Statistical Fault Diagnosis Methods by Using Higher-Order Correlation Information between Sound and Vibration

It is important to specify the occurrence and cause of failure of machines without stopping the machines because of increased use of various complex industrial systems. In this study, two new diagnosis methods based on the correlation information between sound and vibration emitted from the machine are derived. First, a diagnostic method which can detect the part of machine with fault among the assumed several faults is proposed by measuring simultaneously the time series data on sound and vibration. Next, a diagnosis method based on the estimation of the changing information of correlation between sound and vibration is considered by using prior information in only normal situation. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.

Quality of correlation in quantum information

A strong and stable correlation in quantum information is of high quality for quantum information processing.We define two quantities,selective average correlation and ripple coefficient,to evaluate the quality of correlation in quantum information in a time interval.As a new communication channel,Heisenberg spin chains are widely investigated.We select a two-qubit Heisenberg XXZs pin chain with Dzyaloshinskii-Moriya interaction in an inhomogeneous magnetic field as an example,and use the two quantities to evaluate the qualities of the correlation in quantum information with different measures.The result shows that,if the time evolutions are similar,there needs only evaluating one of them to know when the correlation has high quality for quantum information processing.

Novel Fault Detection Optimization Algorithm for Single Event Effect system Based on Multi-information Entropy Fusion

Fault detection caused by single event effect( SEE) in system was studied,and an improved fault detection algorithm by fusing multi-information entropy for detecting soft error was proposed based on multi-objective detection approach and classification management method. In the improved fault detection algorithm, the analysis model of posteriori information with corresponding multi-fault alternative detection points was formulated through correlation information matrix, and the maximum incremental information entropy was chosen as the classification principle for the optimal detection points. A system design example was given to prove the rationality and feasibility of this algorithm.This fault detection algorithm can achieve the purpose of fault detection and resource configuration with high efficiency.

Vibration time series analysis of bubbling and turbulent fluidization

A non-intrusive vibration monitoring technique was used to study the hydrodynamics of a gas-solid fluidized bed. Experiments were carried out in a 15 cm diameter fluidized bed using 226,470 and 700 um sand particles at various gas velocities, covering both bubbling and turbulent regimes. Auto correlation function, mutual information function, Hurst exponent analysis and power spectral density function were used to analyze the fluidized bed hydrodynamics near the transition point from bubbling to turbulent fluidization regimes. The first pass of the autocorrelation function from one half and the time delay at which it becomes zero, and also the first minimum of the mutual information, occur at a higher time delay in comparison to stochastic systems, and the values of time delays were maximum at the bubbling to turbulent transition gas velocity. The maximum value of Hurst exponent of macro structure occurred at the onset of regime transition from bubbling to turbulent. Further increase in gas velocity after that regime transition velocity causes a decrease in the Hurst exponent of macro structure because of breakage of large bubbles to small ones. The results showed these methods are capable of detecting the regime transition from bubbling to turbulent fluidization conditions using vibration signals.