A Power Supply Technology for a Low-Power Online Monitoring Sensor Based on Electric Field Induction.

electric field induction low power online monitoring sensor power supply technology

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
10 May 2019
Historique:
received: 31 03 2019
revised: 05 05 2019
accepted: 07 05 2019
entrez: 15 5 2019
pubmed: 15 5 2019
medline: 15 5 2019
Statut: epublish

Résumé

In order to provide a safe and stable power supply for low-power online monitoring sensors of transmission lines, a method of harvesting space electric field energy by using the impedance conversion characteristics of the transformer and the reactive compensation characteristics of the capacitor is proposed. The method effectively solves the key problem that the power of energy harvesting based on electric field induction is limited by the transformer excitation reactance and is difficult to upgrade. In this paper, the principle of power supply technology based on electric field induction is described in detail, and the influencing factors such as the wire erection mode, polar plate installation position, and capacitance compensation characteristics are simulated and tested. The test results show that when the power supply voltage is 50 kV, the stray capacitance is 14 pF, the compensation capacitance is 0.86 nF, and the load resistance is 1 kΩ, the energy-harvesting power is 340 mW. Finally, the power supply circuit of a drive-away-birds apparatus is designed, which shows that it can provide a stable and reliable power supply for online monitoring sensors.

Identifiants

pubmed: 31083320
pii: s19092169
doi: 10.3390/s19092169
pmc: PMC6539729
pii:
doi:

Types de publication

Journal Article

Langues

eng

Auteurs

Zong Li (Z)

Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China. z-li16@mails.tsinghua.edu.cn.

Hongwei Mei (H)

Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China. mei.hongwei@sz.tsinghua.edu.cn.

Liming Wang (L)

Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China. wanglm@sz.tsinghua.edu.cn.

Classifications MeSH