bullet Sensors & Transducers Journal

    (ISSN: 2306-8515, e-ISSN 1726-5479)


2013 Global Impact Factor


2008 e-Impact Factor

25 Top Downloaded Articles

Best Selling Articles 2012

Journal Subscription 2014

Editorial Calendar

Submit an Article

Editorial Board

Current Issue

S&T journal's cover

Sensors & Transducers Journal 2011

Sensors & Transducers Journal 2010

Sensors & Transducers Journal 2009

Sensors & Transducers Journal 2008

Sensors & Transducers Journal 2007

2000-2002 S&T e-Digest Contents

2003 S&T e-Digest Contents

2004 S&T e-Digest Contents

2005 S&T e-Digest Contents

2006 S&T e-Digest Contents


Best Articles 2011




Vol. 172, Issue 6, June 2014, pp. 124-129




Research on Health State Perception Algorithm of Mining Equipment Based on Frequency Closeness

1 Gang Wang, 1 Yanjun Hu,2 Guoqing Ji

1 The Engineering Research Centre of Perception Mine, China university of Mine & Technology, Xuzhou, 221008, China
2 Department of Aviation Ammunition, Air Force Logistics College, Xuzhou, China, 221006
1 Tel.: 051683899723, fax: 051683899597

E-mail: wgcumt@yeah.net


Received: 16 April 2014 /Accepted: 30 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems


Abstract: The health state perception of mining equipment is intended to have an online real- time knowledge and analysis of the running conditions of large mining equipments. Due to its unknown failure mode, a challenge was raised to the traditional fault diagnosis of mining equipments. A health state perception algorithm of mining equipment was introduced in this paper, and through continuous sampling of the machine vibration data, the time-series data set was set up; subsequently, the mode set based on the frequency closeness was constructed by the d neighborhood method combined with the TSDM algorithm, thus the forecast method on the basis of the dual mode set was eventually formed. In the calculation of the frequency closeness, the Goertzel algorithm was introduced to effectively decrease the computation amount. It was indicated through the simulation test on the vibration data of the drum shaft base that the health state of the device could be effectively distinguished. The algorithm has been successfully applied to equipment monitoring in the Huoer Xinhe Coal Mine of Shanxi Coal Imp&Exp. Group Co., Ltd.


Keywords: Mining equipment, The dual mode set, Health state perception, Time-series data mining, Frequency closeness.


Acrobat reader logo Click <here> or title of paper to download the full pages article in pdf format



Subscribe the full-page Sensors & Transducers journal in print (paper) or pdf formats

(shipping cost by standard mail for paper version is included)

(25 % discount for IFSA Members)




Alternatively we accept a money transfer to our bank account. Please contact for details: sales@sensorsportal.com



Download <here> the Library Journal Recommendation Form






1999 - 2014 Copyright , International Frequency Sensor Association (IFSA) Publishing, S.L. All Rights Reserved.

Home - News - Links - Archives - Tools - Voltage-to-Frequency Converters - Standardization - Patents - Marketplace - Projects - Wish List - e-Shop - Sensor Jobs - Membership - Videos - Publishing - Site Map - Subscribe - Search

 Members Area -Sensors Portal -Training Courses - S&T Digest - For advertisers - Bookstore - Forums - Polls - Submit Press Release - Submit White Paper - Testimonies - Twitter - Facebook - LinkedIn