic for reconstructing the temperature calculation is as follows: ; In the formula, The reconstructed temperature parameter is generated after phase lead correction at the current discrete sampling time. The parameter at the current discrete sampling time; This represents the global average measured temperature at the current sampling time. The first-order thermal response time constant of the temperature sensor is obtained from calibration tests; The historical global average measured temperature of the previous sampling period is recorded. The fixed discrete sampling step size parameter set for internal system operations.

[0063] After obtaining the reconstruction temperature, the control unit accesses the two-dimensional array buffer of multi-domain heterogeneous parameters based on the identification sequence of the fluid micro-particles in the system memory. The control unit extracts the equivalent mechanical shear pressure difference parameter that has been aligned in the previous steps from the spatiotemporal matrix, and simultaneously calculates the transient temperature gradient using the reconstruction temperature of the current cycle. This transient temperature gradient is defined as the first derivative of the reconstruction temperature with respect to time and characterizes the severity of the instantaneous thermal shock experienced by the fluid micro-particles in the heat exchange module. Since the pressure physical quantity characterizing mechanical work and the thermodynamic temperature gradient have different dimensions, the system performs arithmetic division on the extracted multi-domain physical quantities according to the benchmark working pressure and benchmark temperature gradient preset in the process specification before performing the calculation to complete the dimensionless processing.

[0064] The control unit establishes a time-dimensional historical sliding window to perform integral weighted calculations on the dimensionless multi-domain parameters to generate a dynamic micro-group-level shear-thermal stress coupling index. The specific integration logic of the coupling index is as follows: ; In the formula, The dynamic micro-group level shear-thermal stress coupling index generated under the current evaluation benchmark; The parameter is the current global evaluation baseline time. The historical sliding window width and duration for the set physical delay of the coverage device; Weighting coefficients assigned to the work done by mechanical shearing; This is the equivalent mechanical shear pressure difference parameter at the corresponding time within the integration interval; The reference working pressure constant used for dimensional normalization; The weighting coefficients assigned to the thermal stress variation term; The absolute transient temperature gradient parameter is used to reconstruct the temperature at the corresponding integration time. The baseline temperature gradient limit constant set for the system; The forgetting factor parameter characterizes the decay rate of system state memory; Let be the integral variable parameter used to characterize time slippage within the integration interval.

[0065] See attached document Figure 8In this embodiment, the control unit acquires the calculated dynamic micro-group level shear-thermal stress coupling index in real time, and sends the dynamic micro-group level shear-thermal stress coupling index into the boundary monitoring subroutine for continuous comparison with the preset system critical threshold. The system critical threshold is determined by the protein thermal denaturation critical rheological experiment carried out for a specific goat milk formula before production and is fixed in the register as an absolute safety boundary.

[0066] The critical rheological experiment for protein thermal denaturation involves obtaining the viscosity change rate, particle size distribution change rate, sedimentation rate, or protein denaturation rate of goat milk products under different combinations of homogenization pressure, different heating gradients, and different holding temperatures. When any of the above indicators reaches the preset quality instability criterion, the shear-thermal stress coupling index calculated under the corresponding working condition is used as the critical candidate value, and the critical threshold of the system is obtained after correction by the safety factor.

[0067] The mechanical shear weighting coefficient, thermal stress weighting coefficient, and forgetting factor are determined by fitting the quality instability results of multiple sets of calibration samples and stored in the process parameter area of ​​the control unit. When the control unit determines that the current coupling index exceeds the critical threshold of the system, it triggers the cross-domain collaborative protection mechanism. The control unit takes over the control of the heat medium module and sends a command to the positioner of the proportional control valve to lock the current valve opening. Conventional PID algorithms will cause integral saturation under the condition of continuous temperature deviation. While locking the valve opening, the control unit simultaneously suspends the integral term accumulation process of the PID calculation unit and switches the control mode from automatic closed loop to opening hold state.

[0068] As a preferred approach, the control unit activates the reverse constraint logic for the upstream homogenizing module while locking the heat input of the heat exchange module. The comprehensive stress on the fluid micro-element consists of thermodynamic stress and mechanical work. Based on the objective fact that temperature rise and fall have a large inertial physical lag, the control unit reduces the transient change in comprehensive stress caused by the mechanical shear work at the front end. The control unit calculates the reverse pressure reduction command in real time based on the deviation of the current coupling index from the system's critical threshold. The specific calculation logic for the reduction step size is as follows: ; In the formula, Adjust the step size parameter of the homogeneous pressure generated in the current control cycle calculation; The parameter at the current discrete control cycle time; Set the constraint feedback gain coefficient for the system to regulate the rate of pressure drop; The dynamic micro-group level shear-thermal stress coupling index obtained from the current control cycle assessment; This refers to the critical safety threshold parameter of the system obtained through material rheological property experiments.

