Clean coal high-pressure forming system and method based on adaptive control

Abstract

This invention provides a clean coal high-pressure forming system and method based on adaptive control. The system includes a state sensing unit, a feedforward control unit, and a pressing and forming unit. The state sensing unit is configured around the forming cavity to collect internal material state information before pressing. The feedforward control unit is data-connected to the state sensing unit and receives and generates a pressing strategy based on the internal material state information before the physical pressing action occurs, controlling the pressing process. The pressing and forming unit is control-connected to the feedforward control unit and receives and executes the pressing action and pressure release and demolding according to the pressing strategy. This invention solves the technical problems of low energy efficiency, difficulty in state monitoring, and passive process control in existing technologies, achieving high-quality, high-efficiency, and low-energy-consumption operation in the clean coal forming process.

Description

Technical Field

[0001] This invention belongs to the field of clean energy equipment technology, specifically relating to a clean coal high-pressure forming system and method based on adaptive control. Background Technology

[0002] Coal is my country's primary energy source, and its clean and efficient utilization is a crucial path to optimizing the energy structure and protecting the environment. Briquette technology, by processing pulverized coal into blocky fuels with specific shapes, sizes, and strengths, can effectively improve coal combustion characteristics, reduce pollutant emissions, and increase transportation efficiency. High-pressure molding is the core process in briquette production; its essence is to use external mechanical force to rearrange, deform, and interlock loose coal particles, forming a dense body with sufficient mechanical strength.

[0003] Existing high-pressure briquetting technology for coal briquettes mainly suffers from the following technical problems: Traditional hydraulic or mechanical pressing systems typically employ an instantaneous pressurization mode, requiring the power system to provide all energy at the moment of pressing. This results in high motor power demand, high energy consumption, and severe impact loads on the equipment. Some technologies attempt to use accumulators for assistance, but there is a significant time lag in energy transfer between the accumulator and the actuator, making it difficult to meet the requirements for rapid response. During the briquetting process, key state parameters such as the distribution of the internal stress field, the evolution of the pore structure, and the initiation of defects in the material are difficult to obtain in real time. Existing technologies mostly rely on indirect measurements of pressure or displacement on the mold surface, which cannot accurately reflect the physical changes within the material, leading to a lack of sufficient basis for the formulation of control strategies. During high-pressure molding, the non-uniformity of the material often leads to localized stress concentration, making the material's own deformation resistance the dominant factor in the process development. The mold system is in a passive adaptive state, making it difficult to achieve the expected uniform density distribution target.

[0004] In addition, high pressure and sufficient holding time are required to ensure the densification of briquettes. However, this increases the adhesion between the briquettes and the mold wall. The release of residual stress during demolding can easily cause product cracking or surface damage. Existing technologies cannot coordinate the dual requirements of densification and smooth demolding. Coal powder from different origins and batches varies significantly in terms of particle size distribution, moisture content, and binder content. Existing equipment mostly uses fixed process parameters and lacks the ability to dynamically adjust the pressing strategy according to the material characteristics, resulting in large fluctuations in product quality and poor adaptability. Briquettes store a large amount of elastic strain energy under high pressure. Traditional continuous depressurization methods cause the residual stress to be released in a concentrated manner, which can easily cause crack propagation inside the briquettes, resulting in quality problems such as collapse upon depressurization.

[0005] Therefore, existing briquette forming technology is insufficient to meet the comprehensive requirements of modern clean briquette production for high efficiency, high quality, and low energy consumption. Summary of the Invention

[0006] The purpose of this invention is to provide a clean coal high-pressure forming system and method based on adaptive control, so as to achieve high-quality, high-efficiency and low-energy-consumption operation in the clean coal forming process.

[0007] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0008] A clean coal high-pressure forming system based on adaptive control includes a state sensing unit, a feedforward control unit, and a pressing and forming unit;

[0009] The state sensing unit is configured around the molding cavity and is used to collect internal state information of the material before pressing.

[0010] The feedforward control unit is data-connected to the state sensing unit, and is used to receive and generate a pressing strategy and control the pressing process before the physical pressing action occurs based on the internal state information of the material.

[0011] The pressing and molding unit is connected to the feedforward control unit and is used to receive and execute pressing actions and pressure release and demolding according to the pressing strategy.

[0012] Furthermore, the state perception unit includes a potential energy pre-storage module, a situation perception module, and a disturbance detection module; the potential energy pre-storage module is used to receive a standby command signal and inject a pre-pressurized medium into the prestressed elastic energy storage cavity according to the standby command signal to perform potential energy pre-storage processing and obtain energy storage state parameters.

[0013] The situational awareness module is used to receive material entry signals and energy storage status parameters, and to determine the system energy readiness status based on the energy storage status parameters. Under the condition that the system energy is ready and a material entry signal is received, the multispectral monitoring array is activated to collect multispectral radiation data, and the multispectral radiation data is subjected to non-contact stress field evolution analysis processing to obtain the internal state parameters of the material containing the system energy readiness status and stress field distribution information.

[0014] The disturbance detection module is used to receive and determine the detection start conditions based on the system energy readiness state and stress field uniformity index in the internal state parameters of the material. When the detection start conditions are met, the micro-amplitude mechanical vibration injection device is activated to apply a detective mechanical disturbance to the material and then micro-amplitude vibration response data is collected. The micro-amplitude vibration response data is then processed to perform defect distribution inversion to obtain risk map data.

[0015] Furthermore, the situational awareness module includes a multispectral monitoring array, a signal conditioning unit, and a stress field inversion processor. The multispectral monitoring array is deployed around the molding cavity and includes a thermal radiation sensor, a stress luminescence detector, and a microwave scattering receiver to collect thermal radiation, stress luminescence, and microwave scattering signals from the material. The stress field inversion processor inverts the internal stress field distribution of the material and its evolution trend over time from the temperature field distribution based on the thermo-mechanical coupling equation, without requiring physical contact with the material.

[0016] The disturbance detection module includes a micro-amplitude mechanical vibration injection device, an acoustic echo analysis unit, and a defect identification processor. The micro-amplitude mechanical vibration injection device is used to apply linear frequency modulation vibration to the material. The acoustic echo analysis unit includes a transmitting transducer and a receiving transducer array, used to transmit detection pulses to the material and collect echo signals. The defect identification processor performs defect distribution inversion processing on the echo signals based on a tomographic imaging algorithm to obtain risk spectrum data.

[0017] Furthermore, the feedforward control unit includes a prediction deployment module, a strategy adaptation module, a timing control module, and a stiffness reconstruction module; the prediction deployment module is used to receive the material's internal state parameters, risk map data, historical rheological data, and adaptation strategy parameters, and to perform digital twin inference and microtexture deployment processing on the historical rheological data based on the material's internal state parameters, risk map data, and adaptation strategy parameters to obtain suppression strategy parameters and microtexture configuration instructions;

[0018] The strategy adaptation module is used to receive the internal state parameters and historical rheological data of the material, and to retrieve the regional characteristic database based on the material component identification data and historical rheological data extracted from the internal state parameters of the material to perform dynamic matching processing of the compression strategy and obtain the adaptation strategy parameters.

[0019] The timing control module is used to receive the internal state parameters of the material, risk map data and suppression strategy parameters, and generate a critical state judgment signal based on the internal state parameters of the material and risk map data. When the critical state judgment signal meets the triggering conditions, it performs advanced triggering and suppression timing management processing to obtain the suppression execution command and the depressurization stage signal.

[0020] The stiffness reconstruction module is used to receive the microtexture configuration command and the pressing execution command, and to collect local stress concentration data in real time through the piezoresistive sensor array embedded in the mold. Based on the microtexture configuration command and the pressing execution command, the local stress concentration data is subjected to reverse mold stiffness compensation processing to obtain the reconstructed cavity control parameters.

[0021] Furthermore, the prediction and control module pre-simulates the pressing process in virtual space based on the material constitutive model, and pre-deploys a micro-texture array matching the predicted pressure distribution on the surface of the physical mold cavity according to the pre-simulation results.

