Calculation method, device and storage medium for load hoisting

Abstract

The invention relates to the technical field of data processing, and discloses a load hoisting calculation method, device and storage medium, which solves the problems in the prior art that the calculated load hoisting accuracy is low and the amount of calculation is large. The method includes: collecting sample data corresponding to a set working condition; according to the corresponding preset boom inclination angle under each set working condition, the corresponding sample data under each set working condition and preset fitting According to the formula, the corresponding primary samples under each set working condition are obtained, and at least one extrapolation angle is included in the preset boom inclination angle; according to the moment balance method and the corresponding primary samples under each set working condition, all The standard sample set composed of the corresponding standard samples under the set working conditions; according to the standard sample set, the sample data collected under the current working conditions and the generalized regression neural network, the current load corresponding to the current working conditions of the truck crane is obtained. The embodiment of the present invention is applicable to the calculation process of load hoisting.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a calculation method, device and storage medium for load hoisting. Background technique [0002] The real-time calculation of load hoisting is an important function of the truck crane safety monitoring system. Ideally, the load hoisting weight can be directly calculated by measuring the oil pressure of the luffing cylinder and using the moment balance theory. However, in the actual working process, due to the difficult-to-measure errors in the structural parameters of the jib and the inevitable elastic deformation of the jib during work, the load calculated by the theoretical formula is not accurate. [0003] In the prior art, there are two methods for calculating the lifting weight of truck cranes, one is to use the moment balance theory and polynomial correction to obtain the lifting weight of the load, and the other is to use numerical processing methods to fi...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiments of the present invention is to provide a calculation method, device, and storage medium for load hoisting, which solves the problems of low accuracy and large amount of calculation in the prior art. By selecting standard samples, it reduces The number of training samples, and the use of generalized regression neural network to fit the normative samples, the learning process does not need iterative optimization calculations, reducing the amount of calculation, in addition, the normative samples also include angle extrapolation data, and the sample data of overload conditions are obtained, improving Calculation accuracy of generalized regression neural network for load hoisting

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