scholarly journals Service Life Prediction of Shaft Sidewall Exposed to Sulfate Environment

2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Wei He ◽  
Xia Meng ◽  
Ji-hui Zhao
Keyword(s):  
Life Prediction ◽  
Laboratory Tests ◽  
Residual Life ◽  
Underground Water ◽  
Corrosion Mechanism ◽  
Research Subject ◽  
High Concentration ◽  
Degradation Model ◽  
Immersion Corrosion ◽  
Different Parts

Under the influence of underground water with high concentration of sulfate, several vertical shafts in the Huang-Huai region are seriously corroded but have varying degradation degrees in different parts. Taking the auxiliary shaft of Lin-Huan coal mine as the research subject, the mechanism of this phenomenon was studied. Then, wet-dry alternated and immersion corrosion tests were carried out, and it was found that only the dry-wet alternated accelerate test is representative of the corrosion mechanism that cause the corrosion in the shaft. However, it will cost much time and money for the laboratory test to reach the same degradation depth. To solve this problem, combining with field and laboratory tests, a modified theoretical degradation model was developed to evaluate the residual life of the corroded sidewall. The results indicate that the residual life of the shaft sidewall is 25 years, and the damaged parts have no need for an immediate reinforcement.

scholarly journals Remaining Useful Life Prediction of Broken Rotor Bar Based on Data-Driven and Degradation Model

2021 ◽  
Vol 11 (16) ◽  
pp. 7175
Author(s):  
Islem Bejaoui ◽  
Dario Bruneo ◽  
Maria Gabriella Xibilia
Keyword(s):  
Principal Component Analysis ◽  
Induction Motor ◽  
Life Prediction ◽  
Principal Component ◽  
Component Analysis ◽  
Remaining Useful Life ◽  
Degradation Model ◽  
Broken Rotor Bar ◽  
Industrial Sectors ◽  
Useful Life

Rotating machines such as induction motors are crucial parts of most industrial systems. The prognostic health management of induction motor rotors plays an essential role in increasing electrical machine reliability and safety, especially in critical industrial sectors. This paper presents a new approach for rotating machine fault prognosis under broken rotor bar failure, which involves the modeling of the failure mechanism, the health indicator construction, and the remaining useful life prediction. This approach combines signal processing techniques, inherent metrics, and principal component analysis to monitor the induction motor. Time- and frequency-domains features allowing for tracking the degradation trend of motor critical components that are extracted from torque, stator current, and speed signals. The most meaningful features are selected using inherent metrics, while two health indicators representing the degradation process of the broken rotor bar are constructed by applying the principal component analysis. The estimation of the remaining useful life is then obtained using the degradation model. The performance of the prediction results is evaluated using several criteria of prediction accuracy. A set of synthetic data collected from a degraded Simulink model of the rotor through simulations is used to validate the proposed approach. Experimental results show that using the developed prognostic methodology is a powerful strategy to improve the prognostic of induction motor degradation.

Remaining useful life prediction method for machine tools based on meta-action theory

2021 ◽  
pp. 1748006X2110025
Author(s):  
Zongyi Mu ◽  
Yan Ran ◽  
Genbao Zhang ◽  
Hongwei Wang ◽  
Xin Yang
Keyword(s):  
Machine Tools ◽  
Life Prediction ◽  
Action Theory ◽  
Prediction Method ◽  
Operational Reliability ◽  
Remaining Useful Life ◽  
Practical Application ◽  
Dynamic Prediction ◽  
Degradation Model ◽  
Useful Life

Remaining useful life (RUL) is a crucial indictor to measure the performance degradation of machine tools. It directly affects the accuracy of maintenance decision-making, thus affecting operational reliability of machine tools. Currently, most RUL prediction methods are for the parts. However, due to the interaction among the parts, even RUL of all the parts cannot reflect the real RUL of the whole machine. Therefore, an RUL prediction method for the whole machine is needed. To predict RUL of the whole machine, this paper proposes an RUL prediction method with dynamic prediction objects based on meta-action theory. Firstly, machine tools are decomposed into the meta-action unit chains (MUCs) to obtain suitable prediction objects. Secondly, the machining precision unqualified rate (MPUR) control chart is used to conduct an out of control early warning for machine tools’ performance. At last, the Markov model is introduced to determine the prediction objects in next prediction and the Wiener degradation model is established to predict RUL of machine tools. According to the practical application, feasibility and effectiveness of the method is proved.

Optimization of a Leaching Tank for Hydrometallurgical Recovery of Metals

2009 ◽  
Author(s):  
M. C. L. G. Vilarinho ◽  
N. M. B. Gonc¸alves ◽  
J. C. F. Teixeira
Keyword(s):  
Laboratory Tests ◽  
Metal Extraction ◽  
Cfd Model ◽  
High Concentration ◽  
Metal Plating ◽  
Metals Recovery ◽  
High Metal ◽  
Leaching Solution ◽  
Wide Compositional Range ◽  
Overall Efficiency

The sludge wastes generated by the metal plating industries are classified as hazardous wastes because of their high concentration of heavy metals. Amongst the various routes for their treatment, the hydrometallurgical processes are highly attractive because they can be tailored to the wide compositional range of such wastes and assure its metals recovery and/or toxicity reduction. In these processes the leaching operation is paramount to the overall efficiency. In this, the mixing of the leaching solution with sludge has to be effective in order to obtain high levels of metal extraction and make the process attractive. Most of the available data refers to laboratory tests. This paper reports on the use of CFD model to optimize the operation of a pilot size leaching tank. The results regarding the velocity field were compared with experimental data and proved that such techniques can be effectively applied to improve the process. A leaching experiment, with the best configuration for the mixing, yielded a high metal extraction, suggesting that this technique can be successfully implemented for the treatment of such wastes.

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