Real-time system condition monitoring using wireless sensors

Kwan, Chiman; Ayhan, Bulent; Yin, Jing; Liu, X.; Ballal, Prasanna; Athamneh, Abedalgany; Ramani, A.; Lee, W.; Lewis, Frank L.

doi:10.1109/aero.2009.4839681

Cited by 15 publications

(2 citation statements)

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“…The idea is based on history of finite length to establish an accurate reflection of the system's internal operating rules that form the mathematical model. For any given observation time t , the set t X is to describe the past incidents, which could form the AR model of the system using the following equation [10]:…”

Section: B Ar Model Based Network Controlmentioning

confidence: 99%

The diagnosis of wired network malfunctions based on big data and traffic prediction: An overview

Gao¹,

Ao²,

Wang³

et al. 2015

2015 4th International Conference on Computer Science and Network Technology (ICCSNT)

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The increasing demand on higher transmission speed and shorter delay in wired networks becomes critical in recent communication networks. However, the capacity of transmission link is limited by the method of transmission. In this paper, aiming at the situation of large scale networks, an overview of the network optimization based on big data and traffic prediction is given in our proposed work. In wired networks, how to make full use of the transmission bandwidth and provide more reliable QoS is in great demand. Based on the network topology in our facility, we make a summary of current diagnosis method of the network and then propose the future possible way to solve the network malfunction based on big data through network log and complex monitors, then we make an overview of the diagnosis method based on traffic prediction, which could effectively make full use of bandwidth and avoid collision of the network.

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Section: B Ar Model Based Network Controlmentioning

confidence: 99%

The diagnosis of wired network malfunctions based on big data and traffic prediction: An overview

Gao¹,

Ao²,

Wang³

et al. 2015

2015 4th International Conference on Computer Science and Network Technology (ICCSNT)

View full text Add to dashboard Cite

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“…16,17 Others adopt MCU and DSP to complete part of the Transmission Control Protocol/ Internet Protocol (TCP/IP) stack or through Wi-Fi and other chips to achieve network connection. [37][38][39][40][41] However, these methods are not suitable for the SRM monitoring system. In the work environment with severe electromagnetic interference (EMI), the network connection or data transmission of Wi-Fi, ZigBee and other wireless chips may be unstable.…”

Section: Introductionmentioning

confidence: 99%

Remote distributed monitoring system of switched reluctance motor

Cai

Wen-long

Zhang

2019

Measurement and Control

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The reliable operation, dynamic performance analysis and control strategy research of a switched reluctance motor (SRM) require an online monitoring system to display and record its operating status. However, due to the large amount of data, the nonlinear electromagnetic characteristics and the harsh working environment of SRM, it is very difficult to monitor a SRM's operation status in real time. In order to solve these problems, a new structure of the SRM monitoring system, which uses Digital Signal Processor (DSP) and the hardwired Transmission Control Protocol/Internet Protocol embedded Ethernet controller W5500, is presented in this paper. The W5500 and DSP's direct memory access modules are employed for data capture and transfer to reduce the digital signal processing workload. The digital signal processing program is implemented by the hybrid programming method, which shortens the filtering time. Consequently, the DSP has sufficient resources to acquire multiple signals with a high sampling frequency and can adopt a more complex filtering algorithm, which enhances the accuracy and real-time performance of the system. Moreover, the amplitude-frequency characteristics of signals are analyzed. Then, the detection circuits and finite impulse response filters are designed to achieve the targeted acquisition and filtering. Besides, the impact of harsh environment on the system is reduced by adjusting the data transmission modes according to different working conditions. As a result, the scope of application of the system has been extended. The proposed system has a novel structure and strong practicability, which exhibits great guiding significance for the development of a SRM.

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