Diesel knock combustion and its detection using acoustic emission

This paper presents an experimental investigation into the detection of excessive Diesel knock using acoustic emission signals. Three different dual-fuel Diesel engine operating regimes were induced into a compression ignition (Diesel) engine operating on both straight Diesel fuel and two different mixtures of fumigated ethanol and Diesel. The experimentally induced engine operating regimes were; normal, or Diesel only operation, acceptable dual-fuel operation and dual-fuel operation with excessive Diesel knock. During the excessive Diesel knock operating regime, high rates of ethanol substitution induced potentially damaging levels of Diesel knock. Acoustic emission data was captured along with cylinder pressure, crank-angle encoder, and top-dead centre signals for the different engine operating regimes. Using these signals, it was found that acoustic emission signals clearly distinguished between the two acceptable operating regimes and the operating regime experiencing excessive Diesel knock. It was also found that acoustic emission sensor position is critical. The acoustic emission sensor positioned on the block of the engine clearly related information concerning the level of Diesel knock occurring in the engine whist the sensor positioned on the head of the engine gave no indication concerning Diesel knock severity levels.

Field-of-view, detection range, and false alarm trade-offs in vision-based aircraft detection

This paper presents a survey of previously presented vision based aircraft detection flight test, and then presents new flight test results examining the impact of camera field-of view choice on the detection range and false alarm rate characteristics of a vision-based aircraft detection technique. Using data collected from approaching aircraft, we examine the impact of camera fieldof-view choice and confirm that, when aiming for similar levels of detection confidence, an improvement in detection range can be obtained by choosing a smaller effective field-of-view (in terms of degrees per pixel).

Real-time detection of concealed chemical hazards under ambient light conditions using Raman spectroscopy

Current concerns regarding terrorism and international crime highlight the need for new techniques for detecting unknown and hazardous substances. A novel Raman spectroscopy-based technique, spatially offset Raman spectroscopy (SORS), was recently devised for non-invasively probing the contents of diffusely scattering and opaque containers. Here, we demonstrate a modified portable SORS sensor for detecting concealed substances in-field under different background lighting conditions. Samples including explosive precursors, drugs and an organophosphate insecticide (chemical warfare agent surrogate) were concealed inside diffusely scattering packaging including plastic, paper and cloth. Measurements were carried out under incandescent and fluorescent light as well as under daylight to assess the suitability of the probe for different real-life conditions. In each case, it was possible to identify the substances against their reference Raman spectra in less than one minute. The developed sensor has potential for rapid detection of concealed hazardous substances in airports, mail distribution centers and customs checkpoints.

Spectrum sensing using two-stage detection to compensate for reduced primary user duty cycle

Spectrum sensing is considered to be one of the most important tasks in cognitive radio. One of the common assumption among current spectrum sensing detectors is the full presence or complete absence of the primary user within the sensing period. In reality, there are many situations where the primary user signal only occupies a portion of the observed signal and the assumption of primary user duty cycle not necessarily fulfilled. In this paper we show that the true detection performance can degrade from the assumed achievable values when the observed primary user exhibits a certain duty cycle. Therefore, a two-stage detection method incorporating primary user duty cycle that enhances the detection performance is proposed. The proposed detector can improve the probability of detection under low duty cycle at the expense of a small decrease in performance at high duty cycle.

Unusual scene detection using distributed behaviour model and sparse representation

The ability to detect unusual events in surviellance footage as they happen is a highly desireable feature for a surveillance system. However, this problem remains challenging in crowded scenes due to occlusions and the clustering of people. In this paper, we propose using the Distributed Behavior Model (DBM), which has been widely used in computer graphics, for video event detection. Our approach does not rely on object tracking, and is robust to camera movements. We use sparse coding for classification, and test our approach on various datasets. Our proposed approach outperforms a state-of-the-art work which uses the social force model and Latent Dirichlet Allocation.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

Correlation-based damage detection for complicated truss bridges using multi-layer genetic algorithms

The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.

Assessing of circuit breaker restrike risks using computer simulation and wavelet analysis

