Shaft crack diagnostics in a gearbox

Eftekharnejad, Babak; Addali, Abdulmajid

doi:10.1016/j.apacoust.2012.02.004

Cited by 25 publications

(11 citation statements)

References 16 publications

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“…They concluded that the AE technique is less susceptible to background mechanical noise than vibration sensing and is more sensitive to tooth damage in low rotational speeds. Eftekharnejad et al [98] discussed use of acoustic emission for shaft crack detection in gearboxes. Vicuña [99] investigated the effects of varying load, lubricant temperature and rotational speed of planetary gearbox on acoustic emission.…”

Section: Acoustic Emission Signaturementioning

confidence: 99%

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Kandukuri

Klausen

Karimi

et al. 2016

Renewable and Sustainable Energy Reviews

171

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Section: Acoustic Emission Signaturementioning

confidence: 99%

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Kandukuri

Klausen

Karimi

et al. 2016

Renewable and Sustainable Energy Reviews

171

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“…Elforjani and Mba [20] elegantly calculated the size of a ball bearing race defect by measuring the length of the transient AE occurring in wavestreams collected as the bearing rotated at a known angular velocity. Eftekharnejad et al [21] discovered changes in the frequency content of decomposed AE wavestreams before and after shaft fracture occurred in an experiment on a gearbox, demonstrating how wavestream frequency domain information can assist in providing diagnostic information. There are also examples of the use of wavestreaming to investigate non-rotating, cyclically loaded structures.…”

Section: Figure 1: Representation Of Conventional Wavestreaming Hit mentioning

confidence: 99%

Optimisation of acoustic emission wavestreaming for structural health monitoring

McCrory

Pearson

Pullin

et al. 2020

Structural Health Monitoring

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Structural health monitoring has gained wide appeal for applications with high inspection costs, such as aircraft and wind turbines. As the structures and materials used in these industries evolve, so too must the technologies used to monitor them. Acoustic emission is a passive method of detecting damage which lends itself well to structural health monitoring. One form of acoustic emission monitoring, known as wavestreaming, involves intermittently recording data for set periods of time and using the sequential recordings to detect changes in the state of the structure. However, at present, there is no standard method for selecting appropriate wavestream recording parameters, such as their length or their interval of collection. This article investigates a method of optimising acoustic emission wavestreaming for structural health monitoring purposes by introducing the novel concept of adjoining consecutive discrete acoustic emission hit signals to create synthetic wavestreams. To this end, a pre-notched 492 mm × 67.5 mm × 20 mm, 300M grade steel cantilever specimen was subject to cyclic loading and both acoustic emission hit data and conventional wavestreams were collected as a crack grew in the notched region; crack growth activity was also monitored using digital image correlation for comparison. To demonstrate the proposed optimisation process, four sets of synthetic wavestreams were created from the hit data, 0.25, 0.5, 1.0 and 1.5 s in length, and compared with the 1.5-s-long conventional wavestreams. The activity of the peak frequency and frequency centroid bands of interest within the conventional and synthetic wavestreams were examined to determine whether or not cracking activity could be inferred through them. Across comparisons of all data, it was found that the 0.5-s-long synthetic wavestreams contained enough information to identify the same trends as the conventional wavestreams for this application; thus, the use of synthetic wavestreams as a tool for selecting an appropriate wavestream recording length was demonstrated.

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“…However, it should be noted that the load of the motor is greatly affected by the fluctuation of wind speed, and the diagnostic results are greatly affected by the working conditions. Similarly, acoustic signals are used to monitor the cracked shaft [25]. Generator current signals are used to monitor the misalignment of the shaft [26].…”

Section: Shaftmentioning

confidence: 99%

A Survey of Condition Monitoring and Fault Diagnosis toward Integrated O&M for Wind Turbines

Zhang

2019

Energies

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Wind power, as a renewable energy for coping with global climate change challenge, has achieved rapid development in recent years. The breakdown of wind turbines (WTs) not only leads to high repair expenses but also may threaten the stability of the whole power grid. How to reduce the operation and the maintenance (O&M) cost of wind farms is an obstacle to its further promotion and application. To provide reliable condition monitoring and fault diagnosis (CMFD) for WTs, this paper presents a comprehensive survey of the existing CMFD methods in the following three aspects: energy flow, information flow, and integrated O&M system. Energy flow mainly analyzes the characteristics of each component from the angle of energy conversion of WTs. Information flow is the carrier of fault and control information of WT. At the end of this paper, an integrated WT O&M system based on electrical signals is proposed.

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Shaft crack diagnostics in a gearbox

Cited by 25 publications

References 16 publications

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

A review of diagnostics and prognostics of low-speed machinery towards wind turbine farm-level health management

Optimisation of acoustic emission wavestreaming for structural health monitoring

A Survey of Condition Monitoring and Fault Diagnosis toward Integrated O&M for Wind Turbines

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