Reaserch On The Hydraulic Structure Damage Diagnosis Based On The Machine Learning And Modal Parameter Identification Theory

The structural damage diagnosis based on the modal parameter identification is one of issues nowadays in hydraulic structure. The hydraulic structure in the actual operations will be to some extent damaged caused by the design, construction, and the other defects or the load in excess of the design and the sudden powerful external load (such as earthquake, etc.). After happening in a certain degree, the structure damage will have a bad effect on the load capacity and durability greatly or even cause the serious accidents. Thus, it caused not only the significant casualties and economic losses but also a very bad social influence. Therefore, in order to ensure the structural safety, integrity and durability of the structure, some effective measures should be taken to fulfill the health diagnosis. Some conventional structural damage diagnostic methods, due to its own shortcomings, are not fit for the hydropower project. Whereas the response of the structure is easy to be gained under flow-induced vibration and has no negative impacts on the structure, it is no doubt that the modal parameter identification in the use of flow-induced vibration is a good method with the help of the machine learning theory. With the theory of the machine learning and the modal parameter identification and diagnostic methods under flow-induced vibration hydropower structure taken into research, the paper involves the following major research results of innovations:(1) It puts forward the modal parameter identification methods based on band-pass filter and discharge vibration, i.e., according to the analysis of the structural characteristics and the natural frequency, the signals are preprocessed by the band-pass filter. After extracted the interesting signals, the time domain method is used to identify the modal parameter. The results show that the methods can efficiently identify the structure natural frequency in the vibration on the discharge.(2) The genetic algorithm is applied in the modal parameters identification of the hydraulic structure, considering its global optimization. The genetic identification method used in hydraulic structure modal parameters is come up with. Because the measurement noise is taken into the research, not only is the identification accuracy of natural frequencies improved, but also the damping ratio's identification accuracy does to a certain extent. Finally, the result shows that the efficiency of the structure's natural frequency and damping ration is tested.(3) The damage identification method is proposed based on the machine learning theory and modal analysis of the guide wall structural. On the basis of the modal parameters identification, the coupling dynamic characteristics of the structure are calculated by the finite element method so as to construct the sample of the Support Vector Machine (SVM). The damage diagnoses method including the damage position and based on the establishment of Support Vector Machine (SVM) and the damage ration. That is to say, the Support Vector Machine can ensure the global optimal solution in the small sample of events through its quadratic optimization problem solved. It overcomes such the shortcomings caused by the artificial neural network methods as the difficulties in defining the network structure, the over fitting, under fitting and local minimum. Instead of the traditional support vector machines which use quadratic programming method, least-squares linear system is used as the loss function. Thus the problems such as damage positioning and damage degrees are solved successfully in the discharge structure (especially the underwater part).(4) Some of the main advantages of the damage diagnoses method, based on the discharge vibration and parameter identification, over other ones is that it is effectively helpful to save resources and get reliable recognition results. The paper first proposes damage diagnosis method based on the dynamic parameters identification and applies it to the hydraulic structure. Taking the three cross crack in Qing Tongxia as the research object and making the comprehensive analysis of signal collecting, modal identification and the finite element calculation, it concludes that the cross crack is 22m. Finally, the analysis of the safety is performed after the structure damages occur.