Transactions of the Institute of Measurement and Control

Bin Zhang, ; Khawaja, Taimoor; Patrick, Romano; Vachtsevanos, George; Orchard, Marcos; Saxena, Abhinav

doi: 10.1177/0142331209357844pmid: N/A

With increased system complexity, condition-based maintenance (CBM) becomes a promising solution for system safety by detecting faults and scheduling maintenance procedures before faults become severe failures resulting in catastrophic events. For CBM of many mechanical systems, fault diagnosis and failure prognosis based on vibration signal analysis are essential techniques. Noise originating from various sources, however, often corrupts vibration signals and degrades the performance of diagnostic and prognostic routines, and consequently, the performance of CBM. In this paper, a new de-noising structure is proposed and applied to vibration signals collected from a testbed of the main gearbox of a helicopter subjected to a seeded fault. The proposed structure integrates a blind deconvolution algorithm, feature extraction, failure prognosis and vibration modelling into a synergistic system, in which the blind deconvolution algorithm attempts to arrive at the true vibration signal through an iterative optimization process. Performance indexes associated with quality of the extracted features and failure prognosis are addressed, before and after de-noising, for validation purposes.

Grieve, B.D.; Murphy, S.; Burnett-Thompson, A.; York, T.A.

doi: 10.1177/0142331208100108pmid: N/A

A new electrical tomograph that is designed specifically for low-cost and accessibility is described. It offers a unique environment for three-dimensional (3D) electrical impedance imaging. Using a cross-bar switch, the hardware can support ad hoc measurement strategies and is linked to control software, which integrates the complete process from 3D finite element modelling through to image reconstruction and generation of movie files. Digital signal processing algorithms are used to derive measurements of complex impedance from the measurement of amplitude and phase difference between the driven and received signals. This is achieved by rapid sampling of sinusoidal signals having frequencies between 1.0 Hz and 1.0 MHz. The instrument can deliver about 100 measurements per second, corresponding to a typical 16-electrode tomography frame, and is targeted at processes with modest dynamics or for laboratory development of tomographic applications and algorithms. The latest version (LCT2) is described here and uses a USB2 link to provide data transfer rates up to 20 MBytes per second. Sinusoidal excitation signals are derived using a direct digital synthesis chip. Voltage measurements are digitized to 16-bit accuracy and the standard system can accommodate 64 electrodes. The software embraces the EIDORS-3D soft-field reconstruction algorithms and the resulting impedance imaging capability of the device and characterization of the signals are described.

Qing Lu, ; Mahfouf, Mahdi

doi: 10.1177/0142331209103414pmid: N/A

The ‘raison d’être’ of self-organizing fuzzy logic control (SOFLC) algorithms is the performance index table, which normally issues the adequate corrections to the low-level control given certain performance criteria. In the standard SOFLC architecture, the performance index table is generic, fixed a priori and is of a ‘grid-partition’ structure making the whole scheme inefficient in terms of computational complexity and performance. In this paper, we propose a new model-free SOFLC architecture whereby the performance index table is ‘dynamic’, of free structure and starting from an empty table. The new proposed architecture includes the required mechanisms to ensure self-organization such as those associated with the individual evaluation via an online genetic algorithm (GA) and the fine-tuning of individual regeneration range for micro-GAs, to optimize the rules of the performance index table and enhance the system’s performance. Results of experiments on a non-linear muscle relaxation process show that the proposed control scheme is superior to the standard SOFLC algorithm in terms of performance and robustness against the system input/output scaling factors selection and parameter variations.

Barták, Roman; Čepek, Ondřej

doi: 10.1177/0142331208100099pmid: N/A

Constraint-based scheduling is a powerful tool for solving complex real-life scheduling problems thanks to a natural integration of special solving algorithms encoded in so-called global constraints. Global constraints describe subproblems of the scheduling problem, eg, allocation of activities to a disjunctive resource. Filtering algorithms behind these constraints are used to prune the search space by eliminating options that violate the constraint. The filtering algorithms are frequently expressed in the form of propagation rules that react to some change appearing during problem solving, eg, adding a new precedence relation, by proposing a derived restriction, eg, shrinking a time window. These changes can be invoked by other constraints or they can be a result of some search decision. This paper describes new incremental propagation rules integrating propagation of precedence relations and time windows for activities allocated to a disjunctive resource. Moreover, the rules also cover so-called optional activities that may or may not be present in the final schedule.