Plant fiber flexible dissociation and high-valued intelligent production system and method

Abstract

The invention relates to the technical field of fiber material processing, and discloses a plant fiber flexible dissociation and high-valued intelligent production system and method. The collaborative preprocessing module calculates a medicament concentration compensation value based on raw material component fingerprints and a reaction product release rate and executes characteristic feed-forward control, the signal sensing module collects multi-source physical field signals such as stator current and mechanical vibration, and the operation control module receives the signals and executes a dual noise suppression strategy of carrier frequency shift and angular domain resampling. A residual signal representing the rheological state of the material is separated out, then the rigidity and toughness modulus characteristics of the raw material are decoupled and calculated, a variable impedance control model constructed based on the characteristics generates an equivalent rigidity and damping coefficient instruction in real time, and the two-way dissociation module is driven to be adaptively switched between a rigid positioning mode and a flexible floating mode. The problem of fiber damage caused by heterogeneity of raw materials is effectively solved, and the production efficiency and the fiber quality are improved.

Description

Technical Field

[0001] This invention relates to the field of fiber material processing technology, specifically to an intelligent production system and method for flexible dissociation and high-value processing of plant fibers. Background Technology

[0002] The high-value utilization of plant fibers relies on efficient dissociation processes, which involve mechanically separating plant materials into individual fibers and promoting their fine fibrillation, thereby exposing more active hydroxyl groups. Currently, industrial production mainly uses mechanical equipment such as disc mills, which use high-speed rotating discs to generate shearing, extrusion, and frictional forces on the fiber raw materials to change their morphology and structure.

[0003] Plant-based raw materials originate from nature and exhibit significant biological heterogeneity. Raw materials from different origins, batches, and even within the same batch, exhibit dynamic differences in lignin content, hardness, toughness, and fiber aspect ratio. Most existing dissociation equipment employs constant gap, constant power, or simple constant specific energy consumption control modes. This rigid control logic struggles to adapt to real-time fluctuations in raw material characteristics. In actual production, when the raw material is hard or the feed is uneven, the rigidly set mechanical gap often leads to excessive shearing force applied to the fibers by the grinding teeth, directly cutting the fibers instead of achieving the intended kneading and splitting effect. This unexpected decrease in average fiber length severely compromises the physical strength of the final molded material. Conversely, when the raw material is soft or tough, the fixed force may be insufficient to disrupt the cell wall structure, resulting in incomplete dissociation and increased ineffective energy consumption.

[0004] To optimize the dissociation effect, some existing technologies attempt to introduce automatic control systems. However, the dissociation equipment operates under high-intensity mechanical background vibration, and the high-power frequency converter introduces complex electromagnetic interference. The weak physical field signals generated by the rheological behavior of the fiber material within the grinding disc gap are often submerged in the inherent structural vibrations and high-frequency carrier noise of the equipment. Existing signal monitoring methods mainly focus on macroscopic current or total vibration amplitude, making it difficult to effectively separate the characteristic signals that truly characterize the microscopic rheological state of the material in a high-noise environment. The lack of high signal-to-noise ratio process feedback data makes it impossible for the control system to perceive the real-time state of the fiber, hindering the achievement of precise and flexible control for fiber protection. Furthermore, existing production lines typically manage the preceding chemical pretreatment and subsequent mechanical dissociation as independent processes, lacking cross-process collaborative linkage based on raw material characteristics, making it difficult to further reduce overall energy consumption while ensuring the integrity of the fiber morphology. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a plant fiber flexible dissociation and high-value intelligent production system and method, which solves the technical problems of existing dissociation equipment being unable to perceive the real-time rheological state of materials due to strong background noise interference, making it impossible for constant control parameters to adapt to the biological heterogeneity of raw materials, thus causing severe fiber damage and low dissociation efficiency.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a plant fiber flexible dissociation and high-value intelligent production system and its components; The collaborative preprocessing module is used to acquire raw material component fingerprint data and product release rate data during the enzymatic hydrolysis process, and calculate the reagent concentration compensation value of the chemical treatment process based on the raw material component fingerprint data and product release rate data, and perform feature feedforward control. The dual-path dissociation module includes a frequency converter drive unit that adjusts the rotational motion of the dissociation rotor and a hydraulic servo unit that adjusts the axial feed motion of the dissociation cavity. It is used to receive control commands to drive the physical actuator to switch between rigid positioning mode and flexible floating mode. The signal sensing module is used to collect physical field signals that reflect the system's operating status and material rheological behavior. The physical field signals include at least the stator current of the drive motor, the mechanical vibration of the dissociation cavity, and the angular position signal of the dissociation rotor. The computational control module is used to receive the physical field signal, execute a dual noise suppression strategy to separate the residual signal characterizing the rheological state of the raw material, perform feature decoupling analysis on the residual signal, calculate the stiffness modulus characteristic characterizing the hardness and brittleness of the raw material and the toughness modulus characteristic characterizing the toughness of the raw material, and then construct a variable impedance control model, and generate a composite control command containing the equivalent stiffness coefficient and the equivalent damping coefficient in real time and send it to the dual-path decoupling module.

[0007] Preferably, the collaborative pretreatment module includes a spectral analysis unit, a biological enzymatic hydrolysis reaction unit, and a chemical dissociation reaction unit arranged sequentially along the material flow direction; the collaborative pretreatment module is configured to determine the target set concentration of the chemical reagent in the chemical dissociation reaction unit, the target set concentration being determined by subtracting a compensation gain term from a baseline concentration term, the baseline concentration term being the product of the raw material type correction coefficient and the baseline concentration constant of the process design, and the compensation gain term being the product of the biochemical reaction efficiency compensation gain coefficient and the time integral value of the reducing sugar release rate.

[0008] Preferably, the hydraulic servo unit in the dual-path dissociation module adopts a variable structure execution mechanism based on a variable impedance model. The hydraulic servo unit outputs an axial force according to the equivalent stiffness coefficient and equivalent damping coefficient issued by the calculation control module. The axial force is composed of a reference force offset, a position adjustment term, and a speed adjustment term superimposed. The position adjustment term is the product of the equivalent stiffness coefficient and the position deviation of the grinding disc gap, and the speed adjustment term is the product of the equivalent damping coefficient and the speed deviation of the grinding disc gap.

