A continuous production system of polydextrose

Abstract

The present application relates to the technical field of food additive production, and discloses a continuous production system for polydextrose, which comprises a cloth distribution module, a track module, a heat detection module, a heat excitation module and a control module; the heat excitation module injects a forced perturbation heat wave signal into the bottom of the track, and the control module locks and activates a target probe to collect a temperature signal through offset solution; the control module performs four simultaneous matching calculations on the extracted pulse amplitude attenuation nuclear parameters and phase lag time parameters, in combination with a temperature difference gradient convergence rate and an absolute humidity decline feature, to calibrate actual polymerization end horizontal coordinate values; the system adjusts the linear speed of the track in a closed loop according to the deviation parameters of the coordinate values, and simultaneously solves and adjusts the volumetric flow of a feeding pump.

Description

Technical Field

[0001] This invention relates to the field of food additive production technology, specifically a continuous polydextrose production system. Background Technology

[0002] In the industrial continuous production of polydextrose, liquid or semi-solid materials are laid flat on a conveyor belt and pass through the heating and polymerization stages in the drying chamber in sequence. Currently, existing production control methods mostly rely on preset fixed operating line speeds and heating parameters, or passively adjust by detecting the macroscopic temperature of the material surface and the humidity in the drying chamber.

[0003] However, these conventional detection and control methods have obvious limitations. On the one hand, the evaporation and drying of water during the heating process of polydextrose often overlaps with the macromolecular cross-linking polymerization. The surface temperature rise and temperature gradient change exhibited by the material surface due to water evaporation and drying can be confused with the thermodynamic changes caused by the actual micro-cross-linking polymerization. Existing systems cannot penetrate the surface phenomena to obtain the true micro-polymerization state inside the material, making it difficult to accurately determine the actual completion position of the polymerization reaction on the conveyor belt. On the other hand, there is strong background thermal radiation interference inside the continuously heated drying chamber. The temperature signals collected by conventional sensors are mixed with a large amount of thermodynamic noise, which masks the weak material property changes.

[0004] Because it is impossible to accurately locate the actual polymerization endpoint of materials online, existing systems often can only perform lagging single-variable adjustments when faced with fluctuations in raw material moisture content or environmental changes. For example, when incomplete polymerization is detected, operators may simply reduce the linear speed of the conveyor belt to extend the heating time. However, with the feed pump flow rate remaining constant, simply changing the linear speed will directly increase the thickness of the material spread on the conveyor belt. This change in thickness will alter the overall heat transfer efficiency, causing new problems of uneven heating. This lack of multi-variable coordinated control ultimately leads to inconsistent degrees of polymerization in polydextrose products, resulting in poor product quality uniformity and making it difficult to meet the requirements of high-standard continuous and stable production. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a continuous polydextrose production system that solves the problems of difficulty in accurately monitoring the micro-polymerization state of materials during continuous polydextrose production, as well as the fluctuations in material thickness caused by single-variable adjustment.

[0006] To achieve the above objectives, the present invention provides the following technical solution: This invention provides a continuous polydextrose production system, comprising: The fabric module is located at the feed end of the drying chamber and is equipped with a feed pump; The track module runs through the drying chamber and includes a stainless steel track and a drive motor. The drying chamber is divided into an aggregation zone, a drying zone and a cooling zone along the material running direction. A thermal detection module is arranged inside the drying chamber and in the top exhaust duct, including a bottom temperature sensor array, a top infrared sensor array, and a humidity transmitter. A thermal excitation module is disposed between adjacent detection sites of the bottom temperature sensor array for injecting forced micro-perturbation thermal wave signals into the bottom of the stainless steel track. The control module is electrically connected to the fabric module, track module, thermal detection module and thermal excitation module respectively, and includes an acquisition and filtering module, an offset calculation module, a phase-locked loop analysis module, a status verification module and an adaptive control module. The thermal detection module is used to acquire raw thermal detection data and thermal response data formed after the forced micro-perturbation thermal wave signal acts on the material. The control module determines characteristic parameters characterizing the polymerization state of the material based on the raw thermal detection data and thermal response data, calibrates the lateral coordinate value of the actual polymerization endpoint, and implements closed-loop control of the running linear speed of the stainless steel track and the volumetric flow rate of the feed pump based on the positional deviation between the lateral coordinate value of the actual polymerization endpoint and the set value of the spatial coordinate of the target polymerization endpoint.

[0007] The above technical solution injects a forced micro-perturbation thermal wave signal into the bottom of the stainless steel track through a thermal excitation module, allowing the thermal wave to penetrate the material and generate a temperature response on the material surface. The control module combines the raw thermal detection data and thermal response data to track the attenuation and hysteresis characteristics of the thermal wave signal, converting the change in thermal impedance caused by the micro-crosslinking of the material into quantitative parameters, thereby determining the actual spatial coordinates of the material's polymerization and adjusting the transmission linear speed and feed flow rate accordingly.

[0008] Furthermore, the adaptive control module is used to obtain the total length of the effective heating zone and the target retention time of the material, and to calculate the basic running linear speed of the stainless steel track based on the total length of the effective heating zone and the target retention time of the material; the adaptive control module is also used to simultaneously calculate the initial volumetric flow rate setting value of the feed pump based on the curing material spreading width and the preset initial spreading thickness target value.

[0009] During the startup phase, the system converts the retention time set by the process into an initial benchmark for operating speed and flow rate, establishing a physical mapping relationship for the horizontal spatial axis.

[0010] Furthermore, the acquisition and filtering module is used to receive the raw thermal detection data and perform moving average filtering and noise reduction processing, extract the smoothed bottom temperature and surface temperature values, calculate the time-domain convergence rate of the vertical temperature difference gradient, and derive the absolute humidity decrease characteristic based on the difference of the absolute humidity values ​​after smoothing at continuous sampling times.

[0011] The temporal convergence rate of the vertical temperature gradient reflects the heat consumption attenuation trend during the heat transfer process from the heat source to the surface, while the absolute humidity decrease characteristic reflects the change process of gas phase evaporation in the exhaust duct. The two constitute macroscopic thermodynamic passive observation parameters.

[0012] Furthermore, the electromagnetic induction coil inside the thermal excitation module generates an alternating magnetic field according to the received drive pulse command, and generates a forced micro-perturbation thermal wave signal in the stainless steel track area corresponding to the thermal excitation module; the offset calculation module performs integral calculation on the acquired instantaneous running linear velocity data within the time window corresponding to the preset estimated thermal hysteresis parameter to obtain the lateral physical space offset, and superimposes the fixed physical starting coordinates of the thermal excitation module with the lateral physical space offset to obtain the expected physical target coordinates, and selects and locks the target probe in the top infrared sensor array under the preset constraint of the effective field radius of the single probe.

