Various modulated hybrid pulse compression for advanced ultrasound technology and its non-destructive testing application

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonUltrasound is a sound wave with a frequency greater than 20 kHz. It obeys the propagation laws of reflection, refraction, diffraction, and scattering. Because of its excellent physical properties, ultrasound has been used in a variety of fields, including industry and medicine. There are many techniques that use ultrasound as detection methods in the field of non-destructive testing (NDT) and medical treatment. In a typical ultrasound system, a sine wave or pulse signal with a fit window is considered as the transmitted signal. This results in low accuracy in some special situations, such as testing high attenuation material. The signal-to-noise ratio (SNR) is an important parameter for evaluating the performance of an echo signal or imaging. However, under high attenuation materials or noisy conditions, SNR will significantly decrease. Under these conditions, valid information in the received signal will be obscured by noise. This situation can cause errors in the detection system. In an ultrasound system, increasing the SNR of the echo signal can reduce detection errors and improve accuracy. First, in ultrasound systems, a noise reduction method based on pulse compression has been investigated and applied. Convolution and modulation were used in the proposed method to generate new hybrid emission signals. The hybrid codes can only be distinguished by a special matched filter that is related to the emission signals. The echo signals processed by a special matched filter have a high main lobe and a very low side lobe, implying that the side lobe level and SNR will increase. When compared to traditional denoising methods, the proposed method can significantly improve SNR while only requiring a change in the transmission code without requiring any hardware changes. Second, in a low voltage ultrasonic testing (UT) system, a hybrid phase modulated code excitation method based on the Barker and Golay code pairs was proposed and implemented. In a UT system, the lower the pulsing voltage, the lower the SNR of the signal. Attempting to reduce the pulsing voltage will result in noisy and unusable results. The proposed hybrid method can increase main lobe power in low average power transmitted and received signals. The proposed method has been theoretically examined and then tested in simulation studies. The experimental results showed that the main lobe level of the code produced by convolution of Barker code and Golay code pairs is around 30 dB higher than the simple pulse, and the main lobe of the combined code is around 15 dB higher than the traditional Barker code, with the sidelobe being the same as the Baker code that constitutes this combined code. As a result, the combined code’s peak sidelobe level (PSL) is approximately 5 dB lower than the traditional Barker code. Because of this, UT devices can be used in real-world applications, even in low-voltage situations. Third, the torsional wave mode T(0,1) hybrid phase modulated code excitation method has been proposed and applied in a long range guided wave testing (GWT) system. The proposed hybrid method combines the Barker and Golay code pair and is modulated by a fitted sine wave. This method combines the benefits of these two coding methods and increases code length flexibility. The SNR and PSL of the processed signal are used to assess the method’s performance. The proposed method has been tested in GWT using both finite element method (FEM) simulation and real-world testing. The results of pipeline laboratory testing revealed that the best increasing SNR of BCG is around 33.5 dB when compared to a simple pulse at 40 kHz, and the peak sidelobe level is around -24 dB. The proposed method, as well as other traditional methods, were used for pipeline defect detection testing. The results of the tests showed that the hybrid coded excitation method can detect notches that are difficult to detect with other methods and effectively improve the SNR. The applied method’s increasing SNR is around 6 dB, which agrees with the simulation and laboratory testing results. In UGW testing, the proposed coded excitation method was highly regarded. Finally, the non-linear frequency modulated (NLFM) hybrid pulse compression method has been proposed and implemented in an ultrasound imaging (UI) system. The proposed code combines the Barker and Golay codes and is modulated using a non-linear frequency method based on the Zak transform. Theoretical research on signal generation and decoding has been presented, as well as cyst phantom simulation. The simulation analysis shows that the novel code method can improve the contrast ratio by 15.96 dB and the SNR by 36.64 dB when compared to a simple pulse signal. Overall, this study demonstrated that the proposed novel method can be effectively used in ultrasound detection methods to improve performance

A Low-Power, Highly Stabilized Three-Electrode Potentiostat Using Subthreshold Techniques

