CN-121992832-A - Spade loading control method, equipment, medium and product based on working condition identification

CN121992832ACN 121992832 ACN121992832 ACN 121992832ACN-121992832-A

Abstract

The invention discloses a shovel loading control method, equipment, medium and product based on working condition identification, wherein the method comprises the steps of collecting the initial height of a movable arm and the first shovel loading weight of each shovel loading in real time when a loader works; based on the data of the multiple operations, judging the weight and granularity of the material to identify the attribute category of the material, and calling a matched first optimized shovel control parameter from a preset shovel control parameter database according to the attribute category; the loader is controlled to continue to operate according to the parameters, the second shovel loading weight and the operation time of each subsequent operation are collected, and accordingly the average operation efficiency value of the machine is calculated; if the value is lower than the set efficiency threshold, the first optimized shovel loading control parameter is finely adjusted to obtain the second optimized shovel loading control parameter, and the loader is controlled to continue to operate according to the second optimized shovel loading control parameter.

Inventors

LUO JIANWEI
TAO LINYU
JIA CHONG

Assignees

广西柳工元象科技有限公司
广西柳工机械股份有限公司

Dates

Publication Date: 20260508
Application Date: 20260326

Claims (10)

1. The spade loading control method based on the working condition identification is characterized by comprising the following steps of: Collecting the initial height of a movable arm and the first shovel weight corresponding to each shovel loading operation in real time in the process that the loader executes the shovel loading operation in the shovel loading area; judging the weight and granularity of the shoveled materials according to the initial height of each movable arm and the weight of each first shoveling corresponding to multiple shoveling operations, and identifying the attribute type of the shoveled materials according to the judging result; acquiring a first optimized shovel loading control parameter matched with the attribute category of the shovel loading material from a preset shovel loading control parameter database; The loader is controlled to continuously execute the shovel loading operation according to the first optimized shovel loading control parameter, and the second shovel loading weight and the second shovel loading time respectively corresponding to each shovel loading operation which is continuously executed are collected; Calculating an average work efficiency value of the loader according to each second shovel loading weight and each work time corresponding to the continuously executed multiple shovel loading works; And when the average work efficiency value is lower than the set efficiency threshold value, performing fine adjustment on the first optimized shovel loading control parameter to obtain a second optimized shovel loading control parameter, and controlling the loader to continuously execute shovel loading work according to the second optimized shovel loading control parameter.
2. The method of claim 1, wherein the discriminating of the weight and the granularity of the scooped material based on the respective boom initial heights and the respective first scooping weights corresponding to the plurality of scooping operations includes: respectively calculating the weight ratio between the weight of each first shovel and the preset rated load; judging the weight class of the material according to the comparison result of each weight ratio and a preset plurality of weight ratio intervals, and obtaining a weight judging result; according to the first shovel weight corresponding to each movable arm initial height, analyzing the weight difference of different movable arm initial heights to obtain the weight difference rate of the movable arm off-ground height operation and the ground pasting operation; and judging the granularity category of the material according to the comparison result of the weight difference rate and a plurality of preset weight difference rate intervals, and obtaining a granularity judgment result.
3. The method of claim 1, wherein calculating an average work efficiency value for the loader based on each second load weight and each work time corresponding to a plurality of load operations to be performed further comprises: Calculating the efficiency value of the single effective shovel loading operation according to the second shovel loading weight and the operation time which correspond to each shovel loading operation which is continuously executed; and calculating the average work efficiency value of the loader according to a plurality of single effective shovel work efficiency values respectively corresponding to the continuously executed shovel work.
4. A method according to claim 3, wherein fine tuning the first optimized shovel control parameter to obtain the second optimized shovel control parameter comprises: Taking the first optimized shovel loading control parameter as an initialized parameter to be trimmed, and adjusting the parameter to be trimmed based on a preset optimization algorithm to obtain a post-trimming control parameter; The loader is controlled to continuously execute at least one shovel loading operation according to the fine-tuned control parameters, so that a fine-tuned operation efficiency value matched with the fine-tuned control parameters is obtained; If the fine-tuned operation efficiency value is larger than the average operation efficiency value of the loader, taking the fine-tuned control parameter as a second optimized shovel loading control parameter; And if the post-fine adjustment operation efficiency value is smaller than or equal to the average operation efficiency value, taking the post-fine adjustment control parameter as a new parameter to be fine-adjusted, and returning to execute the operation of adjusting the parameter to be fine-adjusted based on a preset optimization algorithm to obtain the post-fine adjustment control parameter until a second optimized shovel loading control parameter is obtained.
5. The method according to any one of claims 1-4, further comprising: Acquiring acceleration of the loader, which is acquired by an inertial measurement unit arranged in the loader, in real time, obtaining a running distance of the loader through integral calculation according to the acceleration of each loader, and accurately positioning the shovel loading area according to the running distance calculation result; After all the shovel materials in the shovel region are shovel, collecting the average work efficiency value of all the loaders executing the shovel operation in the shovel region through the internet of things technology; And acquiring a target loader corresponding to the maximum average work efficiency value, and updating the shovel loading control parameter database according to shovel loading control parameters used by the target loader.
6. The method according to any one of claims 1-4, further comprising: After the loader finishes each shovel loading operation, acquiring real-time road surface bumping degree and real-time road surface gradient acquired by an inertial measurement unit built in the loader in real time; according to a mapping relation between the pre-established bumping degree and the speed limit rated value, a real-time speed limit value matched with the real-time road surface bumping degree and the real-time road surface gradient is obtained; acquiring distance information of a global path formed by a shovel loading end point, a backward stopping point and a discharging stopping point; And planning the running speed of the loader between the shovel loading end point and the unloading stopping point based on the distance information of the global path and a real-time speed limit value matched with the real-time road surface bumping degree and the real-time road surface gradient.
7. The method of claim 6, wherein planning a travel speed of the loader between a shovel loading end point and a dump stopping point based on the distance information of the global path and a real-time speed limit value that matches the real-time road surface bump level and a real-time road surface gradient, comprises: in the process that the loader runs from a backward stopping point to a discharging stopping point, determining the residual running distance from the current position of the loader to the discharging stopping point according to the time point when the movable arm starts to lift; Acquiring the current shovel weight, and determining the lifting time required by lifting the movable arm from the current height to the unloading height; Calculating an optimal running speed curve from the current position to the unloading stopping point based on the residual running distance, the current shovel weight, the lifting time and the real-time speed limit value; And controlling the loader to run according to the optimal running speed curve so as to synchronize the moment when the movable arm is lifted with the moment when the loader reaches the unloading stopping point.
8. An electronic device, the electronic device comprising: At least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the condition recognition-based shovel control method of any one of claims 1-7.
9. A computer readable storage medium storing computer instructions for causing a processor to implement the condition recognition-based shovel load control method of any one of claims 1-7 when executed.
10. A computer program product, characterized in that it comprises a computer program which, when executed by a processor, implements the method of shovel control based on condition recognition according to any one of claims 1-7.