[0013] By integrating and extrapolating the material movement distance, the system determines the physical response location where the forced perturbation thermal wave signal penetrates to the material surface in the moving reference frame.

[0014] Furthermore, the control module is used to directionally activate the locked target probe to perform data acquisition, and simultaneously send a forced shutdown command to block the signal sampling channel of the non-target probe in the top infrared sensor array; the target probe is used to acquire the noisy thermal radiation surface temperature signal and transmit it to the phase-locked parsing module.

[0015] By shielding the probe in non-targeted areas, environmental thermal radiation noise is filtered at the hardware level.

[0016] Furthermore, the phase-locked loop (PLL) analysis module uses the set output excitation frequency as the reference local oscillator to construct an in-phase reference sine wave signal and an orthogonal reference cosine wave signal. The noisy thermal radiation surface temperature signal is then mixed and multiplied with the in-phase reference sine wave signal and the orthogonal reference cosine wave signal, respectively. Within the set integration time window, a time infinitesimal integral extraction operation is performed to output the in-phase component and the orthogonal component.

[0017] The mixing and integration operations have a narrowband filtering effect, which removes the background heat flow signal that is independent of the excitation frequency.

[0018] Furthermore, the phase-locked parsing module obtains the pulse amplitude attenuation kernel parameter by calculating the square root of the sum of the squares of the in-phase component and the quadrature component, and calls the arctangent algorithm to calculate the continuous phase shift angle based on the quadrature component and the in-phase component. The continuous phase shift angle is divided by the reference angular frequency calculated based on the output excitation frequency to obtain the phase hysteresis time parameter.

[0019] The pulse amplitude attenuation kernel parameter and the phase hysteresis time parameter characterize the evolution of microscopic polymerization impedance during the cross-linking and curing process of macromolecules in materials.

[0020] Furthermore, the state verification module extracts the time-domain convergence rate of the vertical temperature gradient, the absolute humidity decrease characteristic, the pulse amplitude attenuation kernel parameter, and the phase hysteresis time parameter, and performs a four-element simultaneous matching calculation on the above parameters according to the internally configured Boolean logic discrimination matrix to make a global judgment, and calibrates and outputs the actual aggregation endpoint horizontal coordinate value within the Boolean constraint domain.

[0021] The above-mentioned judgment logic eliminates misjudgments caused by the evaporation and drying of moisture on the material surface due to temperature gradient convergence, and calibrates the actual location where cross-linking of macromolecular structures occurs.

[0022] Furthermore, the adaptive control module extracts the lateral coordinate value of the actual aggregation endpoint, and when the lateral coordinate value of the actual aggregation endpoint is a non-zero valid value, obtains the spatial coordinate setpoint of the target aggregation endpoint, calculates the spatial position deviation parameter between the spatial coordinate setpoint of the target aggregation endpoint and the lateral coordinate value of the actual aggregation endpoint; the adaptive control module inputs the spatial position deviation parameter into the internally configured discrete proportional-integral controller to perform closed-loop calculation, and superimposes the current deviation correction amount and the historical running linear speed, and outputs the track running linear speed update command.

[0023] The system adjusts the linear speed of the track based on the position deviation, so that the actual position of material aggregation completion approaches the set target spatial coordinates.

[0024] Furthermore, the adaptive control module, based on the solidified material spreading width and the preset initial spreading thickness target value, synchronously calculates the volumetric flow rate setting value that matches the track running linear speed update command and sends it to the feed pump; the adaptive control module also converts the track running linear speed update command into a frequency control signal and sends it to the drive motor to maintain a constant physical spreading thickness of the material on the stainless steel track surface.

[0025] When changing the conveyor speed to perform position correction, the feed flow rate is adjusted synchronously to maintain a constant laying thickness.

[0026] This invention provides a continuous polydextrose production system. It has the following advantages: 1. This invention injects forced micro-perturbation thermal wave signals into stainless steel tracks through a thermal excitation module, and uses a state verification module to perform quaternary simultaneous matching calculations of macroscopic temperature gradient convergence rate and humidity decrease characteristics with microscopic pulse amplitude attenuation kernel parameters and phase hysteresis time parameters; it transforms the thermal impedance change caused by cross-linking of macromolecules inside the material into a quantitative index, eliminates the interference caused by relying solely on surface moisture drying, and achieves accurate calibration of the spatial coordinates of the actual polymerization endpoint.

[0027] 2. This invention uses an offset calculation module to deduce the spatial offset to lock the target probe and shield the sampling channel of the non-target probe. Combined with a phase-locked loop analysis module, it performs frequency mixing, multiplication and integration operations on the noisy temperature signal and the reference sine and cosine wave signals. The mechanism of combining hardware shielding and software narrowband filtering removes the thermal radiation background noise that is unrelated to the excitation frequency in the production environment, ensuring the reliable extraction of microscopic thermal response characteristics under complex background thermal flow interference.

[0028] 3. Based on the deviation of the actual polymerization endpoint coordinates, the present invention adjusts the linear speed of the conveyor belt through a closed loop adaptive control module, and simultaneously calculates the volumetric flow rate setting of the feed pump according to the material spreading width and initial thickness target value. The linkage control strategy maintains the physical match between the feed rate and the conveyor belt speed while dynamically correcting the material polymerization position, avoiding material accumulation or thinning caused by simply adjusting the linear speed, and ensuring the stability of spreading thickness and product quality in continuous production. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the hardware connection topology of the overall control module of the system of the present invention; Figure 2 This is a schematic diagram of the overall main logic flow of the continuous aggregation control method of the present invention; Figure 3 This is a schematic diagram of the logic architecture for thermal wave excitation and targeted probe addressing and tracking in this invention; Figure 4 This is a simulation diagram of the timing of digital phase-locked extraction of weak forced perturbation thermal waves according to the present invention. Among them, (a) is a schematic diagram comparing the noisy temperature signal with the actual perturbation thermal wave response, (b) is a schematic diagram of the orthogonal dual-channel mixing and multiplication sequence of the digital oscillator, and (c) is a schematic diagram of the convergence trajectory of the time infinitesimal integral of the characteristic component. Figure 5 This is a schematic diagram of the global decision architecture topology for state verification Boolean logic in this invention. Figure 6 This is a schematic diagram of the adaptive closed-loop solution and collaborative control architecture topology of the present invention; Figure 7 This is a three-dimensional schematic diagram of the spatiotemporal evolution characteristics of the noisy thermal radiation surface temperature response signal of the present invention; Figure 8The above is a simulation diagram of the adaptive closed-loop spatial position tracking and command coordinated control of the present invention. (a) is a schematic diagram of the convergence of the lateral coordinate position tracking of the actual aggregation endpoint, (b) is a schematic diagram of the timing of the closed-loop update command for the track running linear speed, and (c) is a schematic diagram of the coordinated control of the feed pump volume flow rate by synchronous matching solution. Detailed Implementation

[0030] 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.

