Bin Ma
Tianjin University
6 Papers
Bin Ma is an academic researcher from Tianjin University. The author has contributed to research in topics: Fitness function & Noise (signal processing). The author has an hindex of 6, co-authored 6 publications.
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Papers
Optimal multiaxial sensor placement for modal identification of large structures
TL;DR: The results show that the proposed IMPSO outperforms two existing algorithms in its global optimisation capability and proves that the second fitness function has advantages in sensor distribution and ensuring the well‐conditioned information matrix and observability of multidimensional modal shapes.
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Optimal sensor placement for large structures using the nearest neighbour index and a hybrid swarm intelligence algorithm
TL;DR: A novel fitness function derived from the nearest neighbour index is proposed to overcome the drawbacks of the effective independence method for OSP for large structures and outperforms a genetic algorithm with decimal two-dimension array encoding and DPSO in the capability of global optimization.
52
Signal de-noising method for vibration signal of flood discharge structure based on combined wavelet and EMD
TL;DR: In this article, a new de-noising method combining Wavelet threshold and empirical mode decomposition (WTEMD) was proposed to improve the precision of denoising performance for vibration signal of flood discharge structure in low signal to noise ratio (SNR).
17
Intelligent damage identification method for large structures based on strain modal parameters
Longjun He,Jijian Lian,Bin Ma +2 more
TL;DR: In this article, the authors proposed a new damage detection method that employs the real encoding multi-swarm particle swarm optimization algorithm and fitness functions evolved from strain modes to find the optimal match between measured and simulated modal parameters and to determine the actual condition of structures.
Operation conditions monitoring of flood discharge structure based on variance dedication rate and permutation entropy
TL;DR: Comparison results show that VDR-PE method can be applied to detect the dynamic changes and reveal the vibration characteristic of the overall structure accurately, which provides a new direction for the online monitoring of flood discharge structure.