[0009] Preferably, the signal sensing module includes an electrical acquisition unit, a vibration acquisition unit, and an angle acquisition unit; The electrical acquisition unit includes a high-frequency current transformer installed at the output terminal of the frequency converter drive unit. The upper limit cutoff frequency of the bandwidth of the high-frequency current transformer is set to be no less than 3 times the carrier frequency of the frequency converter drive unit. The vibration acquisition unit includes a piezoelectric accelerometer mounted on the dissociation cavity; the angle acquisition unit includes a rotary encoder mounted on the main shaft of the dissociation rotor, wherein the number of pulses per revolution of the rotary encoder is set according to the angle domain sampling theorem and serves as the signal reference for the operation and control module to perform angle domain resampling.

[0010] Preferably, the dual noise suppression strategy implemented by the operation control module includes active electrical carrier cleaning logic; the operation control module monitors the carrier frequency of the frequency conversion drive unit and the mechanical characteristic frequency of the mechanical structure in real time, and when the carrier frequency falls within the sideband protection range of the mechanical characteristic frequency, it calculates and adjusts the carrier frequency setting value and sends it to the dual-path decoupling module; the carrier frequency setting value is set as the sum of the original carrier frequency and the frequency shift compensation amount, the frequency shift compensation amount is determined by multiplying the frequency domain protection bandwidth and the safety margin frequency by the direction sign function, and the direction sign function depends on the sign of the difference between the original carrier frequency and the mechanical characteristic frequency.

[0011] Preferably, the dual noise suppression strategy implemented by the computation control module further includes angular domain signal reconstruction logic and mechanical background differential logic; the computation control module uses the dissociated rotor angular position signal to resample the mechanical vibration signal into an angular domain stationary signal, and uses a synchronous averaging algorithm to construct a mechanical background baseline, and separates the rheological residual signal by subtracting the angular domain stationary signal from the mechanical background baseline.

[0012] Preferably, the calculation control module is used to calculate the stiffness modulus characteristic, and the calculation method of the stiffness modulus characteristic is as follows: The power spectral density of the rheological residual signal is integrated within a preset high-frequency characteristic band, and the integration result is divided by the normalized reference energy constant.

[0013] Preferably, the calculation control module is used to calculate the toughness modulus characteristic, and the calculation method of the toughness modulus characteristic is as follows: Based on the stator current signal, the sideband energy ratio method is used to calculate the ratio of the sum of current amplitudes at characteristic sideband frequencies to the current amplitude at the fundamental frequency.

[0014] Preferably, the calculation control module calculates the equivalent stiffness coefficient and the equivalent damping coefficient in real time based on the stiffness modulus characteristics and the toughness modulus characteristics; The equivalent stiffness coefficient is set as the sum of the basic stiffness and the stiffness increment term, and the stiffness increment term is proportional to the portion of the stiffness modulus characteristic that exceeds the stiffness characteristic trigger threshold; the equivalent damping coefficient is set as the difference between the nominal damping coefficient and the damping reduction term, and the damping reduction term is proportional to the toughness modulus characteristic.

[0015] A method for intelligent production of flexible dissociation and high-value processing of plant fibers includes the following steps: Near-infrared spectroscopy is used to obtain the spectral data of raw materials to calculate the type correction factor. At the same time, the reducing sugar release rate during the enzymatic hydrolysis process is monitored in real time. Based on the integral deviation between the type correction factor and the release rate, the concentration of reagents in subsequent chemical treatment processes is dynamically calculated and adjusted. The stator current of the drive motor, the mechanical vibration of the dissociation cavity, and the rotor angular position signal are collected synchronously through a current transformer, an accelerometer, and a rotary encoder. During the acquisition process, it is determined whether the inverter carrier frequency covers the characteristic frequency band. If it does, active carrier frequency shifting is performed. At the same time, the rotor angular position signal is used to perform angular domain resampling and synchronous average differential on the mechanical vibration signal to eliminate deterministic mechanical background noise and obtain rheological residual signal. The rheological residual signal is subjected to high-frequency energy integration to calculate the stiffness modulus characteristic of the microhardness of the raw material, and the stator current signal is subjected to sideband analysis to calculate the toughness modulus characteristic of the degree of entanglement of the raw material. Substituting the stiffness modulus characteristics and the toughness modulus characteristics into the variable impedance control model, the equivalent stiffness coefficient and equivalent damping coefficient required by the system are calculated in real time, and pressure and position composite commands are generated accordingly to drive the hydraulic servo mechanism, so that the physical properties of the dissociation process can adaptively switch between rigid crushing and flexible kneading.

[0016] This invention provides an intelligent production system and method for the flexible dissociation and high-value utilization of plant fibers. It has the following beneficial effects: 1. This invention solves the problem of processing quality fluctuations caused by the biological heterogeneity of raw materials by combining the characteristic feedforward of chemical processes with the variable impedance feedback of physical processes. The collaborative pretreatment module compensates for the reagent concentration in advance based on the raw material fingerprint and enzymatic hydrolysis rate, eliminating the initial differences in the anti-dissociation characteristics of the raw materials; the computational control module dynamically adjusts the equivalent stiffness and damping of the actuator based on the real-time hardness and toughness modulus of the raw materials, so that the processing mode automatically switches between rigid crushing and flexible kneading. The composite control mechanism effectively avoids the excessive cutting or insufficient dissociation of fibers caused by traditional constant parameter processing, and significantly improves the long fiber retention rate and product homogeneity.

[0017] 2. This invention avoids the masking of mechanical characteristic frequency bands by electrical harmonics by monitoring the variable frequency carrier frequency and performing active frequency shifting; it uses angular domain resampling and synchronous averaging algorithms to construct and subtract the mechanical background baseline, separating the pure rheological residual signal. This strategy overcomes the deficiency of traditional time-domain analysis in distinguishing between the inherent vibration of equipment and the rheological response of materials, providing a high signal-to-noise ratio data foundation for highly dynamic closed-loop control.