[0031] See attached document Figure 1 The present invention provides a continuous polydextrose production system, which may include: a fabrication module, a conveyor belt module, a drying chamber, a thermal detection module, a thermal activation module, and a control module.

[0032] The material feeding module is located at the feed end of the drying chamber; the material feeding module is equipped with a feed pump; the track module is installed throughout the drying chamber; the track module includes a stainless steel track and a drive motor connected to the stainless steel track; the interior of the drying chamber is divided into an aggregation zone, a drying zone and a cooling zone in sequence along the material running direction; the running extension direction of the stainless steel track is set as a single physical space dimension, defined as the transverse space axis.

[0033] The thermal detection module is arranged inside the drying chamber and in the exhaust duct connected to the top of the drying chamber; the thermal detection module includes a bottom temperature sensor array, a top infrared sensor array and a humidity transmitter; the bottom temperature sensor array is arranged on the bottom plate inside the aggregation area and the drying area; the top infrared sensor array is arranged in parallel at intervals directly above the stainless steel track; the humidity transmitter is installed inside the exhaust duct; the thermal excitation module is inserted between the detection points of adjacent bottom temperature sensor arrays.

[0034] The control module establishes electrical connections with the material feeding module, track module, thermal detection module, and thermal excitation module, respectively. The control module includes an acquisition and filtering module, an offset calculation module, a phase-locked loop analysis module, a state verification module, and an adaptive control module. The thermal detection module is used to acquire raw thermal detection data and thermal response data formed after the forced micro-perturbation thermal wave signal acts on the material. The control module determines the characteristic parameters characterizing the polymerization state of the material based on the raw thermal detection data and thermal response data, calibrates the lateral coordinate value of the actual polymerization endpoint, and implements closed-loop control of the running linear speed of the stainless steel track and the volumetric flow rate of the feed pump based on the positional deviation between the lateral coordinate value of the actual polymerization endpoint and the set value of the spatial coordinate of the target polymerization endpoint.

[0035] See attached document Figure 2 This invention provides a method for controlling the continuous polymerization of polydextrose, comprising the following steps: S1, during the startup phase, the control module outputs the initial drive frequency to the drive motor through the adaptive control module, and simultaneously sends the initial volumetric flow rate setpoint to the feed pump; the material is spread out by the material distribution module and enters the drying chamber, where it continues to run under the drive of the stainless steel track. S2, during the material movement monitoring stage, the acquisition and filtering module acquires the raw sensor data transmitted by the thermal detection module according to the discrete sampling period preset by the control module; the acquisition and filtering module extracts the values ​​of the bottom temperature sensor array, the top infrared sensor array and the humidity transmitter, and calculates and outputs the time-domain convergence rate of the vertical temperature gradient and the absolute humidity decrease characteristics to calibrate the evolution law of moisture evaporation. S3, when the material reaches the base coordinate area where the thermal excitation module is located, the control module triggers the thermal excitation module to inject a forced micro-perturbation thermal wave signal with the output excitation frequency set by the control module into the bottom of the stainless steel track; while the thermal excitation module excites the forced micro-perturbation thermal wave signal, the offset calculation module reads the current instantaneous running linear velocity data and the estimated thermal hysteresis parameters of the stainless steel track, and integrates and calculates the lateral physical space offset generated when the forced micro-perturbation thermal wave signal is transmitted to the surface of the material; based on the calculation result of the lateral physical space offset, the control module directionally activates the target probe at the corresponding coordinate position in the top infrared sensor array to perform high-frequency acquisition operation, while shielding the signal sampling input corresponding to the non-target probe in the top infrared sensor array; S4, the noisy thermal radiation surface temperature signal acquired by the target probe is transmitted to the phase-locked analysis module as thermal response data; the phase-locked analysis module uses the output excitation frequency of the thermal excitation module as the reference local oscillator, performs orthogonal integral extraction operation, and extracts the pulse amplitude attenuation kernel parameter and phase hysteresis time parameter that characterize the evolution of the micro-polymerization impedance of the material from the macro-noise heat flow, and uses them as characteristic parameters characterizing the polymerization state of the material. S5, the state verification module extracts the time-domain convergence rate of the vertical temperature gradient, the absolute humidity decrease characteristics, the pulse amplitude attenuation kernel parameter, and the phase hysteresis time parameter, and performs simultaneous matching calculation; the state verification module filters the convergence judgment of the temperature gradient caused by surface moisture depletion according to the Boolean logic discrimination matrix, and calibrates the actual polymerization endpoint lateral coordinate value of the output material block to achieve the micro-crosslinked macromolecular structure. S6, the adaptive control module extracts the actual lateral coordinate value of the polymerization endpoint and compares it with the set value of the spatial coordinate of the target polymerization endpoint; the adaptive control module sends a frequency control signal to the drive motor to implement track running linear speed regulation and correction; the adaptive control module synchronously regulates the volumetric flow rate of the feed pump to maintain the material spreading thickness at a constant state; the material then passes through the cooling zone with the stainless steel track to complete the cooling and curing.

[0036] In this embodiment, step S1 provided by the present invention may include the following steps in specific implementation: S11, the adaptive control module obtains the target material retention time set by the current batch of polydextrose production process and the total effective heating zone length of the stainless steel conveyor belt in the drying chamber. The target material retention time is set by the host computer's process formula database, and the total effective heating zone length is obtained by calibrating the physical span of the actual heating plates laid in the drying chamber. The adaptive control module calculates the basic running linear speed of the stainless steel conveyor belt by extracting the ratio between the total effective heating zone length and the target material retention time. The specific calculation logic satisfies the following expression: ; In the formula, The base operating linear velocity set for the system; The total physical length of the effective heating zone of the stainless steel track; The reference residence time required for the material to complete the predetermined process crosslinking.

