Online Condition Monitoring Tool for Automated Machinery
نویسندگان
چکیده
منابع مشابه
Rotating Machinery for Condition Monitoring
Novelty detection has been developed into a state-of-the-art technique to detect abnormal behavior and trigger alarm for in-field machine maintenance. With built-up models of normality, it has been widely applied to several situations with normal supervising dataset such as shaft rotating speed and component temperature available meanwhile in the absence of fault information. However, the resea...
متن کاملMetacognitive Learning Approach for Online Tool Condition Monitoring
As manufacturing processes become increasingly automated, so should tool condition monitoring (TCM) as it is impractical to have human workers monitor the state of the tools continuously. Tool condition is crucial to ensure the good quality of products: Worn tools affect not only the surface quality but also the dimensional accuracy, which means higher reject rate of the products. Therefore, th...
متن کاملSensor fusion for online tool condition monitoring in milling
This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, redistribution , reselling , loan, sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date...
متن کاملOnline Tool Condition Monitoring Based on Parsimonious Ensemble+
Accurate diagnosis of tool wear in metal turning process remains an open challenge for both scientists and industrial practitioners because of inhomogeneities in workpiece material, nonstationary machining settings to suit production requirements, and nonlinear relations between measured variables and tool wear. Common methodologies for tool condition monitoring still rely on batch approaches w...
متن کاملAn effective neuro-fuzzy paradigm for machinery condition health monitoring
An innovative neuro-fuzzy network appropriate for fault detection and classification in a machinery condition health monitoring environment is proposed. The network, called an incremental learning fuzzy neural (ILFN) network, uses localized neurons to represent the distributions of the input space and is trained using a one-pass, on-line, and incremental learning algorithm that is fast and can ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia CIRP
سال: 2017
ISSN: 2212-8271
DOI: 10.1016/j.procir.2017.04.003