A methodology to monitor the real-time cutting forces generated by a longwall shearer is developed. Longwall shearers are the single productive element in an underground longwall coal mine, and are a major source of unscheduled system downtime. The cutting forces constitute the interaction between the longwall and the coal face. Knowledge of the forces can improve the reliability and productivity of longwall mines by providing a means of shearer condition monitoring. A Kalman filter based cutting force estimator is developed, and then tested using a comprehensive shearer simulation incorporating a dynamic representation of the cutterhead. Subsequently, prior work on autonomous shearer guidance with measured pick forces is extended by employing the estimated cutting forces to track changes to the shearer's horizon. This is validated by simulation. The force estimation methodology uses an extended Kalman filter to blend noisy measurement information with a nonlinear system model, the latter combining the dynamics of the shearer and its inputs. A detailed model is developed of the shearer rigid body dynamics, and of the measurements required for observability. The formulation avoids the use of sensors at the coal cutting interface. The methodology uses proven, practicable and reliable sensor technologies, making it suitable for longterm force monitoring. A comprehensive simulation of a longwall shearer is developed using the MATLAB(R) Simulink(R) and MSC.visualNastran 4DTM software environments. This incorporates dynamic representations of the major structures and inputs, including the interaction between the cutterhead and the coal face. The simulation is used to investigate the cutting forces in a number of different operational scenarios. This facilitates the construction of a basic dynamic model of the forces, and provides insight into the relationship between the cutting forces and the condition of the cutting interface. The cutting force estimator is tested using measurements from the shearer simulations. It is shown that the cutting force estimates track the fiducial forces well in each scenario. A number of modifications to the force models are also shown to improve the performance of the estimator. Sensitivity analyses are conducted to investigate the effect of tuned process noise covariance and model parameter errors on the estimates. The application to the problems of shearer condition monitoring and horizon tracking are considered. The first is demonstrated by detecting the effects of a worn pick and a seam hardness gradient on the force estimates, and the second by using the force estimates to track the motion of the cutterhead relative to an embedded stone band. The results show that it is possible, in principle, to estimate the cutting forces generated by a longwall shearer from indirect measurements using a Kalman filter methodology. Furthermore, the force estimates reveal changes to the cutting environment, and can track the vertical motion of the shearer as it operates. This thesis represents the first step in the development of a shearer cutting force estimator. The ultimate goal of the research is to improve the reliability and productivity of Australian longwall operations, using the estimated forces to monitor shearer condition. Autonomous horizon tracking with estimated forces can lead to further improvements to longwall productivity, and to the health and safety of mine personnel. A number of recommendations are made for future field validation, and development of an automated shearer condition monitoring system based on the cutting force estimates.

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A methodology to monitor the real-time cutting forces generated by a longwall shearer is developed. Longwall shearers are the single productive element in an underground longwall coal mine, and are a major source of unscheduled system downtime. The cutting forces constitute the interaction between the longwall and the coal face. Knowledge of the forces can improve the reliability and productivity of longwall mines by providing a means of shearer condition monitoring. A Kalman filter based cutting force estimator is developed, and then tested using a comprehensive shearer simulation incorporating a dynamic representation of the cutterhead. Subsequently, prior work on autonomous shearer guidance with measured pick forces is extended by employing the estimated cutting forces to track changes to the shearer's horizon. This is validated by simulation. The force estimation methodology uses an extended Kalman filter to blend noisy measurement information with a nonlinear system model, the latter combining the dynamics of the shearer and its inputs. A detailed model is developed of the shearer rigid body dynamics, and of the measurements required for observability. The formulation avoids the use of sensors at the coal cutting interface. The methodology uses proven, practicable and reliable sensor technologies, making it suitable for longterm force monitoring. A comprehensive simulation of a longwall shearer is developed using the MATLAB(R) Simulink(R) and MSC.visualNastran 4DTM software environments. This incorporates dynamic representations of the major structures and inputs, including the interaction between the cutterhead and the coal face. The simulation is used to investigate the cutting forces in a number of different operational scenarios. This facilitates the construction of a basic dynamic model of the forces, and provides insight into the relationship between the cutting forces and the condition of the cutting interface. The cutting force estimator is tested using measurements from the shearer simulations. It is shown that the cutting force estimates track the fiducial forces well in each scenario. A number of modifications to the force models are also shown to improve the performance of the estimator. Sensitivity analyses are conducted to investigate the effect of tuned process noise covariance and model parameter errors on the estimates. The application to the problems of shearer condition monitoring and horizon tracking are considered. The first is demonstrated by detecting the effects of a worn pick and a seam hardness gradient on the force estimates, and the second by using the force estimates to track the motion of the cutterhead relative to an embedded stone band. The results show that it is possible, in principle, to estimate the cutting forces generated by a longwall shearer from indirect measurements using a Kalman filter methodology. Furthermore, the force estimates reveal changes to the cutting environment, and can track the vertical motion of the shearer as it operates. This thesis represents the first step in the development of a shearer cutting force estimator. The ultimate goal of the research is to improve the reliability and productivity of Australian longwall operations, using the estimated forces to monitor shearer condition. Autonomous horizon tracking with estimated forces can lead to further improvements to longwall productivity, and to the health and safety of mine personnel. A number of recommendations are made for future field validation, and development of an automated shearer condition monitoring system based on the cutting force estimates.