[0022] The strategy adaptation module automatically retrieves the regional characteristic database based on the material composition identification data and calls the optimal pressing strategy that matches the current material characteristics.

[0023] The timing control module activates the pressing action in advance before the physical state of the material reaches the traditional pressing start conditions, and coordinates the action timing of each module.

[0024] The stiffness reconstruction module changes the equivalent elastic modulus of a local area of ​​the mold through a programmable stiffness control array, transforming the stress concentration area originally dominated by the material into a uniform pressure area controlled by the stiffness distribution of the mold.

[0025] Furthermore, the pressing and molding unit includes a pressing execution module, a stress reconstruction module, and a transient demolding module; the pressing execution module is used to receive the pressing execution command and the reconstructed cavity control parameters, and to perform mechanical pressing and cavity shape maintenance processing on the pressing execution command according to the reconstructed cavity control parameters to obtain the pressing process status;

[0026] The stress reconstruction module is used to receive the decompression stage signal and the adaptation strategy parameters, and according to the adaptation strategy parameters, perform non-monotonic decompression curve execution and stress redistribution processing under the condition of receiving the decompression stage signal to obtain the residual stress equilibrium state.

[0027] The transient demolding module is used to receive the residual stress equalization state and the trigger signal, and determine the demolding ready state according to the residual stress equalization state. When the residual stress equalization state meets the equalization condition, it performs millisecond-level cavity state switching and gas pulse demolding processing according to the trigger signal.

[0028] Furthermore, the stress reconstruction module executes a three-stage non-monotonic decompression curve, which redistributes the residual stress inside the briquettes evenly rather than releasing it in a concentrated manner. In the first stage, the pressure is decompressed to a first pressure at a first rate and held for a first duration. In the second stage, the pressure is increased to a second pressure at a second rate, where the second rate is less than the first rate and the second pressure is less than the maximum pressure. In the third stage, the pressure is finally decompressed to atmospheric pressure at a third rate, where the third rate is less than the first rate.

[0029] The transient demolding module uses a rapid demolding mechanism based on shape memory alloy to switch the cavity boundary from a rigid constraint state to an elastic yielding state, while applying a high-pressure gas pulse to achieve instantaneous detachment of the briquettes.

[0030] Furthermore, the system also includes an internal and external coordination module and an energy capture module; the internal and external coordination module is used to receive the pressing process status and the internal state parameters of the material, and determine the coordination triggering condition according to the stress field uniformity index in the internal state parameters of the material. When the stress field uniformity index exceeds the threshold, the external microwave radiation parameters are activated and the internal gasification expansion and external pressure are coordinated to obtain a coordinated dense state.

[0031] The energy capture module is used to receive the cooperative compaction state and determine the decompression start-up conditions based on the cooperative compaction state. When the cooperative compaction state reaches a preset density threshold, it collects the pressure difference data of the decompression channel to capture and convert residual stress energy to obtain recovered electrical energy.

[0032] Furthermore, the internal and external synergy module triggers the controlled gasification expansion of the inducible gasifying agent microcapsules embedded inside the material through external microwave radiation, forming a synergistic densification effect with external mechanical compression; the energy capture module captures the residual pressure energy during the depressurization process and converts it into electrical energy through the Venturi effect pressure difference power generation unit.

[0033] A method for high-pressure forming of clean coal based on adaptive control includes the following steps:

[0034] The state perception step collects internal state information of the material before pressing, including obtaining energy storage state parameters by performing potential energy pre-storage processing through the potential energy pre-storage module, obtaining internal state parameters of the material by collecting multispectral radiation data through the situation perception module and performing non-contact stress field evolution analysis processing, and obtaining risk map data by applying detective mechanical disturbance through the disturbance detection module and performing defect distribution inversion processing.

[0035] The feedforward control step generates a pressing strategy and controls the pressing process before the physical pressing action occurs based on the internal state information of the material. This includes obtaining pressing strategy parameters and micro-texture configuration instructions through digital twin simulation and micro-texture control processing by the prediction and control module; obtaining adapted strategy parameters through dynamic matching processing of the pressing strategy by the strategy adaptation module; obtaining pressing execution instructions and pressure relief stage signals through advance triggering and pressing timing management processing by the timing control module; and obtaining reconstructed cavity control parameters through reverse compensation processing of mold stiffness by the stiffness reconstruction module.

[0036] The pressing and molding step involves executing pressing actions and completing pressure release and demolding according to the pressing strategy. This includes mechanical pressing and cavity shape maintenance through the pressing execution module, non-monotonic pressure release curve execution and stress redistribution processing through the stress reconstruction module to obtain a residual stress equilibrium state, and millisecond-level cavity state switching and gas pulse demolding processing through the transient demolding module.

[0037] Compared with the prior art, the present invention has the following advantages:

[0038] Through the pre-stressed elastic energy storage cavity design of the potential energy pre-storage module, this system completes energy storage during the standby phase and releases it instantaneously during pressing, avoiding the continuous high-load operation of the power system in the traditional instantaneous pressurization mode. This design reduces the power demand of the main motor, decreases the impact load on the equipment, and improves the timing match between energy supply and demand. The instantaneous release characteristic of the pre-stored energy ensures the response speed of pressing start-up and solves the problem of energy transfer time lag in the accumulator auxiliary scheme. The situational awareness module uses a multi-spectral monitoring array to achieve non-contact observation. It inverts the internal stress field distribution of the material through the photoelastic effect and thermo-mechanical coupling principle, breaking through the limitation of traditional technology that only relies on indirect measurement on the mold surface. The disturbance detection module identifies the internal defect distribution before formal pressing through micro-amplitude vibration injection and echo analysis, providing sufficient prior information for the formulation of subsequent control strategies and significantly reducing the blindness of the pressing process.

[0039] The predictive control module, based on digital twin technology, calculates the pressure-density mapping relationship before the physical pressing action occurs. It pre-deploys a micro-texture array matching the predicted results on the mold cavity surface, enabling proactive decision-making. The strategy adaptation module establishes a mapping relationship between material component identification data and regional characteristic databases. Based on the real-time identified material characteristics, it dynamically calls the matching pressing strategy, enabling the same hardware system to adapt to the processing needs of different coal powders from different origins and batches, narrowing the product quality fluctuation range and enhancing equipment versatility. The timing control module activates the pressing action before the material's physical state reaches the traditional pressing start conditions, taking control of the process and allowing the material to achieve densification through passive adaptation, thus achieving timing preemption. The stiffness reconstruction module implements reverse compensation of mold stiffness through a programmable stiffness control array. When local stress concentration is detected, it actively changes the equivalent elastic modulus of the local area of ​​the mold, transforming the originally passive mold cavity into the controlling party, realizing the reconstruction of the mechanical relationship between the mold and the material. This mechanism effectively suppresses the local stress concentration phenomenon caused by material non-uniformity and improves the uniformity of density distribution.

[0040] The pressing execution module adjusts the cavity shape maintenance strategy in real time according to the reconstructed cavity control parameters, so that the pressing process and stiffness reconstruction are coordinated, achieving coordinated pressing inside and outside. The stress reconstruction module adopts a three-segment non-monotonic pressure relief curve design, inserting a staged pressure holding platform and a micro-amplitude repressurization pulse in the pressure relief stroke. Through the non-monotonic stress path, the residual stress is redistributed evenly instead of being released in a concentrated manner. This mechanism effectively avoids the crack propagation problem caused by stress concentration release in the traditional continuous pressure relief method, and improves the product yield. The transient demolding module adopts a rapid demolding mechanism based on shape memory alloy. After receiving the trigger signal, it completes the cavity state switching within 50-200 milliseconds, and achieves instantaneous demolding in conjunction with high-pressure gas pulses, avoiding elastic recovery damage caused by demolding delay and improving product dimensional accuracy. Attached Figure Description

[0041] Figure 1 A schematic diagram of the overall architecture of the clean coal high-pressure forming system based on adaptive control provided in an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of the prestressed elastic energy storage cavity structure of the potential energy pre-storage module provided in an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of the multispectral monitoring array arrangement of the situational awareness module provided in an embodiment of the present invention;

[0044] Figure 4 This is a schematic diagram of the micro-amplitude vibration injection and echo acquisition of the disturbance detection module provided in an embodiment of the present invention;

[0045] Figure 5 A flowchart of the digital twin simulation of the prediction and control module provided in this embodiment of the invention;

[0046] Figure 6 This is a schematic diagram of the working principle of the programmable stiffness control array of the stiffness reconstruction module provided in an embodiment of the present invention.

