Screw conveyor deslagging system applied to hard plastic clay section

Abstract

The invention discloses a screw conveyor deslagging system applied to a hard plastic clay section, and relates to the technical field of shield tunneling, the screw conveyor deslagging system comprises a screw conveyor body, a slag outlet gate, a hydraulic driving mechanism, a control system, a multi-mode sensing module and a hard plastic clay self-adaptive control module, and the multi-mode sensing module is integrated with equipment. Collecting muck physical characteristic parameters and equipment operation state data in real time; the hard plastic clay self-adaptive control module dynamically adjusts the opening degree of the slag outlet gate based on the data; the control system generates an opening degree adjusting instruction, the hydraulic driving mechanism drives the gate to act, and a sensing-decision-execution closed-loop control system is formed; compared with the prior art, muck and equipment state data are obtained in real time through multi-mode sensing, dynamic adjustment of the opening degree of the slag outlet and pre-control of the blocking risk are achieved in combination with the self-adaptive control module, the slag outlet efficiency and construction safety of the hard plastic clay section are effectively improved, the manual intervention cost is reduced, and the construction efficiency is improved. And an intelligent solution is provided for shield construction.

Description

Technical Field

[0001] The present invention relates to the technical field of shield tunneling, and in particular to a spiral machine slag discharge system applied to hard plastic clay areas. Background Art

[0002] In the subway shield construction in hard plastic clay strata, spiral or rotary screw conveyors face severe transportation challenges. Hard plastic clay has a high natural density, dense clay particles and obstructed pore water migration. After being cut by the cutter head, conventional modifiers are difficult to make it form an ideal plastic flow state (slump <5cm). This makes the slag discharged by the screw conveyor appear as a continuous strip-shaped consolidated body with an actual width of 930mm, far exceeding the standard transportation width of 700-800mm of the matching belt conveyor. This causes the slag to accumulate and get stuck at the connection between the screw conveyor outlet and the belt conveyor, seriously affecting the continuous discharge of the screw conveyor. Taking the screw conveyor equipped with a Φ6280 shield machine as an example, a single ring (1.5m excavation) needs to discharge 56m of slag. 3 Due to the increased conveying resistance caused by the consolidation of the slag, four workers had to take turns to intervene and deal with the consolidated slag at the outlet of the screw conveyor. A single ring of soil discharge took up to six hours (400% longer than normal working conditions). Moreover, the screw conveyor had to be frequently started and stopped due to jamming during the soil discharge process. This not only further reduced the conveying efficiency, but also caused the soil bin pressure to fluctuate by more than 0.2 bar, increasing the risk of excessive surface subsidence. The existing passive mode of "manually crushing slag" cannot break the vicious cycle of "screw conveyor transportation obstruction - shutdown for treatment - soil bin pressure imbalance - increased slag consolidation". According to industry statistics, the effective conveying efficiency loss of screw conveyors in such strata is as high as 40% to 60%, which has become the main reason for construction delays caused by conveying equipment problems in domestic subway construction in the past five years. Summary of the Invention

[0003] In response to the problems of easy clogging and manual adjustment lag in spiral machine slag discharge during shield construction in hard plastic clay areas, the present invention provides a spiral machine slag discharge system for hard plastic clay areas. Through the real-time collection of slag characteristics and equipment status data through a multimodal perception module, combined with the hard plastic clay adaptive control module, dynamic adjustment of the slag outlet opening and pre-control of clogging risks are achieved, thereby improving slag discharge efficiency, construction safety and reducing labor costs.

[0004] The present invention is achieved through the following technical solutions:

[0005] A screw conveyor slag discharge system for hard plastic clay soils includes a screw conveyor body, a slag discharge gate, a hydraulic drive mechanism, and a control system, and further includes:

[0006] A multimodal sensing module, integrated with the screw machine body and the slag outlet gate, collects slag physical property parameters and equipment operating status data in real time, and includes an acoustic vibration sensor for collecting soundprint characteristics of friction between the slag and the screw machine blades, combining three-dimensional point cloud data and mechanical data to form a multidimensional feature vector; a hard plastic clay adaptive control module, which is in communication with the multimodal sensing module and the hydraulic drive mechanism and dynamically adjusts the slag outlet gate opening based on the mechanical properties of the slag;

[0007] Among them, the control system generates an opening adjustment instruction based on the output data of the multimodal perception module through the hard plastic clay adaptive control module, and the hydraulic drive mechanism drives the slag outlet gate according to the instruction, forming a "perception-decision-execution" closed-loop control system.

