A simple packet aggregation technique for fault detection

Packet monitoring has become a standard technique in network management and when applied to a large‐scale transit network yields a high volume of packets. To overcome this problem, we discuss the behavior of packets and present a symptom‐based packet aggregation technique which is useful for fault detection. Copyright © 2000 John Wiley & Sons, Ltd.     

A fuzzy model for path delay fault detection

A fuzzy model is proposed to analyze the effectiveness of test pairs targeting path delay faults. This model is accurate enough to rank nonrobust tests by accounting for conditions not considered in existing models. It remains fully consistent with the traditional test robustness analysis. Finally, it also provides a coverage metric to be used to rank whole test sets. The proposed model has been implemented in a logic level path delay fault simulator. Its accuracy has been validated, for a set of combinational benchmarks, by means of a Monte Carlo logic-level event-driven path delay fault simulator.     

Statistically matched wavelet-based method for detection of power quality events

This article presents a new technique for the detection of power quality (PQ) events by using statistically matched wavelet. The statistically matched wavelet is designed based on the characteristics of the PQ event using the concept of fractional Brownian motion. The proposed technique is compared with Daubechies wavelet to show its superiority in the detection of PQ events. To classify the detected events, an iterative closest point algorithm is used which classifies the detected event even in the presence of outlier points and Gaussian noise. The method is applied to classify the various PQ events like transient, sag, swell and harmonics and the results are simulated using MATLAB version 7.3.     

A modified sequential detection procedure

A modified version of sequential testing is proposed and applied to discrete-time signal detection. The resulting detection procedure exhibits simplicity in structure and in analysis and retains most of the optimal features of sequential detection. Also, two Simple and efficient truncation schemes are suggested for the proposed detection procedure which is unrealizable without truncation.     

A wavelet-based multiresolution statistical model for texture

A multiresolution statistical model, consisting of random fields in wavelet subbands, is proposed for texture, and has produced promising results in texture synthesis experiments, the basic idea here is that a complex random field model, e.g., one that contains long-range and nonlinear spatial correlations, can be constructed from several simpler ones.     

A generalized two-threshold detection procedure

A modified sequential procedure for testing binary hypotheses with different means, proposed by C.C. Lee and J.B. Thomas (ibid., vol.IT-30, no.1, p.16-23, Jan. 1984), is generalized for application to the case of multiple hypotheses with different means/variances of the Gaussian distribution. The method constitutes a two-threshold test for fixed-size packages of samples with a sequential procedure of discarding the package for which no decision is reached and subsequently testing a new package. The objective is to find an optimum package size N₀ which leads to the minimum overall average sample number (ASN) for a given overall error probability. An optimization algorithm is developed to extend the application of the Lee-Thomas procedure to the M-ary case. Performance characteristics of the generalized two-threshold (GTT) test procedure are compared with those of conventional sequential as well as fixed-sample-size (FSS) methods. It is shown for the M-ary different means/variances cases that for low error rates the number of samples required by the GTT test is, on the average, approximately half that needed by a FSS test. However, it is somewhat more than the ASN obtained with a conventional sequential test. With decreasing error probabilities the GTT test performance approaches that of conventional sequential methods     

A NEW PROBABILISTIC APPROACH FOR ESTIMATING FAULT DETECTION PROBABILITY

A new approach to calculate fault detection probabilities is presented. Fault-free simulation is used in the approach. The quantities of controllability and observability are defined as probabilities of controlling and observing the nodes in the circuit. The probability distribution of random signals on the circuit nodes is analyzed, and it is proved that controllability is in normal distribution. Thus the unbiasing estimation of the fault detection probability can be obtained. According to the concept of observability, we deal with the fan-out nodes. The fault coverages for actual circuits obtained from this approach agree favorably with the fault simulation results.     