A methodology to monitor the real-time cutting forces generated by a longwall shearer is developed. Longwall shearers are the single productive element in an underground longwall coal mine, and are a major source of unscheduled system downtime. The cutting forces constitute the interaction between the longwall and the coal face. Knowledge of the forces can improve the reliability and productivity of longwall mines by providing a means of shearer condition monitoring. A Kalman filter based cutting force estimator is developed, and then tested using a comprehensive shearer simulation incorporating a dynamic representation of the cutterhead. Subsequently, prior work on autonomous shearer guidance with measured pick forces is extended by employing the estimated cutting forces to track changes to the shearer's horizon. This is validated by simulation. The force estimation methodology uses an extended Kalman filter to blend noisy measurement information with a nonlinear system model, the latter combining the dynamics of the shearer and its inputs. A detailed model is developed of the shearer rigid body dynamics, and of the measurements required for observability. The formulation avoids the use of sensors at the coal cutting interface. The methodology uses proven, practicable and reliable sensor technologies, making it suitable for longterm force monitoring. A comprehensive simulation of a longwall shearer is developed using the MATLAB(R) Simulink(R) and MSC.visualNastran 4DTM software environments. This incorporates dynamic representations of the major structures and inputs, including the interaction between the cutterhead and the coal face. The simulation is used to investigate the cutting forces in a number of different operational scenarios. This facilitates the construction of a basic dynamic model of the forces, and provides insight into the relationship between the cutting forces and the condition of the cutting interface. The cutting force estimator is tested using measurements from the shearer simulations. It is shown that the cutting force estimates track the fiducial forces well in each scenario. A number of modifications to the force models are also shown to improve the performance of the estimator. Sensitivity analyses are conducted to investigate the effect of tuned process noise covariance and model parameter errors on the estimates. The application to the problems of shearer condition monitoring and horizon tracking are considered. The first is demonstrated by detecting the effects of a worn pick and a seam hardness gradient on the force estimates, and the second by using the force estimates to track the motion of the cutterhead relative to an embedded stone band. The results show that it is possible, in principle, to estimate the cutting forces generated by a longwall shearer from indirect measurements using a Kalman filter methodology. Furthermore, the force estimates reveal changes to the cutting environment, and can track the vertical motion of the shearer as it operates. This thesis represents the first step in the development of a shearer cutting force estimator. The ultimate goal of the research is to improve the reliability and productivity of Australian longwall operations, using the estimated forces to monitor shearer condition. Autonomous horizon tracking with estimated forces can lead to further improvements to longwall productivity, and to the health and safety of mine personnel. A number of recommendations are made for future field validation, and development of an automated shearer condition monitoring system based on the cutting force estimates.

A methodology to monitor the real-time cutting forces generated by a longwall shearer is developed. Longwall shearers are the single productive element in an underground longwall coal mine, and are a major source of unscheduled system downtime. The cutting forces constitute the interaction between the longwall and the coal face. Knowledge of the forces can improve the reliability and productivity of longwall mines by providing a means of shearer condition monitoring. A Kalman filter based cutting force estimator is developed, and then tested using a comprehensive shearer simulation incorporating a dynamic representation of the cutterhead. Subsequently, prior work on autonomous shearer guidance with measured pick forces is extended by employing the estimated cutting forces to track changes to the shearer's horizon. This is validated by simulation. The force estimation methodology uses an extended Kalman filter to blend noisy measurement information with a nonlinear system model, the latter combining the dynamics of the shearer and its inputs. A detailed model is developed of the shearer rigid body dynamics, and of the measurements required for observability. The formulation avoids the use of sensors at the coal cutting interface. The methodology uses proven, practicable and reliable sensor technologies, making it suitable for longterm force monitoring. A comprehensive simulation of a longwall shearer is developed using the MATLAB(R) Simulink(R) and MSC.visualNastran 4DTM software environments. This incorporates dynamic representations of the major structures and inputs, including the interaction between the cutterhead and the coal face. The simulation is used to investigate the cutting forces in a number of different operational scenarios. This facilitates the construction of a basic dynamic model of the forces, and provides insight into the relationship between the cutting forces and the condition of the cutting interface. The cutting force estimator is tested using measurements from the shearer simulations. It is shown that the cutting force estimates track the fiducial forces well in each scenario. A number of modifications to the force models are also shown to improve the performance of the estimator. Sensitivity analyses are conducted to investigate the effect of tuned process noise covariance and model parameter errors on the estimates. The application to the problems of shearer condition monitoring and horizon tracking are considered. The first is demonstrated by detecting the effects of a worn pick and a seam hardness gradient on the force estimates, and the second by using the force estimates to track the motion of the cutterhead relative to an embedded stone band. The results show that it is possible, in principle, to estimate the cutting forces generated by a longwall shearer from indirect measurements using a Kalman filter methodology. Furthermore, the force estimates reveal changes to the cutting environment, and can track the vertical motion of the shearer as it operates. This thesis represents the first step in the development of a shearer cutting force estimator. The ultimate goal of the research is to improve the reliability and productivity of Australian longwall operations, using the estimated forces to monitor shearer condition. Autonomous horizon tracking with estimated forces can lead to further improvements to longwall productivity, and to the health and safety of mine personnel. A number of recommendations are made for future field validation, and development of an automated shearer condition monitoring system based on the cutting force estimates.