[0037] After obtaining the basic operating linear velocity, the adaptive control module calculates the initial volumetric flow rate setting of the feed pump based on the material spreading width fixed by the control module and the initial spreading thickness target value preset by the control module. The material spreading width is determined by the mechanical baffle spacing of the flow equalization component of the material distribution module. In this embodiment, the initial spreading thickness target value preset by the control module ranges from 2 mm to 5 mm. The specific initial volumetric flow rate calculation expression is as follows: ; In the formula, The initial volumetric flow rate set for the cloth module; The base operating linear velocity set for the system; The width of the material to be laid out in the system; This is the preset initial tiling thickness target value.

[0038] The adaptive control module converts the basic running linear speed into an initial drive frequency based on the mechanical transmission ratio of the equipment transmission mechanism configured in the track module and sends it to the drive motor to perform closed-loop speed control. The adaptive control module simultaneously sends the initial volumetric flow rate setpoint to the feed pump of the fabric module. The specific working process of the drive motor receiving the initial drive frequency and performing motor speed adjustment can be implemented in this embodiment using a frequency converter vector control mechanism. The drive method of the drive motor is a well-known technology in this field.

[0039] S12, the control module sets the physical contact point between the feed pump outlet and the stainless steel track surface vertically below as the origin of the spatial coordinates. The control module establishes a one-dimensional continuous transverse spatial axis with the physical transmission direction of the stainless steel track as the positive direction. Based on the transverse spatial axis, the transverse physical coordinate position of a specific material element loaded on the stainless steel track at the current moment of continuous integration is defined as the integral of the instantaneous running linear velocity of the stainless steel track with time, and an analytical model of the transverse physical coordinate position is established: ; In the formula, For the infinitesimal element of material at any given time step The horizontal physical coordinate position; The current time point for continuous integration; Let be the instantaneous linear velocity of the stainless steel track within the integral infinitesimal time. This is the time-dependent variable in integration operations; Differential operators for time infinitesimal elements.

[0040] During the initial startup phase, the drive motor maintains the initial drive frequency, and the instantaneous linear velocity of the stainless steel track is numerically equivalent to the basic linear velocity. The control module establishes a lateral spatial axis and coordinate integration logic to convert the issued initial drive frequency into a real-time quantized spatial position coordinate mapping, thus constructing a basic correlation between the time dimension and the physical space dimension of the production process.

[0041] S13, after receiving the initial volumetric flow rate setting value, the material distribution module controls the feed pump to continuously pump the liquid mixture. The liquid mixture flows through the flow equalization component of the material distribution module and is continuously laid on the surface of the stainless steel track at the initial flatness target value preset by the control module. The stainless steel track is pulled by the drive motor and carries the liquid mixture to move into the drying chamber. The liquid mixture passes through the polymerization zone and the drying zone in sequence with the movement of the stainless steel track. The bottom of the liquid mixture continuously absorbs the conductive heat energy of the heating plate in the drying chamber, begins to heat up, and gradually undergoes a water phase change.

[0042] For the temperature control process of the heating plate inside the drying chamber providing a basic constant heat source, in this embodiment, the temperature controller can be configured according to the conventional temperature closed-loop feedback logic for temperature adjustment. The basic heating control method and device configuration of the temperature control process are well-known technologies in the field and will not be described in detail in this embodiment.

[0043] In this embodiment, step S2 provided by the present invention may include the following steps in specific implementation: S21, the acquisition and filtering module sends a synchronous trigger command to the thermal detection module according to the discrete sampling period preset by the control module. In this embodiment, the discrete sampling period ranges from 100 milliseconds to 500 milliseconds. The bottom temperature sensor array in the thermal detection module captures the raw bottom temperature data of the bottom plate inside the polymerization zone and the drying zone. The top infrared sensor array synchronously and non-contactly acquires the raw surface temperature data of the material directly above the stainless steel track. The humidity transmitter in the exhaust duct detects the raw absolute humidity data in the gas phase space inside the exhaust duct in real time. The acquisition and filtering module receives raw bottom temperature data, raw surface temperature data, and raw absolute humidity data, and imports these data into a data buffer sequence within the module in parallel. The module then uses a moving average filtering algorithm based on a preset sliding window length to smooth and denoise the raw bottom temperature data, raw surface temperature data, and raw absolute humidity data in the data buffer sequence. In this embodiment, the preset sliding window length is between 5 and 10 sampling periods. The module removes high-frequency spikes and outputs a basic monitoring signal sequence.

[0044] S22, In the initial stage of heating, a large amount of surface moisture evaporates and absorbs heat, resulting in a large temperature gradient between the upper and lower surfaces of the material. The acquisition and filtering module extracts the smoothed bottom temperature and surface temperature values ​​to establish a vertical cross-section heat conduction model and calculates the vertical temperature difference gradient characteristics at the current sampling time. The acquisition and filtering module further extracts the absolute value of the difference between the vertical temperature difference gradient characteristics of adjacent sampling periods and divides it by the discrete sampling period preset by the control module. The acquisition and filtering module calculates the time-domain convergence rate of the vertical temperature gradient. This rate objectively reflects the attenuation process of heat loss due to moisture vaporization as the heat source provided by the heating plate inside the drying chamber penetrates the material's thickness and reaches the surface. The specific calculation expression for the vertical temperature gradient characteristics and the analytical model for its time-domain convergence rate are as follows: ; ; In the formula, For the system at discrete sampling times The vertical temperature gradient characteristics; This refers to the current discrete sampling time. The bottom temperature after smoothing; The surface temperature after smoothing treatment; The time-domain convergence rate of the vertical temperature gradient; This refers to the current discrete sampling time. For the system at discrete sampling times The vertical temperature gradient characteristics; This represents the historical vertical temperature gradient at the previous sampling time. The discrete sampling period set for the system.

[0045] S23, as the material moisture content decreases, the vapor phase evaporation gradually decreases. The acquisition and filtering module extracts the smoothed absolute humidity value and uses the first-order forward difference algorithm to calculate the physical difference between the smoothed absolute humidity value at the current sampling time and the smoothed absolute humidity value at the previous sampling time. The acquisition and filtering module extracts the absolute value of the smoothed absolute humidity value at the current sampling moment and the smoothed absolute humidity value at the previous sampling moment, divides it by the discrete sampling period preset by the control module, and derives the absolute humidity decrease characteristic. Mathematically, this absolute humidity decrease characteristic corresponds to the instantaneous decay slope of the gas humidity curve within the exhaust duct. The acquisition and filtering module, based on the time-domain convergence rate of the extracted vertical temperature gradient and the absolute humidity decrease characteristic, constitutes macroscopic thermodynamic passive observation parameters. The specific expression for the absolute humidity decrease characteristic calculation model is as follows: ; In the formula, To calculate the absolute humidity decrease characteristic of the output; This refers to the current discrete sampling time. The smoothed absolute humidity in the gas phase space at the current sampling time; The smoothed historical absolute humidity in the gas phase space at the previous sampling time; The discrete sampling period set for the system.

