Research on the Signal Reconstruction of the Phased Array Structural Health Monitoring Based Using the Basis Pursuit Algorithm

The signal processing problem has become increasingly complex and demand high acquisition system,this paper proposes a new method to reconstruct the structure phased array structural health monitoring signal.The method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array signals.According to the principles of the compressive sensing and signal processing method,non-sparse ultrasonic signals are converted to sparse signals by using sparse transform.The sparse coefficients are obtained by sparse decomposition of the original signal,and then the observation matrix is constructed according to the corresponding sparse coefficients.Finally,the original signal is reconstructed by using basis pursuit algorithm,and error analysis is carried on.Experimental research analysis shows that the signal reconstruction method can reduce the signal complexity and required the space efficiently.

Impact Force Magnitude and Location Recognition of Composite Materials

In order to identify the location and magnitude of the impact force accurately,determine the damage range of the structure and accelerate the health monitoring of key components of the composite,this paper studies the location and magnitude of the impact force of composite plates by an inverse method.Firstly,a PZT sensor mounted on the material plate is used to collect the response signal generated by the impact force,which is from several impact locations,and establish transfer functions between the impact location and the PZT sensor.Secondly,this paper applies several forces to any location on the material plate,and collects the corresponding response signals,and reconstructs the impact force of several locations in turn.Finally,according to the reconstruction result of each location,the correct impact location is identified.Then,an improved regularization method is used to optimize the reconstructed impact force and accurate the magnitude of the impact force.The comparison experiments prove that the recognition error of this method is smaller.

Impact Damage Identification for Composite Material Based on Transmissibility Function and OS-ELM Algorithm

A method is proposed based on the transmissibility function and the OnlineSequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to theimpact damage of composite materials. First of all, the transmissibility functions of theundamaged signals and the damage signals at different points are calculated. Secondly,the difference between them is taken as the damage index. Finally, principal componentanalysis (PCA) is used to reduce the noise feature. And then, input to the online sequencelimit learning neural network classification to identify damage and confirm the damagelocation. Taking the amplitude of the transmissibility function instead of the accelerationresponse as the signal analysis for structural damage identification cannot be influencedby the excitation amplitude. The OS-ELM algorithm is based on the ELM (ExtremeLearning Machine) algorithm, in-creased training speed also increases the recognitionaccuracy. Experiment in the epoxy board shows that the method can effectively identifythe structural damage accurately.