Michael G. Lipsett

Hyperspectral imaging for the characterization of athabasca oil sands drill core

Accurately logging oil sands core is a challenging process because sedimentary and biogenic features are difficult to see in bitumen-saturated strata. A suite of oil sands core was scanned using the SisuROCK hyperspectral imaging system. Analysis of the spectral imagery revealed that in the shortwave infrared we can “see through” thin bitumen at the surface and readily identify structures and fabrics that are not visible to the unaided eye. In the spectral data, we identify broad spectral classes that correlate to lithofacies, which are then used to create rudimentary lithological maps. Greyscale ore-grade maps are also created using an existing spectral model for the determination of bitumen content. Developing an automated method for the removal of man-made materials from the hyperspectral imagery, based on a spectral library developed during this study, remains a research preoccupation. Future work will investigate the discrimination of individual clay minerals, particularly swelling vs. non-swelling.

Theoretical and Experimental Study of Hydrocyclone Performance and Equivalent Settling Area

Predicting the performance of a solid-liquid separation process can help in comparing different separators for selection and design. This can be applied to hydrocyclone technology which is used widely in industry due to being an inexpensive device that is easy to operate and maintain and which has no moving parts. Environmental concerns and technological issues in separation processes are motivating the design of higher efficiency systems with less capital and operating costs. There is a need therefore for, methods to compare different separation technologies.In spite of extensive research into hydrocyclone performance, a mathematical model that can predict the performance of a hydrocyclone for comparison with other centrifugal separators is rare in the literature. The main objective of this research is to apply theoretical and experimental approaches to study hydrocyclone performance in order to propose an applicable separation performance model that represents the whole hydrocyclone operating range. A mathematical model is developed to explore the performance of the separator and to predict the hydrocyclone’s equivalent area as compared to a continuous gravity settling tank. A performance chart that can be used for selection and design of hydrocyclones is the result of the model.Copyright

Automated Operating Mode Classification for Online Monitoring Systems

Machine condition monitoring can be defined as two complementary tasks. The first task characterizes the response of a machine during normal fault-free operations using diagnostic indicators from measurements such as vibration and temperature. The second task compares diagnostic indicators from the same machine, during a period of unknown condition, to the original measurements. It is the deviation of the diagnostic indicators representing the unknown condition from the indicators representing the known condition that provides the estimate of the true condition of the machine. The accuracy of a condition estimate depends on a number of factors; the most significant being the sensitivity of the feature that is being observed to a given failure mode. While it is desirable for the diagnostic features to be sensitive to machine condition, it is also imperative that these features are insensitive to factors that are not caused by the machine condition. One such factor is the operating mode of the machine. In many cases, the sensitivity of the diagnostic indicators to operating mode is not a concern. The most obvious example is for those machines that always operate in the same well-defined mode of operation a familiar example of such a machine is a pump that runs at a steady speed. There is a category of machines whose operation can be described as continuously changing in duty such as load and speed. This type includes machines that perform a set of repeatable but variable tasks, often controlled by a human operator. One example of such a machine is an excavator performing a continuous digging task. These machines are often overlooked as candidates for online condition monitoring because of the mode-related influences on the diagnostic parameters. It is this category of machines that is the focus of this research.

Isotherm moisture absorption kinetics in natural-fiber-reinforced polymer under immersion conditions

In natural-fiber-reinforced polymer, absorption of water or moisture is a significant issue in maintaining strength and stiffness. To enhance the understanding of water and moisture sorption behavior, the kinetics of moisture sorption in natural-fiber-reinforced polymers are investigated under immersion conditions. Samples of hemp-bast-fiber-reinforced polyethylene are prepared using an injection molding technique at different hemp fiber volume fractions (vf). The samples are then immersed in water for 274 days. Moisture content and uptake rate are analyzed at different fiber volume factions and matrix crystallinity percentages. A simplified two-dimensional contraction model is developed to investigate the contraction effect on the moisture uptake; it shows that a matrix with high crystallinity has more stiffness contraction on the reinforcing natural fibers, which limits the maximum amount of the absorbed moisture. The Fickian diffusion is found to be the dominant mechanism, shifting toward pseudo-Fickian or anomalous diffusion depending on the natural fiber volume fraction and the crystallinity percentages of the matrix. The natural-fiber-reinforced polymers diffusivity is evaluated and modeled to characterize the ability of liquid molecules to diffuse into these composites at different hemp fiber volume fractions. Both the crystallinity percentage of the matrix material and the volume fraction of the reinforcing fibers were found to interactively affect the sorption kinetics of the tested natural-fiber-reinforced polymers.

