Induction motor diagnosis by advanced notch FIR filters and the wigner-ville distribution

During the last years, several time-frequency decomposition tools have been applied for the diagnosis of induction motors, for those cases in which the traditional procedures, such as motor current signature analysis, cannot yield the necessary response. Among them, the Cohen distributions have been widely selected to study transient and even stationary operation due to their high-resolution and detailed information provided at all frequencies. Their main drawback, the cross-terms, has been tackled either modifying the distribution, or carrying out a pretreatment of the signal before computing its time-frequency decomposition. In this paper, a filtering process is proposed that uses advanced notch filters in order to remove constant frequency components present in the current of an induction motor, prior to the computation of its distribution, to study rotor asymmetries and mixed eccentricities. In transient operation of machines directly connected to the grid, this procedure effectively eliminates most of the artifacts that have prevented the use of these tools, allowing a wideband analysis and the definition of a precise quantification parameter able to follow the evolution of their state. © 1982-2012 IEEE

Recent Advances in Variable Digital Filters

Variable digital filters are widely used in a number of applications of signal processing because of their capability of self-tuning frequency characteristics such as the cutoff frequency and the bandwidth. This chapter introduces recent advances on variable digital filters, focusing on the problems of design and realization, and application to adaptive filtering. In the topic on design and realization, we address two major approaches: one is the frequency transformation and the other is the multi-dimensional polynomial approximation of filter coefficients. In the topic on adaptive filtering, we introduce the details of adaptive band-pass/band-stop filtering that include the well-known adaptive notch filtering

Computer-Aided Design of Switched-Capacitor Filters

This thesis describes a series of computer methods for the design of switched-capacitor filters. Current software is greatly restricted in the types of transfer function that can be designed and in the range of filter structures by which they can be implemented. To solve the former problem, several new filter approximation algorithms are derived from Newton's method, yielding the Remez algortithm as a special case (confirming its convergency properties). Amplitude responses with arbitrary passband shaping and stopband notch positions are computed. Points of a specified degree of tangency to attenuation boundaries (touch points) can be placed in the response, whereby a family of transfer functions between Butterworth and elliptic can be derived, offering a continuous trade-off in group delay and passive sensitivity properties. The approximation algorithms have also been applied to arbitrary group delay correction by all-pass functions. Touch points form a direct link to an iterative passive ladder design method, which bypasses the need for Hurwitz factorisation. The combination of iterative and classical synthesis methods is suggested as the best compromise between accuracy and speed. It is shown that passive ladder prototypes of a minimum-node form can be efficiently simulated by SC networks without additional op-amps. A special technique is introduced for canonic realisation of SC ladder networks from transfer functions with finite transmission at high frequency, solving instability and synthesis difficulties. SC ladder structures are further simplified by synthesising the zeros at +/-2fs which are introduced into the transfer function by bilinear transformation. They cause cancellation of feedthrough branches and yield simplified LDI-type SC filter structures, although based solely on the bilinear transform. Matrix methods are used to design the SC filter simulations. They are shown to be a very convenient and flexible vehicle for computer processing of the linear equations involved in analogue filter design. A wide variety of filter structures can be expressed in a unified form. Scaling and analysis can readily be performed on the system matrices with great efficiency. Finally, the techniques are assembled in a filter compiler for SC filters called PANDDA. The application of the above techniques to practical design problems is then examined. Exact correction of sinc(x), LDI termination error, pre-filter and local loop telephone line weightings are illustrated. An optimisation algorithm is described, which uses the arbitrary passband weighting to predistort the transfer function for response distortions. Compensation of finite amplifier gain-bandwidth and switch resistance effects in SC filters is demonstrated. Two commercial filter specifications which pose major difficulties for traditional design methods are chosen as examples to illustrate PANDDA's full capabilities. Significant reductions in order and total area are achieved. Finally, test results of several SC filters designed using PANDDA for a dual-channel speech-processing ASIC are presented. The speed with which high-quality, standard SC filters can be produced is thus proven

Localized harmonic motion imaging

Localized Harmonic Motion (LHM) Imaging is a new technique of ultrasound imaging which uses the localized stimulus of the oscillatory ultrasonic radiation force as produced by a modulated signal, and estimates the resulting harmonic displacement in the tissue in order to assess its underlying mechanical properties. This method can be highly localized and is considered as a non-invasive modality. In this thesis we first present the background information for LHM imaging and we compare this technique to other tissue mechanical properties imaging techniques. We then describe a setup for LHM induction and how the data is acquired and processed. We first focus on the transducer configuration, its characteristics and the housing built to combine the transducers, then the alignment of these transducers so they are confocal and can induce and detect motion in tissues, and finally we describe the local harmonic motion experiment setup including a supporting system and the induction/detection module. One of the most critical stages is the acquisition of the signal, since signals acquired by the imaging transducer always contain different sources of noise such as acoustic (standing waves, reflection from the tank, mechanical cross-talk between the transducers) and electric noise (electric cross-talk, noise of the high power amplifier) that we need to filter. Electronic filters were designed and implemented into our LHM experiment system. Additionally, digital filters were designed to further improve the performance of the system. We applied several kinds of digital notch filters (finite impulse response (FIR) and infinite impulse response (IIR) classes) and conduct analysis on the performance when obtaining LHM displacement information. After finishing the filtering and the setup, we performed LHM displacement experiments. We analyzed the obtained displacements as well as the noise observed in the final displacement waveforms, and the influence of analog and digital filters on the displacement detection. We finally measured the displacements induced by LHM on samples with different Young modulus and were able to differentiate them by the amplitude of the motion. Finally, we performed optimizations on the algorithm for LHM displacement calculations. Due to the large amount (462) of RF signals, it will typically take around 1h for a 41x41 points image. It was found that the digital filter was the most time consuming part of the processing and it was parallelized using graphics processing unit (GPU)

