Study Of Identification Of Damages In High-rise Frame Construction Based On Genetic Neural Network

Along with the using time passing, the engineering structures inevitably get aged, and frequent natural disasters will also damage them in different degree. Detecting and repairing the damages of the structures plays a very important role in decreasing life and property loss. Meanwhile, early detection of the damages can reduce the expenses whether in repairing or maintaining. Therefore, the identity, location and estimation of the damages are of great importance. The structure damage detecting technology has been widely used in astronautics, civil engineering, mechanical engineering and nuclear industry, which is a multi-disciplinary and comprehensive technology based on damage mechanics, sensor technology, signal analysis technology, computer technology and artificial intelligence technology. Compared to traditional structure damage detecting methods, this article mainly focuses the theories and application of that based on genetic neural network.This article analyzes the combination parameter method which is suitable for the detection of location and degree of the damages. (The combination parameter is a vector consisting of changing information of the natural frequency and the modal components of some selected points) On this basis, a frame structure and a projecting beam structure are employed to receive damage numerical modeling, while some appropriate methods are adapted to construct input parameters of the improved GA—BP neural network, and the trained neural network is applied to carry damage detection to the structure.This article has the following main contents:First of all, as a result of analysis of operating principle of neural network, it's clear that it can identify the damages of the structure.It's a focus and difficult to identify the damages of the structure by modal parameters. This article put forward a method based on improved BP neural network on that topic. It's the powerful mapping capacity, fault-tolerance and the robust that make BP neural network fit for dealing with damage identification. But with the proceeding of the study, there appear two main problems in applications of the neural network: (1) it's hard to determine the initial value of the network structure; (2) it's easy to trap in local minimal solution. For dealing with the shortages, a method based on GA-BP neural network which adapt the mixed technologies to detect the damages is put forward. Thismethod employs genetic algorithm of real coding to optimize the structure and initialparameters of the neural network and it improves the accuracy of the network.Compared to general BP neural network, the detecting results of the three emulatorexamples gained by genetic BP neural network owns better stability, higher accuracyand is much more robust, it is an accurate and effective way to detect the damages ofthe structure.