[0047] Figure 7 A schematic diagram of the inductive gasifying agent microcapsule triggering mechanism of the internal and external synergistic module provided in this embodiment of the invention;

[0048] Figure 8 This is a schematic diagram of the shape memory alloy rapid demolding mechanism of the transient demolding module provided in an embodiment of the present invention;

[0049] Figure 9 A flowchart of a clean coal high-pressure forming method based on adaptive control provided in an embodiment of the present invention. Detailed Implementation

[0050] To facilitate understanding of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the invention and should not be considered as specific limitations thereof.

[0051] In the following description of the embodiments, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of this application with unnecessary detail.

[0052] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of a described feature, integral, step, operation, element, and / or component, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof. It should also be understood that, as used in this specification and the appended claims, the term "and / or" refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0053] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0054] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. References to "one embodiment" or "some embodiments" in this application mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0055] Example 1:

[0056] like Figure 1 As shown in the figure, this embodiment provides a clean coal high-pressure forming system based on adaptive control. The system includes three major functional modules: a state sensing unit, a feedforward control unit, and a pressing and forming unit.

[0057] (I) Specific Implementation of the State-Aware Unit

[0058] The state awareness unit includes a potential energy pre-storage module, a situation awareness module, and a disturbance detection module.

[0059] The structure of the potential energy pre-storage module is as follows: Figure 2 As shown, it includes a prestressed elastic energy storage cavity, a pre-pressurized medium circuit, and a potential energy release valve.

[0060] The prestressed elastic energy storage cavity is made of multi-layer carbon fiber wound composite material. Its energy storage density E is positively correlated with the yield strength of the material to be compressed, satisfying the relationship E=k·σ y 1.5 Where k is a material constant, with a value ranging from 0.05 to 0.2 J·MPa -1.5 ·m -3 , σ y The yield strength of the material is used. The pre-pressurization medium circuit is filled with an emulsion mixture of nitrogen and hydraulic oil, with nitrogen comprising 70% and hydraulic oil 30%. The pre-pressurization pressure is set to 60-80% of the maximum pressing pressure. The potential energy release valve uses an electromagnetic-hydraulic composite drive, with an opening response time of less than 20 milliseconds. A pressure sensor monitors the energy storage status in real time, generates energy storage status parameters, and transmits them to the timing control module. The pre-pressurization pump injects the pre-pressurization medium into the prestressed elastic energy storage chamber at a set flow rate, causing prestress to be generated on the chamber wall and storing elastic potential energy.

[0061] The workflow of the potential energy pre-storage module is as follows:

[0062] Step S11: Receive standby command signal. This signal is a digital level signal from the upper control system; a high level indicates that the system has entered standby preparation state.

[0063] Step S12: Start the pre-pressurization pump and inject the pre-pressurization medium into the prestressed elastic energy storage cavity at a set flow rate (e.g., 10L / min) to generate prestress on the cavity wall and store elastic potential energy.

[0064] Step S13: Monitor the energy storage status in real time using a pressure sensor and generate energy storage status parameters. These parameters include the current energy storage pressure, energy storage density, and releaseable energy value. The energy storage status parameters are transmitted in real time to the timing control module via a data bus for determining the energy readiness for suppression.

[0065] The structure of the situation awareness module is as follows: Figure 3 As shown, it includes a multispectral monitoring array, a signal conditioning unit, and a stress field inversion processor.

[0066] A multispectral monitoring array is deployed around the periphery of the molding cavity, including:

[0067] Thermal radiation sensor: Employs an InSb infrared detector with a working wavelength of 3-5μm, used to collect the temperature field distribution on and near the surface of materials;

[0068] Stress-induced light emission detector: Employs a high-sensitivity photomultiplier tube to capture the weak light emission signal generated by coal powder particles under stress;

[0069] Microwave scattering receiver: Employs Ka-band radar at 35 GHz to detect changes in the dielectric constant inside materials.

[0070] Three sensors are arranged in a 120° pattern around the molding cavity. They achieve non-contact observation through the photoelastic effect and thermo-mechanical coupling principle, and can invert the internal stress field distribution of the material and its evolution trend over time without physical contact with the material.

[0071] The workflow of the situational awareness module is as follows:

[0072] Step S21: When material enters the molding cavity and a material entry signal is generated, the multispectral monitoring array synchronously starts acquisition. This material entry signal is a trigger signal from the material conveying system, generated by a photoelectric sensor installed at the cavity entrance. When material is detected blocking the light beam, a high level is output.

[0073] Step S22: Acquire multispectral radiation data. This data includes thermal radiation intensity distribution maps, stress emission spectra, and microwave scattering echo signals.

[0074] Step S23: The signal conditioning unit filters, amplifies, and performs analog-to-digital conversion on the original signal before sending it to the stress field inversion processor.

[0075] Step S24: The stress field inversion processor establishes the thermo-mechanical coupling equation based on the photoelastic effect principle:

[0076] ∇·(k∇T)+σ ij ·ε̇ ij =ρc p ·∂T / ∂t,

[0077] Where k is thermal conductivity, T is temperature, and σ ij Let ε̇ be the stress tensor. ij where ρ is the strain rate, ρ is the density, and c is the density. pThe specific heat capacity is used as the basis for determining the stress field distribution. By solving this system of equations, the stress field distribution is derived from the temperature field distribution, thus obtaining the internal state parameters of the material. These internal state parameters include the three-dimensional stress field distribution matrix, the maximum principal stress value and its location coordinates, and the stress field uniformity index.

[0078] The structure of the disturbance detection module is as follows: Figure 4 As shown, it includes a micro-amplitude mechanical vibration injection device, an acoustic echo analysis unit, and a defect identification processor.

[0079] The micro-amplitude mechanical vibration injection device is integrated into the mold wall and is driven by a piezoelectric ceramic stack. It can generate mechanical vibrations with a frequency of 50-200Hz and an amplitude of 0.01-0.1mm.

[0080] The acoustic echo analysis unit includes a transmitting transducer and a receiving transducer array. The transmitting transducer emits ultrasonic pulses with a center frequency of 1MHz toward the material, and the receiving transducer array acquires the echo signal at a sampling interval of 0.5μs.

[0081] The disturbance detection module applies a probing micro-disturbance to the material before formal pressing. By analyzing the response characteristics of the material's internal structure, it identifies the distribution of potential defects in advance, providing prior information for the formulation of subsequent control strategies and avoiding hidden damage caused by blind pressing.

[0082] The workflow of the disturbance detection module is as follows:

[0083] Step S31: After receiving the internal state parameters of the material from the situational awareness module, start the micro-amplitude mechanical vibration injection device to apply linear frequency modulation vibration to the material for a duration of 100ms, with the frequency increasing linearly from 50Hz to 200Hz.

[0084] Step S32: The acoustic echo analysis unit transmits detection pulses at a repetition frequency of 1000 times per second and collects echoes.

[0085] Step S33: The defect identification processor performs a short-time Fourier transform on the echo signal to extract time-frequency features. By analyzing the abnormal energy concentration areas in the time spectrum, it identifies the location and size of pores and cracks inside the material, generating risk map data. This risk map data is stored in the form of a three-dimensional matrix, where the matrix element value is the risk index of the corresponding location, ranging from 0 to 1, where 0 represents no defect and 1 represents a severe defect.

[0086] (II) Specific implementation of the feedforward control unit:

[0087] The feedforward control unit includes a predictive deployment module, a strategy adaptation module, a timing control module, and a stiffness reconstruction module. It is connected to the state perception unit to receive internal state information of the material and generate a pressing strategy before the physical pressing action occurs, and actively control the pressing process.