[0069] The control unit deducts the calculated homogenization pressure reduction step size from the current baseline operating setting of the hydraulic power unit. The dynamically reduced electrical analog signal drives the proportional relief valve to release part of the hydraulic oil circuit pressure, thereby reducing the actual work intensity of the high-pressure homogenizer. This mechanism crosses physical space to initiate reverse intervention from the downstream thermal stress end to the upstream mechanical stress end. During the continuous pressure reduction process, the control unit simultaneously monitors the working pressure limit of the homogenization module. When the actual working pressure of the high-pressure homogenizer approaches the minimum homogenization pressure limit specified in the process specification, the control unit performs a hard interception operation to refuse further pressure reduction output and maintain the current pressure command. If the dynamic micro-cluster level shear-thermal stress coupling index continues to exceed the system critical threshold within the set delay period after the hard interception is performed, the control unit pushes the extreme value over-limit flag to the safety area of ​​global memory and activates the subsequent logistics diversion interlock mechanism.

[0070] See attached document Figure 9 In this embodiment, during operation, the system will generate control commands to reduce the operating frequency of the conveying module due to changes in the upstream liquid level or scheduling algorithm calculations. The flow state of the fluid inside the plate heat exchanger directly determines the heat transfer characteristics and crystal deposition tendency of the pipe wall boundary layer. Before issuing frequency modulation commands to the conveying module, the control unit performs feedforward evaluation of the real-time flow dynamics state in the pipeline. The control unit obtains the current structural geometric parameters of the pipeline and simultaneously reads the mass flow rate and measured temperature to construct a flow state evaluation model. Since the dynamic viscosity of the material exhibits nonlinear fluctuations with changes in thermodynamic state, the control unit calls the built-in viscosity compensation curve to dynamically correct the current rheological properties of the material.

[0071] As a preferred approach, the control unit calculates the dimensionless Reynolds number based on the corrected rheological parameters and the real-time flow velocity. The specific logic for calculating the real-time Reynolds number is as follows: ; In the formula, The real-time dimensionless Reynolds number of the fluid inside the heat exchanger pipe during the current sampling period; The parameter at the current discrete sampling time; This represents the instantaneous mass flow rate synchronously collected by the delivery module at the current sampling moment; Pi is a mathematical constant. The equivalent hydraulic diameter parameter inside the heat exchange pipeline; The initial dynamic viscosity constant of the fluid is measured under reference conditions; The viscosity-temperature compensation coefficient is used to reflect the nonlinear change of fluid viscosity with temperature. This represents the global average measured temperature obtained at the current sampling time. This is the reference temperature parameter used to calibrate the initial dynamic viscosity.

[0072] After acquiring the real-time Reynolds number, the control unit continuously compares it with a pre-set critical turbulent Reynolds number baseline. This baseline value is limited to between 4,000 and 4,500 based on fluid dynamics properties. When the theoretically predicted Reynolds number corresponding to the frequency reduction command output by the upper-level control logic falls below this baseline, the control unit activates the anti-fouling feedforward control mechanism to mathematically limit the given frequency of the inverter. The specific frequency cutoff logic is as follows: ; In the formula, This refers to the actual frequency command that the system ultimately issues to the frequency converter of the transmission module during the current control cycle; The parameter at the current discrete control cycle time; The given frequency parameter is the one originally requested by the upper-level scheduling logic for the current control cycle; The minimum operating frequency hard boundary parameter required to maintain the fluid inside the pipeline in a critical turbulent state.

[0073] The control unit calculates the minimum mass flow rate required to maintain critical turbulence based on the dynamic viscosity at the current temperature, the equivalent hydraulic diameter of the heat exchange pipes, the critical turbulent Reynolds number baseline, and the mass flow rate fed back by the Coriolis mass flow meter. It then obtains the corresponding minimum operating frequency based on the calibration curve between the inverter's operating frequency and the actual mass flow rate established before commissioning. The system applies this boundary cutoff action at the bottom layer to force the fluid micro-elements to maintain sufficient kinetic energy to flush the pipe wall.