[0008] In this solution, the spiral convection machine's slag discharge system is integrated with the convection machine body and the slag outlet gate via a multimodal sensing module. This module collects soil physical property parameters and equipment operating status data in real time, overcoming the limitations of existing technologies that rely on manual visual inspection or a single sensor. It achieves multidimensional and accurate perception of the soil state. The hard plastic clay adaptive control module communicates with the multimodal sensing module and the hydraulic drive mechanism, dynamically generating an opening adjustment strategy based on the acquired soil mechanical property data. Based on the output data of the multimodal sensing module, the control system generates specific opening adjustment instructions through the hard plastic clay adaptive control module, actuating the hydraulic drive mechanism to precisely adjust the slag outlet gate opening, forming a closed-loop "perception-decision-execution" control system. This system can effectively address problems such as slag discharge blockage and manual adjustment lag caused by the high friction and stickiness of the soil in hard plastic clay areas. It achieves dynamic adaptive control of the slag discharge process, improves slag discharge efficiency and construction safety, and reduces manual intervention costs.

[0009] Furthermore, the multimodal perception module includes:

[0010] A binocular structured light depth camera is connected above the slag outlet gate to collect 3D point cloud data of slag in real time and identify the plasticity level of hard plastic clay flow using an improved YOLOv7 algorithm;

[0011] The cross shear plate detection unit with a retractable multi-set shear blade structure is connected to the screw machine body through a six-degree-of-freedom robotic arm, which can automatically complete the "insertion-rotation-data collection" cycle;

[0012] The multi-axis force sensor group is distributed on the surface of the screw machine blade and the contact surface of the slag outlet gate to monitor the shear strength τ between the slag and the equipment in real time. f ;

[0013] The multi-modal perception module synchronizes in time and space the acquired three-dimensional point cloud data, shear strength data and mechanical data to form a multi-dimensional feature vector of the physical properties of the slag, and establishes a slag jam risk assessment model according to the multi-dimensional feature vector.

[0014] In the present scheme, the multi-modal perception module acquires slag three-dimensional point cloud data through a binocular structured light depth camera, identifies the flow plasticity grade through an improved YOLOv7 algorithm, and automatically completes the “insertion-rotation-acquisition” cycle to acquire the cohesion c and internal friction angle of the slag through the cross shear plate detection unit. The shear strength of the screw blade and the gate contact surface is monitored by a multi-axis force sensor group, and the three are synchronized in time and space to form a multi-dimensional feature vector, and finally a jam risk assessment model is constructed. This module breaks through the limitations of traditional single sensor monitoring, realizes multi-dimensional and dynamic perception of the physical properties of hard-plastic clay, and provides real-time and accurate data support for subsequent adaptive control. The innovation lies in: fusion analysis of three-dimensional point cloud and mechanical data to improve the accuracy of slag state recognition; automatic shear testing unit solves the problem of manual sampling lag; the risk assessment model is based on multi-dimensional feature vectors to predict jam risk in advance, providing predictive decision basis for system dynamic opening adjustment, significantly reducing the jam probability under hard-plastic clay conditions.

[0015] Further, input parameters to the slag jam risk assessment model include shear strength τ f monitored by the cross shear plate detection, screw torque T monitored by the multi-axis force sensor, and soil cabin pressure P measured by the soil cabin pressure sensor 仓 , so as to obtain a risk value R through the following formula:

[0016]

[0017] wherein τ max is the critical value of the shear strength of hard-plastic clay, T 阈值 is the upper limit of the screw torque, and P 安全 is the safety threshold of the soil cabin pressure; yellow warning is triggered when R≥0.7, and red warning is triggered when R≥0.9.

