The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper studies the fault detection and diagnosis for the most common faults in the rotary equipment. Large amount of experiments are carried out on the machinery fault simulator for simulating different types of rotary machine faults. The study covers from different type of data acquisition sensors, different signal processing and feature extraction techniques. A hierarchical rule-based fault...
The growing interest in predictive maintenance makes industrials and researchers turning themselves to artificial intelligence methods for fulfilling the tasks of condition monitoring and prognostics. Within this frame, the general purpose of this paper is to investigate the capabilities of an Evolving extended Takagi Sugeno (exTS) based neuro-fuzzy algorithm to predict the tool condition in high-speed...
In this paper, two temporal models, Hidden Markov Model and Auto Regressive Moving Average model with exogenous inputs (ARMAX), are used for health condition monitoring of the cutter in a milling machine. Dataset is acquired through real time force signal sensing. A heuristic statistical approach is used to select dominant features, leading to the selection of 3 dominant features from the 16-dimensional...
The challenge to effectively and accurately determine pure partial discharge (PD) signals from the large amount of noise still remains. In this study, individual PD pulses were filtered, extracted and analyzed using digital signal processing techniques and data mining methods. The shape or distribution of the spectral frequency domain could be correlated with different PD signals. Feature extraction...
In this paper, four data-driven classification approaches, that is, K-nearest neighbors (K-NN), self-organizing map (SOM), multi-layer perceptron (MLP), and Bayesian Network classifier (BNC), are applied to a health condition monitoring problem for the wearing cutter. The dataset is produced from a cutting machine using force sensing. A genetic algorithm (GA) based search is performed to select 3...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.