Chad O. Hargrave

Longwall mining automation an application of minimum-variance smoothing [Applications of Control]

This article reviews the development of the minimum-variance smoother and describes its use in longwall automation. We describe both continuous- and discrete-time smoother solutions. It is shown, under suitable assumptions, that the two-norm of the smoother estimation error is less than that for the Kalman filter. A simulation study is presented to compare the performance of the minimum-variance smoother with the methods of H.E. Rauch et al. (1965), and D.C. Fraser and J.E. Potter (1969).

Optimizing Wireless LAN for Longwall Coal Mine Automation

A significant development in underground longwall coal mining automation has been achieved with the successful implementation of wireless LAN (WLAN) technology for communication on a longwall shearer. WIreless-FIdelity (Wi-Fi) was selected to meet the bandwidth requirements of the underground data network, and several configurations were installed on operating longwalls to evaluate their performance. Although these efforts demonstrated the feasibility of using WLAN technology in longwall operation, it was clear that new research and development was required in order to establish optimal full-face coverage. By undertaking an accurate characterization of the target environment, it has been possible to achieve great improvements in WLAN performance over a nominal Wi-Fi installation. This paper discusses the impact of Fresnel zone obstructions and multipath effects on radio frequency propagation and reports an optimal antenna and system configuration. Many of the lessons learned in the longwall case are immediately applicable to other underground mining operations, particularly wherever there is a high degree of obstruction from mining equipment

Localisation of mobile underground mining equipment using wireless Ethernet

This review paper explores the use of IEEE 802.11b wireless Ethernet for the localisation of mobile equipment operating in an underground coal mining environment wireless communication networks have recently been introduced with some success in underground operations such as longwall mining to provide reliable high-speed communications for monitoring and control. We investigate the feasibility of this wireless paradigm for providing a new machine localisation capability underground, as has been recently considered in other non-mining domains. We overview two popular location estimation techniques, namely nearest-neighbour and Monte-Carlo Localisation, which use only the signal strength as received from several wireless access points to estimate location. Because the received signal strength is a highly variable parameter in underground environments, real data experiments are conducted using an in-house test facility to investigate signal properties and to evaluate the potential of the concept for underground mining.

Software defined radar: An open source platform for prototype GPR development

This discussion paper explores the potential of Software Defined Radio (SDR) technology to provide flexible and low-cost subsurface radar prototypes for the GPR community. Unlike traditional fixed hardware implementations, SDR uses software configurable RF modules which can be used to implement customized signal encoding, decoding and processing. However, the full potential of SDR has not yet been fully understood or exploited for radar-based applications, and so is of special interest for GPR development. This paper introduces the fundamental concepts behind SDRs and describes the underlying hardware and software architectures that are used to implement them. It also provides a simple reference design using open source GNU Radio software and the Universal Software Radio Peripheral (USRP) hardware to indicate how low-cost radar configurations can be designed and evaluated. The benefits and challenges of SDR-based radar architectures are highlighted, and opportunities discussed for new and enhanced subsurface sensing capabilities. Overall, SDR technology is seen to provide new opportunities to boost future radar research and development to provide enhanced GPR system capabilities.

Late-Time Estimation for Resonance-Based Radar Target Identification

This communication presents a novel method for determining the commencement of the late-time resonant response of a radar target, without a priori knowledge of the target geometry or orientation. Insights from Kroneckers theorem for Hankel matrices are used to determine the offset for the processing window for extraction of the true complex natural resonances by exploiting characteristic changes in the Hankel matrix, including the matrix rank and the distribution of eigenvalues. Results are presented for both simulated and measured targets.

Optimising wireless LAN for longwall coal mine automation

A significant development in underground longwall coal mining automation has been achieved with the successful implementation of WLAN technology for communication on a longwall shearer. Wi-Fi was selected to meet the bandwidth requirements of the underground data network, and several configurations were installed on operating longwalls to evaluate their performance. Although these efforts demonstrated the feasibility of using WLAN technology in a longwall operation, it was clear that new research and development was required in order to establish optimal, full face coverage. By undertaking an accurate characterisation of the target environment it has been possible to achieve great improvements in WLAN performance over a nominal Wi-Fi installation. The paper discusses the impact of Fresnel zone obstructions and multipath effects on RF propagation, as well as reporting on an optimal antenna and system configuration. Many of the lessons learnt in the longwall case are immediately applicable to other underground mining operations, particularly wherever there is a high degree of obstruction from mining equipment.

Application of signal processing technology for automatic underground coal mining machinery

The paper reports on an industrial application of modern signal processing technology in the development of a new automatic conveyor and bolting machine for underground coal mining. The machine is of special interest to the mining industry as it improves mine personnel safety as well as increasing the efficiency of roadway construction. We show how real-time signal processing component technologies are needed to overcome a range of sensing, monitoring, control, and navigational challenges. We also highlight some of the important practical issues associated with the deployment of intelligent processing systems in coal mining contexts.

Non-Wearable UWB Sensor for Human Identification in Smart Home

Human identification is one of the main challenges for health monitoring systems in smart home. The majority of existing systems employ either wearable tags or video cameras to identify multiple residents in home environment. However, due to the inflexibility and inconvenience of wearable devices, and potential intrusiveness of video cameras, the adoption rate of these approaches remains low. In this paper, we propose a novel non-wearable identification system to recognize multiple residents in a home environment, through ambient non-intrusive ultra-wide band (UWB) sensors. For each room, over the entrance, we propose to install a UWB sensor to monitor and identify individuals who enter or exit the room. As each individual has different body figure and walking gait, they are “seen” differently by UWB sensor. Through the proposed Region of Interest (ROI) extraction approach, our system generates a unique UWB signature for each individual which will be used for their identification. We evaluated our system in a controlled laboratory environment with eight individuals including six males and two females. Our UWB-based approach achieved 88% accuracy in identifying individuals among eight subjects, while a similar ultrasound-based technique [1] achieved only a 54% accuracy rate.

Radar target identification: Estimating the start of the late time resonant response

Determining the correct start for the late-time or resonant response window is a crucial parameter for uncooperative, resonance-based target identification by means of ultra-wideband radar. For low resonance (low-Q) targets this is particularly vital, as the processing must be set late enough to avoid including signal data caused by early-time (non-resonant) scattering, but early enough to maximise the signal-to-noise ratio for the late-time component of the target response. Without knowledge of the targets orientation to the incident excitation, the late-time start must be determined from the signal data alone. The spectral norm of the impulse response data matrix (Hankel matrix), examined over a sliding window, provides a robust indicator of the late-time commencement.

Radar Level Sensor for Longwall Creep and Retreat Measurement

The use of a commercial radar level sensor for measuring two critical parameters related to the longwall coal mining process is investigated. An overview of the longwall coal mining process is provided, and the parameters known as longwall creep and longwall retreat are explained. The test environment and methodology used to simulate these parameters is described, along with the commercial radar level sensor that was employed. The test results are presented, including a comparison of the retreat testing using a flat plate target with a theoretical model based on the geometrical theory of diffraction. It was found that the radar sensor functions effectively as a tool for longwall creep measurement, and that it also shows great potential for measuring longwall retreat.