[0074] In this embodiment, the control unit performs real-time lethality calculation for the fluid microparticles within the sterilization and heat preservation section. The control unit uses the reconstruction temperature obtained in the previous steps and combines it with preset microbial heat resistance parameters to construct a thermodynamic lethality integral model. The thermodynamic lethality integral model is used to evaluate the sterilization level achieved by the fluid microparticles under the current processing path. The specific instantaneous lethality calculation logic is as follows: ; In the formula, This represents the equivalent instantaneous lethality obtained from the fluid micro-particle evaluation under the current discrete sampling period; The parameter at the current discrete sampling time; The reconstructed temperature is generated after dynamic response correction at the current sampling time; This is a baseline sterilization temperature constant set based on food safety regulations; The temperature sensitivity index constant is used to characterize the heat resistance properties of the target microorganism.

[0075] The control unit performs online integral calculations on the instantaneous lethality during the physical residence time of the fluid micro-particles flowing through the sterilization and heat preservation section to generate a global cumulative lethality. The global cumulative lethality reflects the final biological safety assurance strength obtained by the fluid through the superposition effect in the time dimension. The specific cumulative calculation model is as follows: ; In the formula, This represents the global cumulative lethality of the fluid particle at the current moment. The parameter is the current global evaluation baseline time. The pure time delay parameter of fluid micro-elements in the sterilization and heat preservation section; This represents the instantaneous lethality at the corresponding moment in the integration process; Let be the integral variable parameter used to characterize time slippage within the integration interval.

[0076] The control unit continuously compares the global cumulative lethality rate with the target lethality rate threshold specified by the food safety standard. If the calculated cumulative lethality rate is lower than the target threshold, the control unit cancels the positive holding signal output to the control solenoid valve of the pneumatic aseptic diversion valve, so that the control solenoid valve is de-energized and reset, the diversion valve cylinder is depressurized and reversed, and the non-conforming material is introduced into the rework module.

[0077] See attached document Figure 10 In this embodiment, the control unit continuously monitors the system's operating status parameters during the execution of the cross-domain collaborative protection mechanism. When it is determined that the dynamic micro-cluster level shear-thermal stress coupling index has fallen back to the preset safe dead zone below the system's critical threshold and the microbial lethality rate meets the process requirements again, and the reconstruction temperature, transient temperature gradient, Reynolds number, and diversion valve feedback status are all within the allowable recovery range, and the above recovery conditions are maintained for no less than the preset confirmation period, the system enters the recovery process of switching from the emergency state to the basic state. The width range of this safe dead zone is dynamically set according to 1.5 to 2 times the system's measured noise amplitude to maintain the physical stability of the control command at the boundary. During this stage, the control unit cancels the forced locking command for the opening of the heat medium proportional regulating valve and simultaneously releases the reverse pressure reduction constraint for the upstream homogenizing module.

[0078] The control unit performs smooth trajectory planning on the target setpoint on the recovery path using an internally integrated first-order inertial filtering algorithm. This process can mitigate the step disturbance caused by the instantaneous switch of control. The specific recovery path calculation logic is as follows: ; In the formula, Set the smooth recovery value for the output of the current control cycle; Current discrete control cycle time parameters; The fixed control step size parameter preset for the control unit; The set value is the historical smooth recovery value from the previous control cycle; Set the value for the original basic operating state that the system expects to restore; The inertial filter coefficient, which characterizes the smoothing strength of the system state adjustment, is limited to between 0.85 and 0.95 based on the mechanical response frequency of the actuator. The control unit updates the smoothing recovery setpoint in each sampling cycle and sends it to the underlying frequency converter and positioner via the industrial fieldbus.

[0079] To aid in understanding the technical solution of this invention, an application embodiment based on an intelligent collaborative control system for goat milk product processing is provided below. The inner diameter of the system heat exchange pipeline is set to 0.05 meters and the density of the goat milk reference fluid is 1,030 kg / m³. At the current sampling moment, the instantaneous mass flow rate collected by the Coriolis mass flow meter is 2.5 kg / s. The control unit calculates that the current flow velocity is approximately 1.236 m / s. Combined with the pre-determined physical volume constant of 0.15 m / s, the fluid micro-particle mapping lag time is calculated to be 61.8 seconds. The time parameter is directly input into the spatiotemporal matrix to achieve heterogeneous data alignment. The initial dynamic viscosity constant of the fluid is measured to be 0.002 Pa·s. The control unit combines the measured temperature to dynamically correct the dynamic viscosity and obtains a real-time dimensionless Reynolds number of approximately 3,850. After determining that the Reynolds number is below the critical turbulence threshold of 4,200, the control unit triggers the anti-fouling feedforward mechanism, forcibly cuts off the original frequency modulation command, and outputs the lowest frequency of 28 Hz to maintain the critical scouring kinetic energy.

