Control method and system of front-end conveying device for soil leaching remediation

Patent metadata

Field	Value
Publication number	US-2026048425-A1
Application number	US-202519233616-A
Country	US
Kind code	A1
Filing date	Jun 10, 2025
Priority date	Jun 13, 2024
Publication date	Feb 19, 2026
Grant date	—

Abstract

The present invention relates to a control method and system of a front-end conveying device for soil leaching remediation. The method includes: acquiring device monitoring status data, which encompasses soil weight, feeder rate, and conveyor belt speed, along with an image of the soil to be remediated from the conveying device; obtaining the soil remediation boundary region based on the image of the soil to be remediated; performing non-linear correlation mapping learning on the conveyor belt speed according to the soil weight parameters to obtain weight-conveying speed correlation data; conducting multi-level cooperative response neural network learning on the conveyor belt speed and the feeder's feeding rate based on the weight-conveying speed correlation data to generate cooperative response data for the conveying device; acquiring a monitoring image of the front-end conveying device; and deriving 3D component structure data from these images. This approach enables precise feeding control of the conveying device.

First claim

What is claimed is:

1 . A control method of a front-end conveying device for soil leaching remediation, comprising the following steps:
step S 1 : acquiring device monitoring status data and an image of to-be-remediated soil from a conveying device, wherein the device monitoring status data comprises a soil weight parameter, a feeding rate of a feeder, and a conveyor belt speed; and obtaining a soil remediation boundary region based on the image of the to-be-remediated soil from the conveying device; step S 2 : performing nonlinear correlation mapping learning on the conveyor belt speed based on the soil weight parameter to obtain weight-conveying speed correlation data; and performing multi-level cooperative response neural network learning on the conveyor belt speed and the feeding rate of the feeder based on the weight-conveying speed correlation data to generate cooperative response data of the conveying device; step S 3 : acquiring a front-end conveying device monitoring image; obtaining three-dimensional structure data of components based on the front-end conveying device monitoring image; and performing dynamic parameter rendering on the three-dimensional structure data of the components based on the cooperative response data of the conveying device to construct a dynamic rendering model of the conveying device; and step S 4 : performing digital dynamic simulation for soil leaching on the dynamic rendering model of the conveying device to obtain dynamic simulation data for soil leaching; and performing dynamic speed parameter adjustment on the dynamic simulation data for soil leaching based on the soil remediation boundary region to obtain dynamic speed adjustment data of a conveyor belt; wherein the step S 4 specifically comprises: step S41: performing the digital dynamic simulation for soil leaching on the dynamic rendering model of the conveying device to obtain the dynamic simulation data for soil leaching; step S42: performing weight-speed ratio control analysis on the dynamic simulation data for soil leaching based on the weight-conveying speed correlation data to generate soil weight-conveyor belt speed ratio data; step S43: performing dynamic speed parameter adjustment on the soil weight-conveyor belt speed ratio data based on the soil remediation boundary region to obtain the dynamic speed adjustment data of the conveyor belt, wherein the dynamic speed adjustment data of the conveyor belt comprises dynamic acceleration adjustment data and dynamic deceleration adjustment data, and the step S43 specifically comprises: performing morphological analysis on the soil remediation boundary region to obtain morphological data of a remediation region; performing region area calculation on the soil remediation boundary region based on the morphological data of the remediation region to obtain an area of a to-be-remediated boundary region; comparing an area of a to-be-remediated boundary region based on a preset area threshold of the soil remediation boundary region, and if the preset area threshold of the soil remediation boundary region is greater than the area of the to-be-remediated boundary region, determining that the soil remediation boundary region is a relatively small boundary region, and performing acceleration adjustment amplitude analysis to obtain acceleration adjustment amplitude data; performing dynamic acceleration adjustment on the soil weight-conveyor belt speed ratio data based on the acceleration adjustment magnitude data of the conveyor belt to obtain the dynamic acceleration adjustment data; if the preset area threshold of the soil remediation boundary region is less than or equal to the area of the to-be-remediated boundary region, determining that the soil remediation boundary region is a relatively large boundary region, and performing deceleration adjustment amplitude analysis to obtain deceleration adjustment amplitude data; and performing dynamic deceleration adjustment on the soil weight-conveyor belt speed ratio data based on the deceleration adjustment magnitude data to obtain the dynamic deceleration adjustment data; and step S44: performing transient feeding speed calculation on the dynamic simulation data for soil leaching to obtain a transient feeding speed; step S 5 : performing adaptive feeding speed compensation optimization based on the dynamic speed adjustment data of the conveyor belt to obtain a transient feeding compensation speed; performing real-time parameter adjustment on the front-end conveying device based on the transient feeding compensation speed, and acquiring operating status data for real-time adjustment; and step S 6 : performing error parameter identification on the operating status data for real-time adjustment based on the dynamic simulation data for soil leaching to obtain a control error parameter; and performing dynamic feeding balance control optimization on the conveying device based on the control error parameter to generate a dynamic feeding control parameter so as to carry out a soil leaching remediation control operation.

