Search results for "Condition monitoring"
showing 10 items of 41 documents
Online Fault Diagnosis System for Electric Powertrains Using Advanced Signal Processing and Machine Learning
2018
Online condition monitoring and fault diagnosis systems are necessary to prevent unexpected downtimes in critical electric powertrains. The machine learning algorithms provide a better way to diagnose faults in complex cases, such as mixed faults and/or in variable speed conditions. Most of studies focus on training phases of the machine learning algorithms, but the development of the trained machine learning algorithms for an online diagnosis system is not detailed. In this study, a complete procedure of training and implementation of an online fault diagnosis system is presented and discussed. Aspects of the development of an online fault diagnosis based on machine learning algorithms are…
A Review on Approaches for Condition Based Maintenance in Applications with Induction Machines located Offshore
2012
Published version of an article in the journal: Modeling, Identification and Control. Also available from the publisher at: http://dx.doi.org/10.4173/mic.2012.2.4 Open access This paper presents a review of different approaches for Condition Based Maintenance (CBM) of induction machines and drive trains in offshore applications. The paper contains an overview of common failure modes, monitoring techniques, approaches for diagnostics, and an overview of typical maintenance actions. Although many papers have been written in this area before, this paper puts an emphasis on recent developments and limits the scope to induction machines and drive trains applied in applications located offshore.
Methods of Condition Monitoring and Fault Detection for Electrical Machines
2021
Nowadays, electrical machines and drive systems are playing an essential role in different applications. Eventually, various failures occur in long-term continuous operation. Due to the increased influence of such devices on industry, industrial branches, as well as ordinary human life, condition monitoring and timely fault diagnostics have gained a reasonable importance. In this review article, there are studied different diagnostic techniques that can be used for algorithms’ training and realization of predictive maintenance. Benefits and drawbacks of intelligent diagnostic techniques are highlighted. The most widespread faults of electrical machines are discussed as well as techniques fo…
Rib-Roller Wear in Tapered Rolling Element Bearings: Analysis and Development of Test Rig for Condition Monitoring
2020
Rolling Element Bearings (REBs) are present in virtually all machines with moving or rotating parts, and are vital for proper performance and safe operation. Condition Monitoring (CM) of bearings often receive particular interest, as this component group rarely reach design lifetime and hence is responsible for unplanned machine downtime. Unplanned maintenance can represent a large cost which motivates development of improved CM methods for implementation of advanced maintenance regimes. Based on observations of a used bearing from an offshore drilling machine, wear on roller ends in the rib-roller contact area was identified as an area of interest for future research. A test rig for creati…
Observation and Processing of Instantaneous Frequency Variations During Bearing Tests
2020
Laboratory experiments have been performed on medium sized roller bearings with two levels of artificial damage. Recordings of long time series from accelerometers at a wide range of different radial loads and rotation speeds has been performed. Probably due to non-perfect performance of the control systems for the rotational speed or frequency, significant fluctuations were observed at all rotation speeds. The highest relative variation was observed at the lowest rotational speeds. These variations were recorded using a rotary encoder, which allows order tracking of the vibration signal. In real life condition monitoring, tachometers or rotary encoders are not always present, this can be d…
Artificial Intelligence in Monitoring and Diagnostics of Electrical Energy Conversion Systems
2020
Diagnostics and prognostics of electrical energy conversion systems are moving forward with the rapid development of IT and artificial intelligence possibilities. This also broadens the horizons for classical and advanced condition and operation monitoring techniques, resulting in more accurate fault detection, degradation prognosis and calculation of remaining life of energy conversion systems, utilized in every aspect and field of industry today. This paper gives an overview of the necessity for condition monitoring and diagnostics of the mentioned systems, explaining the classical and advanced techniques for diagnostics. Methodology to diagnose and prognose the energy conversion units, w…
Computer vision and thermal monitoring of HMPE fibre rope condition during CBOS testing
2020
Abstract Fibre rope usage in deep sea lifting operations is gaining more prominence in recent times. With rope minimum break loads (MBL) comparable to that of their steel wire counterparts, the use of high modulus polyethylene (HMPE) ropes is seen as a viable option for use in subsea construction cranes. The ropes are worn out during use and visual inspection remains one of the main methods of determining whether a fibre rope is to be retired from use, therefore a natural extension is condition monitoring through computer vision. Creep and temperature are constraining with HMPE ropes and should be monitored continuously, particularly when the rope is cyclically bent over sheaves. Additional…
Rotor bar breakage data obtained from fatigue test
2019
The data hereby provided was acquired during a fatigue test developed at the Department of Electrical Engineering, Universitat Politècnica de València (Universidad Politécnica de Valencia, Spain) in 2011 by PhD student Vicente Climente-Alarcon under supervision of Prof. Martin Riera-Guasp. The fatigue test involved subjecting a 1.5 kW, 1 pole pair induction motor to severe cycling until a bar breakage naturally developed. The cycling consisted of a Direct-on-line (DOL) startup followed by a stationary operation period of at least 10 seconds. A plug stopping was added at the later stages of the test. To maximize the possible damage to the rotor cage, a high load inertia caused heavy (long) s…
Quantitative Rotor Broken Bar Evaluation in Double Squirrel Cage Induction Machines under Dynamic Operating Conditions
2013
Advanced monitoring techniques leading to fault diagnosis and prediction of induction machine faults, operating under non-stationary conditions have gained strength because of its considerable influence on the operational continuation of many industrial processes. In case of rotor broken bars, fault detection based on sideband components issued from currents, flux, instantaneous control or power signals under different load conditions, may fail due to the presence of inter-bar currents that reduce the degree of rotor asymmetry, especially for double squirrel cage induction motors. But the produced core vibrations in the axial direction, can be investigated to overcome the limitation of the …
Toward farm-level health management of wind turbine systems: status and scope for improvements
2018
An outline of health management for OWFs has been detailed in this chapter with description of various important elements. The need for such farm level management is explained and benefits are discussed. Key gaps to be filled in order to realize such a system are identified. The proposed health management system is mainly based on the existing knowledge of fleet-level management in the aerospace sector. Health management is much broader than CM; there are a number of aspects beyond the prognostics capabilities that are to be designed in order to arrive at a comprehensive maintenance management scheme. A comprehensive maintenance program that is sensitive to the health of the assets and adap…