A breaker restrike is an abnormal arcing phenomenon, leading to a possible breaker failure. Eventually, this failure leads to interruption of the transmission and distribution of the electricity supply system until the breaker is replaced. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks in power systems. In 2008 a non-intrusive radiometric restrike measurement method and a restrike hardware detection algorithm were developed by M.S. Ramli and B. Kasztenny. However, the limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current restrike detection methods and algorithms require the use of wide bandwidth current transformers and high voltage dividers. A restrike switch model using Alternative Transient Program (ATP) and Wavelet Transforms which support diagnostics are proposed. Restrike phenomena become a new diagnostic process using measurements, ATP and Wavelet Transforms for online interrupter monitoring. This research project investigates the restrike switch model Parameter „A. dielectric voltage gradient related to a normal and slowed case of the contact opening velocity and the escalation voltages, which can be used as a diagnostic tool for a vacuum circuit-breaker (CB) at service voltages between 11 kV and 63 kV. During current interruption of an inductive load at current quenching or chopping, a transient voltage is developed across the contact gap. The dielectric strength of the gap should rise to a point to withstand this transient voltage. If it does not, the gap will flash over, resulting in a restrike. A straight line is fitted through the voltage points at flashover of the contact gap. This is the point at which the gap voltage has reached a value that exceeds the dielectric strength of the gap. This research shows that a change in opening contact velocity of the vacuum CB produces a corresponding change in the slope of the gap escalation voltage envelope. To investigate the diagnostic process, an ATP restrike switch model was modified with contact opening velocity computation for restrike waveform signature analyses along with experimental investigations. This also enhanced a mathematical CB model with the empirical dielectric model for SF6 (sulphur hexa-fluoride) CBs at service voltages above 63 kV and a generalised dielectric curve model for 12 kV CBs. A CB restrike can be predicted if there is a similar type of restrike waveform signatures for measured and simulated waveforms. The restrike switch model applications are used for: computer simulations as virtual experiments, including predicting breaker restrikes; estimating the interrupter remaining life of SF6 puffer CBs; checking system stresses; assessing point-on-wave (POW) operations; and for a restrike detection algorithm development using Wavelet Transforms. A simulated high frequency nozzle current magnitude was applied to an Equation (derived from the literature) which can calculate the life extension of the interrupter of a SF6 high voltage CB. The restrike waveform signatures for a medium and high voltage CB identify its possible failure mechanism such as delayed opening, degraded dielectric strength and improper contact travel. The simulated and measured restrike waveform signatures are analysed using Matlab software for automatic detection. Experimental investigation of a 12 kV vacuum CB diagnostic was carried out for the parameter determination and a passive antenna calibration was also successfully developed with applications for field implementation. The degradation features were also evaluated with a predictive interpretation technique from the experiments, and the subsequent simulation indicates that the drop in voltage related to the slow opening velocity mechanism measurement to give a degree of contact degradation. A predictive interpretation technique is a computer modeling for assessing switching device performance, which allows one to vary a single parameter at a time; this is often difficult to do experimentally because of the variable contact opening velocity. The significance of this thesis outcome is that it is a non-intrusive method developed using measurements, ATP and Wavelet Transforms to predict and interpret a breaker restrike risk. The measurements on high voltage circuit-breakers can identify degradation that can interrupt the distribution and transmission of an electricity supply system. It is hoped that the techniques for the monitoring of restrike phenomena developed by this research will form part of a diagnostic process that will be valuable for detecting breaker stresses relating to the interrupter lifetime. Suggestions for future research, including a field implementation proposal to validate the restrike switch model for ATP system studies and the hot dielectric strength curve model for SF6 CBs, are given in Appendix A.

Global flash multifocal electroretinogram : early detection of local functional changes and its correlations with optical coherence tomography and visual field loss in diabetic eyes

Purpose: To investigate the correlations of the global flash multifocal electroretinogram (MOFO mfERG) with common clinical visual assessments – Humphrey perimetry and Stratus circumpapillary retinal nerve fiber layer (RNFL) thickness measurement in type II diabetic patients. Methods: Forty-two diabetic patients participated in the study: ten were free from diabetic retinopathy (DR) while the remainder suffered from mild to moderate non-proliferative diabetic retinopathy (NPDR). Fourteen age-matched controls were recruited for comparison. MOFO mfERG measurements were made under high and low contrast conditions. Humphrey central 30-2 perimetry and Stratus OCT circumpapillary RNFL thickness measurements were also performed. Correlations between local values of implicit time and amplitude of the mfERG components (direct component (DC) and induced component (IC)), and perimetric sensitivity and RNFL thickness were evaluated by mapping the localized responses for the three subject groups. Results: MOFO mfERG was superior to perimetry and RNFL assessments in showing differences between the diabetic groups (with and without DR) and the controls. All the MOFO mfERG amplitudes (except IC amplitude at high contrast) correlated better with perimetry findings (Pearson’s r ranged from 0.23 to 0.36, p<0.01) than did the mfERG implicit time at both high and low contrasts across all subject groups. No consistent correlation was found between the mfERG and RNFL assessments for any group or contrast conditions. The responses of the local MOFO mfERG correlated with local perimetric sensitivity but not with RNFL thickness. Conclusion: Early functional changes in the diabetic retina seem to occur before morphological changes in the RNFL.