CN-122018288-A - Self-adaptive control method and device for dynamic risk classification of engineering machinery

CN122018288ACN 122018288 ACN122018288 ACN 122018288ACN-122018288-A

Abstract

The application provides a self-adaptive control method and device for dynamic risk classification of engineering machinery. The method comprises the steps of obtaining initial operation parameters of engineering machinery, carrying out normalization processing on the initial operation parameters to obtain target operation parameters, determining dynamic weights of all the target operation parameters based on an entropy weight method, determining risk grades of the engineering machinery according to the dynamic weights and risk scores of all the target operation parameters, determining dynamic safety boundaries of the engineering machinery according to reference PID parameters and risk grades of preset different risk grades, determining PID parameter correction values according to the target operation parameters and the preset operation parameters, and triggering safety interruption under the condition that the PID parameter correction values exceed the dynamic safety boundaries. By the method, the working safety of the engineering machinery can be improved by carrying out real-time risk assessment and safety judgment on the engineering machinery.

Inventors

GUO YANRUI
LUO DIEFENG
ZHANG TAO
ZHANG SHAOHUA
Mo Yiduo
DUAN XIN
LI MIN
LI JIANZHONG
LI XIAOXIA

Assignees

长沙硕博电子科技股份有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. An adaptive control method for dynamic risk classification of engineering machinery is characterized by comprising the following steps: Acquiring initial operation parameters of engineering machinery, and carrying out normalization processing on the initial operation parameters to obtain target operation parameters; Determining the dynamic weight of each target operation parameter based on an entropy weight method; determining the risk level of the engineering machinery according to the dynamic weight and the risk score of each target operation parameter; determining a dynamic safety boundary of the engineering machinery according to the preset reference PID parameters of different risk levels and the risk levels; determining a PID parameter correction value according to the target operation parameter and a preset operation parameter; And triggering a safety interrupt under the condition that the PID parameter correction value exceeds the dynamic safety boundary.
2. The method of claim 1, wherein said determining the dynamic weight of each of said target operating parameters based on an entropy weight method comprises: calculating information entropy of each target operation parameter according to the target operation parameters; and determining the dynamic weight of each target operation parameter according to the information entropy of each target operation parameter.
3. The method according to claim 2, characterized in that the information entropy satisfies: Wherein, the The information entropy of the ith operation parameter at the moment k is represented, m represents the number of sampling windows, N represents the total number of sampling windows, Representing a normalized probability value of the ith operating parameter at the kth time over the mth employing window; Wherein, the Representing the normalized target operating parameter value for the ith operating parameter over the mth sampling window.
4. The method of claim 1, wherein said determining a PID parameter correction value based on said target operating parameter and a preset operating parameter comprises: determining control errors, error change rates and error variances of the target operation parameters according to the target operation parameters and preset operation parameters; Fuzzification processing is carried out on the control error, the error change rate and the error variance to obtain a fuzzy membership degree; And carrying out rule reasoning and deblurring processing on the fuzzy membership degree to obtain the PID parameter correction value.
5. The method of claim 1, wherein said determining a risk level of the work machine based on the dynamic weights and risk scores for each of the target operating parameters comprises: Linearly mapping the target operation parameters according to a preset proportion to obtain risk scores of the target operation parameters; determining the sum of the products of the risk scores and the dynamic weights of all the target operation parameters as the risk score of the engineering machinery; and dividing the risk grade of the engineering machinery according to the risk grade of the engineering machinery.
6. The method of claim 5, wherein the risk score of the work machine satisfies: Wherein, the Represents the risk score of the work machine at time k, Representing the dynamic weight of the ith operating parameter at time k, Representing the risk score of the ith operating parameter at time k.
7. An adaptive control device for dynamic risk classification of engineering machinery, the device comprising: the acquisition module is used for acquiring initial operation parameters of the engineering machinery, and carrying out normalization processing on the initial operation parameters to obtain target operation parameters; The first determining module is used for determining the dynamic weight of each target operation parameter based on an entropy weight method; The second determining module is used for determining the risk level of the engineering machinery according to the dynamic weight and the risk score of each target operation parameter; The third determining module is used for determining the dynamic safety boundary of the engineering machinery according to the reference PID parameters of different preset risk levels and the risk levels; a fourth determining module, configured to determine a PID parameter correction value according to the target operating parameter and a preset operating parameter; and the control module is used for triggering safety interruption under the condition that the PID parameter correction value exceeds the dynamic safety boundary.
8. An electronic device, comprising: A memory configured to store instructions; A processor configured to invoke the instructions from the memory and to enable, when executing the instructions, the adaptive control method of dynamic risk classification of a work machine according to any of claims 1 to 6.
9. A machine-readable storage medium having stored thereon instructions for causing a machine to perform the adaptive control method of dynamic risk classification of a work machine according to any of claims 1 to 6.
10. A computer program product, characterized in that instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the adaptive control method of dynamic risk classification of a work machine according to any of claims 1-6.