[0046] See attached document Figure 3 In specific implementations, step S3 provided by the present invention may include the following steps: S31, when the material moves with the stainless steel track to the fixed physical coordinate position where the thermal excitation module is deployed, the control module sends a drive pulse command with the output excitation frequency set by the control module to the thermal excitation module. The electromagnetic induction coil inside the thermal excitation module generates an alternating magnetic field according to the drive pulse command with the output excitation frequency set by the control module and penetrates the bottom of the stainless steel track. Under the action of an alternating magnetic field, the stainless steel track generates an eddy current effect and generates a forced micro-perturbation thermal wave signal in a local area. In this embodiment, the pulse frequency of the forced micro-perturbation thermal wave signal ranges from 0.1 Hz to 2 Hz, and the duty cycle of the forced micro-perturbation thermal wave signal is set to 50% by the control module. The forced micro-perturbation thermal wave signal penetrates the material vertically upward from the bottom of the stainless steel track and forms a temperature oscillation with the same period as the forced micro-perturbation thermal wave signal on the surface of the material. For the specific circuit structure of the alternating magnetic field generated by the electromagnetic induction coil and the metal eddy current heating, a conventional high-frequency inverter and induction coil assembly can be used in this embodiment. The eddy current heating method of generating an alternating magnetic field by the electromagnetic induction coil and heating the metal eddy current is a well-known technology in the field.

[0047] S32, after the material receives the forced micro-disturbance heat wave signal generated at the bottom of the stainless steel track, the surface temperature shows a response peak with a time delay. The offset calculation module extracts the estimated thermal hysteresis parameter of the current batch of material. The estimated thermal hysteresis parameter is calculated by dividing the initial flat thickness target value preset by the control module by the experimental calibration heat conduction speed parameter of the material obtained in advance by the control module. In this embodiment, the value range of the estimated thermal hysteresis parameter is 3 seconds to 15 seconds. The offset calculation module synchronously reads the current instantaneous running linear velocity data of the stainless steel track. The offset calculation module takes the injection time of the forced perturbation thermal wave signal as the integration starting point and performs time-element integration on the instantaneous running linear velocity data within the time window corresponding to the estimated thermal hysteresis parameter. The offset calculation module calculates the lateral physical space offset of a specific material element as it moves with the stainless steel track when the forced perturbation thermal wave signal is transmitted to the material surface. The specific expression for the lateral physical space offset calculation model is as follows: ; In the formula, This is the calculated lateral physical space offset; The starting moment for the thermal excitation module to inject the forced micro-perturbation thermal wave signal into the stainless steel track; The set predicted thermal hysteresis parameter; The instantaneous linear velocity of the stainless steel track during continuous integral time; This is the time variable in integration operations; Differential operators for time integration.

[0048] S33, the offset calculation module extracts the fixed physical starting coordinates where the thermal excitation module is located. The offset calculation module performs arithmetic superposition of the fixed physical starting coordinates and the calculated lateral physical space offset to obtain the expected physical target coordinates when the material surface presents the peak value of the forced micro-disturbance thermal wave signal response. The control module traverses the installation coordinate matrix of each individual probe in the top infrared sensor array that is pre-stored in the control module. The control module calculates the absolute difference between the installation coordinates of each individual probe and the expected physical target coordinates. Under the constraint that the absolute difference is less than the effective field of view radius of the individual probe (preset by the control module), the control module selects the specific individual probe corresponding to the smallest absolute difference and locks it as the target probe. The specific expression for calculating the expected physical target coordinates is as follows: ; In the formula, The calculated expected physical target coordinates; The fixed physical starting coordinates of the thermal excitation module are calibrated on the horizontal spatial axis; This is the calculated lateral physical space offset.

[0049] S34, the control module activates the locked target probe to enable the target probe to perform high-frequency data acquisition operation at the high-frequency acquisition frequency set by the control module. The control module synchronously sends a forced shutdown command on the hardware bus to block the signal sampling channel of the non-target probe in the top infrared sensor array. As the stainless steel track moves, the control module continuously updates the expected physical target coordinates according to the current instantaneous running linear speed of the stainless steel track and dynamically switches the locked target probe. The control module, based on the operation of directional activation of the target probe and shielding of the signal sampling channel of the non-target probe, completes the spatial tracking and acquisition of the response position of the forced perturbation thermal wave signal in the moving reference frame, and filters the ambient thermal radiation noise of the non-target area at the hardware level. The target probe acquires the noisy thermal radiation surface temperature signal of the expected physical target coordinate area and transmits the noisy thermal radiation surface temperature signal to the phase-locked analysis module through a dedicated data link. In this embodiment, it is known that shielding the signal sampling channel of the non-target probe in the top infrared sensor array can reduce the bandwidth occupation of the control module and ensure that the forced perturbation thermal wave signal is not masked by the global ambient light and heat.

[0050] See attached document Figure 4 In specific implementations, step S4 provided by the present invention may include the following steps: S41, the noisy thermal radiation surface temperature signal acquired by the target probe is transmitted to the phase-locked loop (PLL) analysis module. The noisy thermal radiation surface temperature signal objectively includes the forced micro-perturbation thermal wave signal response component and the macroscopic environmental radiation noise. The PLL analysis module extracts the output excitation frequency set by the control module when the thermal excitation module injects the forced micro-perturbation thermal wave signal into the stainless steel track. The PLL analysis module uses the output excitation frequency as the reference local oscillator and constructs an orthogonal dual-channel synchronous signal based on the digitally controlled oscillator inside the PLL analysis module. The PLL analysis module generates an in-phase reference sine wave signal with the same frequency as the forced micro-perturbation thermal wave signal and an orthogonal reference cosine wave signal with a 90-degree phase offset.