A wavelet-based method for multiscale tomographic reconstruction

The authors represent the standard ramp filter operator of the filtered-back-projection (FBP) reconstruction in different bases composed of Haar and Daubechies compactly supported wavelets. The resulting multiscale representation of the ramp-filter matrix operator is approximately diagonal. The accuracy of this diagonal approximation becomes better as wavelets with larger numbers of vanishing moments are used. This wavelet-based representation enables the authors to formulate a multiscale tomographic reconstruction technique in which the object is reconstructed at multiple scales or resolutions. A complete reconstruction is obtained by combining the reconstructions at different scales. The authors' multiscale reconstruction technique has the same computational complexity as the FBP reconstruction method. It differs from other multiscale reconstruction techniques in that (1) the object is defined through a one-dimensional multiscale transformation of the projection domain, and (2) the authors explicitly account for noise in the projection data by calculating maximum a posteriori probability (MAP) multiscale reconstruction estimates based on a chosen fractal prior on the multiscale object coefficients. The computational complexity of this maximum a posteriori probability (MAP) solution is also the same as that of the FBP reconstruction. This result is in contrast to commonly used methods of statistical regularization, which result in computationally intensive optimization algorithms.     

A wavelet-based method for action potential detection from extracellular neural signal recording with low signal-to-noise ratio

We present a method for the detection of action potentials, an essential first step in the analysis of extracellular neural signals. The low signal-to-noise ratio (SNR) and similarity of spectral characteristic between the target signal and background noise are obstacles to solving this problem and, thus, in previous studies on experimental neurophysiology, only action potentials with sufficiently large amplitude have been detected and analyzed. In order to lower the level of SNR required for successful detection, we propose an action potential detector based on a prudent combination of wavelet coefficients of multiple scales and demonstrate its performance for neural signal recording with varying degrees of similarity between signal and noise. The experimental data include recordings from the rat somatosensory cortex, the giant medial nerve of crayfish, and the cutaneous nerve of bullfrog. The proposed method was tested for various SNR values and degrees of spectral similarity. The method was superior to the Teager energy operator and even comparable to or better than the optimal linear detector. A detection ratio higher than 80% at a false alarm ratio lower than 10% was achieved, under an SNR of 2.35 for the rat cortex data where the spectral similarity was very high.     

A fault detection sensor for circuit aging using double-edge-triggered flip-flop

In nanoscale technology, transistor aging is one of the most critical problems that impact on the reliability of circuits. Aging sensor is a good online way to detect the circuit aging, which performs during the operating time with no influence of the normal operation of circuits. In this paper, a Double-edge-triggered Detection Sensor for circuit Aging (DSDA) is proposed, which employs data signal of logic circuits as its clock to control the sampling process. The simulation is done by Hspice using 45 nm technology. The results show that this technique is not sensitive to the process variations. The worst case of the detection precision is more than 80% under the different process variations. It can detect aging fault effectively with the 8% power cost and 30% performance cost.     

Generic wavelet-based hyperspectral classification applied to vegetation stress detection

This communication studies the detection of vegetation stress in hyperspectral data. Compared to traditional vegetation stress indices, the proposed approach uses the complete reflectance spectrum and its wavelet representation. The detection strategy is formulated as a classification problem. Experiments are conducted on fruit tree stress detection. The experiments show the superior performance of the proposed strategy and demonstrate its generic nature.     

Using immunology principles for fault detection

The immune system is a cognitive system of complexity comparable to the brain and its computational algorithms suggest new solutions to engineering problems or new ways of looking at these problems. Using immunological principles, a two- (or three-) module algorithm is developed which is capable of launching a specific response to an anomalous situation for diagnostic purposes. Experimental results concerning fault detection in an induction motor are presented as an example illustrating how the immune-based system operates, discussing its capabilities, drawbacks, and future developments.     

A wavelet-based KL-like expansion for wide-sense stationary randomprocesses

We describe a wavelet-based series expansion for wide-sense stationary processes. The expansion coefficients are uncorrelated random variables, a property similar to that of a Karhunen-Loeve (KL) expansion. Unlike the KL expansion, however, the wavelet-based expansion does not require the solution of the eigen equation and does not require that the process be time-limited. This expansion also has advantages over Fourier series, which is often used as an approximation to the KL expansion, in that it completely eliminates correlation and that the computation for its coefficients are more stable over large time intervals. The basis functions of this expansion can be obtained easily from wavelets of the Lemaire-Meyer (1990) type and the power spectral density of the process. Finally, the expansion can be extended to some nonstationary processes, such as those with wide-sense stationary increments     

