Paper: Earthquake Prediction Research


Up-to-Date Report on the Early Detection of Omens of Anomalies in Monitoring Power Plant Equipment
(Anomalous phenomena detected just before earthquakes)

Takumi Yoshioka (Mado-Planning Co.), Hiroaki Kawai (Hokkaido Institute of Technology)
presented at Japan Society of Mechanical Engineers (JSME), 15th Symposium of Power and Energy Technologies, C102, Jun. 20, 2010 (in Japanese)
 
Posted on Mar. 9, 2015
( buttons guide you to the pages written in Japanese.

Editor's Note (Toru Nakagawa, Mar. 8, 2015) 

This paper was presented at a symposium of Japanese Society of Mechanical Engineers (JSME) in June 2010.   The paper describes the intention and results of Professor Yoshioka's original research.

He developed a software system for monitoring the operation of electric power generators in thermal and nuclear power plants and for detecting omens of anomalies and failures for the purpose of maintenance and smooth operation of the equipment.   Introducing knowhows of power plant engineers, he visualized the monitoring data and developed methods for estimating any failure/anomaly of the equipment and its operation, and examined the accuracy and effectiveness of the prediction.  

In such data, he has found effects of earthquakes vividly, he says.  The data monitored every minute show the effect of instantaneous jumping of the generator due to the S-wave of an earthquake, and after the quake the data show unstable increase of wattless currents due to some off-alignment of the generator axes.   In addition, since 30 minutes before the earthquake there appeared anomalous behavior in the data, just like the generator is roaring.   It is not caused by earthquake vibration but by some electromagnetic effect, he says.  

This paper was presented about a year before the March 11 Great Earthquake, and clearly expressed the possibility of predicting an earthquake just beforehand (i.e., 30 minutes beforehand in this case) by monitoring the operation behavior of power generators.   With this paper, we can understand the author's intention in his original research on the development of the power-generator monitoring system and his process of shifting later to the research of earthquake prediction. 

The paper is posted in HTML and in PDF in Japanese.

As you see in the PDF file, the original paper in Japanese contains English translation of the title, abstract, and captions of tables and figures.  But the texts, tables, and figures were not translated in English so far. 

As an academic document, I am citing the title and abstract of the paper in the original English translation (see below).

For introducing the present work by Yoshioka and Kawai to international academic community, I feel it necessary for us to translate the full paper into English, with some revision of the title and abstract as well.  Please give us, the authors and the editor, some more time for English translation.  The title of the present page reflect the temporary revision in English translation. 

 


Abstract  (in the original translation)

The latest report on the early-detection technique of omens of abnormal conditions
in the facilities of the power station

Takumi YOSHIOKA, MADO PLANNING, Chuou-ku Ohdori Higashi 11-24-604, Sapporo
Hiroaki KAWAI, Hokkaido Inst. of Tech., Teine-ku Maeda 7-15-4-1, Sapporo,

presented at Japan Society of Mechanical Engineers (JSME),
15th Symposium of Power and Energy Technologies, C102, Jun. 20, 2010 (in Japanese)

Abstract

This report introduces the operation examples of the real-time online data collection analysis system, which was developed originally. Some extremely effective functions included in this system, that is, double watch of central control room equipment, calibration watch of equipment set up on central post and each site, tuning of various static characteristics and dynamic characteristics, integrated checking of efficiency of system, and etc. were described with the operation case. In addition, possibility of application of this system to power plants, for instance, earlier detection of broken behavior change, trouble sign, and others were referred.

Key Words: Power station, Power plant, Performance diagnostics

 


 

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Last updated on Mar. 9, 2015.     Access point:  Editor: nakagawa@ogu.ac.jp