Electrical impedance tomography (EIT) is a non-destructive, non-invasive, and non-radioactive imaging technique used for reconstructing the internal conductivity distribution of a sensing domain. Performing EIT often requires large, stationary benchtop equipment that can be expensive and impractical. Other researchers have attempted to make portable EIT systems, but they all rely on external computation for image reconstruction/data analysis. This study outlines the development of a low-cost, portable, and wireless EIT data acquisition (DAQ) system that is capable of independently performing image reconstructions on-board. With the proposed system, EIT can be performed on carbon fiber reinforced polymers to spatially locate damages. Since EIT reconstruction algorithms can be extremely computationally intensive, this study has also developed an alternative deep-learning algorithm that leverages the compressed-sensing technique to strategically train a neural network. The proposed neural network has not only achieved comparable results to traditional iterative algorithms, but it can do so in a fraction of the time.

Smart sensors have become and will continue to constitute an enabling technology to wirelessly connect platforms and systems and enable improved and autonomous performance. Automobiles have about two hundred sensors. Airplanes have about eight thousand sensors. With technology advancements in autonomous vehicles or fly-by-wireless, the numbers of these sensors is expected to increase significantly. The need to conserve water and energy has led to the development of advanced metering infrastructure (AMI) as a concept to support smart energy and water grid systems that would respond to emergency shut-offs or electric blackouts. Through the Internet of things (IoT) smart sensors and other network devices will be connected to enable exchange and control procedure toward reducing the operational cost and improving the efficiency of residential and commercial buildings in terms of their function or energy and water use. Powering these smart sensors with batteries or wires poses great challenges in terms of replacing the batteries and connecting the wires especially in remote and difficult-to-reach locations. Harvesting free ambient energy provides a solution to develop self-powered smart sensors that can support different platforms and systems and integrate their functionality. In this dissertation, we develop and experimentally assess the performance of harvesters that draw their energy from air or water flows. These harvesters include centimeter-scale micro wind turbines, piezo aeroelastic harvesters, and micro hydro generators. The performance of these different harvesters is determined by their capability to support wireless sensing and transmission, the level of generated power, and power density. We also develop and demonstrate the capability of multifunctional systems that can harvest energy to replenish a battery and use the harvested energy to sense speed, flow rate or temperature, and to transmit the data wirelessly to a remote location. / PHD / Smart sensors are an essential part of planned connected communities, smart cities and buildings, structural health and pollution monitoring, and autonomous systems including air and ground vehicles. For example, these sensors can be used to monitor different buildings functions such as water flow rates, pressure and temperature, smoke detectors, HVAC and fire alarms systems. Most of the current smart sensors are powered by batteries or connected to a power source with wires. Batteries will need to be replaced frequently. Wires will add a cost and weight to the system. On the other hand, energy can be harvested locally from different sources to power these sensors. In this dissertation, we develop and experimentally assess the performance of energy harvesters that draw power from air or water flows. These devices include centimeter-scale micro wind turbines, piezo aeroelastic harvesters, and micro hydro generators. The level of generated power, and power density of these devices and their capability to support wireless sensing and transmission are evaluated. We also develop and demonstrate the capability of using one device to harvest energy to replenish a battery over specified time periods and use the harvested energy and the same device to sense speed, flow rate or temperature, and to transmit the data wirelessly to a remote location over other time periods.

This research work investigates the development and application of process fingerprinting for conventional micro-injection moulding and ultrasonic micro injection moulding manufacturing of microneedle arrays for drug delivery. The process fingerprinting method covers in-depth analysis, interrogation and selection of certain process data features and correlation of these features with product fingerprints which are defined by the geometrical outcomes of the microneedle arrays in micro scale. The method was developed using the data collected using extensive sensor technologies attached to the conventional and ultrasonic micromoulding machines. Moreover, a machine vision based microneedle product evaluation apparatus is presented. Micromachining capabilities of different processes is also assessed and presented where state-of-the-art laser machining was used for microneedle tool manufacturing in the work. By using process fingerprinting procedures, conventional and ultrasonic micromoulding processes has been characterised thoroughly and aspects of the process that is affecting the part quality was also addressed for microneedle manufacturing. It was found that polymer structure is of paramount importance in obtaining sufficient microneedle replication. An amorphous polymer have been found to be more suitable for conventional moulding whereas semi-crystalline materials performed better in ultrasonic micromoulding. In-line captured micromoulding process data for conventional and ultrasonic moulding provided detailed insight of machine dynamics and understanding. Linear correlations between process fingerprints and micro replication efficiency of the microneedles have been presented for both micromoulding technologies. The in-line process monitoring and product quality evaluation procedures presented in this work for micro-injection moulding techniques will pave ways for zero-defect micromanufacturing of miniature products towards Industry 4.0.