[0088] The structure of the predictive deployment module is as follows: Figure 5 As shown, it includes a digital twin engine, a material constitutive model library, a microtexture configuration executor, and a historical database.

[0089] The digital twin engine constructs a virtual simulation environment for the molding process based on the finite element method, with a mesh generation accuracy of 1 mm. The material constitutive model library includes the Drucker-Prager model, the modified Cambridge model, and custom viscoelastic models, which can be automatically selected or combined according to material properties.

[0090] The workflow of the predictive deployment module is as follows:

[0091] Step S41: Receive the material's internal state parameters, risk map data, and historical rheological data retrieved from the historical database. The historical rheological data consists of the stress-strain curves, compaction density-pressure mapping relationship, and decompression rebound coefficient recorded in the preliminary tests for this batch of material.

[0092] Step S42: The digital twin engine creates a digital twin of the current batch of materials. This twin includes the material's geometric model, constitutive parameters, and initial conditions. The pressing process is simulated using finite element analysis to predict the density distribution, stress concentration locations, and defect evolution trends under different pressure curves.

[0093] Step S43: Based on the simulation results, determine the optimal pressing strategy parameters, including maximum pressing pressure, pressing speed curve, holding time, and depressurization rate. Simultaneously, generate microtexture configuration instructions based on the predicted pressure distribution cloud map. These instructions include the microtexture height h, spacing d, and distribution pattern, where h ranges from 0.1 to 0.5 mm, d ranges from 1 to 5 mm, and the distribution pattern is designed as parallel lines, a grid, or a radial pattern according to the pressure gradient direction. The microtexture configuration actuator controls the precision machining head to etch the corresponding microtexture onto the mold cavity surface according to the instructions. For example, a parallel line pattern with a microtexture height of 0.2 mm and a spacing of 3 mm is set in the high-pressure zone, and a grid pattern with a microtexture height of 0.4 mm and a spacing of 2 mm is set in the low-pressure zone.

[0094] The strategy adaptation module includes a near-infrared spectrometer, an X-ray fluorescence analyzer, a regional characteristic database, and a strategy matching engine.

[0095] Near-infrared spectroscopy is used to quickly determine the moisture content and organic matter content of materials, while X-ray fluorescence analyzer is used to determine the elemental composition of ash.

[0096] The workflow of the strategy adaptation module is as follows:

[0097] Step S51: Receive the internal state parameters of the material, including particle size distribution (measured by a laser particle size analyzer), moisture content (measured by near-infrared spectroscopy), ash content (measured by X-ray fluorescence), and binder type, and extract material component identification data.

[0098] Step S52: The strategy matching engine retrieves the regional characteristic database based on the material composition identification data, calls the optimal pressing strategy matching the material characteristics, and generates adaptive strategy parameters. The regional characteristic database stores the typical characteristics of coal types from different producing areas and their corresponding optimal process parameters, which are continuously updated and optimized through machine learning algorithms.

[0099] The timing control module includes a critical state determiner, an advance trigger logic unit, and a suppression timing manager.

[0100] The workflow of the timing control module is as follows:

[0101] Step S61: The critical state determiner receives the stress field uniformity index λ from the internal state parameters of the material and the defect density ρ from the risk map data. d When λ>0.8 and ρ d When << 0.1, the judgment signal is 1 (the triggering condition is met), and a critical state judgment signal is generated.

[0102] Step S62: The advance triggering logic unit determines the preset triggering pressure P in the suppression strategy parameters. t When the actual pressure of the material reaches 0.7P t The suppression start signal is generated in advance.

[0103] Step S63: The compression timing manager coordinates the timing of actions of each module to ensure that the compression execution command is issued synchronously when the three conditions of energy readiness (pressure > 57 MPa), strategy readiness (microtexture processing completed), and state readiness (critical state judgment signal = 1) are met. The compression execution command includes the target pressure curve, timing nodes, and synchronization signals. The depressurization stage signal is the timing signal that initiates the depressurization process after the compression reaches the target density.

[0104] The structure of the stiffness reconfiguration module is as follows: Figure 6 As shown, it includes a piezoresistive sensor array, a programmable stiffness control array, and a stiffness compensation calculator.

[0105] Piezoresistive sensor arrays are embedded in the mold cavity surface at 5mm intervals to collect pressure distribution data in real time; the programmable stiffness control array is composed of magnetorheological elastomer units and shape memory alloy skeletons, and the local equivalent elastic modulus can be adjusted in real time by changing the applied current, with an adjustment range of 1-100GPa.

[0106] The workflow of the stiffness reconstruction module is as follows:

[0107] Step S71: Receive microtexture configuration instructions, pressing execution instructions, and local stress concentration data. The local stress concentration data consists of the coordinates and amplitudes of areas exhibiting abnormal peak values ​​in the cavity surface pressure distribution data acquired in real time by a piezoresistive sensor array.

[0108] Step S72: The stiffness compensation calculator identifies abnormal peak regions in the pressure distribution data. Let the normal average pressure be P. m When the pressure P in a certain area i >1.3P m This area is identified as a stress concentration zone. For this region, the stiffness compensation ΔE is calculated:

[0109] ΔE=E0·P m / (P i -P m )·α;

[0110] Where E0 is the reference elastic modulus and α is the compensation coefficient, which ranges from 0.5 to 1.0.

[0111] Step S73: Based on the calculation results, a control current is sent to the programmable stiffness control array to increase the local stiffness of the stress concentration area, causing the pressure to redistribute to the surrounding low-stiffness areas, thus obtaining the reconstructed cavity control parameters. These parameters include the stiffness distribution matrix of each control area and the real-time pressure distribution status.

[0112] The stiffness reconstruction module transforms the originally passive mold cavity into the controlling party through reverse compensation of mold stiffness, thereby reconstructing the mechanical relationship between the mold and the material.

[0113] (III) Specific Implementation of the Press Molding Module

[0114] The pressing and forming unit includes a pressing execution module, a stress reconstruction module, and a transient demolding module, which are connected to the feedforward control unit to receive the pressing strategy and execute the pressing action and depressurize to obtain the finished coal briquettes.

[0115] The pressing execution module includes a main hydraulic cylinder, a displacement sensor, and a pressure maintaining controller. The main hydraulic cylinder has a diameter of 500mm, a stroke of 300mm, and a maximum output pressure of 100MPa.

[0116] The workflow of the suppression execution module is as follows:

[0117] Step S81: After receiving the pressing execution command and the reconfigurable cavity control parameters, the main hydraulic cylinder executes the pressing action according to the pressure curve required by the command.

[0118] First stage of pressurization: Pressurize to the first stage target pressure at a set rate. Displacement sensor provides real-time feedback on piston position, calculates volume compression ratio, and calculates real-time density estimate based on displacement and mass.

[0119] Pressure holding phase: The pressure maintaining controller regulates the pressure fluctuation within the allowable range through a proportional valve, with the proportional coefficient K. p =0.5, integral coefficient K i =0.1, differential coefficient K d =0.05, keeping pressure fluctuations less than ±0.5MPa.

[0120] Second stage of pressurization: Pressurize to the maximum pressure at a set rate, during which the stiffness reconstruction module continuously monitors and adjusts the local stiffness.

[0121] Step S82: Generate the pressing process status, including real-time pressure value, piston displacement, pressing time, current density estimate and cavity status.

[0122] The stress reconstruction module includes a pressure relief curve generator, a pressure holding platform controller, and a repressurization pulse generator. The pressure relief curve generator designs a non-monotonic pressure relief curve based on the target pressure relief time in the adaptation strategy parameters.

[0123] The workflow of the stress reconstruction module is as follows:

[0124] Step S91: Receive adaptation strategy parameters and depressurization phase signals.

[0125] Step S92: The pressure relief curve generator generates a three-segment non-monotonic pressure relief curve:

[0126] First stage: Depressurize from 100MPa to 70MPa at a rate of 5MPa / s, and maintain this pressure for 40 seconds with the pressure holding platform controller;

[0127] Second stage: The repressurization pulse generator repressurizes from 70MPa to 80MPa at a rate of 2MPa / s and maintains it for 15 seconds;

[0128] The third stage: finally depressurize to atmospheric pressure at a rate of 4 MPa / s.