[0018] 3. This invention improves the dynamic response characteristics and energy efficiency ratio of the system by utilizing a variable-structure hydraulic servo unit. The execution mechanism based on the variable impedance model allows the dissociation chamber to automatically adjust the axial force according to load changes. The position adjustment term maintains the stability of the dissociation gap, while the speed adjustment term provides necessary flexible buffering. The design enables the system to quickly retract to protect the grinding disc structure when handling hard impurities or instantaneous high loads, while maintaining a constant energy flow density when handling conventional materials. Compared with traditional rigid feed methods, this reduces energy consumption per unit output and extends the service life of core components. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the system framework of the present invention; Figure 2 This is a flowchart of the method of the present invention; Figure 3 This is a flowchart illustrating the operational logic of the collaborative preprocessing module of the present invention. Figure 4 This is a logic diagram of the dual-path decoupling module of the present invention; Figure 5 This is the operational logic diagram of the signal sensing module of the present invention; Figure 6 This is the operational logic diagram of the computation control module of the present invention; Figure 7 This is a simulation waveform diagram of the dynamic response of the present invention; Figure 8 The waveform diagram is a simulation diagram of the dynamic response of the present invention.

[0020] Among them, 10 is the collaborative preprocessing module; 20 is the dual-path decomposition module; 30 is the signal sensing module; and 40 is the operation control module. Detailed Implementation

[0021] 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.

[0022] Please see the appendix Figure 1 This invention provides an intelligent production system for flexible dissociation and high-value production of plant fibers, including a collaborative preprocessing module 10, a dual-path dissociation module 20, a signal sensing module 30, and a computational control module 40. The collaborative preprocessing module 10, the dual-path dissociation module 20, and the signal sensing module 30 are respectively connected to the computational control module 40 to form a closed-loop control circuit based on feature feedforward and state feedback.

[0023] The collaborative pretreatment module 10 is located at the front end of the process flow and is used to determine the initial processing parameters based on the biochemical characteristics of the raw materials. This module integrates a spectral analysis unit and a biochemical reaction monitoring unit, enabling it to acquire raw material component fingerprint data and product release rate data during the enzymatic hydrolysis process. The collaborative pretreatment module 10 internally stores a raw material correction factor library, which is used to calculate the raw material type correction coefficient based on the spectral data and, in conjunction with the enzymatic hydrolysis reaction rate, calculate the reagent concentration compensation value for subsequent chemical treatment processes. Dual-channel dissociation module 20 is the physical execution terminal of the system, receiving control commands to change the physical processing environment. Dual-channel dissociation module 20 includes a frequency conversion drive unit and a hydraulic servo unit. The frequency conversion drive unit is configured to adjust the rotation speed and carrier frequency parameters of the dissociation rotor, and the hydraulic servo unit is used to adjust the dynamic and static gap and axial force of the dissociation cavity. It has variable stiffness and variable damping response capabilities and can switch between rigid positioning mode and flexible floating mode according to the command. The signal sensing module 30 is used to collect physical field signals that reflect the system's operating status and material rheological behavior. It includes an electrical acquisition unit, a vibration acquisition unit, and an angle acquisition unit. The electrical acquisition unit is used to acquire the instantaneous waveform of the stator current of the drive motor, the vibration acquisition unit is used to acquire the mechanical vibration acceleration waveform of the dissociation cavity, and the angle acquisition unit is used to acquire the real-time angular position and speed pulse signals of the dissociation rotor. The operation and control module 40 is used to receive multi-source heterogeneous data transmitted by the signal sensing module 30, and performs electrical carrier frequency shifting and mechanical background angular domain differential processing on the original signal based on a dual noise suppression strategy to separate the residual signal characterizing the rheological state of the raw material; then, it performs frequency domain and order domain feature decoupling analysis on the residual signal, calculates the orthogonal physical modulus characteristics characterizing the hardness and toughness of the raw material, and constructs a variable impedance control model accordingly, and generates a composite control command containing equivalent stiffness and equivalent damping parameters in real time and sends it to the dual-path decoupling module 20, thereby driving the physical actuator to dynamically and adaptively switch between rigid grinding and flexible kneading modes.

[0024] See attached document Figure 2 , Figure 2 This is a flowchart of a plant fiber flexible dissociation method according to an embodiment of the present invention. The present invention provides a plant fiber flexible dissociation method, comprising the following steps: S10 uses near-infrared spectroscopy to obtain raw material spectral data to calculate the type correction factor, while monitoring the reducing sugar release rate in the enzymatic hydrolysis process in real time, and dynamically calculating and adjusting the reagent concentration of subsequent chemical treatment processes based on the integral deviation between the type correction factor and the release rate. S20 synchronously acquires stator current of drive motor, mechanical vibration of dissociation cavity and rotor angular position signals through current transformer, accelerometer and rotary encoder; during the acquisition process, it determines whether the carrier frequency of frequency converter covers the characteristic frequency band. If it does, it performs active carrier frequency shifting; at the same time, it uses angular position signal to perform angular domain resampling and synchronous average difference on mechanical vibration signal to eliminate deterministic mechanical background noise and obtain rheological residual signal. S30, perform high-frequency energy integration on the rheological residual signal obtained in step S20 to calculate the stiffness modulus characteristic of the microhardness of the raw material; at the same time, perform sideband analysis on the stator current signal to calculate the toughness modulus characteristic of the degree of entanglement of the raw material. S40 substitutes the stiffness modulus and toughness modulus characteristics into the variable structure impedance control model, calculates the equivalent mechanical stiffness coefficient and equivalent mechanical damping coefficient required by the system in real time, and generates pressure and position composite commands to drive the hydraulic servo mechanism, so that the physical properties of the dissociation process can adaptively switch between rigid crushing and flexible kneading.

[0025] The above modules will be described in detail below with reference to specific embodiments.

[0026] See attached document Figure 3 , Figure 3This is the operational logic diagram of the collaborative pretreatment module. In this embodiment, the collaborative pretreatment module 10 includes, in terms of physical structure, a spectral analysis unit, a bio-enzymatic hydrolysis reaction unit, and a chemical dissociation reaction unit arranged sequentially along the material flow direction. The spectral analysis unit is located at the feed port of the bio-enzymatic hydrolysis reaction unit and is used for non-contact scanning of the plant fiber raw materials during the transmission process. The material outlet of the bio-enzymatic hydrolysis reaction unit is connected to the material inlet of the chemical dissociation reaction unit through a pipeline, and a biochemical sensor for monitoring the concentration of reaction products is installed inside the bio-enzymatic hydrolysis reaction unit. The chemical dissociation reaction unit is equipped with a controlled fluid metering pump for adjusting the real-time addition amount of the chemical dissociation agent according to control commands.

