Research On The Safety Assessment Of Old Industrial Structures Based On Artificial Neural Network

With the rapid development of economy and China’s ever-accelerating pace of urbanconstruction, contradictions of old buildings demolished and continuous usage appear inmany cities. As for these old buildings, industrial buildings have the advantages of largebay size, firm structure and other characteristics. Through functional replacement, theseold industrial buildings can be transformed into LOFT, creative industries, etc., whichcan prolong the life of these old industrial buildings.A necessary condition for the transformation of old industrial buildings is that theformer old industrial building structure is safe and reliable, ensuring the transformationto normal use.There exist some problems in current structural safety assessment system,and its evaluation methods are too extensive and simple. Based on the detection ofexisting buildings and combination of large numbers of successful transformation casestudies, this article tries to establish the old industrial building structure index systemfor safety assessments. Meanwhile, this paper uses artificial neural network theory,probability theory and statistical evaluation theory to re-establish the old industrialstructural safety assessment methods. Finally, with the new safety assessment method,block6in the east campus of Xi an University of architecture and technology is for casestudy, which is a successful application in practical engineering and software rating.Through the study of this subject, this paper has established an advanced structuralsafety assessment system for old industrial buildings assessment system in hope that itcan make a reference for the future assessment in old industrial structures.