Implantable micro- and nano- sensors and implantable microdevices (IMDs) have demonstrated potential for monitoring various physiological parameters such as glucose, lactate, CO2 [carbon dioxide], pH, etc. Potentiostats are essential components of electrochemical sensors such as glucose monitoring devices for diabetic patients. Diabetes is a metabolic disorder associated with insufficient production or inefficient utilization of insulin. The most important role of this enzyme is to regulate the metabolic breakdown of glucose generating the necessary energy for human activities. Diabetic patients typically monitor their blood glucose levels by pricking a fingertip with a lancing device and applying the blood to a glucose meter. This painful process may need to be repeated once before each meal and once 1- 4 hour after meal. Patients may need to inject insulin manually to keep the blood glucose level at 3.9-6.7 mmol [mili mol] /liter. Frequent glucose measurement can help reduce the long term complication of this disease which includes kidney disease, nerve damage, heart and blood vessel diseases, gum disease, glaucoma and etc. Having an implanted close loop insulin delivery system can help increase the frequency of glucose measurement and the accuracy of insulin injection. The implanted close loop system consists of three main blocks: (1) an electrochemical sensor in conjunction with a potentiostat to measure the blood glucose level, (2) a control block that defines the level of insulin injection and (3) an implanted insulin pump. To provide a continuous health-care monitoring the implantable unit has to be powered up using wireless techniques. Minimizing the power consumption associated with the implantable system can improve the battery life times or minimize the power transfer through the human body. The focus of this work is on the design of low-power potentiostats for the implantable glucose monitoring system. This work addresses the conventional structures in potentiostat design and the problems associated with these designs. Based on this discussion a modification is made to improve the stability without increasing the complexity of the system. The proposed design adopts a subthreshold biasing scheme for the design of a highly-stabilized, low-power potentiostats

Testing a CMOS operational amplifier circuit using a combination of oscillation and IDDQ test methods

This work presents a case study, which attempts to improve the fault diagnosis and testability of the oscillation testing methodology applied to a typical two-stage CMOS operational amplifier. The proposed test method takes the advantage of good fault coverage through the use of a simple oscillation based test technique, which needs no test signal generation and combines it with quiescent supply current (IDDQ) testing to provide a fault confirmation. A built in current sensor (BICS), which introduces insignificant performance degradation of the circuit-under-test (CUT), has been utilized to monitor the power supply quiescent current changes in the CUT. The testability has also been enhanced in the testing procedure using a simple fault-injection technique. The approach is attractive for its simplicity, robustness and capability of built-in-self test (BIST) implementation. It can also be generalized to the oscillation based test structures of other CMOS analog and mixed-signal integrated circuits. The practical results and simulations confirm the functionality of the proposed test method

Phenotypic and Genome-Wide Analysis of an Antibiotic-Resistant Small Colony Variant (SCV) of Pseudomonas aeruginosa

Small colony variants (SCVs) are slow-growing bacteria, which often show increased resistance to antibiotics and cause latent or recurrent infections. It is therefore important to understand the mechanisms at the basis of this phenotypic switch.One SCV (termed PAO-SCV) was isolated, showing high resistance to gentamicin and to the cephalosporine cefotaxime. PAO-SCV was prone to reversion as evidenced by emergence of large colonies with a frequency of 10(-5) on media without antibiotics while it was stably maintained in presence of gentamicin. PAO-SCV showed a delayed growth, defective motility, and strongly reduced levels of the quorum sensing Pseudomonas quinolone signal (PQS). Whole genome expression analysis further suggested a multi-layered antibiotic resistance mechanism, including simultaneous over-expression of two drug efflux pumps (MexAB-OprM, MexXY-OprM), the LPS modification operon arnBCADTEF, and the PhoP-PhoQ two-component system. Conversely, the genes for the synthesis of PQS were strongly down-regulated in PAO-SCV. Finally, genomic analysis revealed the presence of mutations in phoP and phoQ genes as well as in the mexZ gene encoding a repressor of the mexXY and mexAB-oprM genes. Only one mutation occurred only in REV, at nucleotide 1020 of the tufA gene, a paralog of tufB, both encoding the elongation factor Tu, causing a change of the rarely used aspartic acid codon GAU to the more common GAC, possibly causing an increase of tufA mRNA translation. High expression of phoP and phoQ was confirmed for the SCV variant while the revertant showed expression levels reduced to wild-type levels.By combining data coming from phenotypic, gene expression and proteome analysis, we could demonstrate that resistance to aminoglycosides in one SCV mutant is multifactorial including overexpression of efflux mechanisms, LPS modification and is accompanied by a drastic down-regulation of the Pseudomonas quinolone signal quorum sensing system