Description

Spade loading control method, equipment, medium and product based on working condition identification Technical Field The invention relates to the technical field of auxiliary shovel loading, in particular to a shovel loading control method, equipment, medium and product based on working condition identification. Background With the acceleration of intelligent upgrading of engineering machinery, the shovel loading operation efficiency and the intelligent operation level of a loader have become keys for measuring the core competitiveness of the loader. The shovel loading operation relates to multiple factors such as materials, gradient, road conditions and the like, and the efficiency and smoothness of the shovel loading operation directly influence the production cost, the equipment service life and the operator experience. However, the conventional control mode based on fixed parameters is difficult to adapt to a complex unstructured real working environment, so that the problems of efficiency fluctuation, equipment loss, personnel fatigue and the like are increasingly outstanding, and the realization of intelligent loader has become an urgent requirement of the industry. In the prior art, optimization for spading operation mainly depends on two methods, namely, a fixed control parameter is preset based on a typical working condition, the method lacks the perceptibility of actual material properties and working environment, efficiency is reduced and equipment is worn once the working condition changes, and local adjustment is attempted through adding a sensor or adopting a simple rule, but the methods are always remained in single-point optimization and lack overall optimization. Both technologies are difficult to deal with global and time-varying complex working conditions, and cannot meet the current intelligent shovel loading control requirements of high adaptability, self-learning and cluster cooperation. Disclosure of Invention The embodiment of the invention provides a shovel loading control method, equipment, medium and product based on working condition identification, which are used for realizing self-adaptive optimization and intelligent control of shovel loading operation and improving efficiency, safety and comfort. According to an aspect of the embodiment of the invention, there is provided a spade loading control method based on working condition identification, the method comprising: Collecting the initial height of a movable arm and the first shovel weight corresponding to each shovel loading operation in real time in the process that the loader executes the shovel loading operation in the shovel loading area; judging the weight and granularity of the shoveled materials according to the initial height of each movable arm and the weight of each first shoveling corresponding to multiple shoveling operations, and identifying the attribute type of the shoveled materials according to the judging result; acquiring a first optimized shovel loading control parameter matched with the attribute category of the shovel loading material from a preset shovel loading control parameter database; The loader is controlled to continuously execute the shovel loading operation according to the first optimized shovel loading control parameter, and the second shovel loading weight and the second shovel loading time respectively corresponding to each shovel loading operation which is continuously executed are collected; Calculating an average work efficiency value of the loader according to each second shovel loading weight and each work time corresponding to the continuously executed multiple shovel loading works; And when the average work efficiency value is lower than the set efficiency threshold value, performing fine adjustment on the first optimized shovel loading control parameter to obtain a second optimized shovel loading control parameter, and controlling the loader to continuously execute shovel loading work according to the second optimized shovel loading control parameter. According to another aspect of the embodiment of the present invention, there is provided a shovel load control device based on condition recognition, the device including: The data acquisition module is used for acquiring the initial height of the movable arm and the first shovel weight corresponding to each shovel loading operation in real time in the process of executing the shovel loading operation of the loader in the shovel loading area; The identification module is used for judging the weight and granularity of the shoveled materials according to the initial height of each movable arm and the weight of each first shoveled corresponding to multiple shoveling operations, and identifying the attribute type of the shoveled materials according to the judging result; The parameter acquisition module is used for acquiring a first optimized shovel loading control parameter matched with the attribute category of the shovel loading mat