2 . The control method of a front-end conveying device for soil leaching remediation according to claim 1 , wherein the step S 1 specifically comprises:
step S 11 : performing real-time work monitoring on the front-end conveying device to acquire the device monitoring status data, wherein the device monitoring status data comprises the soil weight parameter, the feeding rate of the feeder, and the conveyor belt speed;
step S 12 : acquiring the image of the to-be-remediated soil from the conveying device;
step S 13 : performing visual identification of soil boundaries on the image of the to-be-remediated soil from the conveying device to extract a soil contour line;
step S 14 : performing boundary segmentation on the image of the to-be-remediated soil from the conveying device based on the soil contour line to obtain the soil remediation boundary region;
step S 15 : performing soil granularity identification on the soil remediation boundary region to obtain soil granularity; and
step S 16 : performing quantitative analysis for soil contamination based on the soil granularity to obtain soil contamination degree data.

3 . The control method of a front-end conveying device for soil leaching remediation according to claim 1 , wherein the step S 2 specifically comprises:
step S 21 : performing weight perturbation analysis on the conveyor belt speed based on the soil weight parameter to obtain conveyor belt speed perturbation data for a weight;
step S 22 : performing nonlinear correlation mapping learning on the soil weight parameter and the conveyor belt speed based on the conveyor belt speed perturbation data for the weight to obtain the weight-conveying speed correlation data;
step S 23 : performing speed fluctuation response analysis on the conveyor belt speed and the feeding rate of the feeder to obtain speed-influenced feeding response data; and
step S 24 : performing multi-level cooperative response neural network learning on the weight-conveying speed correlation data and the speed-influenced feeding response data to generate the cooperative response data of the conveying device.

4 . The control method of a front-end conveying device for soil leaching remediation according to claim 1 , wherein the step S 3 specifically comprises:
step S 31 : acquiring the front-end conveying device monitoring image;
step S 32 : performing component space topological analysis on the front-end conveying device monitoring image to obtain component space topological data;
step S 33 : performing three-dimensional structure analysis based on the component space topological data to obtain the three-dimensional structure data of the components;
step S 34 : performing three-dimensional device reconstruction on the front-end conveying d

Assignees

• China Power Construction Eng Consulting Co Ltd
• Univ Central South

Inventors

• Yang Pingyuan
• Hu Huanxiao
• Wu Xuanyu
• Wu Xiaoen
• Xu Yaobing
• Zhou Jinglin
• Li Mengtian
• Wang Xiaolong
• Shen Shifan
• Yan Wenqin

Classifications

• B65G43/08

  Control devices operated by article or material being fed, conveyed or discharged {(and controlling the discharging devices B65G47/42)} · CPC title

• B65G2203/0258

  Weight of the article · CPC title

• B65G2201/045

  Sand, soil and mineral ore · CPC title

• B65G2203/0291

  Speed of the load carrier · CPC title

• B65G2203/044

  Optical · CPC title