Network End-to-End Data Link Evaluation System Transceiver Health Monitoring

2016 ◽  
Author(s):  
2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Chengyin Liu ◽  
Jun Teng ◽  
Ning Wu

Structural strain under external environmental loads is one of the main monitoring parameters in structural health monitoring or dynamic tests. This paper presents a wireless strain sensor network (WSSN) design for monitoring structural dynamic strain field. A precision strain sensor board is developed and integrated with the IRIS mote hardware/software platform for multichannel strain gauge signal conditioning and wireless monitoring. Measurement results confirm the sensor’s functionality regarding its static and dynamic characterization. Furthermore, in order to verify the functionality of the designed wireless strain sensor for dynamic strain monitoring, a cluster-star network evaluation system is developed for strain modal testing on an experimental steel truss structure. Test results show very good agreement with the finite element (FE) simulations. This paper demonstrates the feasibility of the proposed WSSN for large structural dynamic strain monitoring.


1978 ◽  
Vol 7 (1) ◽  
pp. 69-77
Author(s):  
Trevor G. S. Paine

The Canadian Government, through its Department of Transport (Transport Canada) Air Traffic Services organization is responsible for a variety of ATC programs of which the Simulation and Evaluation program is fast attaining its potential as an experimental tool. Simulation and Evaluation has been a way of life in aviation for many many years; in ATC however, it is perhaps only in the last ten years that computer-aided simulators have become an essential part of the service. Since commissioning the Canadian ATC Simulation and Evaluation System in 1976, not only has it been effective and reliable in providing objective experimental results, it has also provided economic benefits to our operations. As a training aid it is yet to attain its full worth. Being the newest of ATC Simulation Systems, the Canadian system incorporates several computers, an integrated communications control capability, an elaborate software package, modern digital radar displays and data link features.


Author(s):  
Mohammad Hanan Bhat

: Plant health monitoring has been a significant field of research since a very long time. The scope of this research work conducted lies in the vast domain of plant pathology with its applications extending in the field of agriculture production monitoring to forest health monitoring. It deals with the data collection techniques based on IOT, pre-processing and post-processing of Image dataset and identification of disease using deep learning model. Therefore, providing a multi-modal end-to-end approach for plant health monitoring. This paper reviews the various methods used for monitoring plant health remotely in a non-invasive manner. An end-to-end low cost framework has been proposed for monitoring plant health by using IOT based data collection methods and cloud computing for a single-point-of-contact for the data storage and processing. The cloud agent gateway connects the devices and collects the data from sensors to ensure a single source of truth. Further, the deep learning computational infrastructure provided by the public cloud infrastructure is exploited to train the image dataset and derive the plant health status


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