The economic implications of equipment failure are called for effective maintenance techniques. The research investigates current maintenance practice in several New Zealand industries and the improvements that could be obtained by the use of predictive maintenance techniques. Initial research was undertaken in a series of case studies within New Zealand industries situated in Auckland. The first two cases studies were of preventative maintenance techniques of two conveyor lines in a biscuit manufacturing company. The results showed a well defined preventive maintenance schedules that was Systems Applications Products (SAP) programme was used to managed for daily, weekly, monthly and yearly maintenance activities. A third case study investigated current predictive maintenance technique involving Fast Fourier Transform analysis of shaft vibration to identify a bearing defect. The results diagnosed a machine with a ball bearing defect and recommendation was given to change the bearing immediately and install new one. The machine was opened up, a big dent was on one of the balls as predicted by the analysis and the bearing was changed. Research then looked at a novel technique called Cepstrum analysis that al lows the deconvolution of vibration spectra from separate sources. This allows identification of several defects from the monitoring of a single vibration signal . Experiments were carried out to generate transfer functions for different gear faults at two different loadings. Blind deconvolution of the signal using a homomorphic filter was used to separate the source forcing frequencies from the structure resonance effects of the two gear faults, indicating that the technique could be used successfully to monitor equipment for a range of gear faults occurring simultaneously.

The scarcity of fossil energy resources in conjunction with increasing demand has recently created record commodity price rises. Global warming and dimming are some of the harmful effects of increasing use of this resource. Furthermore, fossil fuel exhaust emissions, produced in internal combustion engines (ICE), generate significant health concerns. For decades, fears and numerous alarms have been raised regarding these problems. Many researchers believe that hydrogen would be an ideal alternative solution. Reduced fossil fuel consumption and lower thermal emanations (CO, CO2, HC and NO) are expected if hydrogen is used, as a principal or supplementary fuel, in standard ICE’s. However, hydrogen dual-fuel use has historically been associated with injection and/or detonation problems. Direct injection (DI) strategy, in spark and compression engines, is commonly used to overcome some, but not all, of these difficulties. This experimental research investigated detonation free, diesel-hydrogen fuel consumptions, and exhaust emissions using an indirect injection (IDI) strategy in a generic compression diesel engine. A novel analogue Mechatronic Injection Unit (MICU) in conjunction with a multi point injection tactic (MPI) were devised to indirectly deliver low pressure hydrogen to a stationary Lister-Pitter diesel engine combustion chamber. The hydrogen injection system was created to be used as a generic dual-fuel kit. With off-the-shelf parts the MICU design was simple, robust, and purposeful in its function. The MICU component also formed an important element of a proposed innovative dual-fuel conversion kit. Nine hydrogen injection rates were tested. Diesel consumption savings were measured and the ‘effectiveness’ of hydrogen vitiated injection was computed. The research outcomes demonstrated that with a conventional diesel mechanical governor and an assumed engine compression ratio of 15.5, detonation free combustion can be achieved with low pressure hydrogen vitiation and enrichment . However, an injection rate limit existed above which detonation occurred. The study also demonstrated that through low pressure hydrogen vitiation and enrichment, diesel consumption savings were achieved. The research confirmed that the experimental fuel mass savings were lower than their expected/theoretical counterparts. The research particularly established that vitiation and enrichment effectiveness was only realised at low rather than high loads indicating that hydrogen achieved more than diesel mass substitutions. In this study a new confined area dual-fuel static emission testing procedure, coupled with an on-site use test cycle was proposed and termed the Dual-fuel fixed speed emission-testing guideline. Dry thermal emissions were measured, and both the cycle average and median dry- and wet-emissions were computed, substance/species comparisons were performed and conclusions were drawn. The shortcomings of the procedure however were also highlighted. Finally, the research established that one action or measure, such as dual-fuel hydrogen vitiation and enrichment, can not address all the environment and health concerns. Contrary to the common belief, green house gases, nitrogen oxides, hydrocarbons and opacity substances do not coincidently all increase and/or decrease. Indeed, this experiment demonstrated that although the diesel-hydrogen nitrogen monoxide (NO) wet-emissions at all injection rates were partially lower than the diesel baseline, carbon oxides, hydrocarbon emissions, opacity (N) and absorption coefficients (k) were higher. In other words, a measure taken to limit the harm done to human health can increase the damage to the environment and vice versa.