Published August 2014 | Version v1
Miscellaneous

Feasibility of Johnson Noise Thermometry based on Digital Signal Processing Techniques

  • 1. KAERI, Daejeon (Korea, Republic of)
  • 2. Chungnam National University, Daejeon (Korea, Republic of)

Description

This paper presents an implementation strategy of noise thermometry based on a digital signal processing technique and demonstrates its feasibilities. A key factor in its development is how to extract the small thermal noise signal from other noises, for example, random noise from amplifiers and continuous electromagnetic interference from the environment. The proposed system consists of two identical amplifiers and uses a cross correlation function to cancel the random noise of the amplifiers. Then, the external interference noises are eliminated by discriminating the difference in the peaks between the thermal signal and external noise. The gain of the amplifiers is estimated by injecting an already known pilot signal. The experimental simulation results of signal processing methods have demonstrated that the proposed approach is an effective method in eliminating an external noise signal and performing gain correction for development of the thermometry

Part of:
ISOFIC/ISSNP 2014: International Symposium on Future I and C for Nuclear Power Plants/International Symposium on Symbiotic Nuclear Power Systems

Additional details

Publishing Information

Publisher
KNS
Imprint Place
Daejeon (Korea, Republic of)
Imprint Title
Proceedings of the ISOFIC/ISSNP 2014
Imprint Pagination
[1 CD-ROM]
Journal Page Range
[6 p.]

Conference

Title
ISOFIC/ISSNP 2014
Dates
24-28 Aug 2014
Place
Jeju (Korea, Republic of)

INIS

Country of Publication
Korea, Republic of
Country of Input or Organization
Korea, Republic of
INIS RN
46074566
Subject category
S22: GENERAL STUDIES OF NUCLEAR REACTORS;
Resource subtype / Literary indicator
Conference, Non-conventional Literature
Descriptors DEI
COMPUTERIZED SIMULATION; CORRELATIONS; FEASIBILITY STUDIES; NOISE; SIGNALS
Descriptors DEC
SIMULATION

Optional Information

Notes
7 refs, 7 figs, 2 tabs