Description

Self-adaptive control method and device for dynamic risk classification of engineering machinery Technical Field The invention relates to the technical field of engineering machinery, in particular to a self-adaptive control method and device for dynamic risk classification of engineering machinery. Background The working environment of engineering machinery (crane, excavator and loader) is complex, and factors such as load fluctuation, attitude deviation and environmental interference can cause various safety risks such as capsizing, collision, mechanical injury, falling, fire explosion and system runaway. The risk classification of the traditional control method mostly adopts a fixed threshold value, and the weight difference of each risk factor under different working conditions (such as that the load weight is higher than the inclination angle during heavy load and vice versa during light load) is not considered, so that the risk assessment precision is low, and the safety of engineering machinery is insufficient. Disclosure of Invention The application aims to provide a self-adaptive control method and device for dynamic risk classification of engineering machinery, so as to improve the working safety of the engineering machinery. In a first aspect, an adaptive control method for dynamic risk classification of engineering machinery is provided, where the method includes: Acquiring initial operation parameters of engineering machinery, and carrying out normalization processing on the initial operation parameters to obtain target operation parameters; Determining the dynamic weight of each target operation parameter based on an entropy weight method; determining the risk level of the engineering machinery according to the dynamic weight and the risk score of each target operation parameter; determining a dynamic safety boundary of the engineering machinery according to the preset reference PID parameters of different risk levels and the risk levels; determining a PID parameter correction value according to the target operation parameter and a preset operation parameter; And triggering a safety interrupt under the condition that the PID parameter correction value exceeds the dynamic safety boundary. Optionally, determining the dynamic weight of each target operation parameter based on the entropy weight method includes: calculating information entropy of each target operation parameter according to the target operation parameters; and determining the dynamic weight of each target operation parameter according to the information entropy of each target operation parameter. Optionally, the information entropy satisfies: Wherein, the The information entropy of the ith operation parameter at the moment k is represented, m represents the number of sampling windows, N represents the total number of sampling windows,Representing a normalized probability value of the ith operating parameter at the kth time over the mth employing window; Wherein, the Representing the normalized target operating parameter value for the ith operating parameter over the mth sampling window. Optionally, determining the PID parameter correction value according to the target operating parameter and the preset operating parameter includes: determining control errors, error change rates and error variances of the target operation parameters according to the target operation parameters and preset operation parameters; Fuzzification processing is carried out on the control error, the error change rate and the error variance to obtain a fuzzy membership degree; And carrying out rule reasoning and deblurring processing on the fuzzy membership degree to obtain the PID parameter correction value. Optionally, determining the risk level of the engineering machine according to the dynamic weight and the risk score of each target operation parameter includes: Linearly mapping the target operation parameters according to a preset proportion to obtain risk scores of the target operation parameters; determining the sum of the products of the risk scores and the dynamic weights of all the target operation parameters as the risk score of the engineering machinery; and dividing the risk grade of the engineering machinery according to the risk grade of the engineering machinery. Optionally, the risk score of the work machine satisfies: Wherein, the Represents the risk score of the work machine at time k,Representing the dynamic weight of the ith operating parameter at time k,Representing the risk score of the ith operating parameter at time k. In a second aspect, there is provided an adaptive control apparatus for dynamic risk classification of an engineering machine, the apparatus comprising: the acquisition module is used for acquiring initial operation parameters of the engineering machinery, and carrying out normalization processing on the initial operation parameters to obtain target operation parameters; The first determining module is used for de