MEMS Accelerometers

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc

Induced pluripotency: dissecting the role of ADAR-mediated RNA editing

Whereas RNA editing of adenosine-to-inosine (A-to-I) catalyzed by ADAR proteins is intricately linked to transcriptome structural and functional diversity, how this RNA chemical modification contributes to overriding somatic cell identity during reprogramming to pluripotency is largely unexplored. Here, I show that the absence of ADAR1-mediated A-to-I editing hampers mesenchymal-to-epithelial transition and impedes the acquisition of pluripotency. Mechanistically, my data reveals that lack of A-to-I editing induces aberrant innate immune response programs through double-stranded sensor MDA5, unleashing endoplasmic reticulum stress and hindering epithelial fate acquisition. Thus, this study establishes a critical role for A-to-I RNA modification in cell fate transitions during reprogramming and opens new avenues for exploring the involvement of ADAR1 in health and disease

A Novel test structure for automated measurement of charge transfer efficiency in charge coupled imaging devices

None provided

Computing Intelligence Technique and Multiresolution Data Processing for Condition Monitoring

Condition monitoring (CM) of rotary machines has gained increasing importance and extensive research in recent years. Due to the rapid growth of data volume, automated data processing is necessary in order to deal with massive data efficiently to produce timely and accurate diagnostic results. Artificial intelligence (AI) and adaptive data processing approaches can be promising solutions to the challenge of large data volume. Unfortunately, the majority of AI-based techniques in CM have been developed for only the post-processing (classification) stage, whereas the critical tasks including feature extraction and selection are still manually processed, which often require considerable time and efforts but also yield a performance depending on prior knowledge and diagnostic expertise. To achieve an automatic data processing, the research of this PhD project provides an integrated framework with two main approaches. Firstly, it focuses on extending AI techniques in all phases, including feature extraction by applying Componential Coding Neural Network (CCNN) which has been found to have unique properties of being trained through unsupervised learning, capable of dealing with raw datasets, translation invariance and high computational efficiency. These advantages of CCNN make it particularly suitable for automated analyzing of the vibration data arisen from typical machine components such as the rolling element bearings which exhibit periodic phenomena with high non-stationary and strong noise contamination. Then, once an anomaly is detected, a further analysis technique to identify the fault is proposed using a multiresolution data analysis approach based on Double-Density Discrete Wavelet Transform (DD-DWT) which was grounded on over-sampled filter banks with smooth tight frames. This makes it nearly shift-invariant which is important for extracting non-stationary periodical peaks. Also, in order to denoise and enhance the diagnostic features, a novel level-dependant adaptive thresholding method based on harmonic to signal ratio (HSR) is developed and implemented on the selected wavelet coefficients. This method has been developed to be a semi-automated (adaptive) approach to facilitate the process of fault diagnosis. The developed framework has been evaluated using both simulated and measured datasets from typical healthy and defective tapered roller bearings which are critical parts of all rotating machines. The results have demonstrated that the CCNN is a robust technique for early fault detection, and also showed that adaptive DD-DWT is a robust technique for diagnosing the faults induced to test bearings. The developed framework has achieved multi-objectives of high detection sensitivity, reliable diagnosis and minimized computing complexity