Skip to Main Content
 

Global Search Box

 
 
 

ETD Abstract Container

Abstract Header

SELF-POWERED WIRELESS SENSORS WITH DUAL-MODALITY SENSING FOR INTERNET OF THINGS (IOT) APPLICATIONS

Wei, Ran
http://orcid.org/0000-0002-5981-9219
http://rave.ohiolink.edu/etdc/view?acc_num=case1589315291704576

Abstract Details

2020, Doctor of Philosophy, Case Western Reserve University, EECS - Electrical Engineering.
The emerging internet of things (IoT) is all about connecting machines and systems together through sensors and actuators. The meaningful information collected from the sensors can be processed timely and possible actions can be taken either by the actuator or human to enhance productivity, efficiency, and reliability. We will see IoT devices and embedded systems become more and more prevalent in our daily lives. One such area is the power generation industry. Not surprisingly, the power generation industry has been one of the early adopters of IoT. The expensive electricity generator is embedded with massive internet-connected sensors for its operation condition monitor to prevent potential catastrophic failure. This dissertation presents the development of a low-cost, easy-to-deploy, self-powered wireless sensor nodes and integrates them with existing solutions into wireless sensor networks to monitor temperature and vibration information of the instruments in a power plant (e.g., motor, pump, etc.). Each sensor node includes: (a) energy harvesting components (which convert the vibrational motion of the instruments into electricity) made by a piezoelectric material; (b) a power management application-specific integrated circuit (ASIC) for AC to DC, DC to DC and voltage regulation; (c) the multi-physical sensor components, including temperature and vibration sensors; (d) an ultralow-power wireless communication unit using ZigBee protocol. We design a customer-specific printed circuit board (PCB) to integrate the sensor node components and a robust package to protect the sensor node for field deployment and harsh environment applications. The sensors communicate with a powered gateway unit intermittently while constantly harvesting and storing energy, maintaining always-on operation without external energy input. Attribute reporting allows the system to transmit data in a more intelligent and energy-efficient way. These sensor nodes can be installed by the end-users (requiring no professional training) in a non-intrusive way by retrofitting or mounting onto an equipment’s surface using strong magnetic tape. The proposed wireless sensors can be implemented in any industrial power plant and require minimal maintenance while providing continuous, long-term monitoring of equipment with the real-time readout of temperature and vibration, and possibly other parameters of interest.
Philip Feng (Advisor)
Soumyajit Mandal (Committee Member)
Kenneth Loparo (Committee Member)
Xiong Yu (Committee Member)
154 p.
Electrical Engineering

Recommended Citations

Citations

  • Wei, R. (2020). SELF-POWERED WIRELESS SENSORS WITH DUAL-MODALITY SENSING FOR INTERNET OF THINGS (IOT) APPLICATIONS [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1589315291704576

    APA Style (7th edition)

  • Wei, Ran. SELF-POWERED WIRELESS SENSORS WITH DUAL-MODALITY SENSING FOR INTERNET OF THINGS (IOT) APPLICATIONS. 2020. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1589315291704576.

    MLA Style (8th edition)

  • Wei, Ran. "SELF-POWERED WIRELESS SENSORS WITH DUAL-MODALITY SENSING FOR INTERNET OF THINGS (IOT) APPLICATIONS." Doctoral dissertation, Case Western Reserve University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1589315291704576

    Chicago Manual of Style (17th edition)

case1589315291704576
102
© 2020, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.