[0018] In the present scheme, multi-dimensional parameters such as shear strength monitored by the cross shear plate detection, screw torque T monitored by the multi-axis force sensor, and soil cabin pressure P measured by the soil cabin pressure sensor are input to the slag jam risk assessment model. The measured values are normalized with the critical value of the hard-plastic clay condition through a formula to obtain a comprehensive risk value R, and R≥0.7 and R≥0.9 are used as yellow and red warning thresholds. This not only builds a quantitative evaluation system through multi-source data fusion to realize graded warning of hard-plastic clay jam risk, but also effectively reduces the jam risk caused by parameter mutation compared to the traditional single torque monitoring mode, improving the intelligent warning capability and safety of shield construction.

[0019] Furthermore, the insertion depth of the cross shear plate detection unit is coupled with the propulsion speed of the screw machine body, and the specific relationship is:

[0020] h = k × v + c, where h is the insertion depth (m), v is the screw machine propulsion speed (m / min), k = 0.015, and c = 0.02.

[0021] In this solution, the cross shear plate detection unit dynamically adjusts the shear plate insertion depth based on the density difference of hard plastic clay at different advancing speeds, ensuring the acquisition of soil mechanical data that is representative of the working conditions, providing more accurate mechanical parameters for the hard plastic clay adaptive control module, and then optimizing the opening adjustment strategy and blockage risk assessment model to ensure that the soil mechanical properties can be reflected in real time and accurately under different advancing speed conditions, significantly improving the system's adaptability and detection reliability to complex working conditions of hard plastic clay.

[0022] Furthermore, the insertion angle of the cross shear plate detection unit is 45±5° with respect to the horizontal plane.

[0023] In this scheme, the cross shear plate detection unit is designed to be inserted into the slag at an angle of 45±5° to the horizontal plane. Its function is to simulate the force direction of the natural shear failure surface of the soil, so that the direction of the shear force when the shear plate rotates is consistent with the potential sliding surface inside the hard plastic clay, thereby more realistically triggering the shear failure process of the slag and obtaining accurate shear strength data.

[0024] Furthermore, the hard plastic clay adaptive control module includes a dynamic parameter PID control unit;

[0025] The dynamic parameter PID control unit is based on the soil flow plasticity score deviation e s , shear strength deviation e τ and the volume change rate e v And adjust the proportional coefficient K in real time through the fuzzy inference system p , integral coefficient K i , differential coefficient K d , the opening adjustment amount ΔL of the slag outlet gate action is output through the following formula;

[0026]

[0027] Among them, e s =S r,target -S r ,measured,S r,target is the plasticity score of the target flow, S r ,measured is the real-time measurement value;

[0028] V t is the current moment slag volume;

[0029] ΔK p , ΔK i , ΔK d is the parameter adjustment amount of fuzzy inference output.

[0030] In the present scheme, the dynamic parameter PID control unit of the hard plastic clay self-adaptive control module adjusts the proportional coefficient, integral coefficient and differential coefficient in real time through the fuzzy inference system based on the slag flow plasticity score deviation, shear strength deviation and volume change rate, and outputs the slag gate opening degree adjustment amount, breaking through the limitation of fixed parameters of traditional PID controller, and realizing dynamic self-adaptive control for the high viscosity and nonlinear mechanical properties of hard plastic clay. Specifically, the slag viscosity degree change is quantified through the flow plasticity score deviation, the slag dynamic trend is judged in combination with the volume change rate, the PID parameters are optimized in real time by using fuzzy inference, the proportional coefficient K p , the integral coefficient K i and the differential coefficient K d are dynamically adjusted according to the working conditions, and the problems such as regulation lag and large overshoot caused by fixed parameters in traditional control method are solved; and the mechanism significantly improves the adaptability of the system to the viscosity state fluctuation of hard plastic clay, ensures that stable slagging can be maintained through precise opening degree adjustment under complex working conditions such as slag flow plasticity change and propulsion speed fluctuation, and avoids the risk of blockage or gushing caused by rough parameter adjustment.

