Investigation of a Rotating Shaft with a Novel Integrated Wireless Accelerometer

Rotating shafts are the most critical components of rotating machines such as motors, pumps, engines and turbines. Due to their heavy workloads, defects are more likely to develop during operation. There are many techniques used to monitor shaft defects by analysing the vibration of the shaft as well as the instantaneous angular speed (IAS) of the shaft. The signals are measured either using non-contact techniques such as laser-based measurement or indirect measurement such as the vibration on bearing housings. The advancement in low cost and low power Micro Electro Mechanical Systems (MEMS) make it possible to develop an integrated wireless sensor mounted on rotating shafts directly. This can make the fault diagnosis of rotating shafts more effective as it is likely to capture more details of shaft dynamics. This paper presents a novel integrated wireless accelerometer mounted directly on a rotating shaft and demonstrates that it can effectively monitor different degree of misalignments occurring commonly in a shaft system

Superior memory efficiency of quantum devices for the simulation of continuous-time stochastic processes

Continuous-time stochastic processes pervade everyday experience, and the simulation of models of these processes is of great utility. Classical models of systems operating in continuous-time must typically track an unbounded amount of information about past behaviour, even for relatively simple models, enforcing limits on precision due to the finite memory of the machine. However, quantum machines can require less information about the past than even their optimal classical counterparts to simulate the future of discrete-time processes, and we demonstrate that this advantage extends to the continuous-time regime. Moreover, we show that this reduction in the memory requirement can be unboundedly large, allowing for arbitrary precision even with a finite quantum memory. We provide a systematic method for finding superior quantum constructions, and a protocol for analogue simulation of continuous-time renewal processes with a quantum machine.Comment: 13 pages, 8 figures, title changed from original versio

CNV and nervous system diseases - what's new?

Several new genomic disorders caused by copy number variation (CNV) of genes whose dosage is critical for the physiological function of the nervous system have been recently identified. Dup(7)(q11.23) patients carry duplications of the genomic region deleted in Williams-Beuren syndrome, they are characterized by prominent speech delay. The phenotypes of Potocki-Lupski syndrome and MECP2 duplication syndrome were neuropsychologically examined in detail, which revealed autism as an endophenotype and a prominent behavioral feature of these disorders. Tandem duplication of LMNB1 was reported to cause adult-onset autosomal dominant leukodystrophy. PAFAH1B1/LIS1 and YWHAE, which were deleted in isolated lissencephaly (PAFAH1B1/LIS1 alone) and Miller-Dieker syndrome (both genes), were found to be duplicated in patients with developmental delay. Finally, two novel microdeletion syndromes affecting 17q21.31 and 15q13.3, as well as their reciprocal duplications, were also identified. In this review, we provide an overview of the phenotypic manifestation of these syndromes and the rearrangements causing them. Copyright (C) 2009 S. Karger AG, Base

Non-parametric models in the monitoring of engine performance and condition: Part 2: non-intrusive estimation of diesel engine cylinder pressure and its use in fault detection

An application of the radial basis function model, described in Part 1, is demonstrated on a four-cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the trained model are validated against measured data and an example is given of the application of this model to the detection of a slight fault in one of the cylinders