Spectral correction method based on improved flat-top convoluted window for parameter estimation of power harmonic

Točna procjena harmonijskog parametra je važan zadatak u obradi signala elektroenergetskog sustava. Predlaže se nova vrsta flat-top prozora koja se generira vlastitim konvolucijama brzo padajućeg flat-top prozora (FDMS-FT) u domenu vremena. Proučavaju se značajke bočnog i glavnog režnja novog prozora. Nadalje, kako bi se poboljšala glatkoća glavnog režnja novog prozora, optimiziraju se koeficijenti matičnog prozora. Predstavlja se izmjenjivi algoritam ispravke razlike faze duljine prozora baziran na novom prozoru kako bi se procijenio strujni harmonični parametar. Kako bi se provjerila učinkovitost i točnost prikazane metode, provedeno je nekoliko računalnih simulacija i praktičnih eksperimenata s višefrekvencijskim strujnim signalima. Rezultati pokazuju da predložena metoda može učinkovito smanjiti opseg računanja i daje visok parametar točnosti procjene harmonijske snage.Accurate estimation of harmonic parameter is an important task in signal processing of power system. A new class of flat-top windows is proposed, which is generated by self-convolutions of the fast-decaying minimum-sidelobe flat-top (FDMS-FT) window in the time-domain. The mainlobe and sidelobe features of the new window are studied. In addition, to improve the flatness of mainlobe of the new window, the coefficients of its parent window are optimized. A window-length changeable discrete phase difference correction algorithm based on the new window is presented to estimate power harmonic parameter. In order to inspect the efficiency and accuracy of the presented method, several computer simulations and practical experiments were conducted with power multi-frequency signals. Results show that the proposed method can reduce the computation load efficiently and gives a high parameter estimation accuracy of power harmonic

Alternative techniques for detection of inaccessible pipe corrosion

Testing for corrosion in the petrochemical industry has always been a significant challenge which takes up a large portion of the operating expenditure. Whereas major advancements have been made for the detection of general corrosion, inspection at inaccessible locations, such as at pipe supports, remains a demanding prospect; this signifies the need for an alternative technique, capable of dealing with various surface conditions encountered when testing at such locations including weld patches, T-joints, surface roughness and coatings. Long range guided waves are commonly used to detect relatively severe defects in plain sections of pipe but are less suited to inspection at supports because the support itself gives significant reflection. The reflection coefficient at the support reduces with frequency so it would be beneficial to test at higher frequencies, which can also improve the sensitivity of the test to smaller, pitting-type defects. Following the attractive properties of the Higher Order Mode Cluster (HOMC) proposed by Balasubramaniam et al. (IIT Madras), this research starts by investigating the nature of the mode cluster and shows that the features of this method are essentially those of the A1 mode in the high frequency-thickness regime. The study then goes on to investigate the possibility of exciting a single mode Lamb wave with low dispersion at a frequency-thickness of around 20 MHz-mm. Excitation of the A1 mode was considered because of its relationship with HOMC and due to its non-dispersive nature and low surface motion at such frequency-thickness products; this makes it attractive for inspection at supports since it will be unaffected by the support itself and also by surface roughness and attenuative coatings. The thesis then explores the relative ability of different transducer types for single mode excitation in the medium and high frequency-thickness regimes; here the practical feasibility of exciting the A1 mode at around 20 MHz-mm, in spite of its low surface motion, is investigated. Next, a systematic performance analysis of the A1 mode compared to the existing inspection techniques is carried out and, finally the sensitivity of this technique to realistic 3-D pitting-type holes is established. The thesis shows that the A1 mode is an attractive tool for the detection of localized, sharp, severe defects that will be missed by standard, lower frequency guided wave testing.Open Acces

Investigation of Non-coherent Discrete Target Range Estimation Techniques for High-precision Location

