Trans. Nonferrous Met. Soc. China 24(2014) 3666−3673 Short-term warning and integrity monitoring algorithm for coal mine shaft safety Jian WANG 1,2 , Xing-long TAN 1,2 , Hou-zeng HAN 1,2 , T. B. AFENI 3 1. National Administration of Surveying, Mapping and Geoinformation (NASG) Key Laboratory for Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China; 2. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China 3. School of Mining Engineering, University of the Witwatersrand, Johannesburg 2000, South Africa Received 10 July 2013; accepted 21 January 2014 Abstract: A new short-term warning and integrity monitoring algorithm was proposed for coal mine shaft safety. The Kalman filter (KF) model was used to extract real global positioning system (GPS) kinematic deformation information. The short-term warning model was built by using the two-side cumulative sum (CUSUM) test, which further improves the warning system reliability. Availability (the minimum warning deformation, MWD), false alarm rate (the average run length, ARL), missed rate (the warning delay, WD) and the relationships among them were analyzed and the method choosing warning parameters is given. A test of a deformation simulation platform shows that the warning algorithm can be effectively used for steep deformation warning. A field experiment of the Malan mine shaft in Shanxi coal area illustrates that the proposed algorithm can detect small dynamic changes and the corresponding occurring time. At given warning thresholds (MWD is 15 mm and ARL is 1000)， the detected deformations of two consecutive days’ deformation sequences with the algorithm occur at the 705th epoch (705 s) and the 517th epoch (517 s), respectively. Key words: coal mine shaft; deformation; cumulative sum; short-term warning; Kalman filter; integrity monitoring 1 Introduction With the wide use of new materials, the development of new construction techniques and design technology, more and more large-scale infrastructures are being built. However, large structures are susceptible to environmental loadings, including strong winds, earthquakes and mining [1,2]. Structural collapses will cause severe economic loss, therefore, the early warning system should be exploited to predict hazards [3]. The global positioning system(GPS) based monitoring scheme can provide real-time and high rate observations, it has been validated as an efficient tool for monitoring engineering structures such as tall buildings [4], long bridges [5] and mining deformation monitoring [6,7]. Coal mine shaft is one of the key parts in mines and the deformation of the shaft that is affected by the complex physical factors, geological factors, mechanic factors, etc., is the indication of the shaft safety [8]. It is very important to monitor the deformation of the coal mine shaft. However, systematic studies on coal mine shaft deformation monitoring and warning using GPS are seldom mentioned. Precise and continuous displacement measurement is critical for evaluating structure’s condition and generating warning in time. Significant work has been done to overcome the drawback of the inadequate accuracy of GPS. CHAN et al [9] presented an integrated GPS-accelerometer data processing technique, which can significantly enhance the measurement accuracy of the total displacement of a structure. SHAN et al [10] proposed an optimization model of the global navigation satellite system (GNSS)/PLs integration positioning system, which is helpful for improving the positioning performance in open-pit mine. A reliable independent component regression method was used to model dam deformation by DAI et al [11]. The Kalman filter model can process the deformation time series in real- time and obtain the optimal estimation [12], which is Foundation item: Projects (2013RC16, 2012LWB28) supported by the Fundamental Research Funds for the Central Universities, China; Project (NCET-13-1019) supported by the Program for New Century Excellent Talents in University, China Corresponding author: Jian WANG; Tel: +86-516-83591306; E-mail: wjian@cumt.edu.cn DOI: 10.1016/S1003-6326(14)63513-5