A review on machinery diagnostics and prognostics implementing condition-based maintenance

Support vector machine in machine condition monitoring and fault diagnosis

Selecting the most efficient maintenance approach using fuzzy multiple criteria decision making

The oldest and most common maintenance and repair strategy is “fix it when it breaks”. The appeal of this approach is that no analysis or planning is required. The problems with this approach include the occurrence of unscheduled downtime at times that may be inconvenient, perhaps preventing accomplishment of committed production schedules. Unscheduled downtime has more serious consequences in applications such as aircraft engines. These problems provide motivation to perform maintenance and repair before the problem arises. The simplest approach is to perform maintenance and repair at pre-established intervals, defined in terms of elapsed or operating hours. This strategy can provide relatively high equipment reliability, but it tends to do so at excessive cost (higher scheduled downtimes). A further problem with time-based approaches is that failures are assumed to occur at specific intervals.

System health monitoring and prognostics — a review of current paradigms and practices

The role of maintenance in improving companies’ productivity and profitability

1.Introduction - aspects of maintenance. 2. Maintenance information systems. 3. Basic diagnostic techniques. 4. Vibration monitoring. 5. Fluid condition and particle monitoring. 6. Systems approach to condition monitoring. 7. Application of system condition monitoring. 8. Processing of diagnostics data. 9. Future developments of condition-based maintenance in manufacture. Index

Condition-based maintenance and machine diagnostics

This paper develops the use of principal component analysis as an aid to quality assurance. The sensitivity of the analysis to changes in the statistical characteristics of the measurements is examined. The analysis can reduce the number of time series that have to be monitored for quality assurance. The technique is to linearly combine groups of the measurements. This grouping of measurements excludes the use of the cusum as a quality assurance aid. A new quality monitoring process is proposed; the cumoderror, which enables the detection of mean level and variance changes in single or combined measurements.

https://ieeexplore.ieee.org/iel5/5266378/5268263/05268269.pdf

Principal component analysis of production data

The paper develops a methodology for the automatic test program generation (ATPG) for a large analogue circuit subject to component drifts. An optimization algorithm developed selects the best set of intermediate access points for a.c. and d.c. tests of the circuit.During ATPG, faults are simulated by varying each component over a wide range. Voltages measured at all available nodes are thus used in the pre-processing stage of node selection. An optimization procedure based on the discriminating power of measurements and separability between fault signatures is used to select the best set of frequencies applicable for all nodes in a.c. testing. A preamplifier and control amplifier of 56 components is chosen as Unit Under Test (UUT) to demonstrate the ATPG. The fault isolation scheme used is based on the nearest neighbour rule.The rexlationship between diagnosability and number of test features is shown to follow the customary Pareto type curve. However, four carefully chosen nodes and three carefully chosen test frequencies are shown to give an adequate level of diagnosability. The whole scheme is implemented automatically using a minicomputer interfaced to the UUT.

J. Hywel Williams

Papers

Condition-based maintenance and machine diagnostics

Principal component analysis of production data

Optimization of access points for automatic test program generation and fault location in large analogue circuits and systems

The simulation of the procurement of an avionic logistic system