China University Of Mining And Technology Research Articles

Longwall Mining Automation—The Shearer Positioning Methods between the Longwall Automation Steering Committee and China University of Mining and Technology

The shearer positioning method is of great significance to the automation of longwall mining. The research teams in the Longwall Automation Steering Committee (LASC) of Australia and China University of Mining and Technology (CUMT) have focused on shearer positioning and identified the shearer inertial navigation system, the measurement of longwall retreat and creep displacement, and the backward calibration of the shearer trajectory as three key technologies to obtain accurate shearer positioning information. In underground environments without GPS, due to the characteristics of inertial navigation system (INS) autonomous full-parameter navigation, shearer positioning based on INS is adopted by the LASC and CUMT, and error reduction algorithms are proposed to inhibit the rapid error accumulation of INS. In order to obtain the periodic calibration information when the shearer reaches the end of the longwall face, it is necessary to measure the retreat and creep displacements in order to back-correct the shearer trajectory. Finding a suitable measurement method for this task is challenging, especially in the presence of dust and moisture. The LASC used a scanning laser and FMR 250 microwave radar to measure these two displacements, while CUMT adopted an ultra-wideband (UWB) radar. In terms of the backward calibration method, minimum-variance fixed-interval smoothing (MFS) proposed by LASC and the global optimization model (GOM) for the shearer trajectory from CUMT are described in detail. The experiment demonstrates that the GOM outperforms MFS in terms of accuracy but requires more computational resources. Therefore, our next research objective is to develop an efficient and accurate algorithm for performing backward calibration on the shearer trajectory.

From Golden to Xuzhou: Teaching a graduate student workshop in China

In late spring 2019, eight staff members from the Colorado School of Mines (Mines) Arthur Lakes Library, in Golden, Colorado, visited the China University of Mining and Technology (CUMT) in Xuzhou, China. The trip was intended to develop a relationship between the two libraries and foster future partnerships. The visit, which centered around the Symposium on Mines-CUMT Library Collaboration, included presentations by Mines and CUMT staff, museum visits, cultural activities, and a full-day workshop for early career researchers.

A Novel Dual-Domain Filtering Method to Improve GNSS Performance Based on a Dynamic Model Constructed by TDCP

To overcome the strikes from the tremendous noise of pseudorange and the integer ambiguity of carrier phase observation, we developed a novel dual-domain filtering method that integrates the traditional observation- and an innovative position- domain filtering method. The novel method employed the conventional Hatch's smoother to improve the precision of pseudorange at the observation-domain filtering part. At the position- domain filtering part, the proposed method constructs an accurate dynamical model for KF (Kalman filter) or ARKF (adaptive-robust KF) that relies on the TDCP (time differential carrier phase) velocity measurement technology. To assess the effectiveness of the novel method, we compared it with other methods under various system integration by measured data from IGS (International GNSS Service) MGEX (Multi-GNSS Experiment) and dynamic data collected at CUMT (China University of Mining and Technology). The static numerical experiments obtained from IGS datasets show that the ARKF improves the precision of 60/84 and 55/84 situations' directions compared with the LS method based on OP (original pseudorange) and SP (smoothed pseudorange), respectively, and Hatch's smother improves the precision of all situations' directions. The experiment results prove that both types of observation- and position- domain filtering methods can improve positioning precision. Also, the novel dual-domain filtering improved the precision of 80/84 situations' directions compared with the LS method. Moreover, the dynamic experiment shows that the novel method can improve all of the situations' directions except the N (North) direction provided by KF base on SP under GC and U (Upon) direction provided by LS base on SP under GR. The average of improved accuracy is 0.212m, 0.346m, and 0.588m at the E (East), N, U direction and its corresponding average percentage of improved accuracy is 30.2%, 60.2%, and 26.7%, respectively, which proves the novel dual-domain filtering method provided the best performance among the tested algorithms.

Heading Estimation with Real-time Compensation Based on Kalman Filter Algorithm for an Indoor Positioning System

The problem of heading drift error using only low cost Micro-Electro-Mechanical (MEMS) Inertial-Measurement-Unit (IMU) has not been well solved. In this paper, a heading estimation method with real-time compensation based on Kalman filter has been proposed, abbreviated as KHD. For the KHD method, a unified heading error model is established for various predictable errors in magnetic compass for pedestrian navigation, and an effective method for solving the model parameters is proposed in the indoor environment with regular structure. In addition, error model parameters are solved by Kalman filtering algorithm with building geometry information in order to achieve real-time heading compensation. The experimental results show that the KHD method can not only effectively correct the original heading information, but also effectively inhibit the accumulation effect of positioning errors. The performance observed in a field experiment performed on the fourth floor of the School of Environmental Science and Spatial Informatics (SESSI) building on the China University of Mining and Technology (CUMT) campus confirms that apply KHD method to PDR(Pedestrian Dead Reckoning) algorithm can reliably achieve meter-level positioning using a low cost MEMS IMU only.