[0129] This stress path causes the residual stress inside the briquette to be redistributed evenly rather than released in a concentrated manner, resulting in a residual stress equilibrium state. The residual stress equilibrium state is a stress distribution state in which the difference in residual stress at each point inside the briquette is less than 10% of the material's yield strength, including the difference in residual stress at each point inside the briquette and the equilibrium index.

[0130] The structure of the transient demolding module is as follows: Figure 8 As shown, it includes a shape memory alloy rapid demolding mechanism, a high-pressure gas pulse generator, and a demolding monitor.

[0131] The shape memory alloy rapid demolding mechanism uses NiTi alloy drive components, with a phase transformation temperature A. f=80℃, and the phase transformation from martensite to austenite is completed within 50-200 milliseconds after being heated by electricity, generating 5% recovery strain, so that the cavity boundary changes from a rigid constraint state to an elastic yielding state.

[0132] The workflow of the transient demolding module is as follows:

[0133] Step Sa1: Receive the residual stress equilibrium state and shape memory alloy trigger signal. This trigger signal is a fast-response trigger signal generated when the residual stress equilibrium state reaches stability and the decompression stage signal is confirmed.

[0134] Step Sa2: A pulsed current is applied to the shape memory alloy rapid demolding mechanism, which completes the state switching within 100 milliseconds. Simultaneously, a high-pressure gas pulse generator injects a 0.5MPa nitrogen (N2) pulse into the bottom of the cavity for 50 milliseconds, forming an air cushion at the bottom of the briquette. Combined with the elastic yielding of the cavity wall, this propels the briquette to detach instantaneously.

[0135] Step Sa3: The demolding monitor detects whether the briquettes have been successfully demolded using a photoelectric sensor. Once confirmed, the finished briquettes are generated.

[0136] Example 2:

[0137] The enhanced functional modules in this embodiment include an internal and external coordination module, an energy capture module, a cavity reconstruction module, a flow induction module, a gradient suppression module, and a virtual potential creation module. These modules can be used in combination with the core system of the first embodiment.

[0138] (a) Internal and external coordination module and energy capture module

[0139] The structure of the internal and external collaboration module is as follows: Figure 7 As shown, it includes inducible vaporizing agent microcapsules, a microwave radiation array, and a synergistic trigger controller.

[0140] Inducible gasifying agent microcapsules are uniformly mixed into coal powder during the material preparation stage. The particle size is 0.5-2mm, and the microcapsules contain a composite foaming agent of ammonium bicarbonate and azodicarbonamide, with a mass fraction of 0.5-2% of the total material. A microwave radiation array is arranged around the molding cavity, with a frequency of 2.45GHz and an adjustable power range of 100-1000W.

[0141] The workflow of the internal and external collaboration module is as follows:

[0142] Step Sb1: Receive the pressing process status and stress field uniformity index. When the stress field uniformity index λ exceeds the threshold (e.g., 0.8), it is determined that the cooperative triggering condition is met.

[0143] Step Sb2: The co-triggered controller activates the microwave radiation array, irradiating the material with 500W power for 10-15 seconds. The microwaves penetrate the material, causing the internal microcapsules to decompose and produce gas. At 120°C, the decomposition produces ammonia (NH3), carbon dioxide (CO2), and water vapor (H2O), expanding the volume approximately 20 times. This generates an expansion pressure of approximately 15MPa from the inside out, forming a synergistic densification effect with the external mechanical pressure. That is, it is superimposed with the external mechanical pressure (100MPa), and the total densification pressure is equivalent to the external pressure effect of 115MPa.

[0144] Step Sb3: Generate a cooperative compaction state, including a cooperative compaction completion signal and the current density value. Confirm this through real-time density monitoring. When the density reaches the target value, cooperative compaction is determined to be complete.

[0145] The internal and external synergistic module triggers the vaporization and expansion of the embedded microcapsules through microwave radiation, forming a synergistic densification effect with external mechanical compression, achieving internal and external field coupling and densification, and solving the problem of far-field densification difficulties.

[0146] The energy harvesting module includes a venturi tube, a differential pressure power generation unit, and an energy manager.

[0147] The venturi tube is installed in the depressurization channel, with a throat diameter 0.3 times the inlet diameter. The differential pressure power generation unit uses a piezoelectric ceramic stack to generate electricity by utilizing the pressure difference vibration generated by the high-speed airflow during depressurization.

[0148] The workflow of the energy harvesting module is as follows:

[0149] Step Sc1: When the pressure release module begins to depressurize, the high-pressure fluid flows through the depressurization channel through the venturi tube, and the inlet pressure (e.g., 100MPa), throat pressure (e.g., 30MPa), inlet velocity (e.g., 2m / s), and throat velocity (calculated according to Bernoulli's equation, approximately 124m / s) are collected.

[0150] Step Sc2: Capture the residual pressure energy during the depressurization process using the Venturi effect differential pressure power generation unit and convert it into electrical energy. Store the captured electrical energy in a supercapacitor to generate recycled electrical energy, which is used to drive the microwave radiation array of the internal and external collaborative module or the magnetorheological elastomer of the cavity reconstruction module.

[0151] The energy harvesting module captures residual stress energy during the decompression process through the Venturi effect differential pressure power generation unit and converts it into electrical energy to drive the microwave radiation array of the internal and external collaborative module or the magnetorheological elastomer of the cavity reconstruction module, forming a cascade utilization of energy and reducing external energy consumption.

[0152] (II) Cavity Reconstruction Module and Flow Induction Module

[0153] The cavity reconstruction module receives the pressing strategy parameters and recovered electrical energy, generates a magnetic field strength command based on the target coal specification in the pressing strategy parameters, and uses the recovered electrical energy to apply the magnetic field strength command to the boundary of the magnetorheological elastomer to perform magnetorheological elastomer topology reconstruction processing to obtain virtual cavity geometric parameters. The flow induction module receives the virtual cavity geometric parameters and material rheological characteristic data, configures the sacrificial feed block parameters based on the virtual cavity geometric parameters and material rheological characteristic data, and performs degradation and pore generation processing on the sacrificial feed block to obtain internal pore structure parameters.

[0154] The cavity reconstruction module includes a magnetorheological elastomer boundary, an excitation coil array, and a magnetic field controller.

[0155] The magnetorheological elastomer boundary is composed of a silicone rubber matrix and carbonyl iron powder particles, with a particle volume fraction of 30%. It has a zero-field shear modulus of 0.5 MPa and a shear modulus of up to 5 MPa under a saturated magnetic field. The excitation coil array is arranged in a Halbach array configuration, which can generate a spatially controllable magnetic field.

[0156] The workflow of the cavity reconstruction module is as follows:

[0157] Step Sd1: Receive the pressing strategy parameters, recovered electrical energy, and magnetic field strength instructions. The magnetic field strength instruction is to calculate the required cavity geometric parameters based on the target coal specifications, and then solve for the required magnetic field strength distribution using a finite element inversion algorithm.

[0158] Step Sd2: Current is supplied to the excitation coil array according to the calculation results, changing the local stiffness distribution of the magnetorheological elastomer boundary, causing it to undergo controllable deformation. A virtual cavity matching the target specifications is generated within milliseconds, yielding the virtual cavity's geometric parameters. These parameters include the cavity's volume V, aspect ratio L / D, and surface roughness Ra.

[0159] The cavity reconstruction module uses magnetorheological elastomers as the cavity boundary material. By applying an external magnetic field, the geometric topology of the magnetorheological elastomer boundary is changed in real time, enabling the same set of physical molds to generate virtual cavities of various specifications, reducing the frequency of mold replacement and improving production flexibility.

[0160] The flow induction module includes a sacrificial feed block storage unit, a chemical trigger, and a degradation monitor.