[0051] S42, the phase-locked loop (PLL) parsing module performs frequency mixing and multiplication operations on the input noisy thermal radiation surface temperature signal with the in-phase reference sine wave signal and the quadrature reference cosine wave signal, respectively. The PLL parsing module then performs time-incremental integral extraction on the multiplied signal sequence within an integration time window set by the PLL parsing module. The integration time window set by the PLL parsing module is an integer multiple of the period corresponding to the output excitation frequency set by the control module. In this embodiment, the multiple of the period corresponding to the output excitation frequency set by the control module for the integration time window set by the PLL parsing module ranges from 10 to 100 times. The quadrature integral extraction operation has extremely narrow-band low-pass filtering characteristics and filters out macroscopic noise thermal flux interference components that are not at the same frequency as the output excitation frequency set by the control module. The specific integral calculation model expressions for the in-phase component and the quadrature component are as follows: ; ; In the formula, Extract the in-phase component of the output of the orthogonal integral operation; The set integration time window; The noisy thermal radiation surface temperature signal acquired by the targeted probe; This is the time variable in integration operations; The output excitation frequency of the local oscillator is used as a reference. It is a sine function operator; Pi is a constant. Differential operators for time integration; Extract the orthogonal components from the output of the orthogonal integral operation; The output excitation frequency of the local oscillator is used as a reference. It is the cosine function operator.

[0052] S43, the phase-locked loop (PLL) analysis module extracts the calculated in-phase and quadrature components. It then derives the purified pulse amplitude attenuation kernel parameter after removing background noise by extracting the square root of the sum of the squares of the in-phase and quadrature components. The PLL analysis module calls the four-quadrant arctangent algorithm to calculate the continuous phase shift angle using the quadrature and in-phase components. It divides the continuous phase shift angle by the reference angular frequency calculated based on the output excitation frequency set by the control module to derive the phase hysteresis time parameter during the forced perturbation thermal wave signal transmission process. The pulse amplitude attenuation kernel parameter and the phase hysteresis time parameter physically characterize the evolution of the microscopic polymerization impedance caused by the cross-linking and solidification of macromolecules within the material. The specific conversion model expressions for the pulse amplitude attenuation kernel parameter and the phase hysteresis time parameter are as follows: ; ; In the formula, To purify the pulse amplitude decay kernel parameters that characterize the evolution of the microscopic polymerization impedance of materials; Extract the in-phase component of the output of the orthogonal integral operation; Extract the orthogonal components from the output of the orthogonal integral operation; To purify and characterize the phase hysteresis time parameter that characterizes the evolution of the microscopic polymerization impedance of materials; This is a four-quadrant arctangent operation operator based on joint determination of horizontal and vertical coordinates; Extract the orthogonal components from the output of the orthogonal integral operation; Extract the in-phase component of the output of the orthogonal integral operation; Pi is a constant. The output excitation frequency is used as the reference local oscillator.

[0053] See attached document Figure 5 In specific implementations, step S5 provided by the present invention may include the following steps: S51, the actual aggregation endpoint horizontal coordinate value of the final calibration output of the state verification module is determined by the direct truth value operation result of the Boolean logic discrimination matrix configured by the state verification module. The conventional initial physical boundary verification and multi-dimensional feature mapping layer data processing and other pre-processing procedures have been confirmed by the control module as valid basic execution contexts. The pre-denoising and dimensional normalization mapping operations in the pre-processing procedures directly inherit the existing well-known algorithm framework in this field and are completed by the control module in the operation initialization stage.

[0054] S52, the extreme value constant and threshold parameters set by the control module are directly imported into the comparator module inside the state verification module as predetermined known conditions to execute the standard state verification process. In this embodiment, the value range of the convergence rate determination extreme value constant preset by the control module is 0.05 to 0.15, the value range of the humidity attenuation extreme value constant preset by the control module is 0.01 to 0.05, the value of the amplitude attenuation lower limit threshold preset by the control module is set to 10% of the initial response peak value of the forced micro-perturbation thermal wave signal pre-calibrated by the control module, and the value range of the phase hysteresis upper limit threshold preset by the control module is 0.2 to 0.4 times the period corresponding to the output excitation frequency set by the control module.

[0055] S53, the state verification module skips the linear univariate iterative discrimination step and directly calls the Boolean logic discrimination matrix to perform global result judgment. The state verification module extracts the time-domain convergence rate of the vertical temperature difference gradient, the absolute humidity decrease feature, the pulse amplitude attenuation kernel parameter, and the phase hysteresis time parameter, and forces the execution of a quaternion simultaneous matching calculation. The state verification module directly outputs the actual aggregation endpoint lateral coordinate value through mask multiplication within the Boolean constraint domain. The specific aggregation endpoint latching conditions and coordinate calibration analytical model expressions are as follows: ; ; In the formula, The state truth value output by the Boolean logic discrimination matrix; The time-domain convergence rate of the vertical temperature gradient; The current time of the determination; The preset convergence rate is used to determine the extreme value constant; This is the preset extreme constant for humidity attenuation; To calculate the absolute humidity decrease characteristic of the output; To purify the pulse amplitude decay kernel parameters that characterize the evolution of the microscopic polymerization impedance of materials; This is the preset lower threshold for amplitude attenuation; To purify and characterize the phase hysteresis time parameter that characterizes the evolution of the microscopic polymerization impedance of materials; The preset upper limit threshold for phase hysteresis; For logical AND operator; To calibrate the actual horizontal coordinate value of the aggregation endpoint in the output; To determine the horizontal physical coordinate position corresponding to the moment when the truth value is true; The current time of the determination; The state truth value output by the Boolean logic discrimination matrix.

[0056] See attached document Figure 6 In specific implementations, step S6 provided by the present invention may include the following steps: S61, the adaptive control module extracts the actual aggregation endpoint horizontal coordinate value output by the state verification module. The adaptive control module is configured with zero value filtering logic. When the actual aggregation endpoint horizontal coordinate value is zero, the adaptive control module maintains the instruction state of the previous discrete control cycle. When the actual aggregation endpoint horizontal coordinate value is a non-zero valid value, the adaptive control module synchronously reads the target aggregation endpoint spatial coordinate setting value issued by the host computer process formula database. In this embodiment, the target aggregation endpoint spatial coordinate setpoint ranges from 80% to 90% of the total effective heating range of the stainless steel conveyor belt within the drying chamber. The adaptive control module calls the differential operation unit within the adaptive control module to calculate the spatial position deviation parameter under the current discrete control cycle. The adaptive control module achieves quantitative tracking of the physical state by comparing the positional difference between the target aggregation endpoint spatial coordinate setpoint and the actual aggregation endpoint lateral coordinate value. The specific spatial position deviation calculation model expression is as follows: ; In the formula, For the first Spatial position deviation parameters for each discrete control cycle; This is the current discrete control cycle number; Set values ​​for the spatial coordinates of the target aggregation endpoint; For the status verification module in the current number The actual horizontal coordinate value of the aggregation endpoint output in each control cycle.

