Research On Crane Hoisting Working Condition Choose Expert System

Along with the hoisting machinery been widely used in large-scale construction projects such as port, wind power and chemical industry, more accurate, efficient and reliable design of hoisting scheme is demanded. Current hoisting proposal is mainly formulated manually, the feasibility cannot be verified, and resource utilization cannot be arranged reasonable. Aiming at addressing these deficiencies, this paper presents an expert system which selecting lifting condition based on lifting weight, under the background of our school’s large hoisting program planning system of all-terrain crane in cooperation with Zoomlion.Crane hoisting working conditions selection expert system is a sub-module of the large hoisting program planning system of all-terrain crane. This paper analyzed the system’s demand from design philosophy, design parameters and design requirements. This paper constructed the overall structure of the system and designed three main module packages included expert system core functionality, interface operation and the basic operation for the system. The expert system core functionality module contains knowledge base, inference engine, human machine interface, integrated database. Using the production representation method, the knowledge base including rule and case was established. With the adoption of forward reasoning method for the inference mechanism, a comprehensive database supporting the entire program planning system was established. This paper realized the calculation of the lifting conditions’key parameters, including automatic gaining the virtual scene’s information data, checking factors of the crane such as operating radius, lifting height, lifting weight, magnification, and calculating motion’s protection.Based on the above research, a crane lifting working condition selection expert system is developed and embedded in the large hoisting program planning system of all-terrain crane. With successfully application in the enterprise, the hoisting working conditions selected by this expert system is proved correct and feasible.