Study On Application Of Cloud Computing In Structural Health Monitoring Of Things System

Structural health monitoring (SHM) system is an important measure toguarantee the safety of major engineering structures. It’s really of greatsignificance for the safety and the normal exertion of the city’s function and theeconomic and social sustainable development. The combination of SHM andInternet of Things (IoT) is an inevitable requirement of the construction of adigitized city. It can improve the level of monitoring and the degree ofintelligence in SHM system, and make SHM play a more important role. Cloudcomputing technology is a key support for the intelligent and efficientmagnanimity sense data processing in the IoT. It is an important researchdirection to apply the IoT and cloud computing technology to the field of SHM.In order to achieve IoT applications in the field of structural healthmonitoring, according to the requirements of SHM, this paper combined the IoTtechnology and cloud computing technology with it, and presented an overallscheme of structural health monitoring of Things. Considering cloud computingsupport for the system, it also analysed the parallelism of a series of tasks ofstructural health monitoring, such as acceleration response signal processing.Then, it developed a concept design of computing and storage in structural healthmonitoring cloud by making use of the parallelism analysis results. In order toverify the analysis of the application of cloud computing, it simulated thedistributed computing of ITD method modal parameter identification task byusing MATLAB. This paper mainly contains the following three points.It presented an overall scheme of structural health monitoring of Things.Basesd on the functional requirement, it analysed different sub-layers’ conceptdesigns and designed the architecture of management system for structural healthmonitoring of Things system in which C/S and B/S are combined.It analysed and got the parallelism analysis results of these tasks, such as,modal parameter identification, damage identification, model updating and safetyassessment of structural health monitoring based on the acceleration response.The decomposition of related tasks, the strategy of calculation and storage, andthe applicability of distributed computing were analysed. It developed a conceptdesign of computing and storage in structural health monitoring cloud. Inaddition, as to longitudinal data partitioning strategies, it exemplified theintegration and migration of cloud computing and storage using task of ITDmodal parameter identification and finit element model updating.It simulated the distributed computing of ITD method modal parameter identification task by using MATLAB. The simulation involved three kinds ofparallel structure: pmode, parfor, SPMD including five programs. It conducted acomparative analysis of stand-alone serial and stand-alone parallel computing.The results indicated that the simulation improves computational efficiency, andthe communication cost could not be ignored. Besides, it analysed the differenceof distributed computing between the simulation and the actual cloud, thedistributed computing in cloud are more Reliable.