[0031] Further, the system further comprises a slag improvement collaborative control module. When it is detected that the slag flow plasticity score S r , measured is less than 50 points, the slag improvement collaborative control module injects a high polymer modifier through the grouting hole built in the blade of the screw machine body, and adjusts the screw machine speed in linkage, so that the modifier and the slag are fully mixed.

[0032] In the present scheme, the slag improvement collaborative control module constructs an integrated intelligent regulation and control mechanism of “detection-improvement-mixing” for the high friction and easy caking problems caused by insufficient flow plasticity (score < 50 points) of hard plastic clay, and through real-time detection triggering, quantitative injection and speed collaborative closed-loop control, the flow plasticity score is improved to the optimization interval of 60-70 points, so that the hard plastic clay is transformed from “easy to block state” to “controllable slagging state”, and the faults such as screw machine jamming and gate blockage caused by slag viscosity are significantly reduced, and the continuous operation ability of shield construction in the low flow plasticity hard plastic clay section is improved.

[0033] Further, the injection amount of the modifier is according to the following formula:

[0034] Where ρ is the density of soil, V is the volume of the improved area, S r ,measured is the real-time measurement value.

[0035] In this scheme, the soil density ρ, the volume of the improved area V and the real-time flow plasticity score S r , measured is the input, so that the injection amount Q of the modifier is proportional to the degree of insufficient plasticity of the slag flow, ensuring that the amount of high-molecular polymer modifier is dynamically matched with the viscosity characteristics of the hard plastic clay. In addition, this formula is deeply coupled with the real-time data of the multimodal perception module, which not only avoids the failure of the improvement effect due to insufficient dosage, but also prevents excessive injection from causing material waste and abnormal soil compartment pressure. Combined with the coordinated adjustment of the screw machine speed, the plasticity of the slag flow is accurately improved to the optimal slag discharge range of 60 to 70 minutes, reducing the risk of blockage caused by viscosity from the root.

[0036] Furthermore, the hard plastic clay adaptive control module also includes a critical working condition prediction model, which is constructed based on the LSTM neural network, and the input includes the historical shear strength sequence, the torque fluctuation mean square error σ T and peak frequency f p , the output is the congestion risk probability P r , according to P r Trigger different control strategies.

[0037] In this scheme, by analyzing the historical shear strength series, torque fluctuation mean square error σ T , peak frequency f p The LSTM neural network can capture the trend change of shear strength and the periodic characteristics of torque fluctuation during the accumulation of soil viscosity, and automatically match the control strategy according to the probability threshold. The model upgrades the control logic from "post-response" to "pre-control", effectively identifying the potential blockage risk of hard plastic clay caused by viscosity accumulation, and forms a full-process intelligent closed loop of "prediction-regulation-execution" in combination with the dynamic parameter PID controller.

[0038] Furthermore, when P r <60%, maintain conventional PID control; when 60%≤P r <75%, start the soil improvement linkage and inject high molecular polymer; when 75%≤P r <90%, the gate pulse vibration and the screw machine are alternately rotated forward and reverse; when P r When it is ≥90%, emergency stop is triggered and the cutter disc is linked to reduce speed.

[0039] In this scheme, the hard plastic clay adaptive control module is based on the blockage risk probability P output by the critical working condition prediction model.r A four-level progressive risk response mechanism has been established, and precise and differentiated control strategies have been implemented for different levels of hard plastic clay blockage risks, realizing full-process risk management of "prevention-intervention-emergency disposal".

[0040] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0041] 1. This invention uses a multimodal sensing module to collect real-time data on slag characteristics and equipment status. Combined with a hard plastic clay adaptive control module, it achieves dynamic adjustment of the slag outlet opening and pre-control of blockage risks, improving slag discharge efficiency, construction safety, and reducing labor costs.

[0042] 2. Through the systematic innovation of "intelligent perception + adaptive control + forward-looking pre-control + coordinated linkage", this invention has overcome the industry's difficult problem of spiral machine slag discharge in hard plastic clay areas, significantly improved the intelligence level, safety and economy of shield construction, and has outstanding technological progress and engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0044] Figure 1 This is a schematic diagram of the planar structure of the slag outlet of the spiral machine;

[0045] Figure 2 This is a schematic diagram of the three-dimensional structure of the slag outlet of the spiral machine;

[0046] Figure 3 This is a schematic diagram of the automatic adjustment process of the slag outlet opening of the spiral machine.