[0057] S62, the adaptive control module directly inputs the calculated spatial position deviation parameter into the discrete proportional integral controller configured inside the adaptive control module to perform closed-loop calculation. When performing closed-loop calculation for the first time, the adaptive control module assigns the historical running linear velocity of the previous control cycle to the base running linear velocity and initializes the historical spatial position deviation parameter of the previous control cycle to zero. The adaptive control module extracts the proportional gain constant and integral gain constant preset by the control module, and calculates and outputs the track running linear speed update command by combining the spatial position deviation parameter under the current discrete control cycle and the historical spatial position deviation parameter of the previous control cycle. In this embodiment, the value range of the proportional gain constant is 0.1 to 0.5, and the value range of the integral gain constant is 0.01 to 0.05. The adaptive control module outputs a track speed update command by superimposing the historical linear velocity of the stainless steel track executed in the previous control cycle with the current deviation correction calculated based on the spatial position deviation parameter of the current discrete control cycle and the historical spatial position deviation parameter. The specific analytical model expression for the linear velocity closed-loop regulation is as follows: ; In the formula, To solve the output of the first Track running linear speed update command for each control cycle; This is the current discrete control cycle number; The historical operating linear velocity executed in the previous control cycle; For the first Spatial position deviation parameters for each discrete control cycle; This refers to the historical spatial position deviation parameter from the previous control cycle; The proportional gain constant is configured; This is the configured integral gain constant.

[0058] S63, the adaptive control module synchronously calculates the volumetric flow rate setpoint that matches the track running linear speed update command based on the material spreading width fixed by the control module and the initial spreading thickness target value preset by the control module. The adaptive control module converts the track running linear speed update command into a frequency control signal and sends it to the drive motor based on the mechanical transmission ratio of the equipment transmission mechanism configured in the track module. Simultaneously, the adaptive control module sends the volumetric flow rate setpoint to the feed pump of the material distribution module. The adaptive control module maintains a constant physical spreading thickness of the material on the stainless steel track surface based on a fixed volumetric flow rate conservation relationship. The specific volumetric flow rate synchronous matching calculation model expression is as follows: ; In the formula, For the first Volumetric flow rate setpoint for each control cycle; This is the current discrete control cycle number; To solve the output of the first Track running linear speed update command for each control cycle; The width of the material to be laid out in the system; This is the preset initial tiling thickness target value.

[0059] S64. The specific basic hardware execution process of the discrete proportional-integral controller performing closed-loop calculation and the drive motor receiving frequency control signals to perform speed regulation can be directly configured in this embodiment based on the conventional variable frequency vector control protocol and the ladder diagram logic of the programmable logic controller. The basic drive and instruction interaction method of the discrete proportional-integral controller performing closed-loop calculation and the drive motor receiving frequency control signals to perform speed regulation is a well-known technology in this field.

[0060] Application Examples: See attached document Figure 7 and attached Figure 8 To better understand the technical solution of the present invention, the following is an application example using the continuous production of polydextrose: When the system starts, the adaptive control module calculates the basic operating linear velocity and simultaneously calculates the initial volumetric flow rate of the feed pump. The liquid mixture flows through the flow equalization component and is spread evenly onto the stainless steel conveyor belt before entering the drying chamber. In the initial heating stage, the surface moisture of the material evaporates and absorbs heat. The bottom temperature sensor array and the top infrared sensor array respectively acquire the raw data of the bottom temperature and the surface temperature. The humidity transmitter acquires the raw data of the absolute humidity in the gas phase space inside the exhaust duct.

[0061] When the material moves to a fixed physical coordinate position with the stainless steel track, the thermal excitation module generates an alternating magnetic field at the bottom of the stainless steel track and generates a forced micro-perturbation thermal wave signal. The forced micro-perturbation thermal wave signal penetrates the material vertically upward and forms temperature oscillations on the material surface. As the production process progresses, the material gradually changes from a liquid state to a colloidal structure through micro-crosslinking. The targeted probe acquires the noisy thermal radiation surface temperature signal of a specific coordinate area. The phase-locked analysis module performs orthogonal integral extraction on the noisy thermal radiation surface temperature signal. The phase-locked analysis module calculates the pulse amplitude attenuation kernel parameters and phase hysteresis time parameters after purification and stripping of background noise.

[0062] The state verification module extracts the time-domain convergence rate of the vertical temperature gradient, the absolute humidity decrease characteristics, the pulse amplitude attenuation kernel parameter, and the phase hysteresis time parameter. The state verification module uses a Boolean logic discrimination matrix to perform a quaternary simultaneous matching calculation. The state verification module calibrates and outputs the actual polymerization endpoint lateral coordinate value. The adaptive control module calculates the spatial position deviation parameter between the actual polymerization endpoint lateral coordinate value and the target polymerization endpoint spatial coordinate setpoint. The adaptive control module outputs the track running linear speed update command to the drive motor. The adaptive control module synchronously sends the updated volumetric flow rate setpoint to the feed pump. The actual polymerization endpoint lateral coordinate value converges to the target polymerization endpoint spatial coordinate setpoint with the iteration of the discrete control cycle. The material then passes through the cooling zone with the stainless steel track to complete the cooling and solidification to produce polydextrose product.

[0063] In the experimental verification and effect comparison stage, the system introduced a constant speed and constant temperature open-loop control method as a control group to conduct a comparative experiment on continuous production of polydextrose. The control group adopted a fixed track linear speed and fixed feed volume flow rate operation mode and relied on the set drying chamber to operate at a fixed heating temperature. The experimental group used a thermal detection module, thermal excitation module, phase-locked analysis module and an adaptive control module based on Boolean logic discrimination matrix judgment. The experimental group dynamically adjusted the drive motor speed and synchronously matched the feed pump volume flow rate according to the spatial position deviation parameter.

[0064] After continuous production was completed, the polydextrose products produced by the control group and the experimental group were sampled and tested, and the equipment status parameters during the production process were statistically analyzed. According to the statistical comparison results, the fluctuation range of the horizontal coordinate value of the polymerization endpoint position of the experimental group was smaller than that of the control group, the degree of polymerization qualification rate of the product of the experimental group was higher than that of the control group, the difference in moisture content between batches of the product of the experimental group was smaller than that of the control group, the statistical value of system unit product operating energy consumption of the experimental group was lower than that of the control group, and the time required for the experimental group to reach the target polymerization endpoint spatial coordinate setting value from the system startup stage was shorter than that of the control group.

