Search results for "Prognostics"
showing 10 items of 15 documents
Novel Threshold Calculations for Remaining Useful Lifetime Estimation of Rolling Element Bearings
2018
The prognostics objective is to avoid sudden machinery breakdowns and to estimate the remaining useful life after initial degradation. Typically, physical health indicators are derived from available sensor data, and a mathematical model is tuned to fit them. The time it takes for the model to reach a failure threshold is the estimated remaining useful life. The failure threshold may be determined from historical failure data, but that is not always readily available. ISO standard 10816–3 defines permissible velocity vibration levels for machines that may be used as a failure threshold. However, velocity vibration is not suitable for bearing prognostics due to the effect of integration from…
A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management
2016
Abstract Large wind farms are gaining prominence due to increasing dependence on renewable energy. In order to operate these wind farms reliably and efficiently, advanced maintenance strategies such as condition based maintenance are necessary. However, wind turbines pose unique challenges in terms of irregular load patterns, intermittent operation and harsh weather conditions, which have deterring effects on life of rotating machinery. This paper reviews the state-of-the-art in the area of diagnostics and prognostics pertaining to two critical failure prone components of wind turbines, namely, low-speed bearings and planetary gearboxes. The survey evaluates those methods that are applicabl…
Reliable diagnostics using wireless sensor networks
2019
International audience; Monitoring activities in industry may require the use of wireless sensor networks, for instance due to difficult access or hostile environment. But it is well known that this type of networks has various limitations like the amount of disposable energy. Indeed, once a sensor node exhausts its resources, it will be dropped from the network, stopping so to forward information about maybe relevant features towards the sink. This will result in broken links and data loss which impacts the diagnostic accuracy at the sink level. It is therefore important to keep the network's monitoring service as long as possible by preserving the energy held by the nodes. As packet trans…
Impact of decision horizon on post-prognostics maintenance and missions scheduling: a railways case study
2021
International audience; In this paper, we propose a study of the decision horizon duration for rolling stock mission assignment and maintenance planning in a prognostics and health management (PHM) context. The aim is to determine the best decision horizon duration that allows the con- struction of a suitable schedule that assigns railway vehicles to missions and integrates required maintenance operations accord- ing to the current and future health of the vehicles. A genetic algorithm is used to minimize the overall cost of the joint schedule as a function of the decision horizon. The results are compared to three proposed heuristics to study the influence of the resolution method on the d…
Autoencoders and Recurrent Neural Networks Based Algorithm for Prognosis of Bearing Life
2018
Bearings are one of the most critical components in electric motors, gearboxes and wind turbines. Therefore, bearing fault detection and prognosis of remaining useful life are important to prevent productivity losses. In this study, a novel method is proposed for prognosis of bearing life using an autoencoder and recurrent neural networks-based prediction algorithm. Promising results have been obtained from the experimental data. A monotonic upward trend of the produced health indicator is obtained for all test cases, being one of critical indicators of a proper prognosis. The remaining useful life estimation is moderately accurate under a limited data.
Rotor-bar breakage mechanism and prognosis in an induction motor
2015
© 1982-2012 IEEE. This paper proposes a condition-based maintenance and prognostics and health management (CBM/PHM) procedure for a rotor bar in an induction motor. The methodology is based on the results of a fatigue test intended to reproduce in the most natural way a bar breakage in order to carry out a comparison between transient and stationary diagnosis methods for incipient fault detection. Newly developed techniques in stator-current transient analysis have allowed tracking the developing fault during the last part of the test, identifying the failure mechanism, and establishing a physical model of the process. This nonlinear failure model is integrated in a particle filtering algor…
UiA Accelerated Life Time Bearing Test Rig – Test 1, 250 rpm
2020
Vibration data from an accelerated lifetime test of a bearing. Contains raw vibration data and shaft position data. The mean shaft speed is 250 rpm. Can be used for fault diagnosis and remaining useful lifetime estimation. Please see "00_ReadMe.pdf" file for more details. Update - 3 January 2022: This dataset is now updated to use floating point values for shaft position data, which gives a much more accurate description of the shaft position.
UiA Accelerated Life Time Bearing Test Rig – Test 3, Variable speed around 50rpm
2021
Vibration data from an accelerated lifetime test of a bearing. Contains raw vibration data and shaft position data. The mean shaft speed is 50rpm with a variation +- 40 rpm. Can be used for fault diagnosis and remaining useful lifetime estimation. Please see "00_ReadMe.pdf" file for more details.
Integrated Production and Predictive Maintenance Planning based on Prognostic Information
2019
International audience; This paper address the problem of scheduling production and maintenance operation in predictive maintenance context. It proposes a contribution in the decision making phase of the prognostic and health management framework. Theprognostics and decision processes are merged and an ant colony optimization approach for finding the sequence of decisions that optimizes the benefits of a production system is developed. A case study on a single machine composed of several components where machine can have several usage profiles. The results show thatour approach surpasses classical condition based maintenance policy.
On the Use of Prognostics and Health Management to Jointly Schedule Production and Maintenance on a Single Multi-purpose Machine
2020
This paper address the problem of using prognostic information in the decision-making process of a single multi-purpose machine. The prognostics and health management method is compared to condition-based maintenance combined with a genetic algorithm to determine the joint schedule of maintenance and production. The paper presents a methodology to select the adequate strategy while considering several factors that influence the functioning of the machine. The results show that operational and conditions variability influence the choice of the suitable methods. In the presented case, we show configurations where prognostic information is useless or useful.