[0027] In the specific implementation process, the spectral analysis unit is an online near-infrared spectrometer, whose working band covers the characteristic absorption peak regions of plant cellulose, hemicellulose, and lignin. The collaborative preprocessing module 10 uses the spectral analysis unit to collect the raw spectral data of the raw materials and performs standard normal variable transformation and second derivative preprocessing on the raw spectral data to obtain fingerprint spectral vectors that can characterize the components of the raw materials. The collaborative preprocessing module 10 has a pre-built feature database containing standard spectral data of various plant fiber raw materials. By calculating the Mahalanobis or Euclidean distance between the real-time acquired fingerprint spectral vector and the standard vector in the feature database, the category cluster to which the current raw material belongs is determined, and the corresponding raw material type correction coefficient is extracted accordingly. The correction factor for the type of raw material. It is a dimensionless scalar used to quantify the differences in cell wall density among raw materials from different species.

[0028] The bio-enzymatic hydrolysis unit, as a pre-processing step before chemical treatment, is not only used for the initial softening of raw materials, but in this embodiment, its biochemical reaction kinetics are also used to characterize the anti-dissociation properties of the raw materials. The co-treatment module 10 monitors the changes in reducing sugar concentration within the bio-enzymatic hydrolysis unit in real time using biochemical sensors. Based on physicochemical control principles, the cumulative release amount or the integral value of the release rate of reducing sugar during the enzymatic hydrolysis reaction reflects the degree of damage to the microstructure of the fiber cell wall. When the degree of fiber wall damage is high during the enzymatic hydrolysis stage, it is manifested as a large integral value, meaning that the chemical bond breaking energy required for subsequent chemical dissociation processes is reduced, thus allowing for a corresponding reduction in the concentration of chemical reagents. Conversely, if the enzymatic hydrolysis effect is not significant, the concentration of chemical reagents needs to be increased to compensate for the deficiencies in the pre-treatment, thereby ensuring the stability of the final slurry quality.

[0029] The collaborative pretreatment module 10 dynamically calculates the required chemical reagent concentration setpoints for subsequent chemical dissociation reaction units based on the reducing sugar release rate and raw material type correction coefficient using a feedforward control algorithm. The specific feedforward calculation formula for chemical reagent concentration is as follows: ; In the formula, Indicates time The target concentration of chemical reagents in the chemical dissociation reaction unit. Represents a time variable. This represents the correction factor for the type of raw material determined by the spectral analysis unit. Indicates time The concentration of reducing sugars measured by a biochemical sensor. Represents the time variable of integration. This represents the instantaneous rate of change in reducing sugar concentration, i.e., the rate of enzymatic hydrolysis. Represents the differential symbol; Denotes an integral infinitesimal element. d This indicates the rate of enzymatic hydrolysis reaction within a time interval. The points on the top This represents the baseline concentration constant for process design. This constant corresponds to the recommended chemical reagent concentration for standard raw materials at standard enzymatic hydrolysis efficiency. The specific chemical pulping process specifications are determined based on the actual process, such as in alkaline pulping. The value usually corresponds to the effective alkali concentration, ranging from 20 g / L to 80 g / L (converted molar concentration).

[0030] This represents the compensation gain coefficient for biochemical reaction efficiency with respect to chemical dosage, used to adjust the sensitivity of feedforward control. The decrease in fiber polymerization degree corresponding to a unit concentration of reducing sugar release is determined through a pre-calibration experiment, and then converted into an equivalent amount of chemical reagent saved.

[0031] See attached document Figure 4 , Figure 4 This is the operational logic diagram of the dual-path dissociation module. In this embodiment, the dual-path dissociation module 20 includes a frequency converter drive unit and a hydraulic servo unit. The frequency converter drive subunit and the hydraulic servo execution subunit control the rotational motion of the dissociation rotor and the axial feed motion of the dissociation cavity, respectively, thereby creating a physical processing environment with multi-dimensional adjustment capabilities.

[0032] In practical implementation, the variable frequency drive unit uses a high-performance variable frequency drive (VFD) with vector control functionality. This VFD drive unit is equipped not only with a speed control interface for receiving speed commands but also with a carrier frequency modulation interface for establishing communication with the operational control module. The VFD drive unit is configured to respond to external commands and adjust the carrier frequency in real time within the switching frequency range allowed by the power devices. This configuration gives the VFD drive unit a dual function: firstly, it acts as a power source to drive the main drive motor at a set speed; secondly, it acts as a controllable signal generator, actively avoiding electrical interference in specific frequency bands by changing the carrier frequency in conjunction with subsequent noise suppression strategies.

[0033] The hydraulic servo unit's hydraulic circuit includes a high-frequency electro-hydraulic servo valve, a hydraulic cylinder, and an accumulator group connected in series. A micron-level displacement sensor is integrated at the piston rod end of the hydraulic cylinder, and pressure sensors are installed on the rod-side and rodless-side pipelines of the hydraulic cylinder. The displacement sensors provide real-time feedback on the actual gap position of the grinding disc. The pressure sensor provides real-time feedback on the output pressure of the hydraulic cylinder and converts it into the actual axial force. The electro-hydraulic servo valve adjusts the flow rate and direction of the hydraulic fluid entering the hydraulic cylinder based on the received control current, thus establishing the physical basis for dual regulation capabilities of position closed loop and force closed loop.

[0034] A variable structure actuation mechanism based on a variable impedance model is adopted. By establishing a dynamic relationship between the output force of the actuator and its position and velocity deviations, the hydraulic actuator exhibits variable mechanical impedance characteristics. The hydraulic servo unit operates according to the equivalent stiffness coefficient issued by the computational control module. and equivalent damping coefficient This dynamically changes the response characteristics of the hydraulic cylinder to changes in external load. Specifically, the output force of the hydraulic servo unit... It follows the impedance control equation as follows: ; In the formula, Indicates the reference force offset. This represents the equivalent stiffness coefficient, and the force gain corresponding to the positional deviation. This represents the equivalent damping coefficient and the force gain corresponding to the velocity deviation. and These represent the reference setting value and the actual measured value of the grinding disc clearance, respectively. and These represent the reference speed and the actual speed at which the grinding disc gap changes, respectively.