[0161] The sacrificial initiator block is made of a blend of polylactic acid and starch, with a density of 1.2 g / cm³, lower than that of pulverized coal, and superior rheological properties compared to the material to be processed (viscosity 200 Pa·s, lower than the material viscosity 500 Pa·s). The sacrificial initiator block is configured with a mass of 10 g, a volume of 8.3 cm³, and is placed at the cavity inlet. The chemical trigger utilizes enzyme catalysis or hydrothermal triggering, initiating degradation within 10-30 minutes after pressing.

[0162] The workflow of the flow induction module is as follows:

[0163] Step Se1: Receive the virtual cavity geometry parameters and material rheological property data. The material rheological property data includes the material's viscosity, yield stress, and flow index.

[0164] Step Se2: In the initial stage of pressing, the sacrificial feed block is placed at the cavity inlet. Under pressure, the feed block enters the cavity first, and its low viscosity guides the flow path of subsequent materials, avoiding material accumulation and blockage at the inlet.

[0165] Step Se3: Once the main material fills the cavity, a chemical trigger initiates the degradation reaction. The chemical trigger employs a hydrothermal triggering mechanism, injecting a small amount of high-temperature steam (120℃, 2g) into the cavity. This causes the priming block to hydrolyze and degrade into lactic acid, oligosaccharides, and porous carbon residue within 15 minutes, forming a connected pore structure inside the briquettes. The internal pore structure parameters are then obtained. These parameters include porosity (12%), pore size distribution (average pore size 0.5mm), and pore connectivity (0.6).

[0166] The flow-inducing module guides the material flow path in the early stage of compression through the design of sacrificial feed blocks, and then degrades it into the internal pore structure of the briquettes through chemical triggering in the later stage, thereby achieving active control of porosity and pore size distribution and improving the combustion characteristics of the briquettes.

[0167] (III) Gradient suppression module and virtual potential creation module

[0168] The gradient pressing module receives the internal pore structure parameters and spatial coordinates, and performs differentiated pressing processing based on these parameters to obtain a gradient dense distribution state. The virtual potential creation module receives the gradient dense distribution state and demolding stage signal, determines the pressing completion state based on the gradient dense distribution state, and performs controllable micro-convex array activation and retraction processing upon receiving the demolding stage signal to obtain a temporary friction coefficient distribution.

[0169] The gradient suppression module includes a spatial position identifier, a frequency modulator, and an amplitude distributor.

[0170] The spatial position identifier divides the pressing stroke into a near-field compaction zone (0-30% of the cavity radius from the wall) and a far-field homogenization zone (30-100% of the cavity radius from the wall) based on the cavity geometry parameters.

[0171] The gradient suppression module works as follows:

[0172] Step Sf1: Receive the internal pore structure parameters and spatial coordinates. The spatial coordinates are the distance coordinates of the material inside the cavity relative to the mold wall.

[0173] Step Sf2: The frequency modulator applies a high-frequency, low-amplitude oscillation of 20Hz and 1.2mm amplitude to the near-field region, and a low-frequency, high-amplitude static pressure of 0.5Hz and 8mm amplitude to the long-field region. The amplitude distributor dynamically adjusts the amplitude distribution ratio based on real-time density feedback to ensure global density uniformity.

[0174] Step Sf3: Let the current density ρ in the near-range region be... near Density ρ in the remote region far Target density ρ target When the density difference between the two regions is greater than 0.02 g / cm³, the amplitude of the near-field region is adjusted to 1.5 mm, while the amplitude of the far-field region is maintained at 9 mm, until the density difference is less than the threshold, resulting in a gradient dense distribution state. This state includes the density of the near-field region, the density of the far-field region, and the global density uniformity.

[0175] The gradient suppression module adopts a differentiated strategy of high frequency and low amplitude in the near field and low frequency and high amplitude in the far field. It optimizes the combination of frequency and amplitude for different spatial positions of the cavity, solves the problem of different densification requirements in the near-wall region and the far-field region, and improves the global density uniformity.

[0176] The virtual potential creation module includes a controllable micro-convex array, a micro-convex drive circuit, and a friction coefficient calculator.

[0177] The controllable micro-bump array is composed of shape memory alloy wire and piezoelectric ceramic sheet. The height of the micro-bump is adjustable from 0 to 0.5 mm, and the response time is less than 100 ms.

[0178] The workflow of the virtual potential creation module is as follows:

[0179] Step Sg1: Receive the gradient compaction distribution state and demolding stage signal. The demolding stage signal is a timing trigger signal generated when pressing is completed and demolding is ready.

[0180] Step Sg2: During the pressing stage, the micro-bump drive circuit supplies a DC current of 1.5A to the controllable micro-bump array, heating the shape memory alloy wire to above the phase transition temperature, causing the micro-bumps to protrude to a height of 0.3mm, imprinting temporary textures (such as diamond textures with a depth of 0.25mm and a spacing of 2mm) on the surface of the briquette, increasing the apparent coefficient of friction to 0.6-0.8, ensuring reliable engagement between the briquette and the mold cavity during the pressing process.

[0181] Step Sg3: Demolding stage. Upon receiving the demolding stage signal, the driving current is cut off. The shape memory alloy wire cools naturally in the air and recovers to the martensitic state within 100 milliseconds. The micro-convexity automatically retracts to be flush with the cavity surface (height difference << 0.02 mm). The apparent coefficient of friction recovers to below 0.25. The adhesion resistance between the briquette and the cavity is significantly reduced, and the briquette is successfully demolded, resulting in a temporary coefficient of friction distribution.

[0182] To ensure densification, high pressure must be applied and sufficient holding time must be maintained. However, this increases the adhesion between the briquettes and the mold wall. The release of residual stress during demolding can easily cause product cracking or surface damage. The virtual potential creation module creates a temporary interlocking state during the pressing stage through a controllable micro-protrusion array and automatically retracts to eliminate adhesion during the demolding stage, thus achieving the dual requirements of coordinating densification and smooth demolding.

[0183] Example 3:

[0184] like Figure 9 As shown in the figure, this embodiment provides a method for high-pressure forming of clean coal based on adaptive control. The method includes the following steps:

[0185] State perception: Collect internal state information of materials before pressing;

[0186] Feedforward control generates a pressing strategy and actively controls the pressing process based on the internal state information of the material before the physical pressing action occurs.

[0187] The coal is pressed and molded according to a pressing strategy, and then depressurized and demolded to obtain the finished coal briquettes.

[0188] The above state awareness steps can be further refined into the following specific steps:

[0189] Potential energy pre-storage: The potential energy pre-storage module receives a standby command signal and injects a pre-pressurized medium into the prestressed elastic energy storage cavity according to the standby command signal to perform potential energy pre-storage processing, obtains energy storage state parameters, and sends them to the timing control module.

[0190] Situational awareness: Upon receiving a material entry signal, the situational awareness module collects multispectral radiation data, including material thermal radiation, stress luminescence, and microwave scattering signals, through a multispectral monitoring array deployed around the molding cavity. Based on the photoelastic effect and thermo-mechanical coupling principle, the multispectral radiation data is processed non-contactly without physical contact with the material to analyze the stress field evolution and inversely determine the internal stress field distribution and its evolution trend over time. The internal state parameters of the material are obtained and sent to the disturbance detection module, prediction and control module, timing control module, and strategy adaptation module.

[0191] The disturbance detection module, upon receiving the internal state parameters of the material, applies a probing mechanical disturbance with a frequency of 50-200Hz and an amplitude of less than 0.1mm to the material through a piezoelectric ceramic stack drive device integrated into the mold wall. It then collects micro-amplitude vibration response data, including the response signals of the internal structure of the material. Based on the echo time-frequency characteristics, the module performs defect distribution inversion processing on the micro-amplitude vibration response data to identify the distribution of pores, cracks, and uneven density areas within the material. This results in a risk map data, which is then sent to the prediction and control module and the timing control module.

