Search results for "Bearing"
showing 10 items of 284 documents
Autonomous Bearing Fault Diagnosis Method based on Envelope Spectrum
2017
Abstract Rolling element bearings are one of the fundamental components of a machine, and their failure is the most frequent cause of machine breakdown. Monitoring the bearing condition is vital to preventing unexpected shutdowns and improving their maintenance planning. Specifically, the bearing vibration can be measured and analyzed to diagnose bearing faults. Accurate fault diagnosis can be achieved by analyzing the envelope spectrum of a narrowband filtered vibration signal. The optimal narrow-band is centered at the resonance frequency of the bearing. However, how to determine the optimal narrow-band is a challenge. Several methods aim to identify the optimal narrow-band, but they are …
Failure maps to assess bearing performances of glass composite laminates
2018
Aim of this article is the assessment of the bearing mechanical performances of pin-loaded glass laminates as function of their geometrical configuration. To this concern, 32 specimens having different hole diameter (D), laminate width (W), and hole center to laminate free edge distance (E) have been tested under bearing conditions. The maximum bearing stress and the stress-displacement curves were analyzed as function both of hole to laminate free edge distance E and hole diameter D. Moreover, an experimental 2D failure map was created by placing the experimental results (i.e., the kind of failure mechanism occurred for each geometrical configuration) in the plane E/D versus W/D ratios. In…
Multi-Component Fault Detection in Wind Turbine Pitch Systems Using Extended Park's Vector and Deep Autoencoder Feature Learning
2018
Pitch systems are among the wind turbine components with most frequent failures. This article presents a multicomponent fault detection for induction motors and planetary gearboxes of the electric pitch drives using only the three-phase motor line currents. A deep autoencoder is used to extract features from the extended Park's vector modulus of the motor three-phase currents and a support vector machine to classify faults. The methodology is validated in a laboratory setup of a scaled pitch drive, with four commonly occurring faults, namely, the motor stator turns fault, broken rotor bars fault, planetary gearbox bearing fault and planet gear faults, under varying load and speed conditions.
Cross-correlation of whitened vibration signals for low-speed bearing diagnostics
2019
Abstract Rolling-element bearings are crucial components in all rotating machinery, and their failure will initially degrade the machine performance, and later cause complete shutdown. The period between an initial crack and complete failure is short due to crack propagation. Therefore, early fault detection is important to avoid unexpected machine shutdown and to aid in maintenance scheduling. Bearing condition monitoring has been applied for several decades to detect incipient faults at an early stage. However, low-speed conditions pose a challenge for bearing fault diagnosis due to low fault impact energy. To reliably detect bearing faults at an early stage, a new method termed Whitened …
Accelerated bearing life-Time test rig development for low speed data acquisition
2017
Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…
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…
Health Indicator for Low-Speed Axial Bearings Using Variational Autoencoders
2020
This paper proposes a method for calculating a health indicator (HI) for low-speed axial rolling element bearing (REB) health assessment by utilizing the latent representation obtained by variational inference using Variational Autoencoders (VAEs), trained on each speed reference in the dataset. Further, versatility is added by conditioning on the speed, extending the VAE to a conditional VAE (CVAE), thereby incorporating all speeds in a single model. Within the framework, the coefficients of autoregressive (AR) models are used as features. The dimensionality reduction inherent in the proposed method lowers the need of expert knowledge to design good condition indicators. Moreover, the sugg…
Magnetic field-assisted single-point incremental forming with a magnet ball tool
2021
Abstract This paper describes magnetic field-assisted single-point incremental forming (M-SPIF) with a Nd-Fe-B magnet ball tool. In M-SPIF, the tool driven by magnetic force plastically deforms a sheet. The polarity of the magnet tool helps to make the magnetic force (i.e., forming force) more controllable. In creating a truncated cone, the direction of the magnetic force gradually points more outward as the process progresses, and material is forced outwards from the cone center, increasing thinning in M-SPIF, while the cone center remains undeformed in traditional SPIF. Moreover, M-SPIF creates less localized plastic strain than traditional SPIF while forming the desired geometry.
Parallel distributed compensation for voltage controlled active magnetic bearing system using integral fuzzy model
2018
Parallel Distributed Compensation (PDC) for current-controlled Active Magnetic Bearing System (AMBS) has been quite effective in recent years. However, this method does not take into account the dynamics associated with the electromagnet. This limits the method to smaller scale applications where the electromagnet dynamics can be neglected. Voltage-controlled AMBS is used to overcome this limitation but this comes with serious challenges such as complex mathematical modelling and higher order system control. In this work, a PDC with integral part is proposed for position and input tracking control of voltage-controlled AMBS. PDC method is based on nonlinear Takagi-Sugeno (T-S) fuzzy model. …
Strategies of Identification of a Base-Isolated Hospital Building by Coupled Quasi-Static and Snap-Back Tests
2020
In this paper, the description of a series of quasi-static pushing tests and dynamic snap-back tests is proposed, involving the base-isolated emergency building of the Palermo university hospital. The base isolation system is characterized by a set of double-curved friction pendulum isolators placed on the top of the columns of the underground level, characteristics that cannot be found in the experimental studies available in the literature. The aim of the work was to investigate the static and dynamic properties of the building in question and comparing the in-situ results with the characteristics assigned during the design process and to assess the level of agreement. Static lateral push…