Analysis to Xuzhou aerosol optical characteristics with ground-based measurements by sun photometer

Atmospheric aerosols are fine particulate matters suspended in atmosphere, and vary in size distribution, geometrical shape, total column content, and chemical composition. The Aerosol Robotic Network (AERONET) comprised of hundreds of ground-based monitoring stations all over the world aims to measure regularly and continuously the aerosol optical properties, such as aerosol optical depth (AOD) and Angstrom exponent. AERONET has supported the international researches on global, regional and local atmospheric environment issues including aerosol pollution and haze episodes. However, the past researches on China aerosol issues were mainly related with Beijing-Tianjin-Hebei region, Yangtze River delta, and Cheng-Yu plain. It had been much ignored in the Huaihai economic zone, which is also densely populated and economically developed, locates in the north-to-south geographical transition zone of China. An AERONET station was established in 2013 in the Nahu campus of China University of Mining and Technology (CUMT), supported by the China MAESTRO (Mining Area Environment Synergic Observation Proving Ground) program, and a CE318 sun photometer was installed in this station to monitor continuously the characteristics of atmospheric aerosol variations in Xuzhou. The CE318 provides ground measurements on aerosol optical depth (AOD), Angstrom exponent, complex refractive index, single scatter albedo, and some other important aerosol parameters. In this paper, the AERONET CE318 measurements from July 2013 to April 2015 were systematically analyzed to reveal the daily, monthly, and yearly variations of atmospheric aerosols in Xuzhou. Referring to meteorological data including wind speed, relative humidity and total rainy days, the aerosol properties were analyzed with mathematical statistics and K -means cluster methods.

An Improved PDR/Magnetometer/Floor Map Integration Algorithm for Ubiquitous Positioning Using the Adaptive Unscented Kalman Filter

In this paper, a scheme is presented for fusing a foot-mounted Inertial Measurement Unit (IMU) and a floor map to provide ubiquitous positioning in a number of settings, such as in a supermarket as a shopping guide, in a fire emergency service for navigation, or with a hospital patient to be tracked. First, several Zero-Velocity Detection (ZDET) algorithms are compared and discussed when used in the static detection of a pedestrian. By introducing information on the Zero Velocity of the pedestrian, fused with a magnetometer measurement, an improved Pedestrian Dead Reckoning (PDR) model is developed to constrain the accumulating errors associated with the PDR positioning. Second, a Correlation Matching Algorithm based on map projection (CMAP) is presented, and a zone division of a floor map is demonstrated for fusion of the PDR algorithm. Finally, in order to use the dynamic characteristics of a pedestrian’s trajectory, the Adaptive Unscented Kalman Filter (A-UKF) is applied to tightly integrate the IMU, magnetometers and floor map for ubiquitous positioning. The results of a field experiment performed on the fourth floor of the School of Environmental Science and Spatial Informatics (SESSI) building on the China University of Mining and Technology (CUMT) campus confirm that the proposed scheme can reliably achieve meter-level positioning.

A Bluetooth/PDR Integration Algorithm for an Indoor Positioning System.

This paper proposes two schemes for indoor positioning by fusing Bluetooth beacons and a pedestrian dead reckoning (PDR) technique to provide meter-level positioning without additional infrastructure. As to the PDR approach, a more effective multi-threshold step detection algorithm is used to improve the positioning accuracy. According to pedestrians’ different walking patterns such as walking or running, this paper makes a comparative analysis of multiple step length calculation models to determine a linear computation model and the relevant parameters. In consideration of the deviation between the real heading and the value of the orientation sensor, a heading estimation method with real-time compensation is proposed, which is based on a Kalman filter with map geometry information. The corrected heading can inhibit the positioning error accumulation and improve the positioning accuracy of PDR. Moreover, this paper has implemented two positioning approaches integrated with Bluetooth and PDR. One is the PDR-based positioning method based on map matching and position correction through Bluetooth. There will not be too much calculation work or too high maintenance costs using this method. The other method is a fusion calculation method based on the pedestrians’ moving status (direct movement or making a turn) to determine adaptively the noise parameters in an Extended Kalman Filter (EKF) system. This method has worked very well in the elimination of various phenomena, including the “go and back” phenomenon caused by the instability of the Bluetooth-based positioning system and the “cross-wall” phenomenon due to the accumulative errors caused by the PDR algorithm. Experiments performed on the fourth floor of the School of Environmental Science and Spatial Informatics (SESSI) building in the China University of Mining and Technology (CUMT) campus showed that the proposed scheme can reliably achieve a 2-meter precision.

A floor-map-aided WiFi/pseudo-odometry integration algorithm for an indoor positioning system.

