Condition monitoring

About: Condition monitoring is a research topic. Over the lifetime, 13911 publications have been published within this topic receiving 201649 citations.

Analysis and Diagnosis of Open-Circuit Faults in Matrix Converters

Abstract: The monitoring of power converters is critical for obtaining systems with self-diagnostic capabilities and fault-tolerant features. This paper presents an analytical work concerning the operation of matrix converters (MCs) under the presence of open-circuit faults and discusses the applicability of a method for the diagnosis of this type of failures. The proposed method uses the absolute values of nine modulated error voltages for the continuous monitoring of the condition of the bidirectional switches of an MC. This method allows a fast detection and location of the faulty switches, independent of the modulation strategy of the converter, its voltage transfer ratio, output frequency, or type of load connected to it, both in steady-state and transient regimes. The theory, validated by simulation and experimental results, demonstrates the applicability of the proposed technique for the diagnosis of faults in MCs.

Cutting tool wear monitoring for reliability analysis using proportional hazards model

Abstract: Aiming at operational reliability analysis and assessment based on condition monitoring information, a methodology of reliability modeling and assessment based on feature extraction from cutting tool vibration signals using proportional hazards model is proposed in this paper. Root mean square and peak of time domain index from vibration signals, which are closely related to cutting tool wear degradation states, are selected as covariates introduced to proportional hazards model for the cutting tool wear reliability analysis. The proposed approach shows considerable advantages of establishing significant association relationship between the cutting tool condition monitoring information and the life distribution of cutting tool wear. It is appropriate to provide individual cutting tool operational reliability assessment effectively. The experimental study on a CNC lathe turning process is given to validate the effectiveness of the proposed method. The results show that the approach is desirable and gives a good estimation of the reliability for cutting tool wear degradation states.

Sensory-Based Failure Threshold Estimation for Remaining Useful Life Prediction

Abstract: The rapid development of sensor and computing technology has created an unprecedented opportunity for condition monitoring and prognostic analysis in various manufacturing and healthcare industries. With the massive amount of sensor information available, important research efforts have been made in modeling the degradation signals of a unit and estimating its remaining useful life distribution. In particular, a unit is often considered to have failed when its degradation signal crosses a predefined failure threshold, which is assumed to be known a priori . Unfortunately, such a simplified assumption may not be valid in many applications given the stochastic nature of the underlying degradation mechanism. While there are some extended studies considering the variability in the estimated failure threshold via data-driven approaches, they focus on the failure threshold distribution of the population instead of that of an individual unit. Currently, the existing literature still lacks an effective approach to accurately estimate the failure threshold distribution of an operating unit based on its in-situ sensory data during condition monitoring. To fill this literature gap, this paper develops a convex quadratic formulation that combines the information from the degradation profiles of historical units and the in-situ sensory data from an operating unit to online estimate the failure threshold of this particular unit in the field. With a more accurate estimation of the failure threshold of the operating unit in real time, a better remaining useful life prediction is expected. Simulations as well as a case study involving a degradation dataset of aircraft turbine engines were used to numerically evaluate and compare the performance of the proposed methodology with the existing literature in the context of failure threshold estimation and remaining useful life prediction.

System and Method for Calculating Remaining Useful Time of Objects

Abstract: An aspect of the present invention is to provide a system and method for predicting the remaining useful time of mechanical components such as bearings. Another aspect of the present invention is to provide a system and method for predicting the remaining useful time of bearings based on available condition monitoring data. Another aspect of the present invention is to provide a system and method for automatically deciding which columns of input information are the most significant for predicting the remaining useful life of bearings. Another aspect of the present invention is to provide a system and method for performing an analysis of both test bearings and training bearings and determining which training bearings are most similar to a given test bearing. Another aspect of the present invention is to provide a system and method for training an artificial neural network.