Gabriel I. Rowe

Classification of power quality events using optimal time-frequency representations-Part 2: application

Classification of power-quality (PQ)-related voltage and current waveform disturbances is a key task for power system monitoring. A new method based on the optimized time-frequency representation (TFR) has been proposed in the first paper of this two-paper series. This paper (the second paper) presents a case study of PQ event classification with the proposed method. The classification algorithm has been successfully tested with 860 real world PQ events that cover five classes, achieving a recognition rate of 98%. The algorithm is implemented on a digital signal processor (DSP) based hardware system and optimized according to the DSP architecture to meet the hard real-time constraints. The DSP-based system is capable of processing a five-cycle (83.3 ms) PQ waveform within 11.2 ms. The real-time computing capability of the algorithm has been verified with this result. The scalability of this method is also discussed.

The thermal conductivity of prosthetic sockets and liners

Elevated stump skin temperatures and the accompanying thermal discomfort are side effects of prosthesis use that may reduce amputee quality of life, particularly in hot or humid surroundings. Lower skin temperatures might be achieved through more effective heat transfer in the prosthesis, a process governed in part by the thermal conductivity of the sock, liner, and socket layers. To assess the thermodynamic properties of currently available components, an instrument capable of measuring the heat flux across a regulated temperature differential was developed. Experimental results show that the thermal conductivity ranged from 0.085 – 0.266 W/m · °K for liner materials and from 0.148 – 0.150 W/m · °K for socket materials. The results of this study demonstrate that the prescription of typical multi-layer prostheses constructed with the higher thermal conductivity materials might reduce temperature-related discomfort in patients.

Capacitive sensing of interfacial forces in prosthesis

In this paper, we present a capacitive sensor that measures the interfacial forces in prosthesis. The sensors design, transfer function and performance metrics are tested and discussed. The sensor is uniquely able to measure both shear and normal stress simultaneously.

Shear sensor for lower limb prosthetic applications

Lower limb amputees using a prosthetic device often suffer from mechanically-induced skin injuries. Shear stresses are believed to play a significant role in the formation of these skin injuries. The work presented in this paper is aimed at creating a new class of adaptive prosthetic and orthotic interfaces involving a capacitive shear stress sensor. The sensor design and transfer function are discussed. A few preliminary test results demonstrating the functionality of the sensor are also presented.

Simulation of a sensor array for multiparameter measurements at the prosthetic limb interface

Sensitive skin is a highly desired device for biomechanical devices, wearable computing, human-computer interfaces, exoskeletons, and, most pertinent to this paper, for lower limb prosthetics. The measurement of shear stress is very important because shear effects are key factors in developing surface abrasions and pressure sores in paraplegics and users of prosthetic/orthotic devices. A single element of a sensitive skin is simulated and characterized in this paper. Conventional tactile sensors are designed for measurement of the normal stress only, which is inadequate for comprehensive assessment of surface contact conditions. The sensitive skin discussed here is a flexible array capable of sensing shear and normal forces, as well as humidity and temperature on each element.

Parametric modeling of concentric fringing electric field sensors

Fringing electric field (FEF) sensors are widely used for non-invasive measurement of material properties, such as porosity, viscosity, temperature, hardness, and degree of cure. FEF sensors have also been used to detect the presence of a material or estimate the concentration of a material within the test environment. There are no generic analytical models for FEF sensors. Their design optimization process often involves complex and time-consuming finite element simulations. This paper presents a tool for improvement of the design process through formulating a universal equation for three-electrode concentric FEF sensors. The equation models the effect of sensor geometry and substrate material on sensor output. The model parameters are determined from a 3-D surface fit of finite element simulation results for the most common type of sensor geometry. The variables in the model are non-dimensionalized, which makes the model applicable to a wider range of sensor designs. Based on the model, the terminal capacitance can be estimated for three-electrode concentric sensors of wide range of sizes.

Real-time power quality waveform recognition with a programmable digital signal processor

Power quality (PQ) monitoring is an important issue to electric utilities and many industrial power customers. This paper presents a DSP-based hardware monitoring system based on a recently proposed PQ classification algorithm. The algorithm is implemented with a Texas Instruments (TI) TMS320VC5416 digital signal processor (DSP) with the TI THS1206 12-bit 6 MSPS analog to digital converter. A TI TMS320VC5416 DSP starter kit (DSK) is used as the host board with the THS1206 mounted on a daughter card. The implemented PQ classification algorithm is composed of two processes: feature extraction and classification. The feature extraction projects a PQ signal onto a time-frequency representation (TFR), which is designed for maximizing the separability between classes. The classifiers include a Heaviside-function linear classifier and neural networks with feedforward structures. The algorithm is optimized according to the architecture of the DSP to meet the hard realtime constraints of classifying a 5-cycle segment of the 60 Hz sinusoidal voltage/current signals in power systems. The classification output can be transmitted serially to an operator interface or control mechanism for logging and issue resolution.

Capacitive sensing of interfacial stresses

Studying interfacial stresses is an important step towards understanding load distributions in mechanical, biomedical, and industrial systems. This paper presents a capacitive sensor that is capable of simultaneously measuring compressive and shear stresses. The sensor consists of two electrode layers separated by a set of flexible and compressible polymer pillars. The sensors response to compressive and shear stresses was tested and characterized up to 320 kPa and 70 kPa respectively. An algorithm to estimate the applied stresses based on sensor output was developed and validated. The applied compressive stresses were estimated with an accuracy of 95.04 % and shear stress with an accuracy of 89.45 %.

On-chip characterization of fluids using microsurface plasmon resonance sensors

The design of a Micro Surface Plasmon Resonance Sensor is proposed. The possibility of implementing the modified Kretschmann-Raether scheme on a chip is investigated. A moving waveguide is used to change the angle of incidence of the beam of light. The main advantages of this sensor are potentially low cost, simplicity of design and very high parallelization. It is possible to have large number of such sensors on one chip, each of them with distinct activated sensing surfaces. The modeling of the sensor, design optimization procedures, and fabrication are also discussed. Computer simulations are used to validate the design.