基于电动机电流信号双谱分析的齿轮传动故障诊断

电动机电流信号分析广泛应用于电动机本身的监测,但用该项技术监测与电动机相连设备的研究却很少。提出应用异步电动机的电流信号的调制信号双谱分析方法,实现对与电动机连接的齿轮传动系统的故障监测。试验表明调制信号双谱波峰的升高可以作为检测故障的依据。齿轮的故障可通过观测相关轴的双频波峰的变化进行诊断,与齿轮直接相连的轴产生较大的波峰增高,而与齿轮相邻的轴产生较小的波峰增高但轴不对中的故障可以只观测与该轴相应的双频波峰增高来确定。

人群分类与车内噪声声品质主观评价研究(英文)

本文以等响处理后的车内噪声为研究对象,进行噪声声品质的主观评价研究。研究发现,人群分类处理对于揭示噪声声品质的主观感知属性起着重要的作用。对于评价者分类处理之后,两类评价者对于车内噪声的偏好性均可采用一个维度表示,并可直接采用成对比较法的直接排序法获得;一类评价者的偏好性与低沉度成正比,而另一类评价者与低沉度成反比。如果未进行人群分类处理,则不能很好地解释其主观感知属性。

Achieving high bit rate logical stochastic resonance in a bistable system by adjusting parameters

The phenomenon of logical stochastic resonance （LSR） in a nonlinear bistable system is demonstrated by numerical simulations and experiments. However, the bit rates of the logical signals are relatively low and not suitable for practical applications. First, we examine the responses of the bistable system with fixed parameters to different bit rate logic input signals, showing that an arbitrary high bit rate LSR in a bistable system cannot be achieved. Then, a normalized transform of the LSR bistable system is introduced through a kind of variable substitution. Based on the transform, it is found that LSR for arbitrary high bit rate logic signals in a bistable system can be achieved by adjusting the parameters of the system, setting bias value and amplifying the amplitudes of logic input signals and noise properly. Finally, the desired OR and AND logic outputs to high bit rate logic inputs in a bistable system are obtained by numerical simulations. The study might provide higher feasibility of LSR in practical engineering applications.

A Study of Motor Bearing Fault Diagnosis using Modulation Signal Bispectrum Analysis of Motor Current Signals

Failure of induction motors are a large concern due to its influence over industrial production. Motor current signature analysis (MCSA) is common practice in industry to find motor faults. This paper presents a new approach to detection and diagnosis of motor bearing faults based on induction motor stator current analysis. Tests were performed with three bearing conditions: baseline, outer race fault and inner race fault. Because the signals associated with faults produce small modulations to supply component and high nose levels, a modulation signal bispectrum (MSB) is used in this paper to detect and diagnose different motor bearing defects. The results show that bearing faults can induced a detestable amplitude increases at its characteristic frequencies. MSB peaks show a clear difference at these frequencies whereas conventional power spectrum provides change evidences only at some of the frequencies. This shows that MSB has a better and reliable performance in extract small changes from the faulty bearing for fault detection and diagnosis. In addition, the study also show that current signals from motors with variable frequency drive controller have too much noise and it is unlikely to discriminate the small bearing fault component.

A Transient Enhancement Method for Two-Stage Helicopter Gearbox Fault Diagnosis Based on ALE

Periodical impulse component is one of typical fault characteristics in vibration signals from rotating machinery. However, this component is very small in the early stage of the fault and masked by various noises such as gear meshing components modulated by shaft frequency, which make it difficult to extract accurately for fault detection. The adaptive line enhancer (ALE) is an effective technique for separating sinusoidals from broad-band components of an input signal for detecting the presence of sinusoids in white noise. In this paper, ALE is explored to suppress the periodical gear meshing frequencies and enhance the fault feature impulses for more accurate fault diagnosis. The results obtained from simulated and experimental vibration signals of a two stage helical gearbox prove that the ALE method is very effective in reducing the periodical gear meshing noise and making the impulses in vibration very clear in the time-frequency analysis. The results show a clear difference between the baseline and 30% tooth damage of a helical gear which has not been detected successfully in author’s previous studies.

Preface

Diagnostics and condition monitoring are aspects of a field of engineering that aims to manage the health of engineering machinery and structures,but which has increasing applicability to many other complex systems in the world from the medical care of people,through the reliability of supply chain logistics to the secure operation of a large and complex organisation.The management of health generally requires a number of sequential steps,which are usually as follows:the detection of any abnormality in the procedural operation of the system,the location of the abnormal behaviour within the system,an assessment of the severity of the abnormality and identification of the potential system vulnerabilities that result from it,a detailed diagnosis of the problem including the identification of its root cause,and finally a predictive assessment of the future prospects for the continued operation of the system,including any remedial action that should be taken to minimise impact and maximise continued operational performance.

A New Method for Modelling and Simulation of the Dynamic Behaviour of the Wheel-rail contact

This paper presents a new method for modelling and simulation of the dynamic behaviour of the wheel-rail contact. The proposed dynamic wheel-rail contact model comprises wheel-rail contact geometry, normal contact problem, tangential contact problem and wheelset dynamic behaviour on the track. This two-degree of freedom model takes into account the lateral displacement of the wheelset and the yaw angle. Single wheel tread rail contact is considered for all simulations and Kalker’s linear theory and heuristic non-linear creep models are employed. The second order differential equations are reduced to first order and the forward velocity of the wheelset is increased until the wheelset critical velocity is reached. This approach does not require solving mathematical equations in order to estimate the critical velocity of the dynamic wheel-rail contact model. The mathematical model is implemented in Matlab using numerical differentiation method. The simulated results compare well with the estimated results based on classical theory related to the dynamic behaviour of rail-wheel contact so the model is validated.

Applicability of nonmetric multidimensional scaling to noise quality research

With loudness-equalized car interior noise as sound stimuli, the work focused on apphcabihty of nonmetric multidimensional scaling （NMDS） to sound quality research. It is presented that NMDS is an effective tool for subjective assessment research of sound quality, when listeners are clustered through correlation between hsteners. With this key clustering process, the perceptual structure of car interior noise with strong consistency is revealed. The results shown that： for car interior noise, ‘preference＇ can be regarded as a main sub-dimension in ‘similarity＇ space and listeners could be divided into two groups; For both groups of listeners, the perceptual ‘preference＇ can be characterized as one-dimensional descriptor, with one group has a positive relation to ‘low-frequency＇, while another group has a negative relation to ‘low- frequency＇.