[0047] Markings and corresponding parts names in the accompanying drawings:

[0048] 1-slag outlet gate, 2-articulated system, 3-articulated cylinder, 4-high-pressure oil inlet, 5-transport belt, 6-control system, 7-electromagnetic control valve, 8-high-pressure hydraulic oil. DETAILED DESCRIPTION

[0049] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0050] Example

[0051] This embodiment provides a spiral conveyor slag discharge system for hard plastic clay areas, such as Figure 1-Figure 3As shown, it includes a screw machine body, a slag outlet gate 1, a hydraulic drive mechanism, and a control system 6;

[0052] The screw machine body pushes the slag in the soil bin axially to the slag outlet gate 1 through a rotating shaft with blades. When the slag outlet gate 1 opens to 700mm, the screw machine body controls the slag discharge flow by adjusting the speed (0-12rpm) to ensure that it matches the speed of the conveyor belt 5 located below the output end of the screw machine body to avoid slag accumulation. At the same time, the shaft core of the screw machine body has a built-in six-degree-of-freedom robot arm interface for installing a cross shear plate detection unit, and 6 sets of strain force sensors are attached to the surface of the blades, distributed in the front, middle and rear sections, to monitor the friction resistance F between the slag and the blades in real time. f In addition, there are grouting holes built into the blades of the screw machine body. Through the slag improvement collaborative control module, high molecular polymer modifier can be injected into the grouting holes to reduce the screw machine jamming, gate blockage and other faults caused by slag viscosity.

[0053] After the shield cutterhead cuts the hard plastic clay, the particles become densely bonded and pore water migration is blocked, making it difficult for conventional modifiers (foam / dispersants) to effectively penetrate. The soil cannot form an ideal plastic flow state (slump < 5 cm), resulting in the slag discharged by the screw conveyor forming a continuous strip-shaped consolidated body (width = 930 mm), far exceeding the standard transport width of the conveyor belt 5. Therefore, a slag outlet gate 1 is installed at the slag outlet. The slag outlet gate 1 is a three-stage rectangular gate with an effective opening width of 1000 mm. The slag outlet gate 1 is connected to a hydraulic drive mechanism, namely, to the output end of an articulated cylinder 3. The articulated cylinder 3 is connected to the side wall through an articulated system 2. The electromagnetic control valve 7 controls the high-pressure hydraulic oil 8 in the high-pressure oil inlet pipe 4, thereby controlling the opening of the slag outlet gate 1. The slag outlet gate 1 also has a built-in magnetostrictive displacement sensor, which provides real-time feedback on the opening to the control system 6.

[0054] In this embodiment, in order to avoid the detection lag problem of traditional external sensors and realize "in-situ detection and real-time feedback", the screw machine body and the slag outlet gate 1 are physically integrated with a multi-modal sensing module. Specifically, in the screw machine body, the multi-modal sensing module is provided with a cross shear plate detection unit, which adopts a retractable multi-set shear blade structure. The cross shear plate detection unit is rigidly connected to the front flange of the screw machine body through a six-degree-of-freedom robotic arm (such as UR10e). The base of the robotic arm is fixed to the hollow shaft core of the screw machine, and the shear plate can be extended and retracted along the axis of the screw machine. In this embodiment, because the natural shear surface of hard plastic clay is at an angle of about 45°+φ / 2 (φ is the internal friction angle) with the horizontal plane, this angle can make the force direction of the shear plate consistent with the natural failure surface. Therefore, the six-degree-of-freedom robotic arm drives the shear plate to be inserted into the slag at an angle of 45°±5°. The insertion depth h of the slag is dynamically calculated by the screw machine propulsion speed v through the formula h=0.015v+0.02, automatically completing the "insertion-rotation-data collection" cycle, and collecting the peak torque T during the rotation process. peak , through the formula Calculation of shear strength τ f , synchronously reverse the cohesion c and internal friction angle