[0192] The above feedforward control steps can be further refined into the following specific steps:

[0193] The predictive deployment module receives material internal state parameters, risk map data, historical rheological data of the stress-strain curve / compacted density-pressure mapping relationship and unloading rebound coefficient recorded in the preliminary test of this batch of material, and adaptation strategy parameters output by the strategy adaptation module. Based on the material constitutive model, it pre-simulates the pressing process in virtual space and, according to the material internal state parameters, risk map data and adaptation strategy parameters, pre-deploys a microtexture array on the surface of the physical mold cavity that matches the predicted pressure distribution through digital twin inference and microtexture deployment processing. This yields pressing strategy parameters and microstructure configuration instructions, including microtexture height / spacing / spatial distribution patterns. The pressing strategy parameters are then sent to the timing control module, and the microtexture configuration instructions are sent to the stiffness reconstruction module.

[0194] The strategy adaptation module receives the internal state parameters of the material and historical rheological data, and extracts material component identification data including particle size distribution, moisture content, ash content and binder type from the internal state parameters of the material. Based on the material component identification data and historical rheological data, it retrieves and stores the regional characteristic database of the physical and chemical characteristics of coal types from different producing areas and their corresponding optimal pressing strategy parameters, performs dynamic matching processing of pressing strategies, obtains the adapted strategy parameters, and sends them to the prediction and control module.

[0195] The timing control module receives energy storage state parameters, suppression strategy parameters, material internal state parameters, and risk map data. Based on the material internal state parameters and risk map data, it generates a critical state judgment signal when the stress field uniformity index exceeds a preset threshold and the defect density is lower than the safety limit. When the critical state judgment signal meets the triggering conditions, it performs advanced triggering and suppression timing management processing to activate the suppression action in advance before the material's physical state reaches the traditional suppression start-up conditions, thereby taking control of the process. This results in the suppression execution command and the timing signal for starting the depressurization process after the suppression reaches the target density. The suppression execution command is then sent to the stiffness reconstruction module and the suppression execution module, and the depressurization stage signal is sent to the stress reconstruction module.

[0196] Stiffness reconstruction: The stiffness reconstruction module receives microtexture configuration instructions and pressing execution instructions, and collects local stress concentration data, including the coordinates and amplitude of areas with abnormal peak values ​​in the pressure distribution data on the cavity surface, in real time through a piezoresistive sensor array embedded in the mold. Furthermore, it changes the equivalent elastic modulus of the local area of ​​the mold through a programmable stiffness control array, transforming the stress concentration area into a uniform pressure area controlled by the mold stiffness distribution. This reverse compensation process of mold stiffness obtains the reconstructed cavity control parameters and sends them to the pressing execution module.

[0197] The above compression molding process can be further broken down into the following specific steps:

[0198] The pressing execution module receives the pressing execution command and the reconstructed cavity control parameters, and performs mechanical pressing and cavity shape maintenance processing on the pressing execution command according to the reconstructed cavity control parameters to obtain the pressing process status.

[0199] The stress reconstruction module receives the decompression stage signal output by the timing control module and the adaptation strategy parameters output by the strategy adaptation module. Based on the adaptation strategy parameters, under the condition of receiving the decompression stage signal, it performs non-monotonic decompression curve processing by inserting at least one stage pressure holding platform and micro-amplitude repressurization pulse into the total decompression stroke to redistribute the residual stress inside the briquette evenly rather than releasing it in a concentrated manner. This process yields a residual stress equilibrium state where the residual stress difference between points inside the briquette is less than 10% of the material yield strength, and sends it to the transient demolding module.

[0200] The transient demolding module receives the residual stress equilibrium state and the shape memory alloy trigger signal generated after the residual stress equilibrium state reaches stability and the pressure relief stage signal is confirmed. Under the condition that the residual stress equilibrium state meets the equilibrium condition and the shape memory alloy trigger signal is received, the rapid demolding mechanism based on shape memory alloy completes the state switching of the cavity boundary from a rigid constraint state to an elastic yielding state within 50-200 milliseconds after receiving the trigger signal. At the same time, a high-pressure gas pulse is applied to achieve the millisecond-level cavity state switching and gas pulse demolding processing for instantaneous detachment of the briquettes, resulting in the finished briquettes.

[0201] Example 4:

[0202] The functional enhancement steps in this embodiment can be used in combination with the core method of Embodiment 3, and specifically include the following steps:

[0203] Internal and external coordination: When the internal and external coordination module receives the pressing process status and the stress field uniformity index extracted from the internal state parameters of the material exceeds the threshold, it activates the external microwave radiation parameters and performs internal gasification expansion and external pressure coordination processing to obtain a coordinated dense state.

[0204] Energy capture: Under the condition of receiving a cooperative compaction state, the energy capture module collects the pressure difference data of the pressure relief channel, and performs residual stress energy capture and conversion processing on the pressure difference data of the pressure relief channel to obtain recovered electrical energy.

[0205] Cavity reconstruction: The cavity reconstruction module receives the pressing strategy parameters and the recovered electrical energy, generates a magnetic field strength command based on the pressing strategy parameters, and uses the recovered electrical energy to apply the magnetic field strength command to the boundary of the magnetorheological elastomer to perform magnetorheological elastomer topology reconstruction processing to obtain virtual cavity geometric parameters.

[0206] Flow induction: The flow induction module receives virtual cavity geometric parameters and material rheological property data, configures sacrificial feed block parameters according to the virtual cavity geometric parameters and material rheological property data, and performs degradation and pore generation treatment on the sacrificial feed block to obtain internal pore structure parameters.

[0207] Gradient suppression: The gradient suppression module receives the internal pore structure parameters and spatial coordinates, and performs differentiated suppression processing based on the internal pore structure parameters and spatial coordinates, resulting in a gradient dense distribution state.

[0208] The virtual potential creation module receives the gradient density distribution state and demolding stage signal, and determines the pressing is completed based on the gradient density distribution state. Under the condition of receiving the demolding stage signal, it performs controllable micro-convex array activation and retraction processing to obtain a temporary friction coefficient distribution.

[0209] In summary, this invention achieves adaptive control of the high-pressure molding process for clean coal briquettes through the coordinated operation of the state sensing unit, feedforward control unit, and pressing and molding unit. By organically linking modules such as potential energy pre-storage, situational awareness, disturbance detection, predictive deployment, strategy adaptation, timing control, stiffness reconstruction, pressing execution, stress reconstruction, and transient demolding, it solves several technical problems in existing technologies and significantly improves the quality stability and production efficiency of coal briquettes.

[0210] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0211] In various embodiments, the hardware implementation of the technology can directly utilize existing smart devices, including but not limited to industrial control computers, PCs, smartphones, handheld devices, and floor-standing devices. Its input device preferably uses an on-screen keyboard, its data storage and computing modules utilize existing memory, calculators, and controllers, its internal communication modules utilize existing communication ports and protocols, and its remote communication utilizes existing GPRS networks, the World Wide Web, etc.

[0212] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0213] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / terminal devices and methods can be implemented in other ways. For example, the apparatus / terminal device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0214] In the various embodiments of the present invention, the functional units can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units can be implemented in hardware or as software functional units. If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments, or it can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

Claims

1. A clean coal high-pressure forming system based on adaptive control, characterized in that, It includes a state sensing unit, a feedforward control unit, and a pressing and forming unit; The state sensing unit is configured around the molding cavity and is used to collect internal state information of the material before pressing. The feedforward control unit is data-connected to the state sensing unit, and is used to receive and generate a pressing strategy and control the pressing process before the physical pressing action occurs based on the internal state information of the material. The pressing and molding unit is connected to the feedforward control unit and is used to receive and execute pressing actions and pressure release and demolding according to the pressing strategy.

2. The clean coal high-pressure forming system based on adaptive control according to claim 1, characterized in that, The state perception unit includes a potential energy pre-storage module, a situation perception module, and a disturbance detection module; the potential energy pre-storage module is used to receive a standby command signal and inject a pre-pressurized medium into the prestressed elastic energy storage cavity according to the standby command signal to perform potential energy pre-storage processing and obtain energy storage state parameters. The situational awareness module is used to receive material entry signals and energy storage status parameters, and to determine the system energy readiness status based on the energy storage status parameters. Under the condition that the system energy is ready and a material entry signal is received, the multispectral monitoring array is activated to collect multispectral radiation data, and the multispectral radiation data is subjected to non-contact stress field evolution analysis processing to obtain the internal state parameters of the material containing the system energy readiness status and stress field distribution information. The disturbance detection module is used to receive and determine the detection start conditions based on the system energy readiness state and stress field uniformity index in the internal state parameters of the material. When the detection start conditions are met, the micro-amplitude mechanical vibration injection device is activated to apply a detective mechanical disturbance to the material and then micro-amplitude vibration response data is collected. The micro-amplitude vibration response data is then processed to perform defect distribution inversion to obtain risk map data.