Ranging is an essential and crucial task for radar systems. How to solve the range-detection problem effectively and precisely is massively important. Meanwhile, unambiguity and high resolution are the points of interest as well. Coherent and non-coherent techniques can be applied to achieve range estimation, and both of them have advantages and disadvantages. Coherent estimates offer higher precision but are more vulnerable to noise and clutter and phase wrap errors, particularly in a complex or harsh environment, while the non-coherent approaches are simpler but provide lower precision. With the purpose of mitigating inaccuracy and perturbation in range estimation, miscellaneous techniques are employed to achieve optimally precise detection. Numerous elegant processing solutions stemming from non-coherent estimate are now introduced into the coherent realm, and vice versa. This thesis describes two non-coherent ranging estimate techniques with novel algorithms to mitigate the instinct deficit of non-coherent ranging approaches. One technique is based on peak detection and realised by Kth-order Polynomial Interpolation, while another is based on Z-transform and realised by Most-likelihood Chirp Z-transform. A two-stage approach for the fine ranging estimate is applied to the Discrete Fourier transform domain of both algorithms. An N-point Discrete Fourier transform is implemented to attain a coarse estimation; an accurate process around the point of interest determined in the first stage is conducted. For KPI technique, it interpolates around the peak of Discrete Fourier transform profiles of the chirp signal to achieve accurate interpolation and optimum precision. For Most-likelihood Chirp Z-transform technique, the Chirp Z-transform accurately implements the periodogram where only a narrow band spectrum is processed. Furthermore, the concept of most-likelihood estimator is introduced to combine with Chirp Z-transform to acquire better ranging performance. Cramer-Rao lower bound is presented to evaluate the performance of these two techniques from the perspective of statistical signal processing. Mathematical derivation, simulation modelling, theoretical analysis and experimental validation are conducted to assess technique performance. Further research will be pushed forward to algorithm optimisation and system development of a location system using non-coherent techniques and make a comparison to a coherent approach

Reconstruction of undersampled signals and alignment in the frequency domain

Imperial Users onl

Interactive digital signal processor

The Interactive Digital Signal Processor (IDSP) is examined. It consists of a set of time series analysis Operators each of which operates on an input file to produce an output file. The operators can be executed in any order that makes sense and recursively, if desired. The operators are the various algorithms used in digital time series analysis work. User written operators can be easily interfaced to the sysatem. The system can be operated both interactively and in batch mode. In IDSP a file can consist of up to n (currently n=8) simultaneous time series. IDSP currently includes over thirty standard operators that range from Fourier transform operations, design and application of digital filters, eigenvalue analysis, to operators that provide graphical output, allow batch operation, editing and display information

New Digital Audio Watermarking Algorithms for Copyright Protection

This thesis investigates the development of digital audio watermarking in addressing issues such as copyright protection. Over the past two decades, many digital watermarking algorithms have been developed, each with its own advantages and disadvantages. The main aim of this thesis was to develop a new watermarking algorithm within an existing Fast Fourier Transform framework. This resulted in the development of a Complex Spectrum Phase Evolution based watermarking algorithm. In this new implementation, the embedding positions were generated dynamically thereby rendering it more difficult for an attacker to remove, and watermark information was embedded by manipulation of the spectral components in the time domain thereby reducing any audible distortion. Further improvements were attained when the embedding criteria was based on bin location comparison instead of magnitude, thereby rendering it more robust against those attacks that interfere with the spectral magnitudes. However, it was discovered that this new audio watermarking algorithm has some disadvantages such as a relatively low capacity and a non-consistent robustness for different audio files. Therefore, a further aim of this thesis was to improve the algorithm from a different perspective. Improvements were investigated using an Singular Value Decomposition framework wherein a novel observation was discovered. Furthermore, a psychoacoustic model was incorporated to suppress any audible distortion. This resulted in a watermarking algorithm which achieved a higher capacity and a more consistent robustness. The overall result was that two new digital audio watermarking algorithms were developed which were complementary in their performance thereby opening more opportunities for further research

Automatic roI detection for camera-based pulse-rate measurement

Remote photoplethysmography (rPPG) enables contactless measurement of pulse-rate by detecting pulse-induced colour changes on human skin using a regular camera. Most of existing rPPG methods exploit the subject face as the Region of Interest (RoI) for pulse-rate measurement by automatic face detection. However, face detection is a suboptimal solution since (1) not all the subregions in a face contain the skin pixels where pulse-signal can be extracted, (2) it fails to locate the RoI in cases when the frontal face is invisible (e.g., side-view faces). In this paper, we present a novel automatic RoI detection method for camerabased pulse-rate measurement, which consists of three main steps: subregion tracking, feature extraction, and clustering of skin regions. To evaluate the robustness of the proposed method, 36 video recordings are made of 6 subjects with different skin-types performing 6 types of head motion. Experimental results show that for the video sequences containing subjects with brighter skin-types and modest body motions, the accuracy of the pulse-rates measured by our method (94 %) is comparable to that obtained by a face detector (92 %), while the average SNR is significantly improved from 5.8 dB to 8.6 dB