[0055] The multi-modal sensing module also installs a multi-axis force sensor group on the blade part to monitor the equipment load in real time. That is, the strain force sensor is attached to the surface of the screw machine blade through high-temperature resistant glue (two groups each in the front, middle and rear sections) to monitor the tangential stress σ in real time. t and normal stress σ n , calculate the friction resistance F by integration f =∫(σ t +μσ n )dA, μ is the friction coefficient, when F f When the value is greater than 300kN, the slag viscosity is determined to be out of limit, triggering the intervention of the hard plastic clay adaptive control module; in addition, the cable of the above-mentioned sensor is introduced into the hollow shaft of the screw machine along the wire groove on the back of the blade, and is connected to the signal interface of the control system 6 through the slip ring assembly to ensure data transmission in the rotating state.

[0056] At the same time, at the slag outlet gate 1, the multimodal perception module is equipped with a binocular structured light depth camera and an acoustic vibration sensor. The binocular structured light depth camera is connected above the slag outlet gate 1, and the lens is vertically downward aimed at the slag discharge area to collect the slag three-dimensional point cloud data in real time, extract the slag volume V and volume change rate e v , morphological characteristics (such as aspect ratio, density) and surface texture information, and then the obtained point cloud data is input into the improved YOLOv7 model to identify the flow plasticity score S through the trained hard plastic clay sample r ,measured(0-100 points, hard plastic state corresponds to S r, measured<60 points), and a set of low-frequency acoustic sensors (measuring range 10-1000Hz) are installed on the hinged shaft seat between the slag outlet gate 1 and the hydraulic drive mechanism. They are fixed by a magnetic base to collect the low-frequency impact sound generated by the collision and extrusion of the gate and the consolidated slag. The collected acoustic vibration signals can be synchronized in time and space with the visual data of the binocular structured light depth camera. For example, when the three-dimensional point cloud recognizes the slag agglomeration, the peak frequency fp of the acoustic vibration signal will synchronously show a characteristic peak of 200-500Hz, providing a multi-modal verification basis for the blockage risk assessment model.

[0057] The multi-axis force sensor group in the gate part is embedded in the contact surface between the gate and the hinge system 2. The sensor signal line is led out through the internal channel of the hinge cylinder 3 and connected to the control system 6. The multi-axis force sensor group in this part monitors the normal force F in real time. n , tangential force, torque T and soil compartment pressure P 仓 , calculate the shear strength at the gate A is the contact area, and torque fluctuation characteristics (mean square error σ T ,σ T Reflects the torque fluctuation amplitude, σ T The increase indicates that the viscosity of the slag is enhanced, and the peak frequency f p , f p The number of torque peaks per unit time, f p An increase in the pressure indicates a tendency for agglomerate formation), providing key parameters for critical condition prediction.

[0058] In order to achieve multi-dimensional and dynamic perception of the physical properties of hard plastic clay, the multimodal perception module collects 10 sets of data per second and generates a 10-dimensional feature vector after spatiotemporal synchronization processing. The eigenvector X is transmitted to the hard plastic clay adaptive control module, which uses the multidimensional eigenvector to establish a soil blockage risk assessment model as follows:

[0059]

[0060] Among them, τ max is the critical value of shear strength of hard plastic clay, T 阈值 is the upper limit of the screw machine torque safety, P 安全 It is the safety threshold of soil compartment pressure; when R ≥ 0.7, a yellow warning is triggered, and when R ≥ 0.9, a red warning is triggered, providing a complete link from "accurate data acquisition" to "intelligent risk assessment" for the spiral machine slag discharge system in hard plastic clay sections.