This paper proposes a scheme for indoor positioning by fusing floor map, WiFi and smartphone sensor data to provide meter-level positioning without additional infrastructure. A topology-constrained K nearest neighbor (KNN) algorithm based on a floor map layout provides the coordinates required to integrate WiFi data with pseudo-odometry (P-O) measurements simulated using a pedestrian dead reckoning (PDR) approach. One method of further improving the positioning accuracy is to use a more effective multi-threshold step detection algorithm, as proposed by the authors. The “go and back” phenomenon caused by incorrect matching of the reference points (RPs) of a WiFi algorithm is eliminated using an adaptive fading-factor-based extended Kalman filter (EKF), taking WiFi positioning coordinates, P-O measurements and fused heading angles as observations. The “cross-wall” problem is solved based on the development of a floor-map-aided particle filter algorithm by weighting the particles, thereby also eliminating the gross-error effects originating from WiFi or P-O measurements. The performance observed in a field experiment performed on the fourth floor of the School of Environmental Science and Spatial Informatics (SESSI) building on the China University of Mining and Technology (CUMT) campus confirms that the proposed scheme can reliably achieve meter-level positioning.

Optimization model of GNSS/pseudolites structure design for open-pit mine positioning

A new pseudolites (PLs) structure optimization model of global navigation satellite system (GNSS)/PLs integration positioning system used in deep open-pit mine was presented. Position dilution of precision (Pdop) and reliability were selected as the optimization indicators to build a multi-objective optimization model to decide the optimum PLs location. A scheme was designed by establishing a four-dimensional model taking azimuth (a), elevation angle (e) and epoch (t) of satellites as the input independent variables and Pdop as the dependent variable to calculate the optimum PLs location zone considering the real circumstances. And then the ultimate PLs location can be fixed by testing the curves of Pdop along time. A field collected Trimble R8 GPS data set in China University of Mining and Technology (CUMT) campus was used for the model test to show the effectiveness, and the proposed PLs optimum design scheme was used at the west open-pit mine of Fushun mining group Co., Ltd., in China, better Pdop and reliability have been achieved for the integration system. Both experiments show that the proposed scheme is excellent in designing GNSS/PLs system which is helpful for improving the performance of the positioning system and reducing the cost.

Building international business relations: China-Canada education MODEL

This short paper is a summary of the keynote speech that will be given by Dr. Prosper Bernard in Xuzhou at the 6th International Conference on Mining and Technology at the China University of Mining and Technology. The presentation will refer to concrete examples that show ways to create long term business relations and technology transfer. One example is the relationship created by a joint MBA program between China University of Mining and Technology (CUMT) and the University of Quebec (UQAM). Another example is that CUMT receives every year a delegation of executive MBA participants from Quebec who meet the Xuzhou MBA participants. Another way is to create international internships for our graduates. International Business and Technology transfer start with `RELATIONS``. It is suggested that education creates the best relations.

Methane control for mechanised longwall top-coal caving faces in high gas content mines

In China, mechanised longwall top-coal caving technology (LTCT) has been widely used under suitable thick coal seam conditions due to its low cost, high production and productivity since it was introduced in 1982. It has even been applied in some high gas-content mines (e.g. No. 5 Mine, Yangquan coalfield), where methane is the most serious hazard affecting production in the mine. With the introduction of LTCT in 1992, the frequency of production delays greatly increased due to excess methane. In order to solve these problems, China University of Mining and Technology (CUMT) has been carrying out methane research jointly with Yangquan Coal Group Co. (YCGC) since 1993. The major focus of the research was concerned with the gas source and emission characteristics of the longwall top-coal caving face (LTCF) and the methane drainage methods from the adjacent strata during initial and normal mining. The research has helped the mine to control methane-related production delays to tolerable levels. The methane problems during normal mining were solved by the adoption of the high-level strike drainage roadway (HSDR). The methane concentration during initial mining was kept below the statutory limits by the adoption of the mid-level drainage roadway (MDR). In this way, the methane-related production delay problems were successfully solved by introduction of the HSDR in conjunction with the MDR. This paper analyses the gas source and emission characteristics of LTCF, and describes the experiences and methodologies adopted in methane control at the LTCF during normal and initial mining.

Cyclo-microbubble Column Flotation of Fine Coal

Cyclo-microbubble flotation column (CMFC) is an advanced column flotation technology for fine coal cleaning developed by China University of Mining and Technology (CUMT). It combines cyclone separation with column flotation to enhance pyritic sulfur rejection and separation efficiency. A specially designed external bubble generator is employed to efficiently precipitate fine bubbles on particle surface. A set of screen plates inside the column produces nearly plug-flow condition, which is preferred for flotation process. The CMFC technology has been successfully employed to recover fine coal from discarded waste ponds and replace conventional mechanical cells. Typical commercial testing results are described and analyzed. The column is very effective in cleaning particles down to 45 μm. Laboratory- and pilot-scale testing of CMFC has also demonstrated that the CMFC process can produce a superclean coal product of 1.5∼1.6% ash content from a 9.8% ash feed.