[0080] During operation, the control unit synchronously monitors the thermodynamic state of the system. At the reference sterilization temperature of 121 degrees Celsius, the global cumulative lethality of the fluid micro-particles is within the range specified by the process specification. The sudden increase in homogenization working pressure causes the equivalent mechanical shear pressure difference to deviate from the basic operating state. The transient temperature gradient extracted by the system synchronously shows a step signal. The dynamic micro-particle-level shear thermal stress coupling index generated by the control unit through online integration reaches 1.5 and exceeds the critical safety threshold of 1.2 set by the system. At this point, the system locks the opening of the proportional regulating valve of the heat medium module and calculates the homogenizing pressure based on the constraint gain coefficient, adjusting the step size to 2.5 MPa. After receiving the reverse command, the hydraulic power unit performs a pressure relief operation to reduce the mechanical work intensity. After intervention for several control cycles, the coupling index falls back to the safe dead zone. At this stage, the control unit calls the first-order inertial filtering algorithm with an inertial filtering coefficient of 0.9 and outputs a gradual recovery set value to guide the high-pressure homogenizer and frequency converter to smoothly return to the initial operating trajectory.

[0081] In conjunction with the above application embodiment's operating mechanism, a comparative experimental verification step is added. A traditional PID independent control strategy and the intelligent collaborative control system provided in this embodiment are deployed on a standardized goat milk processing platform equipped with the same measurement and control components. When the system is running smoothly for three hundred seconds, a step disturbance equivalent to a 20% flow drop is injected into the upstream front-end balance cylinder feeding branch. The experimenters use a high-speed data acquisition card to extract the dynamic multidimensional parameters inside the control unit in parallel at the bus end. They record key process parameters such as temperature overshoot, cumulative lethality extreme value, and scaling thermal resistance of the heat exchange pipeline wall during the two hours of continuous operation after the disturbance. The specific quantitative data collected is output according to the table below and used as the numerical comparison basis for evaluating the transient anti-disturbance performance and long-term physical stability of different control algorithms.

[0082] Table 1: Comparative Experimental Data of Core Indicators in Goat Milk Processing under Different Control Strategies

[0083] According to Table 1 and Figure 11 It can be seen that when dealing with the same magnitude of flow disturbance, the system using the traditional control strategy exhibits obvious adjustment lag and physical quantity overshoot. The maximum temperature overshoot reaches 3.14 degrees Celsius, and the increase in thermal resistance due to scaling on the pipe wall reaches 0.00847. The minimum cumulative lethality of some micro-clusters drops to 9.82, causing instability in the physical properties of the product. The experimental data using the solution provided in this embodiment show strong convergence characteristics. The maximum temperature overshoot of the system is maintained in the extreme range of 0.42 degrees Celsius, and the cumulative lethality of micro-clusters throughout the process is distributed above 12. Combined with the feedforward control executed by the system, the increase in thermal resistance due to scaling is reduced to 0.00193. The inertial filtering mechanism reduces the number of mechanical oscillations during the pressure recovery stage to zero. The above numerical characteristics confirm that the spatiotemporal mapping and cross-domain coupled calculation logic has a definite system coordinated adjustment capability under multivariable constraints.

[0084] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent collaborative control system for processing goat milk products, characterized in that, include: The conveying module is equipped with a centrifugal material conveying pump connected to a frequency converter and a Coriolis mass flow meter for collecting instantaneous mass flow rate. The homogenization module, located downstream of the conveying module, is equipped with a high-pressure homogenizer with a hydraulic power unit and a diaphragm pressure transmitter for collecting pressure parameters. The heat exchange module, located downstream of the homogenization module, is equipped with a plate heat exchanger. The plate heat exchanger is equipped with a multi-point thin-film temperature transmitter that collects multi-point measured temperatures as temperature parameters and a proportional regulating valve. At the end, a pneumatic sterile diversion valve is provided. The control unit, connected to the aforementioned components, is configured to execute the following logic: The pure time delay of the fluid micro-particle is calculated based on the instantaneous mass flow rate and physical volume parameters. A time window is established based on the pure lag time to align the pressure parameters of the same fluid micro-particle in the homogenizing module with the temperature parameters in the heat exchange module. Dynamic micro-group-level shear-thermal stress coupling index is generated based on the aligned pressure and temperature parameters. When the dynamic micro-cluster level shear-thermal stress coupling index reaches the critical threshold, the opening of the proportional regulating valve is locked and a pressure reduction command is sent to the hydraulic power unit.