[0061] When the multimodal perception module determines that the slag viscosity exceeds the limit, the hard plastic clay adaptive control module is triggered to intervene. At this time, the dynamic parameter PID control unit in the hard plastic clay adaptive control module will be based on the slag flow plasticity score deviation e s , shear strength deviation e τ and the volume change rate e v The proportional coefficient K is adjusted in real time through the fuzzy inference system p , integral coefficient K i , differential coefficient K d , the opening adjustment value ΔL of the slag outlet gate action is output through the following formula;

[0062]

[0063] Among them, e s =S r,target -S r ,measured,S r,target is the plasticity score of the target flow, S r ,measured is the real-time measurement value;

[0064] V t is the volume of soil at the current moment;

[0065] ΔK p , ΔK i , ΔK d It is the parameter adjustment amount output by fuzzy inference.

[0066] The viscosity change of the slag is quantified by the flow plasticity score deviation, and the dynamic trend of slag discharge is judged by combining the volume change rate. The PID parameters are optimized in real time using fuzzy reasoning to make the proportional coefficient K p , integral coefficient K i , differential coefficient K d Dynamic adjustment according to working conditions solves the problems of adjustment lag and large overshoot caused by fixed parameters in traditional control methods.

[0067] At the same time, the slag improvement collaborative control module detects the slag flow plasticity score S r When measured < 50 minutes, the soil improvement collaborative control module injects a polymer improver through the grouting holes built into the blades of the screw machine body. The amount of improver injected is determined according to the following formula:

[0068] Where ρ is the density of soil, V is the volume of the improved area, S r ,measured is the real-time measurement value.

[0069] At the same time, through closed-loop control coordinated with the rotation speed, the modifier and slag are fully mixed, and the flow plasticity score is increased to the optimized range of 60 to 70 points, so that the hard plastic clay is transformed from an "easy to block state" to a "controllable slag discharge state."

[0070] During the improvement process, the hard plastic clay adaptive control module adjusts the PID parameters synchronously. As the fluidity of the improved slag is improved, the proportional coefficient K is automatically reduced. p (such as from 1.3 to 1.0), to avoid excessive opening adjustment leading to gushing; according to the volume change rate e v Increase, increase the integral coefficient K i (For example, increase from 0.03 to 0.05) to maintain a stable slag discharge flow rate.

[0071] If the improved S r , measured failed to reach the target (e.g. S within 3 minutes r , measured<60 points), the critical operating condition prediction model in the hard plastic clay adaptive control module automatically improves the blocking risk probability P r To 80%, triggering "pulse opening adjustment + screw machine forward and reverse alternating", strengthening mechanical debonding, forming a "chemical improvement + physical impact" dual intervention.

[0072] In this embodiment, the critical working condition prediction model can realize the forward-looking prediction of the blockage risk by mining the nonlinear law of viscosity accumulation through historical data. The critical working condition prediction model is constructed based on the LSTM neural network, and the input includes the historical shear strength series, the torque fluctuation mean square error σ T and peak frequency f p , the output is the congestion risk probability P r , driving the four-level progressive control strategy, that is, when P r <60%, maintain conventional PID control; when 60%≤P r <75%, start the soil improvement linkage and inject high molecular polymer; when 75%≤P r <90%, the gate pulse vibration and the screw machine are alternately rotated forward and reverse; when P r When it is ≥90%, emergency stop is triggered and the cutter disc is linked to reduce speed.

[0073] Therefore, this embodiment automatically matches the control strategy according to the probability threshold, upgrading the control logic from "post-response" to "pre-control", effectively identifying the potential blockage risk caused by viscosity accumulation in hard plastic clay, and combining it with the dynamic parameter PID controller to form a full-process intelligent closed loop of "prediction-regulation-execution".

[0074] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A screw conveyor slag discharge system for hard plastic clay soil, comprising a screw conveyor body, a slag discharge gate (1), a hydraulic drive mechanism and a control system (6), characterized in that: Also includes: A multimodal sensing module is integrated with the screw machine body and the slag outlet gate (1) to collect physical property parameters of slag and equipment operation status data in real time. The multimodal sensing module includes an acoustic vibration sensor for collecting sound pattern characteristics of friction between slag and screw machine blades, and combining three-dimensional point cloud data and mechanical data to form a multidimensional feature vector; A hard plastic clay adaptive control module, the hard plastic clay adaptive control module being in communication with the multimodal sensing module and the hydraulic drive mechanism, and dynamically adjusting the opening of the slag outlet gate (1) based on the multidimensional feature vector; The control system (6) generates an opening adjustment instruction through the hard plastic clay adaptive control module based on the output data of the multimodal perception module, and the hydraulic drive mechanism drives the slag outlet gate (1) to operate according to the instruction, forming a "perception-decision-execution" closed-loop control system.

2. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 1, characterized in that: The multimodal perception module also includes: A binocular structured light depth camera is connected above the slag outlet gate (1) to collect 3D point cloud data of slag in real time and identify the plasticity level of hard plastic clay flow by using an improved YOLOv7 algorithm; The cross-shear plate detection unit with a retractable multi-set shear blade structure is connected to the screw machine body through a six-degree-of-freedom robotic arm, which can automatically complete the "insertion-rotation-data collection" cycle; The multi-axis force sensor group is distributed on the surface of the screw machine blade and the contact surface of the slag outlet gate (1) to monitor the shear strength τ between the slag and the equipment in real time. f ; The multimodal perception module synchronizes the acquired three-dimensional point cloud data, shear strength data and mechanical data in time and space to form a multidimensional feature vector of the physical properties of the slag, and establishes a slag blockage risk assessment model based on the multidimensional feature vector.

3. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 2, characterized in that: Input parameters to the soil blockage risk assessment model include the shear strength τ of the cross shear plate test f , the screw torque T monitored by the multi-axis force sensor and the soil tank pressure P measured by the soil tank pressure sensor 仓 , and thus obtain the risk value R through the following formula: Among them, τ max is the critical value of shear strength of hard plastic clay, T 阈值 is the upper limit of the screw machine torque safety, P 安全 is the safety threshold of the soil compartment pressure; when R ≥ 0.7, a yellow warning is triggered, and when R ≥ 0.9, a red warning is triggered.

4. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 2, characterized in that: The insertion depth of the cross shear plate detection unit is coupled with the propulsion speed of the screw machine body, and the specific relationship is: h = k × v + c, where h is the insertion depth (m), v is the propulsion speed of the screw machine (m / min), k = 0.015, and c = 0.

02.

5. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 4, characterized in that: The insertion angle of the cross shear plate detection unit is 45±5° with the horizontal plane.

6. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 3, characterized in that: The hard plastic clay adaptive control module includes a dynamic parameter PID control unit; The dynamic parameter PID control unit is based on the soil flow plasticity score deviation e in the multidimensional feature vector. s , shear strength deviation e τ and the volume change rate e v And adjust the proportional coefficient K in real time through the fuzzy inference system p , integral coefficient K i , differential coefficient K d , output the opening adjustment amount ΔL of the slag outlet gate (1); wherein, e s =S r,target -S r ,measured,S r,target is the plasticity score of the target flow, S r ,measured is the real-time measurement value; V t is the volume of soil at the current moment.

7. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 6, characterized in that: The system also includes a slag improvement collaborative control module, when it detects that the slag flow plasticity score S r When the measured value is less than 50 minutes, the slag improvement cooperative control module injects a high molecular polymer improver through the grouting holes built into the blades of the screw machine body, and adjusts the speed of the screw machine in a linked manner to fully mix the improver with the slag.

8. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 7, characterized in that: The amount of the modifier injected is based on the following formula: Where ρ is the density of the soil, V is the volume of the improved area, S r ,measured is the real-time measurement value.

9. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 6, characterized in that: The hard plastic clay adaptive control module also includes a critical working condition prediction model, which is constructed based on an LSTM neural network. The input includes a historical shear strength sequence, a torque fluctuation mean square error σ T and peak frequency f p , the output is the congestion risk probability P r , according to P r Trigger different control strategies.

10. The spiral conveyor slag discharge system for hard plastic clay soil according to claim 9, characterized in that: When P r <60%, maintain conventional PID control; when 60%≤P r <75%, start the soil improvement linkage and inject high molecular polymer; when 75%≤P r <90%, the gate pulse vibration and the screw machine are alternately rotated forward and reverse; when P r When it is ≥90%, emergency stop is triggered and the cutter disc is linked to reduce speed.

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