Health Assessment and Fault Classification for Centrifugal Pump Using Logistic Regression

Real-time health monitoring of industrial components and systems that can detect, classify and predict impending faults is critical to reducing operating and maintenance cost. This paper presents a logistic regression based prognostic method for on-line health assessment and failure modes classification. System condition is evaluated by processing the information gathered from access controllers or sensors mounted at different points in the system, and maintenance is performed only when the failure/ malfunction prognosis indicates instead of periodic maintenance inspections. The wavelet packet decomposition and fast Fourier transform (FFT) technique is used to extract features from non-stationary vibrations signals, wavelet package energies and fundamental frequency amplitude are used as features and Principal Component Analysis (PCA) is used to features reduction. Reduced features are input into logistic regression (LR) models to assess machine health condition and identify possible failure modes. The maximum likelihood method is used to determine parameters of LR models. The effectiveness and feasibility of this methodology have been illustrated by applying the method to a real centrifugal pump

Complete Axiomatization for Divergent-Sensitive Bisimulations in Basic Process Algebra with Prefix Iteration

AbstractWe study the divergent-sensitive spectrum of weak bisimulation equivalences in the setting of process algebra. To represent the infinite behavior, we consider the prefix iteration extension of a fragment of Milner's CCS. The prefix iteration operator is a variant on the binary version of the Kleene star operator obtained by restricting the first argument to be an atomic action and allows us to capture the notion of recursion in a pure algebraic way. We investigate four typical divergent-sensitive weak bisimulation equivalences, namely divergent, stable, completed and divergent stable weak bisimulation equivalences from an axiomatic perspective. A lattice of distinguishing axioms is developed and thus pure equational axiomatizations for these congruences are obtained. A large part of the current paper is devoted to a considerable complicated proof for completeness. This work, to some extent, sheds light on distinct semantics of divergence

Study on Evaluation Models of Highway Safety Based on Catastrophe Theory

Evaluating safety performance of first-class highways in China is important due to their high mortality rates. Traditional models for statistical crash prediction and traffic conflict techniques require long periods of data collection which is time-consuming and labor-intensive. This paper introduces a safety evaluation method based on catastrophe theory for highways in China. The method firstly divides the highway into multiple road sections and uses video-based road detection (VRD) system to collect video data of existing road conditions. Then, experienced drivers and experts are invited to watch the collected videos to establish a multilayer safety index system and assign values to bottom indexes. By applying catastrophe theory, a general safety index is derived, which indicates the relative safety level of a road section. Finally, all road sections can be ranked based on the general safety index. A case study shows encouraging results where (1) the safety index is highly correlated with real mortality rates and (2) the safety index successfully identifies most dangerous road sections. The proposed method can be considered as a promising supplementary safety evaluation method that could help traffic engineers to better understand safety implications of first-class highways in China

Cooperative non-orthogonal multiple access in cognitive radio

This letter studies the application of non-orthogonal multiple access to a downlink cognitive radio (termed CR-NOMA) system. A new cooperative transmission scheme is proposed aimed at exploiting the inherent spatial diversity offered by the CR-NOMA system. The closed-form analytical results are developed to show that the cooperative transmission scheme gives better performance when more secondary users participate in relaying, which helps achieve the maximum diversity order at secondary user and a diversity order of two at primary user. The simulations are performed to validate the performance of the proposed scheme and the accuracy of the analytical results

An approach to fault diagnosis for gearbox based on reconstructed energy and support vector machine

Normally sensors can only be mounted on the outer shell of gearbox, which induce more difficulties to diagnose gearbox such as serious noise contamination, signal coupling and transmission path effect. Taking into account the unique structural characteristics of gearbox, this paper presents a novel method of using reconstructed energy and Support Vector Machine (SVM) to diagnose various failure or fault modes of gears, shafts and bearings. First, FFT is performed to get the frequency domain information of raw vibration signals. Then, a series of reconstruction filters are designed to remove unwanted information and enhance signal components of interest, which correspond to specific fault information of various elements. Finally, SVM is utilized to classify different faults such as bent shaft, broken gear and defect bearing. The proposed approach has proved to be effective in solving gearbox faults classification of the 2009 PHM Conference Data Analysis Competition