[0035] This represents the equivalent mechanical stiffness coefficient of the hydraulic system, used to ensure high stiffness in rigid positioning mode and compliance in flexible floating mode. The value range is set to the inherent stiffness of the hydraulic column. 5% to 95%. Among them, The effective working area of ​​the hydraulic cylinder, the bulk modulus of elasticity of the hydraulic oil, and the stroke are determined. The set value is close to At this time, it exhibits a rigid connection. Parameters This represents the equivalent mechanical damping coefficient of a hydraulic system, and its value is determined based on the system's critical damping. Determined, the range is usually set as follows Up to 4 (in (Equivalent mass of the moving grinding disc assembly) to ensure that the system does not oscillate or diverge while absorbing impact energy.

[0036] Through real-time adjustments and The parameters indicate that the dual-path decoupling module 20 can physically realize two processing modes and the stepless switching between them. When a high-stiffness command (i.e., Value greater than When the hydraulic servo unit reaches 80% of its set position, it enters rigid positioning mode. At this time, the hydraulic cylinder generates a large reverse restoring force against the positional deviation, forcing the grinding disc to remain within the set gap. This mode is suitable for powerfully crushing brittle and hard materials. When a low-stiffness, high-damping command is received (i.e.,...), the hydraulic servo unit enters rigid positioning mode. Value less than 20% and When the pressure is increased, the hydraulic servo unit enters the flexible floating mode. At this time, the hydraulic cylinder allows the grinding disc to elastically retract when it is squeezed by the raw material fiber clusters, and absorbs the impact energy through the damping phase. It is suitable for kneading and separating tough raw materials without cutting the fibers.

[0037] See attached document Figure 5 , Figure 5 This is the operational logic diagram of the signal sensing module. In this embodiment, the signal sensing module 30 is used to synchronously acquire multi-dimensional physical field data reflecting the rheological state of the dissociation process. The signal sensing module 30 includes an electrical acquisition unit, a vibration acquisition unit, and an angle acquisition unit, which are respectively arranged for the stator circuit of the drive motor, the dissociation cavity, and the rotating spindle.

[0038] The electrical acquisition unit is configured to capture the high-frequency modulation component in the stator current of the drive motor. Based on the principle of motor current characteristic analysis, when the plant fiber raw material undergoes rheological behavior in the dissociation gap, it causes instantaneous small fluctuations in the load torque. This torque fluctuation is coupled to the stator winding through the air gap magnetic field, manifesting as amplitude modulation or frequency modulation of the fundamental current, thereby generating sideband components containing raw material rheological information in the stator current spectrum. In this embodiment, the electrical acquisition unit includes a high-frequency current transformer installed on the three-phase connection cable between the output terminal of the frequency converter drive unit and the input terminal of the main drive motor.

[0039] To ensure complete capture of the stator current sideband signal caused by fiber entanglement, the bandwidth of this high-frequency current transformer needs to cover the fundamental frequency, the inverter carrier frequency, and its multiple harmonics. Specifically, the upper limit cutoff frequency of this bandwidth... It should be set to no less than the inverter carrier frequency. 3 times (i.e.) This ensures that higher-order sideband components near the carrier frequency can be acquired without distortion.

[0040] Based on the operating conditions of commonly used frequency converters, it exhibits a linearity better than 0.5%. The obtained instantaneous waveform of the stator current... It not only contains the fundamental component used for torque control, but also retains the high-frequency characteristic signals that are usually filtered out by conventional filters.

[0041] The vibration acquisition unit is configured to pick up the mechanical vibration response of the dissociation cavity during processing. The acquisition unit uses an industrial-grade piezoelectric accelerometer (IEPE), installed perpendicular to the shaft axis to acquire radial vibration, or parallel to the shaft axis to acquire axial vibration. The accelerometer's frequency response range is set to 0.5Hz to 10kHz, with a sensitivity of no less than 100mV / g, to output a vibration acceleration waveform that reflects the mechanical transfer function. .

[0042] The angle acquisition unit is the hardware reference for implementing the core function of angle domain resampling in this system. It includes an incremental high-resolution rotary encoder coaxially mounted on the unloaded end of the main drive motor. Unlike conventional encoders used only for speed feedback, the rotary encoder in this embodiment is configured to provide a high-precision angular position pulse signal as the angle reference signal for signal processing. The resolution of this rotary encoder is selected according to the angle domain sampling theorem, i.e., the number of pulses per revolution... Should meet ,in This represents the maximum mechanical order that the system needs to analyze.

[0043] During signal acquisition, the pulse signal output by the rotary encoder is not simply used to calculate the rotational speed, but rather serves as an external trigger source or interpolation reference for the resampling algorithm. This is achieved by acquiring the real-time rotor angle. This establishes a deterministic correspondence between time-domain sampling points and spatial rotation angles. For rotating machinery, many characteristic frequencies in vibration and current signals fluctuate with rotational speed, which manifests as energy dispersion and spectral diffusion in the time-domain spectrum. By introducing a high-resolution angle reference, subsequent calculation and control modules can establish a deterministic correspondence between time-domain sampling points and spatial rotation angles. Non-stationary signals in the time domain Resampling as a stationary signal in the angular domain This eliminates the interference of rotation speed fluctuations on feature extraction at the physical level.

[0044] See attached document Figure 6 In this embodiment, the computation control module 40 is used to extract the weak rheological characteristics of plant fiber raw materials from a strong industrial interference environment and convert them into real-time physical control commands for the dual-path dissociation module 20.

[0045] The operation and control module 40 first runs a dual-noise active suppression strategy. This includes electrical carrier active cleaning logic, corner domain signal reconstruction logic, and mechanical background differential logic. In the electrical carrier active cleaning logic, the operation and control module 40 monitors the current carrier frequency of the frequency converter drive unit in real time. and the real-time rotational frequency of the main drive motor A set of key mechanical characteristic frequencies requiring monitoring is pre-stored. The mechanical characteristic frequencies in this set... This mainly includes the frequency of rotor blade passage ( ,in (The number of teeth or blades of the grinding disc) and its first three harmonics.