A DSP for DCT-based and wavelet-based video codecs for consumerapplications

We have developed a video digital signal processor (VDSP1) which performs real-time encoding and decoding for discrete cosine transform- (DCT-) based algorithms such as ITU-T H.261, H.263 and wavelet-based subband encoding algorithms. This LSI is suitable for consumer applications, as it was implemented using 0.5 μm CMOS process technology to realize compactness (one million transistors on 65 mm²) and low power (maximum: 560 mW). It features a processing unit which performs wavelet filtering at high speeds, a compact DCT circuit, and a fast, flexible DRAM interface for low-cost systems. At 40 MHz, a single chip is capable of processing quarter common intermediate format (QCIF) (176×144 pixels) size pictures at a rate greater than 15 frames/s     

A quality-on-demand algorithm for wavelet-based compression of electrocardiogram signals

For the compression of medical signals such as electrocardiogram (ECG), excellent reconstruction quality of a highly compressed signal can be obtained by using a wavelet-based approach. The most widely used objective quality criterion for the compressed ECG is called the percent of root-mean-square difference (PRD). In this paper, given a user-specified PRD, an algorithm is proposed to meet the PRD demand by searching for an appropriate bit rate in an automatic, smooth, and fast manner for the wavelet-based compression. The bit rate searching is modeled as a root-finding problem for a one-dimensional function, where an unknown rate-distortion curve represents the function and the desired rate is the root to be sought. A solution derived from root-finding methods in numerical analysis is proposed. The proposed solution is incorporated in a well-known wavelet-based coding strategy called set partitioning in hierarchical trees. ECG signals taken from the MIT/BIH database are tested, and excellent results in terms of convergence speed, quality variation, and coding performance are obtained.     

A model of asynchronous machines for stator fault detection and isolation

This paper presents a new model of asynchronous machines. This model allows one to take into account unbalanced stator situations which can be produced by stator faults like short circuits in windings. A mathematical transformation is defined and applied to the classical abc model equations. All parameters which affect this new model can be known online. This makes the model very useful for control algorithms and fault detection and isolation algorithms. The model is checked by comparing simulation data with actual data obtained from laboratory experiments.     

A deep network solution for intelligent fault detection in analog circuit

Analog Integrated Circuits and Signal Processing - Automatic fault diagnosis in analog electronic circuits is one of the interesting and important cases for researchers of this field that has...     

A novel wavelet-based generalized sidelobe canceller

This paper presents a novel narrow-band adaptive beamformer with the generalized sidelobe canceller (GSC) as the underlying structure. The new beamformer employs a wavelet-based approach for the design of the blocking matrix of the GSC, which is now constituted by a set of regular M-band wavelet filters. Such a construction of the blocking matrix can not only block the desired signals from the lower path as required provided the wavelet filters have sufficiently high regularity, but it also encompasses the widely used one with ones and minus ones along the diagonals as a special case. In addition, it possesses two advantageous features. First, the eigenvalue spreads of the covariance matrices of the blocking matrix outputs, as demonstrated in various scenarios, are decreased as compared with those of previous approaches. Since the popular least mean squares (LMS) algorithm has been notorious for its slow convergence rate, the reduction of the eigenvalue spreads can, in general, accelerate the convergence speed of the succeeding LMS algorithm. Second, the new beamformer belongs to a specific type of partially adaptive beamformers, wherein only a portion of the available degree of freedom is utilized in the adaptive processing. As such, the overall computational complexity is substantially reduced when compared to previous works. The issues of choosing the parameters involved for superior performance are also addressed. Simulation results are furnished as well to justify this new approach     

A wavelet-based watermarking algorithm for ownership verificationof digital images

Access to multimedia data has become much easier due to the rapid growth of the Internet. While this is usually considered an improvement of everyday life, it also makes unauthorized copying and distributing of multimedia data much easier, therefore presenting a challenge in the field of copyright protection. Digital watermarking, which is inserting copyright information into the data, has been proposed to solve the problem. In this paper, we first discuss the features that a practical digital watermarking system for ownership verification requires. Besides perceptual invisibility and robustness, we claim that the private control of the watermark is also very important. Second, we present a novel wavelet-based watermarking algorithm. Experimental results and analysis are then given to demonstrate that the proposed algorithm is effective and can be used in a practical system.