Gantry Crane Based On Fuzzy Neural Network Dynamic Weighing System

Along with the social and economic development, the cargo throughput of port and dock is increasing, and the gate-type crane as an important handling machinery of port plays an important role. In order to enhance the effectiveness of enterprise, the new request to gate-type crane has been brought forward: hoping that the cargo can be weighed and measured in the handling of dynamic process. At present, because only simple digital signal filter processing for dynamic weighing signal and lack of deeper signal processing technology, the accuracy of the gate-type crane dynamic weighing system can hardly be greatly improved.The paper strives to solve it by fuzzy neural networks.The paper first introduced the general dynamic portal crane weighing system theory and design, and then their problems were analyzed, based on fuzzy neural network portal crane dynamic weighing system design, then details of the fuzzy neural network the basic principles, structure and learning algorithm, the last of the simulation system.Using fuzzy neural network dynamic portal crane weighing system, the problem is transformed into a dynamic weighing fuzzy neural network model, learning algorithm and data processing and so on. Fuzzy neural network as a result of a strong fuzzy, and self-learning, non-linear characteristics, so make the whole system is anti-dynamic weighing equation sick good, good stability, high accuracy, good tracking, etc.In addition, in practice application high frequency interferer and data mutation are considered, so the data acquired directly are pre-disposed. By analyzing the dynamic weighing signal interference factors, two pre-disposed methods are adopted: the first step using digital low-pass filter to filter out high frequency noise interference; the second step, adopting optimization algorithm to fit out periodic signal Low-frequency interference signals and eliminate them.Experimental results show that fuzzy neural network based control algorithm is feasible and achieves the technical requirements put forward by the experiment, and also obtains a quite high dynamic weighing accuracy, which has a good reference value for the future practical system exploitation.