[0065] The control group experienced a drift in the polymerization endpoint position due to differences in the initial state of the material caused by surface temperature control. The experimental group extracted the response parameters of the forced micro-perturbation thermal wave signal and used the time-domain convergence rate of the vertical temperature gradient and the absolute humidity decrease characteristics as the basis for judgment. The experimental group used a discrete proportional-integral controller to perform closed-loop calculation to control the actual horizontal coordinate value of the polymerization endpoint at the set value of the target polymerization endpoint spatial coordinate. The experimental group matched the volumetric flow rate of the feed pump according to a fixed volumetric flow rate conservation relationship to maintain the material spreading thickness at a constant state. The system and method provided by this invention realize the constant thickness and control of the target polymerization endpoint position in the continuous production process of polydextrose.

[0066] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these specific embodiments are merely illustrative. Those skilled in the art can omit, substitute, and modify the details of the above methods and systems in various ways without departing from the principles and essence of the present invention. For example, combining the above method steps to perform substantially the same function and achieve substantially the same result using substantially the same method falls within the scope of the present invention.

Claims

1. A continuous polydextrose production system, characterized in that, include: The fabric module is located at the feed end of the drying chamber and is equipped with a feed pump; The track module runs through the drying chamber and includes a stainless steel track and a drive motor. The drying chamber is divided into an aggregation zone, a drying zone and a cooling zone along the material running direction. A thermal detection module is arranged inside the drying chamber and in the top exhaust duct, including a bottom temperature sensor array, a top infrared sensor array, and a humidity transmitter. A thermal excitation module is disposed between adjacent detection sites of the bottom temperature sensor array for injecting forced micro-perturbation thermal wave signals into the bottom of the stainless steel track. The control module is electrically connected to the fabric module, track module, thermal detection module and thermal excitation module respectively, and includes an acquisition and filtering module, an offset calculation module, a phase-locked loop analysis module, a status verification module and an adaptive control module. The thermal detection module is used to acquire raw thermal detection data and thermal response data formed after the forced micro-perturbation thermal wave signal acts on the material. The control module determines characteristic parameters characterizing the polymerization state of the material based on the raw thermal detection data and thermal response data, calibrates the lateral coordinate value of the actual polymerization endpoint, and implements closed-loop control of the running linear speed of the stainless steel track and the volumetric flow rate of the feed pump based on the positional deviation between the lateral coordinate value of the actual polymerization endpoint and the set value of the spatial coordinate of the target polymerization endpoint.

2. The polydextrose continuous production system according to claim 1, characterized in that, The adaptive control module is used to obtain the total length of the effective heating zone and the target retention time of the material, and to calculate the basic running linear speed of the stainless steel track based on the total length of the effective heating zone and the target retention time of the material; the adaptive control module is also used to simultaneously calculate the initial volumetric flow rate setting value of the feed pump based on the curing material spreading width and the preset initial spreading thickness target value.

3. The polydextrose continuous production system according to claim 1, characterized in that, The acquisition and filtering module is used to receive the raw thermal detection data and perform moving average filtering to remove noise, extract the smoothed bottom temperature and surface temperature values, calculate the time-domain convergence rate of the vertical temperature gradient, and derive the absolute humidity decrease characteristics based on the difference in absolute humidity values ​​after smoothing at continuous sampling times.

4. The polydextrose continuous production system according to claim 3, characterized in that, The electromagnetic induction coil inside the thermal excitation module generates an alternating magnetic field according to the received drive pulse command, and generates a forced micro-perturbation thermal wave signal in the stainless steel track area corresponding to the thermal excitation module. The offset calculation module performs integral calculation on the acquired instantaneous running linear velocity data within the time window corresponding to the preset estimated thermal hysteresis parameter to obtain the lateral physical space offset. The fixed physical starting coordinates where the thermal excitation module is located are superimposed with the lateral physical space offset to obtain the expected physical target coordinates. Under the constraint of the preset effective field of view radius of a single probe, the target probe in the top infrared sensor array is selected and locked.

5. The polydextrose continuous production system according to claim 4, characterized in that, The control module is used to directionally activate the locked target probe to perform data acquisition, and simultaneously send a forced shutdown command to block the signal sampling channel of the non-target probe in the top infrared sensor array; the target probe is used to acquire the noisy thermal radiation surface temperature signal and transmit it to the phase-locked parsing module.

6. The polydextrose continuous production system according to claim 5, characterized in that, The phase-locked analysis module uses the set output excitation frequency as the reference local oscillator to construct an in-phase reference sine wave signal and an orthogonal reference cosine wave signal. It then performs frequency mixing and multiplication operations on the noisy thermal radiation surface temperature signal with the in-phase reference sine wave signal and the orthogonal reference cosine wave signal, respectively. Within the set integration time window, it performs time infinitesimal element integration extraction operations and outputs the in-phase component and the orthogonal component.

7. The polydextrose continuous production system according to claim 6, characterized in that, The phase-locked loop (PLL) parsing module obtains the pulse amplitude attenuation kernel parameter by calculating the square root of the sum of the squares of the in-phase component and the quadrature component, and calls the arctangent algorithm to calculate the continuous phase shift angle based on the quadrature component and the in-phase component. The continuous phase shift angle is then divided by the reference angular frequency calculated based on the output excitation frequency to obtain the phase hysteresis time parameter.

8. The polydextrose continuous production system according to claim 7, characterized in that, The state verification module extracts the time-domain convergence rate of the vertical temperature gradient, the absolute humidity decrease feature, the pulse amplitude attenuation kernel parameter, and the phase hysteresis time parameter, and performs a quaternary simultaneous matching calculation on the above parameters according to the internally configured Boolean logic discrimination matrix to make a global judgment, and calibrates and outputs the actual aggregation endpoint horizontal coordinate value within the Boolean constraint domain.

9. The polydextrose continuous production system according to claim 1, characterized in that, The adaptive control module extracts the lateral coordinate value of the actual aggregation endpoint, and when the lateral coordinate value of the actual aggregation endpoint is a non-zero valid value, it obtains the spatial coordinate setpoint of the target aggregation endpoint, calculates the spatial position deviation parameter between the spatial coordinate setpoint of the target aggregation endpoint and the lateral coordinate value of the actual aggregation endpoint; the adaptive control module inputs the spatial position deviation parameter into the internally configured discrete proportional-integral controller to perform closed-loop calculation, and superimposes the current deviation correction amount and the historical running linear speed, and outputs the track running linear speed update command.

10. The polydextrose continuous production system according to claim 9, characterized in that, The adaptive control module calculates the volumetric flow rate setting value that matches the track running linear speed update command based on the solidified material spreading width and the preset initial spreading thickness target value, and sends it to the feed pump. The adaptive control module also converts the track running linear speed update command into a frequency control signal and sends it to the drive motor to maintain a constant physical spreading thickness of the material on the stainless steel track surface.

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