2. The intelligent collaborative control system for goat milk product processing according to claim 1, characterized in that, The control unit aligns the pressure and temperature parameters of the same fluid micro-element in the following manner: The time window containing Gaussian weights is generated by extending a preset width forward and backward from the theoretical timestamp of the fluid micro-particle arriving at the heat exchange module as the center. Gaussian distribution weights are calculated for historical sampling points within the time window, and the equivalent mechanical shear parameters are obtained by weighted summation of historical mechanical shear pressure differences recorded by the homogeneous module within the time window. The equivalent mechanical shear parameters are correlated with the temperature parameters collected by the heat exchange module at the current moment and stored in the spatiotemporal matrix.

3. The intelligent collaborative control system for goat milk product processing according to claim 2, characterized in that, The temperature parameter is the reconstruction temperature; the process by which the control unit acquires the reconstruction temperature includes: The multi-point measured temperatures are aggregated using an internal arithmetic averaging algorithm to generate a global average measured temperature. The global average measured temperature is processed using a first-order differential compensation algorithm to eliminate thermal response hysteresis and generate the reconstructed temperature.

4. The intelligent collaborative control system for goat milk product processing according to claim 3, characterized in that, The process by which the control unit generates the dynamic micro-group-level shear-thermal stress coupling index includes: Extract the equivalent mechanical shear parameters and the transient temperature gradient corresponding to the reconstructed temperature of the fluid micro-elements in the spatiotemporal matrix, and perform dimensionless processing based on the reference working pressure and the reference heating gradient, respectively. A historical sliding window is established in the time dimension, and integral weighted calculation is performed on the equivalent mechanical shear parameter and the transient temperature gradient after dimensionless processing to generate the dynamic micro-group level shear-thermal stress coupling index.

5. The intelligent collaborative control system for goat milk product processing according to claim 1, characterized in that, The control unit is also configured to: Simultaneously monitor the operating pressure baseline of the high-pressure homogenizer while continuously issuing the pressure reduction command; When the working pressure of the high-pressure homogenizer is reduced to the preset minimum homogenization pressure limit, and the dynamic micro-cluster level shear-thermal stress coupling index remains higher than the critical threshold within the preset delay period, a rework switching command is output to the pneumatic sterile diversion valve, so that the current material enters the rework module.

6. The intelligent collaborative control system for goat milk product processing according to claim 1, characterized in that, The control unit is also configured to: Within the same issuance cycle of the pressure reduction command, the feedforward loop is activated to issue a frequency reduction command to the frequency converter to reduce the instantaneous mass flow rate; The Reynolds number at the current flow velocity inside the pipeline is calculated in real time. When the Reynolds number reaches the preset critical turbulent Reynolds number threshold, the frequency reduction command is cut off to maintain the current instantaneous mass flow rate.

7. The intelligent collaborative control system for goat milk product processing according to claim 6, characterized in that, The process by which the control unit obtains the Reynolds number includes: The built-in viscosity compensation curve is invoked to dynamically correct the current rheological properties of the material and obtain the corrected dynamic viscosity. The Reynolds number is calculated based on the corrected dynamic viscosity, the instantaneous mass flow rate, the equivalent hydraulic diameter of the heat exchange pipeline, and the multi-point measured temperature.

8. The intelligent collaborative control system for goat milk product processing according to claim 1, characterized in that, The control unit is also configured to: A thermodynamic lethality integral model is constructed using the temperature parameters combined with preset microbial heat resistance parameters. The instantaneous lethality of the fluid micro-particles in the sterilization and heat preservation section is calculated, and the instantaneous lethality is integrated online during the physical residence time of the fluid micro-particles in the sterilization and heat preservation section to generate a global cumulative lethality. When the global cumulative mortality rate is lower than the target mortality rate threshold, a valve position switching command is output to the pneumatic aseptic diversion valve to connect the rework module.

9. The intelligent collaborative control system for goat milk product processing according to claim 8, characterized in that, The control unit is also configured to: The dynamic micro-cluster level shear-thermal stress coupling index is continuously monitored. When it is determined that the dynamic micro-cluster level shear-thermal stress coupling index falls back to the safe dead zone range, the global cumulative lethality reaches the target lethality threshold, the temperature parameter does not exceed the maximum temperature protection value, and is maintained for no less than the preset confirmation period, the locking command for the opening of the proportional regulating valve is canceled, and the reverse pressure reduction constraint for the high-pressure homogenizer is released.

10. The intelligent collaborative control system for goat milk product processing according to claim 9, characterized in that, The control unit is also configured to: After confirming that the valve position feedback signal of the pneumatic aseptic diversion valve is in a positive flow state, the first-order inertial filtering algorithm is called to calculate the smooth recovery set value. The inverter's operating frequency and the high-voltage homogenizer's working pressure are gradually restored to their initial process settings according to the smooth recovery setting value.

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