Statistical gear health analysis which is robust to fluctuating loads and operating speeds

Condition-based maintenance is concerned with the collection and interpretation of data to support maintenance decisions. The non-intrusive nature of vibration data enables the monitoring of enclosed systems such as gearboxes. It remains a significant challenge to analyze vibration data that are generated under fluctuating operating conditions. This is especially true for situations where relatively little prior knowledge regarding the specific gearbox is available. It is therefore investigated how an adaptive time series model, which is based on Bayesian model selection, may be used to remove the non-fault related components in the structural response of a gear assembly to obtain a residual signal which is robust to fluctuating operating conditions. A statistical framework is subsequently proposed which may be used to interpret the structure of the residual signal in order to facilitate an intuitive understanding of the condition of the gear system. The proposed methodology is investigated on both simulated and experimental data from a single stage gearbox. © 2011 Elsevier Ltd. All rights reserved.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

High efficiency liquid crystal lasers giving "white light" emission from arrays and flexible substrates

The self-organization of the helical structure of chiral nematic liquid crystals combined with their sensitivity to electric fields makes them particularly interesting for low-threshold, wavelength tunable laser devices. We have studied these organic lasers in detail, ranging from the influence specific macroscopic properties, such as birefringence and order parameter, have on the output characteristics, to practical systems in the form of two-dimensional arrays, double-pass geometries and paintable lasers. Furthermore, even though chiral nematics are responsive to electric fields there is no facile means by which the helix periodicity can be adjusted, thereby allowing laser wavelength tuning, without adversely affecting the optical quality of the resonator. Therefore, in addition to studying the liquid crystal lasers, we have focused on finding a novel method with which to alter the periodicity of a chiral nematic using electric fields without inducing defects and degrading the optical quality factor of the resonator. This paper presents an overview of our research, describing (i) the correlation between laser output and material properties,(ii) the importance of the gain medium,(iii) multicolor laser arrays, and (iv) high slope efficiency (>60%) silicon back-plane devices. Overall we conclude that these materials have great potential for use in versatile organic laser systems.

Energy efficiency, resilience to future climates and long-term sustainability: the role of the built environment

Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.

Energy efficiency, resilience to future climates and long-term sustainability: the role of the built environment.

Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in our existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.

Statistical image modelling using interscale phase relationships of complex wavelet coefficients

A novel method for modelling the statistics of 2D photographic images useful in image restoration is defined. The new method is based on the Dual Tree Complex Wavelet Transform (DT-CWT) but a phase rotation is applied to the coefficients to create complex coefficients whose phase is shift-invariant at multiscale edge and ridge features. This is in addition to the magnitude shift invariance achieved by the DT-CWT. The increased correlation between coefficients adjacent in space and scale provides an improved mechanism for signal estimation. © 2006 IEEE.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

High-efficiency InGaN/GaN quantum well structures on large area silicon substrates

The growth techniques which have enabled the realization of InGaN-based multi-quantum-well (MQW) structures with high internal quantum efficiencies (IQE) on 150mm (6-in.) silicon substrates are reviewed. InGaN/GaN MQWs are deposited onto GaN templates on large-area (111) silicon substrates, using AlGaN strain-mediating interlayers to inhibit thermal-induced cracking and wafer-bowing, and using a SiN x interlayer to reduce threading dislocation densities in the active region of the MQW structure. MQWs with high IQE approaching 60% have been demonstrated. Atomic resolution electron microscopy and EELS analysis have been used to study the nature of the important interface between the Si(111) substrate and the AlN nucleation layer. We demonstrate an amorphous SiN x interlayer at the interface about 2nm wide, which does not, however, prevent good epitaxy of the AlN on the Si(111) substrate. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.