3. The clean coal high-pressure forming system based on adaptive control according to claim 2, characterized in that, The situation awareness module includes a multispectral monitoring array, a signal conditioning unit, and a stress field inversion processor; the multispectral monitoring array is deployed around the molding cavity and includes a thermal radiation sensor, a stress luminescence detector, and a microwave scattering receiver, used to collect material thermal radiation, stress luminescence, and microwave scattering signals. The stress field inversion processor is based on the thermo-mechanical coupling equation to invert the internal stress field distribution of the material and its evolution trend over time from the temperature field distribution, without the need for physical contact with the material; The disturbance detection module includes a micro-amplitude mechanical vibration injection device, an acoustic echo analysis unit, and a defect identification processor. The micro-amplitude mechanical vibration injection device is used to apply linear frequency modulation vibration to the material. The acoustic echo analysis unit includes a transmitting transducer and a receiving transducer array, used to transmit detection pulses to the material and collect echo signals. The defect identification processor performs defect distribution inversion processing on the echo signal based on the tomographic imaging algorithm to obtain risk map data.

4. The clean coal high-pressure forming system based on adaptive control according to claim 1, characterized in that, The feedforward control unit includes a prediction deployment module, a strategy adaptation module, a timing control module, and a stiffness reconstruction module. The prediction and control module is used to receive the internal state parameters of the material, risk map data, historical rheological data and adaptation strategy parameters, and perform digital twin inference and micro-texture control processing on the historical rheological data based on the internal state parameters of the material, risk map data and adaptation strategy parameters to obtain the suppression strategy parameters and micro-texture configuration instructions. The strategy adaptation module is used to receive the internal state parameters and historical rheological data of the material, and to retrieve the regional characteristic database based on the material component identification data and historical rheological data extracted from the internal state parameters of the material to perform dynamic matching processing of the compression strategy and obtain the adaptation strategy parameters. The timing control module is used to receive the internal state parameters of the material, risk map data and suppression strategy parameters, and generate a critical state judgment signal based on the internal state parameters of the material and risk map data. When the critical state judgment signal meets the triggering conditions, it performs advanced triggering and suppression timing management processing to obtain the suppression execution command and the depressurization stage signal. The stiffness reconstruction module is used to receive the microtexture configuration command and the pressing execution command, and to collect local stress concentration data in real time through the piezoresistive sensor array embedded in the mold. Based on the microtexture configuration command and the pressing execution command, the local stress concentration data is subjected to reverse mold stiffness compensation processing to obtain the reconstructed cavity control parameters.

5. The clean coal high-pressure forming system based on adaptive control according to claim 4, characterized in that, The prediction and control module pre-simulates the pressing process in virtual space based on the material constitutive model, and pre-deploys a micro-texture array on the surface of the physical mold cavity that matches the predicted pressure distribution according to the pre-simulation results. The strategy adaptation module automatically retrieves the regional characteristic database based on the material composition identification data and calls the optimal pressing strategy that matches the current material characteristics. The timing control module activates the pressing action in advance before the physical state of the material reaches the traditional pressing start conditions, and coordinates the action timing of each module. The stiffness reconstruction module changes the equivalent elastic modulus of a local area of ​​the mold through a programmable stiffness control array, transforming the stress concentration area originally dominated by the material into a uniform pressure area controlled by the stiffness distribution of the mold.

6. The clean coal high-pressure forming system based on adaptive control according to claim 1, characterized in that, The pressing and molding unit includes a pressing execution module, a stress reconstruction module, and a transient demolding module; The pressing execution module is used to receive the pressing execution command and the reconstructed cavity control parameters, and to perform mechanical pressing and cavity shape maintenance processing on the pressing execution command according to the reconstructed cavity control parameters to obtain the pressing process status; The stress reconstruction module is used to receive the decompression stage signal and the adaptation strategy parameters, and according to the adaptation strategy parameters, perform non-monotonic decompression curve execution and stress redistribution processing under the condition of receiving the decompression stage signal to obtain the residual stress equilibrium state. The transient demolding module is used to receive the residual stress equalization state and the trigger signal, and determine the demolding ready state according to the residual stress equalization state. When the residual stress equalization state meets the equalization condition, it performs millisecond-level cavity state switching and gas pulse demolding processing according to the trigger signal.

7. The clean coal high-pressure forming system based on adaptive control according to claim 6, characterized in that, The stress reconstruction module executes a three-stage non-monotonic decompression curve, which redistributes the residual stress inside the briquette evenly rather than releasing it in a concentrated manner. In the first stage, the pressure is decompressed to the first pressure at the first rate and held for the first time. In the second stage, the pressure is increased to the second pressure at the second rate, which is less than the first rate and the second pressure is less than the maximum pressure. In the third stage, the pressure is finally decompressed to normal pressure at the third rate, which is less than the first rate. The transient demolding module uses a rapid demolding mechanism based on shape memory alloy to switch the cavity boundary from a rigid constraint state to an elastic yielding state, while applying a high-pressure gas pulse to achieve instantaneous detachment of the briquettes.

8. The clean coal high-pressure forming system based on adaptive control according to claim 1, characterized in that, The system also includes an internal and external coordination module and an energy capture module; The internal and external coordination module is used to receive the pressing process status and the internal state parameters of the material, and to determine the coordination triggering condition based on the stress field uniformity index in the internal state parameters of the material. When the stress field uniformity index exceeds the threshold, the external microwave radiation parameters are activated and the internal gasification expansion and external pressure coordination are performed to obtain a coordinated dense state. The energy capture module is used to receive the cooperative compaction state and determine the decompression start-up conditions based on the cooperative compaction state. When the cooperative compaction state reaches a preset density threshold, it collects the pressure difference data of the decompression channel to capture and convert residual stress energy to obtain recovered electrical energy.

9. The clean coal high-pressure forming system based on adaptive control according to claim 8, characterized in that, The internal and external synergy module triggers the controlled gasification and expansion of the inducible gasifying agent microcapsules embedded in the material through external microwave radiation, forming a synergistic densification effect with external mechanical compression; the energy capture module captures the residual pressure energy during the depressurization process and converts it into electrical energy through the Venturi effect pressure difference power generation unit.

10. A method for high-pressure forming of clean coal based on adaptive control, characterized in that, Includes the following steps: The state perception step collects internal state information of the material before pressing, including obtaining energy storage state parameters by performing potential energy pre-storage processing through the potential energy pre-storage module, obtaining internal state parameters of the material by collecting multispectral radiation data through the situation perception module and performing non-contact stress field evolution analysis processing, and obtaining risk map data by applying detective mechanical disturbance through the disturbance detection module and performing defect distribution inversion processing. The feedforward control step generates a pressing strategy and controls the pressing process before the physical pressing action occurs based on the internal state information of the material. This includes obtaining pressing strategy parameters and micro-texture configuration instructions through digital twin simulation and micro-texture control processing by the prediction and control module; obtaining adapted strategy parameters through dynamic matching processing of the pressing strategy by the strategy adaptation module; obtaining pressing execution instructions and pressure relief stage signals through advance triggering and pressing timing management processing by the timing control module; and obtaining reconstructed cavity control parameters through reverse compensation processing of mold stiffness by the stiffness reconstruction module. The pressing and molding step involves executing pressing actions and completing pressure release and demolding according to the pressing strategy. This includes mechanical pressing and cavity shape maintenance through the pressing execution module, non-monotonic pressure release curve execution and stress redistribution processing through the stress reconstruction module to obtain a residual stress equilibrium state, and millisecond-level cavity state switching and gas pulse demolding processing through the transient demolding module.

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