Suppression of narrowband interference generated by the power supply of the railway systems in public defibrillators devices

A specific problem using the public access defibrillators arises at the railway stations. Some countries as Germany, Austria, Switzerland, Norway, Sweden and Slovenia are using AC railroad net power-supply system with rated frequency of 16.6(6) Hz, frequency modulated from 15.69 Hz to 17.36 Hz. The power supply frequency contaminates the electrocardiogram (ECG). It is difficult to be suppressed or eliminated due to the fact that it considerably overlaps the frequency spectra of the ECG. The interference impedes the automated decision of the public access defibrillators whether a patient should be (or should not be) shocked. The aim of study of this thesis is the suppression of the 16.6(6) Hz interference generated by the power supply of the railway systems in few central european countries. For this purpose, an adaptive filter and a band-stop filter are used and the results obtained are compared in order to get the most suitable solution.Ingeniería Técnica de Telecomunicación, especialidad Sonido e ImagenTelekomunikazio Ingeniaritza Teknikoa. Soinua eta Irudia Berezitasun

Improving particular components of the audio signal chain: optimising listening in the control room

In the field of audio engineering there is a constant need for optimising the listening situation. Listening to, judging and finally optimising the recorded material are essential tasks of audio engineers. The author of this contextual statement has been working in the field of audio engineering since 1993. In addition, various research projects have been undertaken in this field. A selection of three research areas and their published outputs are presented in this contextual statement: Research Area 1: Improving acoustic modules to increase efficiency in the acoustical treatment of control rooms Research Area 2: Measuring time alignment errors, testing their impact on the listening experience and providing solutions for time alignment of loudspeakers Research Area 3: Using equalisation for correcting and shaping a loudspeaker's frequency response These research areas relate to a consistent listening 'defect' that leads to a blurred and broader sound image. Measures to overcome these defects are presented and proven to be effective by built prototypes and/or products. The results of the research are published in articles and books and can be experienced in the form of hardware systems such as acoustic modules or modified loudspeakers

BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients

Purpose: Brain–computer interface (BCI)-controlled assistive robotic systems have been developed with increasing success with the aim to rehabilitation of patients after brain injury to increase independence and quality of life. While such systems may use surgically implanted invasive sensors, non-invasive alternatives can be better suited due to the ease of use, reduced cost, improvements in accuracy and reliability with the advancement of the technology and practicality of use. The consumer-grade BCI devices are often capable of integrating multiple types of signals, including Electroencephalogram (EEG) and Electromyogram (EMG) signals. Materials and Methods: This paper summarizes the development of a portable and cost-efficient BCI-controlled assistive technology using a non-invasive BCI headset “OpenBCI” and an open source robotic arm, U-Arm, to accomplish tasks related to rehabilitation, such as access to resources, adaptability or home use. The resulting system used a combination of EEG and EMG sensor readings to control the arm. To avoid risks of injury while the device is being used in clinical settings, appropriate measures were incorporated into the software control of the arm. A short survey was used following the system usability scale (SUS), to measure the usability of the technology to be trialed in clinical settings. Results: From the experimental results, it was found that EMG is a very reliable method for assistive technology control, provided that the user specific EMG calibration is done. With the EEG, even though the results were promising, due to insufficient detection of the signal, the controller was not adequate to be used within a neurorehabilitation environment. The survey indicated that the usability of the system is not a barrier for moving the system into clinical trials. Implication on rehabilitation For the rehabilitation of patients suffering from neurological disabilities (particularly those suffering from varying degrees of paralysis), it is necessary to develop technology that bypasses the limitations of their condition. For example, if a patient is unable to walk due to the unresponsiveness in their motor neurons, technology can be developed that used an alternate input to move an exoskeleton, which enables the patient to walk again with the assistance of the exoskeleton. This research focuses on neuro-rehabilitation within the framework of the NHS at the Kent and Canterbury Hospital in UK. The hospital currently does not have any system in place for self-driven rehabilitation and instead relies on traditional rehabilitation methods through assistance from physicians and exercise regimens to maintain muscle movement. This paper summarises the development of a portable and cost-efficient BCI controlled assistive technology using a non-invasive BCI headset “OpenBCI” and an open source robotic arm, U-Arm, to accomplish tasks related to rehabilitation, such as access to resources, adaptability or home use. The resulting system used a combination of EEG and EMG sensor readings to control the arm, which could perform a number of different tasks such as picking/placing objects or assist users in eating

Digital signal processing algorithms and structures for adaptive line enhancing

Imperial Users onl