Data acquisition from multiple analog channels is an important function in many embedded devices used in avionics, medical electronics, robotics and space applications. It is desirable to engineer these systems to reduce their size, power consumption, heat dissipation and cost. The goal of this research is to explore designs that exploit a priori knowledge of the input signals in order to achieve these objectives. Sparsity is a commonly observed property in signals that facilitates sub-Nyquist sampling and reconstruction through compressed sensing, thereby reducing the number of A to D conversions. New architectures are proposed for the real-time, compressed acquisition of streaming signals. A. It is demonstrated that by sampling a collection of signals in a multiplexed fashion, it is possible to efficiently utilize all the available sampling cycles of the analogue-to-digital converters (ADCs), facilitating the acquisition of multiple signals using fewer ADCs. The proposed method is modified to accommodate more general signals, for which spectral leakage, due to the occurrence of non-integral number of cycles in the reconstruction window, violates the sparsity assumption. When the objective is to only detect the constituent frequencies in the signals, as against exact reconstruction, it can be achieved surprisingly well even in the presence of severe noise (SNR ~ 5 dB) and considerable undersampling. This has been applied to the detection of the carrier frequency in a noisy FM signal. Information redundancy due to inter-signal correlation gives scope for compressed acquisition of a set of signals that may not be individually sparse. A scheme has been proposed in which the correlation structure in a set of signals is progressively learnt within a small fraction of the duration of acquisition, because of which only a few ADCs are adequate for capturing the signals. Signals from the different channels of EEG possess significant correlation. Employing signals taken from the Physionet database, the correlation structure of nearby EEG electrodes was captured. Subsequent to this training phase, the learnt KLT matrix has been used to reconstruct signals of all the electrodes with reasonably good accuracy from the recordings of a subset of electrodes. Average error is below 10% between the original and reconstructed signals with respect to the power in delta, theta and alpha bands: and below 15% in the beta band. It was also possible to reconstruct all the channels in the 10-10 system of electrode placement with an average error less than 8% using recordings on the sparser 10-20 system. In another design, a set of signals are collectively sampled on a finer sampling grid using ADCs driven by phase-shifted clocks. Thus, each signal is sampled at an effective rate that is a multiple of the ADC sampling rate. So, it is possible to have a less steep transition between the pass band and the stop band, thereby reducing the order of the anti-aliasing filter from 30 to 8. This scheme has been applied to the acquisition of voltages proportional to the deflection of the control surfaces in an aerospace vehicle. The idle sampling cycles of an ADC that performs compressive sub-sampling of a sparse signal, can be used to acquire the residue left after a coarse low-resolution sample is taken in the preceding cycle, like in a pipelined ADC. Using a general purpose, low resolution ADC, a DAC and a summer, one can acquire a sparse signal with double the resolution of the ADC, without having to use a dedicated pipelined ADC. It has also been demonstrated as to how this idea can be applied to achieve a higher dynamic range in the acquisition of fetal electrocardiogram signals. Finally, it is possible to combine more than one of the proposed schemes, to handle acquisition of diverse signals with di_erent kinds of sparsity. The implementation of the proposed schemes in such an integrated design can share common hardware components so as to achieve a compact design.

ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada / While any vehicle that is typically part of a flight test campaign is heavily instrumented to validate its performance, long term vehicle health monitoring is performed by a significantly reduced number of sensors due to a number of issues including cost, weight and maintainability. The development and deployment of smart sensor buses has reached a time in which they can be integrated into a larger data acquisition system environment. The benefits of these types of buses include a significant reduction in the amount of wiring and overall system complexity by placing the appropriate signal conditioners close to their respective sensors and providing data back over a common bus, that also provides a single power source. The use of a smart-sensor data collection bus, such as IntelliBus™1 or IEEE-1451, along with the continued miniaturization of signal conditioning devices, leads to the interesting possibility of permanently embedding data collection capabilities within a vehicle after the initial flight test effort has completed, providing long-term health-monitoring and diagnostic functionality that is not available today. This paper will discuss the system considerations and the benefits of a smart sensor based system and how pieces can be transitioned from flight qualification to long-term vehicle health monitoring in production vehicles.

