The deployment cost of the structural health monitoring (SHM) system is the major argument against the more widespread use of the structural health monitoring techniques. Optimization of sensor pla...

Optimization of sensor placement for structural health monitoring: a review:

Structural health monitoring plays an increasingly significant role in detecting damages for large and complex structures to ensure their serviceability and sustainability. Optimal sensor placement...

Computational methodologies for optimal sensor placement in structural health monitoring: A review:

Observation of wind fields over different terrains and wind effects on a super-tall building during a severe typhoon and verification of wind tunnel predictions

Summary

Optimal sensor placement technique plays a key role in the design of an effective structural health monitoring system. Recent advances in sensing technologies have also promoted using multiaxial sensors to perform efficiently and economically monitoring for civil engineering structures. However, the available evaluation criteria for the optimal sensor placement can only guarantee that the optimization is conducted in a single structural direction but not in multi-dimension space, which may result in the non-optimal placement of multiaxial sensors. To tackle this issue thoroughly, a new multiaxial optimal criterion termed as the triaxial modal assurance criterion is developed by taking account into three translational degrees of freedom as a single unit in the Fisher information matrix. Afterwards, a novel distributed wolf algorithm is proposed to improve the optimization performance in identifying the best sensor locations. The dual-structure coding method is improved and adopted to represent the solution. The shuffling strategy is proposed to enhance the searching capability and convergence performance. The attacking process is also modified to prevent the algorithm from being trapped in a local minimum. The effectiveness of the proposed scheme is investigated by the benchmark structure developed by the University of Central Florida, USA. The results clearly demonstrate that the proposed distributed wolf algorithm outperforms the existing algorithm in its global optimization capability. Copyright © 2015 John Wiley & Sons, Ltd.

Multiaxial sensor placement optimization in structural health monitoring using distributed wolf algorithm: Multiaxial Sensor Placement Optimization in SHM Using DWA

Summary

The extensive utilization of wireless sensor networks (WSNs) in SHM systems promotes optimal wireless sensor placement (OWSP) as an important topic. In this paper, the theoretical framework of OWSP in SHM is presented. Within the framework, the energy-aware wireless sensor placement is formulated as a discrete optimization problem in which the linear independence of identified mode shapes is achieved, the connectivity of the WSN is guaranteed, and the energy efficiency of an entire WSN is pursued. A hybrid discrete firefly algorithm (HDFA) is developed to solve this complex optimization problem. The one-dimensional binary coding system and the Hamming distance are adopted to characterize the fireflies so that the distinguished optimization mechanism in the basic FA can be applied to the OWSP problem. A hybrid movement scheme including directive movement and nondirective movement is proposed to improve the convergence speed, enhance the capability of searching global optimization, and avoid falling into the local optimum. The HDFA is applied to a long-span suspension bridge for verifications, and two other optimization methods, a simple discrete FA and a simple genetic algorithm, are also employed for facilitating comparisons. The results demonstrate that the HDFA can extract an optimal wireless sensor configuration with highly linear independence of identified mode shapes and outstanding WSN performance. And the combination of directive movement and nondirective movement proves that the HDFA can outperform the simple discrete FA and the simple genetic algorithm in terms of computational efficiency and superiority of results. Copyright © 2014 John Wiley & Sons, Ltd.

Energy-aware wireless sensor placement in structural health monitoring using hybrid discrete firefly algorithm

