Particle Swarm Optimization-Support Vector Machine Model for Machinery Fault Diagnoses in High-Voltage Circuit Breakers

According to statistic data,machinery faults contribute to largest proportion of High-voltage circuit breaker failures,and traditional maintenance methods exist some disadvantages for that issue.Therefore,based on the wavelet packet decomposition approach and support vector machines,a new diagnosis model is proposed for such fault diagnoses in this study.The vibration eigenvalue extraction is analyzed through wavelet packet decomposition,and a four-layer support vector machine is constituted as a fault classifier.The Gaussian radial basis function is employed as the kernel function for the classifier.The penalty parameter c and kernel parameterδof the support vector machine are vital for the diagnostic accuracy,and these parameters must be carefully predetermined.Thus,a particle swarm optimizationsupport vector machine model is developed in which the optimal parameters c andδfor the support vector machine in each layer are determined by the particle swarm algorithm.The validity of this fault diagnosis model is determined with a real dataset from the operation experiment.Moreover,comparative investigations of fault diagnosis experiments with a normal support vector machine and a particle swarm optimization back-propagation neural network are also implemented.The results indicate that the proposed fault diagnosis model yields better accuracy and e-ciency than these other models.

Investigation of the hydrodynamics of slug flow in airlift pumps

A slug flow model considering the dispersed bubbles entrained from the tail of Taylor bubble(TB) and recoalesced with the successive TB was proposed. Experiment was conducted to test the validity of this model by using a high-speed camcorder and particle image velocimetry(PIV). It was found that the model was valid for predicting the characteristics of slug flow in airlift pump within average error of 14%. Moreover, large pipe diameter was found to accelerate the rise velocity of TB and decreases void fraction in liquid slug by a small margin.

Simultaneous pyridine biodegradation and nitrogen removal in an aerobic granular system

Simultaneous pyridine biodegradation and nitrogen removal were successfully achieved in a sequencing batch reactor（SBR） based on aerobic granules. In a typical SBR cycle, nitritation occurred obviously after the majority of pyridine was removed, while denitrification occurred at early stage of the cycle when oxygen consumption was aggravated. The effect of several key operation parameters, i.e., air flow rate, influent NH4~＋-N concentration,influent p H and pyridine concentration, on nitritation, pyridine degradation and total nitrogen（TN） removal, was systematically investigated. The results indicated that high air flow rate had a positive effect on both pyridine degradation and nitritation but a negative impact of overhigh air flow rate. With the increase of NH4~＋ dosage, both nitritation and TN removal could be severely inhibited. Slightly alkaline condition, i.e., pH 7.0–8.0, was beneficial for both pyridine degradation and nitritation. High pyridine dosage often resulted in the delay of both pyridine degradation and nitritation. Besides, extracellular polymeric substances production was affected by air flow rate, NH4~＋ dosage, pyridine dosage and p H.In addition, high-throughput sequencing analysis demonstrated that Bdellovibrio and Paracoccus were the dominant species in the aerobic granulation system. Coexistence of pyridine degrader, nitrification related species, denitrification related species, polymeric substances producer and self-aggregation related species was also confirmed by highthroughput sequencing.

Fractal-based dynamic response of a pair of spur gears considering microscopic surface morphology

The meshing surfaces of a gear pair are rough from a microscopic perspective and the surface topography will affect the dynamic response.To study the influence of real surface topography on the gear system dynamic performance,this paper es-tablishes a 3-degree of freedom transverse-torsional dynamic model with regard to the morphology of the interface.By fractal theory,the expression of backlash be-tween gears is modified based on the height of asperities.The time-varying sifness is calculated according to the fractal method rather than assuming a constant,which is more realistic.The dimensionless dynamic differ ential equations are established and solved with surface topography affected backlash function and time-varying sifess.The dynamic response of the gear system with respec to fractal dimension and fractal roughness is analyzed.

Targeted lipidomics reveals plasmalogen phosphatidylethanolamines and storage triacylglycerols as the major systemic lipid aberrations in Bietti crystalline corneoretinal dystrophy

First reported by Bietti in 1937(Bietti,1937),Bietti crystalline corneoretinal dystrophy(BCD,OMIM 210370)is a rare,autosomal recessively inherited progressive retinal disease.The disease is more common in Asian populations,particularly in Chinese and Japanese(Li et al.,2004).The prevalence of BCD is estimated at 1 in 67,000,representing around only 21,000 individuals in China(Ng et al.,2016).CYP4V2 was identified as the disease-causing gene in 2004.It encodes a member of the cytochrome P450 family 4.