International Telemetering Conference Proceedings / October 27-30, 1997 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Flight Safety concerns increase proportionally with increasing missile performance. These concerns are greatest in the near launch arena where a missile has the greatest potential energy. Systems such as radar, GPS tracking systems, and optics are normally of limited use in this arena for a number of reasons. A system was required that would provide useful tracking data in the first few seconds of a missile launch. This system has met that requirement providing nominal path deviation data from the launcher out to as much as 120 seconds. The tracking system described herein uses the principle of radio interferometry to derive phase difference measurements between carefully spaced antennas. These measurements are transmitted to the Operational Display Facility and converted to a usable angular deviation plot for use by Flight Safety Personnel. This paper provides an elementary radio interferometer system background and discusses this particular system setup and use. Some detail is provided on the premission simulation and setup of the system as well as the real-time display setup and output of the final data product.

International Telemetering Conference Proceedings / October 27-30, 1997 / Riviera Hotel and Convention Center, Las Vegas, Nevada / Telemetry & Instrumentation, in conjunction with NASA’s Kennedy Space Center, has developed a commercial, intelligent, data acquisition module that performs all functions associated with acquiring and digitizing a transducer measurement. These functions include transducer excitation, signal gain and anti-aliasing filtering, A/D conversion, linearization and digital filtering, and sample rate decimation. The functions are programmable and are set up from information stored in a local Transducer Electronic Data Sheet (TEDS). In addition, the module performs continuous self-calibration and self-test to maintain 0.01% accuracy over its entire operating temperature range for periods of one year without manual recalibration. The module operates in conjunction with a VME-based data acquisition system.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / The Common Airborne Instrumentation System (CAIS) was developed under the auspices of the Department of Defense to promote standardization, commonality, and interoperability among flight test instrumentation. The central characteristic of CAIS is a common suite of equipment used across service boundaries and in many airframe and weapon systems. The CAIS system has many advanced capabilities which must be tested during ground support and system test. There is a need for a common set of low cost, highly capable ground support hardware and software tools to facilitate these tasks. The ground support system should combine commonly available PC-based telemetry tools with unique devices needed for CAIS applications (such as CAIS Bus Emulator, CAIS Hardware Simulator, etc.). An integrated software suite is imperative to support this equipment. A CAIS Ground Support Unit (GSU) has been developed to promote these CAIS goals. This paper presents the capabilities and features of a PC-based CAIS GSU, emphasizing those features that are unique to CAIS. Hardware tools developed to provide CAIS Bus Emulation and CAIS Hardware Simulation are also described.

International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California / This paper describes a system in which multiple embedded processors are used for real-time processing of telemetry streams from satellites and radars. Embedded EPC-5 modules are plugged into VME slots in a Loral System 550. Telemetry streams are acquired and decommutated by the System 550, and selected parameters are packetized and appended to a mailbox which resides in VME memory. A Windows-based program continuously fetches packets from the mailbox, processes the data, writes to log files, displays processing results on screen, and sends messages via a modem connected to a serial port.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / MIL-STD-1553 multiplex data buses are commonly used to link complex software-controlled systems in modern aircraft. The software in these aircraft is routinely updated; each update requires flight testing. Also, sophisticated weapons and electronic warfare systems which are integrated into operationally-ready aircraft must be routinely evaluated. The simplest way to perform the required evaluation is to record all the data from the multiplex data buses during an operational flight; these data can then be replayed and examined after the flight. Traditionally, some operational systems had to be disabled or removed from an aircraft to allow installation of a data acquisition system. This paper discusses a MILSTD- 1553 multiplex bus Record-All Small Data Acquisition System (RASDAS) installed in a McDonnell Douglas CF-188 fighter aircraft to record all data from two 1553 multiplex data buses without displacing any operational equipment. The specific requirements and constraints associated with evaluating the integrated systems of a CF-188 aircraft are examined; further, RASDAS implementation in this aircraft type is discussed from planning to flight evaluation.