Modeling Erosion Wear Rates in Slurry Flotation Cells

In processes using slurry as the working fluid, wear due to solid particles impinging on elements of the process units is a serious reliability issue. This study considers modeling wear damage in flotation cells, which are widely used in mineral processing. Flotation cells are typically cylindrical vessels where an impeller is used to agitate the fluid, enabling the liberation of the minerals from the slurry. Some solids, particularly those entrained in the impeller stream, can impact on the wall of the cell, leading to material loss and eventually to loss of structural integrity. The problem of predicting the remaining life of the unit due to erosion requires understanding of various sub-processes: flow modeling, particle–fluid interaction, energy interactions at the surface, and the mechanism of erosion itself. In this study, empirically developed equations for the flow field of cylindrical mixing vessel with a Rushton turbine are used in formulating a model relating and the damage accumulation rate to a simple set of measurable variables. To validate a model, a PIV technique was used to measure velocities in the flow field and near the wall on a physical model of the cell with transparent walls and particles that match the refractive index of the fluid. An Eulerian–Langrangian approach has been used to determine the particle trajectories and the effect of a squeeze film is incorporated into the model to modify the velocity distribution of particles prior to impacts. An analytical model based on equations of impulse and momentum for a particle of any shape striking a flat massive surface has been used to describe the energy lost at the walls. Finally, a damage model is developed that takes into account impact velocity, attack angle, properties of the impinging particles and the surface. This model is verified against a second physical model that measures material loss rate at different locations within the cell.

Modeling Excavator-Soil Interaction

This paper reviews models of how ground-engaging tools interact with soils, the rigid-body dynamics of excavating machines, and how to combine these models to estimate soil parameters or to find faults in machines from anomalous dynamic behaviour. Soil-tool interaction models rely primarily on assumptions of homogeneous, isotropic soil properties, and tools that have simple geometries and steady motion through the soil. In many cases, these are reasonable assumptions, provided that the strain rate of the soil is not extreme. Parametric formulations are discussed for soil failure under stress from a non-deformable tool; but finiteelement and distinct-element methods are not considered. The formulation of governing equations for the rigid-body dynamics of the machine that carries the tool are discussed. By using parametric equations for the combined system of machine and soil, it is possible to estimate the parameters of the system by measuring machine motions and interaction forces at the tool and base. Possible sources of error are discussed for this approach, with recommendations for how to determine the parameters of the system.

Automated Duty Cycle Classification for Online Monitoring Systems

Transient operation of machinery can greatly complicate the task of vibration-based online condition monitoring. Because the operating mode of a machine affects the physical response and hence the diagnostic parameters, real-time information regarding the operating mode is likely to improve the performance of an online fault detection system. This paper proposes a method for automated duty cycle classification to augment the performance of vibration-based online condition monitoring systems for applications such as gearboxes, motors, and their constituent components. Experimental work is carried out on the swing machinery of an electromechanical excavator, which demonstrates how such a method might function on actual dynamic signals gathered from an operating machine. Several variations of the system are tested.Copyright

Uniaxial tensile behaviour modelling of natural-fiber-reinforced viscoplastic polymer using normalized stress–strain curves

The monotonic uniaxial tensile behaviour of hemp-fiber-reinforced high density polyethylene (HDPE) was investigated at different values of hemp fiber volume fraction (vf) and strain rate ( ɛ . ). A normalized stress–strain family of curves was generated. An exponential normalized monotonic model was developed. A general uniaxial monotonic model was developed from the normalized model to simulate the stress–strain relationship at different values of ɛ . and vf. A modified Harris mechanistic model and a linear model were proposed to incorporate the effect of vf and the absorbed moisture into the developed model.

Condition Monitoring of Remote Industrial Installations Using Robotic Systems

Distributed industrial systems present increasing risk as assets age. For systems such as pipelines and utility corridors, the cost of inspection to mitigate this risk needs to be controlled without compromising reliability. Major elements of remote inspection cost and effectiveness are the number of personnel, where they are located, inspection quality control, and travel time. One approach to reduce such costs is to use robotic systems for information gathering and preliminary feature extraction to detect anomalies and identify faults and their location. A combination of aerial and terrestrial robots can be deployed to cover the territory of interest and collect information necessary to extract features of interest in a timely manner. A system conceptual design is reviewed, and specific elements for a robotic mission to monitor the integrity of a pipeline and characteristics of a mine tailings structure are presented and discussed, with options for condition indicator data collection and feature extraction. Strategies are discussed for ensuring that the robotic inspection system itself has high reliability. Preliminary development and testing results for two prototype robotic systems are presented.

Particle Motion in a Macroscale, Multiwavelength Acoustic Field

Particle motion due to ultrasonic acoustic radiation in a macroscale, multiwavelength acoustic chamber is investigated and compared with available theories. Primary acoustic radiation force theory has been extensively developed to predict single particle motion in a microscale, single-node acoustic chamber/channel. There is a need to investigate the applicability of this theory to macroscale, multiwavelength acoustic channels utilizing the acoustic radiation force for separating polydispersed particles. A particle-tracking velocimetry (PTV) approach for measuring individual particle motion is developed specifically to track particles as they densify at an acoustic pressure node. Particle motion is tracked over the lifetime of their motion to a node. Good agreement between the experimental and theoretical results is observed in the early stages of particle motion, where particles can be considered individually. Only in the densified region of the acoustic pressure node is there some mismatch with theory. The acoustic energy density of the acoustic chamber, a parameter intrinsically associated with the system by the theory, is also determined experimentally for different conditions and shown to be constant for all investigated system settings. The investigation demonstrates the capability of available theory in predicting the motion of polydispersed particles in macroscale, multiwavelength acoustic chambers.