[0046] When carrier frequency is detected Falling into a certain mechanical characteristic frequency Within the protection zone of the side strip, the judgment condition is met. At that time, it was determined that an interference conflict existed. Among these, the frequency domain guard bandwidth... The value is determined based on the resonance characteristics of the mechanical structure, and is set as the half-power bandwidth of the mechanical resonance peak, typically taken as 5 to 10 times the fundamental frequency. At this point, the calculation and control module 40 calculates the new carrier frequency setpoint. And send it to the frequency converter drive unit, the calculation formula follows the principle of minimum offset: ; In the formula, This represents the original carrier frequency at the current moment. This indicates the adjusted carrier frequency setting. Represents the characteristic frequency of a mechanical structure. Indicates the frequency domain protection bandwidth. Indicates the safety margin frequency, used to ensure a margin of safety for obstacle avoidance. Sign function. By actively shifting the frequency, the noise from the electrical carrier wave is prevented from overwhelming the characteristic frequency band of the mechanical vibration signal.

[0047] After completing the frequency domain cleanup of the electrical signal, the operation and control module 40 uses the angular position pulse signal acquired by the angle acquisition unit as a reference to process the acquired raw time-domain vibration signal. Angular domain signal reconstruction is performed. The arithmetic control module 40 employs order tracking technology, using the pulse of the rotary encoder as the trigger moment, to resample the non-stationary time-domain signal into a stationary angular domain signal. This eliminates spectral energy dispersion caused by speed fluctuations. Based on the reconstructed angular domain signal, the computation control module 40 further employs a synchronous averaging algorithm to construct the mechanical background baseline under the current operating conditions. : ; This represents the mechanical background baseline signal obtained through multi-rotation synchronous averaging. This represents the angle variable within a single rotation cycle. Indicates the rotation period index, Indicates the rotation period involved in synchronous averaging. This is the original angular domain signal after angular domain resampling.

[0048] After obtaining the baseline, the system performs differential calculations. This allows for the separation of residual signals characterizing the rheological state of the raw materials. ,in This represents the original angular domain signal after angular domain resampling. This represents the angular domain residual signal, used to characterize non-periodic perturbation components.

[0049] After acquiring a clean signal, the computational control module 40 enters the rheological characteristic decoupling and calculation stage. Microscopic fractures in hard materials can excite high-frequency stress waves, while long fiber entanglement in tough materials can cause low-frequency load torque fluctuations. Based on this, the computational control module 40 calculates the stiffness modulus characteristics respectively. With toughness modulus characteristics .

[0050] For stiffness modulus characteristics The operation and control module 40 handles rheological residual signals. Perform a Fast Fourier Transform and integrate the power spectral density within a preset high-frequency characteristic band. The calculation formula is as follows: ; In the formula, This represents the power spectral density of the rheological residual signal. Frequency variable, and These represent the lower and upper limits of the integration band, respectively. The normalized reference energy constant is the average high-frequency energy value measured by standard raw materials under rated operating conditions.

[0051] Targeting the characteristics of toughness modulus The operation and control module 40 uses the sideband energy ratio method to perform calculations based on the cleaned stator current signal: ; In the formula, Indicates the stator current at the fundamental frequency The amplitude at that point, Indicates the characteristic sideband frequency , To characterize the characteristic frequency of load fluctuation, To calculate the order, This represents the characteristic quantity of toughness modulus, used to characterize the modulation energy level related to raw material load fluctuations. This indicates the fundamental frequency of the stator current. Indicates the first two sides of the fundamental wave The characteristic sideband frequency of the first order, This indicates the order index of the sideband.

[0052] Finally, the operation and control module 40 executes the variable impedance control model and execution logic based on the characteristic indicators obtained from decoupling. This logic equates the hydraulic servo system to a second-order mechanical system with adjustable stiffness and damping, whose output pressure command... Following the impedance control equation: ; In the formula, Indicates the reference force offset. This represents the equivalent stiffness coefficient, and the force gain corresponding to the positional deviation. This represents the equivalent damping coefficient and the force gain corresponding to the velocity deviation. and These represent the reference setting value and the actual measured value of the grinding disc clearance, respectively. and These represent the reference speed and the actual speed at which the grinding disc gap changes, respectively.

[0053] To achieve adaptive machining, the computational control module 40 calculates based on stiffness modulus characteristics. Calculate the equivalent stiffness coefficient The calculation formula is: ; Simultaneously based on the toughness modulus characteristics Calculate the equivalent damping coefficient The calculation formula is: ; In the formula, This represents the equivalent stiffness coefficient, used for adaptive adjustment of the closed-loop stiffness of the system. This indicates the maximum allowable closed-loop stiffness of the hydraulic system. Indicates stiffness adaptive gain. Represents the characteristic quantity of stiffness modulus. This indicates the threshold for triggering stiffness characteristics. This represents the equivalent damping coefficient, used for adaptive adjustment of the system's damping level. This indicates the nominal damping coefficient. Indicates the damping adaptive gain. This indicates the expected range of variation in toughness characteristics, when high raw material hardness is detected ( Large), automatically increases To enhance crushing force; when high fiber toughness is detected ( (Large), the system automatically reduces It provides flexible yielding, thereby enabling intelligent dissociation for different raw material characteristics.

[0054] To enable those skilled in the art to better understand the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other.

[0055] This embodiment provides a high-yield chemimechanical pulp adaptive refining application based on the above system. To verify the actual application effect and compatibility of this system, the raw material system selected in this embodiment is consistent with the industry standard, but the variable impedance active flexible dissociation technology of this invention is used in the control method.

[0056] Measurement Principle: In high-concentration pulping processes, the raw material typically consists of a mixture of softened wood chips, fiber bundles, and incompletely reacted hardwood knots. Traditional pulpers use constant gap or constant pressure control, which cannot distinguish the heterogeneity within the raw material, leading to the contradiction of unground hardwood knots and the cutting of high-quality long fibers. This system addresses this by real-time decoupling... (characterizing hard knots) and (Characterizing long fiber aggregation), dynamically adjusting the stiffness of the hydraulic actuator. With damping It enables intelligent processing that involves grinding hard materials to achieve a dense finish and kneading tough materials to achieve a flexible finish.