SUMMARY

Research on optimal sensor placement has become a very important topic because of the need to obtain effective testing results with limited testing resources in modal identification and structural health monitoring. An integer-encoding multi-swarm particle swarm optimisation (IMPSO) algorithm is proposed to place multiaxial sensors optimally on large structures for modal identification. The concepts of grade evaluation and migration strategy and the mutation operators of genetic algorithm are introduced into the integer-encoding particle swarm optimisation algorithm. Three different fitness functions for optimal multiaxial sensor placement (OMSP) are investigated. The second fitness function considers spatial correlation based on Moran's I to solve the information redundancy of multiaxial sensor placement, whereas the other two functions evolve from the existing methods for comparison with the second fitness function. The novel algorithm and three fitness functions are further applied to the Laxiwa arch dam for verifications. The results show that the proposed IMPSO outperforms two existing algorithms in its global optimisation capability. The results also prove that the second fitness function has advantages in sensor distribution and ensuring the well-conditioned information matrix and observability of multidimensional modal shapes. The multiaxial sensor placement scheme determined by the proposed method is applied to the modal test of the Laxiwa arch dam under simulative ambient excitation. The results show that the scheme determined by the second fitness function can identify the frequencies and multidimensional mode shapes accurately, indicating that this method may be used to provide guidance for OMSP in various types of large structures. Copyright © 2013 John Wiley & Sons, Ltd.

Optimal multiaxial sensor placement for modal identification of large structures

The invention relates to an at-sea wind generation unit foundation formed by a barrel type foundation and a mooring rope anchor, which is composed of the barrel type foundation, a connection tower barrel, a cable rope and a suction anchor, the barrel type foundation is a steel cylinder structure which is provided with a sealing top cover, the connection tower barrel is a steel conical cylinder shape structure, the connection tower barrel and the barrel type foundation are fixed by welding and are reinforced by a rib plate, and the connection tower barrel and a connection tower barrel tower barrel are fixedly connected by a flange, and two ends of the cable rope are respectively fixed with the connection tower barrel and the suction anchor by welding. The at-sea wind generation unit foundation has the advantages that: the structure is simple, the construction is convenient, the work amount is low and the structure stress is rational. The barrel type foundation of the foundation self-floats to the construction position at sea by traction, the transportation cost can be reduced; a large hoisting ship does not need to be placed at seabed or pile driving construction at sea is not needed, the barrel type foundation can be recycled, thereby being environmental-protection; the load of the foundation structure, especially for moment load, can be effectively dispersed by the suction anchor, so as to improve the antidumping capacity of the single barrel type foundation.

At-sea wind generation unit foundation formed by barrel type foundation and mooring rope anchor

The capacity and size of hydro-generator units are increasing with the rapid development of hydroelectric enterprises, and the vibration of the powerhouse structure has increasingly become a major problem. Field testing is an important method for research on dynamic identification and vibration mechanisms. Research on optimal sensor placement has become a very important topic due to the need to obtain effective testing information from limited test resources. To overcome inadequacies of the present methods, this paper puts forward the triaxial effective independence driving-point residue (EfI3-DPR3) method for optimal sensor placement. The EfI3-DPR3 method can incorporate both the maximum triaxial modal kinetic energy and linear independence of the triaxial target modes at the selected nodes. It was applied to the optimal placement of triaxial sensors for vibration testing in a hydropower house, and satisfactory results were obtained. This method can provide some guidance for optimal placement of triaxial sensors of underground powerhouses.

Optimal sensor placement in hydropower house based on improved triaxial effective independence method

To scientifically and reasonably evaluate the influence of dangerous goods anchorage on bridge safety, we used the quantitative risk assessment (QRA) method to investigate the external safety distance between anchorage and bridge. The accident consequence and frequency are analyzed and calculated qu 

/pdf/research-on-the-external-safety-distance-between-dangerous-1w1gbr4t.pdf

Research on the External Safety Distance between Dangerous Goods Anchorage and Bridge in Inland River

According to the current situation of domestic transportation, this paper identifies and analyzes the characteristics and causes of accidents in ro-ro operation of dangerous goods in port. Combined with the quantitative risk assessment of accident consequences, this paper emphatically analyzes mutual safety influence with the surrounding environment. Based on that, safety design for dangerous goods ro-ro terminal engineering is demanded. The research results may serve as a reference for improving the inherent safety of dangerous goods ro-ro terminal engineering.

/pdf/study-on-safety-design-for-port-dangerous-goods-ro-ro-3iwn6953.pdf

Study on Safety Design for Port Dangerous Goods Ro-Ro Terminal Engineering

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