[0057] Experimental reagents and sample preparation Raw material preparation: Poplar chips were selected as the substrate, pretreated by a spiral extrusion shredder and chemically impregnated (NaOH 40g / L, H2O 2 30g / L) before being used as the raw material to be ground. To simulate complex working conditions, 5% (mass fraction) of unsoftened hardwood blocks (simulating raw meal) and 10% of long fiber clumps (simulating reflocculation) were artificially added to the raw material. Equipment configuration: Example system (this invention): equipped with a dual-channel decoupling module, a hydraulic servo unit with a maximum thrust of 50kN and a response bandwidth of 100Hz; the operation and control module runs the above-mentioned variable impedance algorithm.

[0058] Proportional system (traditional control): It uses the same mechanical body, but the control logic is locked to constant position control (constant clearance mode), and it does not have stiffness and damping adjustment functions.

[0059] Automated Measurement and Implementation Steps This embodiment utilizes the aforementioned intelligent production system to perform the following steps: Step S1: Collaborative preprocessing and parameter initialization. The collaborative preprocessing module 10 is started, and the spectral analysis unit scans the feed online. If poplar wood is detected as the raw material, a raw material type correction coefficient is output after spectral fingerprint matching. (Poplar cell walls are relatively soft). The biochemical sensor detected a rapid initial impregnation reaction rate, and the computational control module 40 set the initial grinding disc gap accordingly. Basic stiffness ; Step S2: Real-time decoupling of rheological characteristics, with signal sensing module 30 synchronously acquiring data. When a stream of material containing hard wood blocks enters the grinding zone... At any given moment, the vibration acquisition unit captures the high-frequency impact signal, and the calculation and control module 40 obtains the stiffness modulus characteristic value through integration. Instantly jumped to the threshold That's all. Then, when a long fiber slurry enters the grinding zone... At any given moment, the electrical acquisition unit detects a significant slip frequency sideband in the stator current and calculates the characteristic toughness modulus. Significantly increased; Step S3: Variable impedance control is executed for hardwood blocks ( Based on formula The system rapidly increases its equivalent stiffness. to The hydraulic cylinder exhibits extremely high rigidity, refusing to yield to the pressure of the wood block, forcing the grinding disc to maintain a gap, and using high shear force to pulverize the wood block, targeting long fiber clumps ( Based on formula The system reduces the equivalent damping. At this moment, the hydraulic cylinder enters a flexible floating mode, and as the slurry passes through, the moving grinding disc undergoes a rapid retraction at the micrometer level. (Slight increase), avoiding the cutting of long fibers, only applying a rubbing action; Experimental verification and effect comparison: To further illustrate the technical effects of the present invention, a comparative example is provided for data comparison with this embodiment.

[0060] Comparison settings: Comparative method (traditional constant gap method): Set a fixed gap of 0.30mm, fix the PID control parameters, and do not adjust the stiffness / damping.

[0061] Example (variable impedance method of the present invention): Activate the complete closed-loop control strategy.

[0062] Analysis of experimental results: Comparison of slurry quality indicators: The physical properties of the finished slurry were sampled and tested, and the results are shown in Table 1: Table 1

[0063] Dynamic response process analysis: See attached document Figure 7 , Figure 7 This is a MATLAB simulation waveform diagram of the system's dynamic response to different material properties in this embodiment.

[0064] Feature recognition: The curve is The blue curve represents .exist Place, The appearance of sharp peaks accurately identifies hard impurities; Place, The appearance of broad peaks indicates the identification of high-toughness fiber clusters.

[0065] Impedance parameter adjustment; corresponding The increase in stiffness corresponds to the output equivalent stiffness command. Synchronous step ascent; corresponding The increase in [damping], the equivalent damping command output by the system. The depression is lowered.

[0066] Gap response results; the solid line represents the actual gap of the present invention. The dashed line represents the response of traditional constant gap control. It can be seen that... At the (hard object) location, the gap in this invention remains stable, ensuring crushing; while... At the (tough cluster) location, the gap of the present invention generates approximately 50 The instantaneous avoidance, while the gap remains unchanged under traditional control, results in an extremely high instantaneous power spike at that point (meaning the fiber is cut).

[0067] Reference Appendix: Comprehensive Energy Efficiency Frontier Analysis Figure 8 , Figure 8 This is a scatter plot showing the relationship between fiber length retention rate and degree of freeness under different control strategies.

[0068] In the figure, the dots represent the experimental data set of this embodiment, and the crosses represent the comparative data set.

[0069] As can be seen from the figure, the data points of this invention are mainly distributed in the upper right corner (where there are many long fibers and good water permeability). This indicates that, under the same freeness target, the slurry prepared by this invention has a higher weighted average fiber length.

[0070] MATLAB fitting curves show that the mass-energy Pareto front of this invention is significantly better than traditional methods, proving that by distinguishing... and Orthogonal control was implemented, breaking through the technical bottleneck that increasing the cutting rate inevitably reduces fiber length in traditional pulping.

[0071] in conclusion: This embodiment confirms that the flexible plant fiber decomposition system provided by the present invention can accurately decouple the hardness and toughness characteristics of raw materials through the computational control module 40. Compared with traditional methods, this system reduces the pulp residue content by 84.0% (solving the hard material treatment problem mentioned in the insufficient disclosure), while increasing the average fiber length by 28.0% (verifying the flexible rheological protection mechanism), achieving dual optimization of quality and energy consumption in high-yield pulp production.

[0072] 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. A plant fiber flexible dissociation and high-value intelligent production system, characterized in that, include: The collaborative preprocessing module is used to acquire raw material component fingerprint data and product release rate data during the enzymatic hydrolysis process, and calculate the reagent concentration compensation value of the chemical treatment process based on the raw material component fingerprint data and product release rate data, and perform feature feedforward control. The dual-path dissociation module includes a frequency converter drive unit that adjusts the rotational motion of the dissociation rotor and a hydraulic servo unit that adjusts the axial feed motion of the dissociation cavity. It is used to receive control commands to drive the physical actuator to switch between rigid positioning mode and flexible floating mode. The signal sensing module is used to collect physical field signals that reflect the system's operating status and material rheological behavior. The physical field signals include at least the stator current of the drive motor, the mechanical vibration of the dissociation cavity, and the angular position signal of the dissociation rotor. The computational control module is used to receive the physical field signal, execute a dual noise suppression strategy to separate the residual signal characterizing the rheological state of the raw material, perform feature decoupling analysis on the residual signal, calculate the stiffness modulus characteristic characterizing the hardness and brittleness of the raw material and the toughness modulus characteristic characterizing the toughness of the raw material, and then construct a variable impedance control model, and generate a composite control command containing the equivalent stiffness coefficient and the equivalent damping coefficient in real time and send it to the dual-path decoupling module.

2. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 1, characterized in that, The collaborative pretreatment module includes a spectral analysis unit, a biological enzymatic hydrolysis reaction unit, and a chemical dissociation reaction unit arranged sequentially along the material flow direction. The collaborative pretreatment module is configured to determine the target set concentration of the chemical reagent in the chemical dissociation reaction unit. The target set concentration is determined by subtracting a compensation gain term from a baseline concentration term. The baseline concentration term is the product of the raw material type correction coefficient and the baseline concentration constant of the process design. The compensation gain term is the product of the biochemical reaction efficiency compensation gain coefficient and the time integral value of the reducing sugar release rate.

3. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 1, characterized in that, The hydraulic servo unit in the dual-path dissociation module adopts a variable structure execution mechanism based on a variable impedance model. The hydraulic servo unit outputs an axial force according to the equivalent stiffness coefficient and equivalent damping coefficient issued by the calculation control module. The axial force is composed of a reference force offset, a position adjustment term, and a speed adjustment term. The position adjustment term is the product of the equivalent stiffness coefficient and the position deviation of the grinding disc gap, and the speed adjustment term is the product of the equivalent damping coefficient and the speed deviation of the grinding disc gap.

4. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 1, characterized in that, The signal sensing module includes an electrical acquisition unit, a vibration acquisition unit, and an angle acquisition unit; The electrical acquisition unit includes a high-frequency current transformer installed at the output terminal of the frequency converter drive unit. The upper limit cutoff frequency of the bandwidth of the high-frequency current transformer is set to be no less than 3 times the carrier frequency of the frequency converter drive unit. The vibration acquisition unit includes a piezoelectric accelerometer mounted on the dissociation cavity; the angle acquisition unit includes a rotary encoder mounted on the main shaft of the dissociation rotor, wherein the number of pulses per revolution of the rotary encoder is set according to the angle domain sampling theorem and serves as the signal reference for the operation and control module to perform angle domain resampling.

5. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 1, characterized in that, The dual noise suppression strategy implemented by the computational control module includes active electrical carrier cleaning logic. The computational control module monitors the carrier frequency of the frequency conversion drive unit and the mechanical characteristic frequency of the mechanical structure in real time. When the carrier frequency falls within the sideband protection range of the mechanical characteristic frequency, the module calculates and adjusts the carrier frequency setting value and sends it to the dual-path decoupling module. The carrier frequency setting value is set as the sum of the original carrier frequency and the frequency shift compensation amount. The frequency shift compensation amount is determined by multiplying the frequency domain protection bandwidth and the safety margin frequency by the direction sign function. The direction sign function depends on the sign of the difference between the original carrier frequency and the mechanical characteristic frequency.

6. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 1, characterized in that, The dual noise suppression strategy implemented by the computation control module also includes corner domain signal reconstruction logic and mechanical background differential logic; The computational control module uses the dissociated rotor angular position signal to resample the mechanical vibration signal into an angular domain stationary signal, and uses a synchronous averaging algorithm to construct a mechanical background baseline. By subtracting the angular domain stationary signal from the mechanical background baseline, the rheological residual signal is separated.

7. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 6, characterized in that, The calculation control module is used to calculate the stiffness modulus characteristic, and the calculation method of the stiffness modulus characteristic is as follows: The power spectral density of the rheological residual signal is integrated within a preset high-frequency characteristic band, and the integration result is divided by the normalized reference energy constant.

8. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 6, characterized in that, The computation control module is used to calculate the toughness modulus characteristic, and the calculation method of the toughness modulus characteristic is as follows: Based on the stator current signal, the sideband energy ratio method is used to calculate the ratio of the sum of current amplitudes at characteristic sideband frequencies to the current amplitude at the fundamental frequency.

9. The intelligent production system for flexible dissociation and high-value utilization of plant fibers according to claim 3, characterized in that, The calculation and control module calculates the equivalent stiffness coefficient and the equivalent damping coefficient in real time based on the stiffness modulus characteristics and the toughness modulus characteristics; The equivalent stiffness coefficient is set as the sum of the basic stiffness and the stiffness increment term, and the stiffness increment term is proportional to the portion of the stiffness modulus characteristic that exceeds the stiffness characteristic trigger threshold; the equivalent damping coefficient is set as the difference between the nominal damping coefficient and the damping reduction term, and the damping reduction term is proportional to the toughness modulus characteristic.

10. A method for intelligent production of flexible plant fiber dissociation and high-value processing, applied to an intelligent production system for flexible plant fiber dissociation and high-value processing as described in any one of claims 1-9, characterized in that, Includes the following steps: Near-infrared spectroscopy is used to obtain the spectral data of raw materials to calculate the type correction factor. At the same time, the reducing sugar release rate during the enzymatic hydrolysis process is monitored in real time. Based on the integral deviation between the type correction factor and the release rate, the concentration of reagents in subsequent chemical treatment processes is dynamically calculated and adjusted. The stator current of the drive motor, the mechanical vibration of the dissociation cavity, and the rotor angular position signal are collected synchronously through a current transformer, an accelerometer, and a rotary encoder. During the acquisition process, it is determined whether the inverter carrier frequency covers the characteristic frequency band. If it does, active carrier frequency shifting is performed. At the same time, the rotor angular position signal is used to perform angular domain resampling and synchronous average differential on the mechanical vibration signal to eliminate deterministic mechanical background noise and obtain rheological residual signal. The rheological residual signal is subjected to high-frequency energy integration to calculate the stiffness modulus characteristic of the microhardness of the raw material, and the stator current signal is subjected to sideband analysis to calculate the toughness modulus characteristic of the degree of entanglement of the raw material. Substituting the stiffness modulus characteristics and the toughness modulus characteristics into the variable impedance control model, the equivalent stiffness coefficient and equivalent damping coefficient required by the system are calculated in real time, and pressure and position composite commands are generated accordingly to drive the hydraulic servo mechanism, so that the physical properties of the dissociation process can adaptively switch between rigid crushing and flexible kneading.

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