403 research outputs found
Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery
At present, countless approaches to fault diagnosis in reciprocating machines have been proposed, all considering that the available machinery dataset is in equal proportions for all conditions. However, when the application is closer to reality, the problem of data imbalance is increasingly evident. In this paper, we propose a method for the creation of diagnoses that consider an extreme imbalance in the available data. Our approach first processes the vibration signals of the machine using a wavelet packet transform-based feature-extraction stage. Then, improved generative models are obtained with a dissimilarity-based model selection to artificially balance the dataset. Finally, a Random Forest classifier is created to address the diagnostic task. This methodology provides a considerable improvement with 99% of data imbalance over other approaches reported in the literature, showing performance similar to that obtained with a balanced set of data.National Natural Science Foundation of China, under Grant 51605406National Natural Science Foundation of China under Grant 7180104
Instantaneous failure mode remaining useful life estimation using non-uniformly sampled measurements from a reciprocating compressor valve failure
One of the major targets in industry is minimisation of downtime and cost, and maximisation of availability and safety, with maintenance considered a key aspect in achieving this objective. The concept of Condition Based Maintenance and Prognostics and Health Management (CBM/PHM) , which is founded on the principles of diagnostics, and prognostics, is a step towards this direction as it offers a proactive means for scheduling maintenance. Reciprocating compressors are vital components in oil and gas industry, though their maintenance cost is known to be relatively high. Compressor valves are the weakest part, being the most frequent failing component, accounting for almost half maintenance cost. To date, there has been limited information on estimating Remaining Useful Life (RUL) of reciprocating compressor in the open literature. This paper compares the prognostic performance of several methods (multiple linear regression, polynomial regression, Self-Organising Map (SOM), K-Nearest Neighbours Regression (KNNR)), in relation to their accuracy and precision, using actual valve failure data captured from an operating industrial compressor. The SOM technique is employed for the first time as a standalone tool for RUL estimation. Furthermore, two variations on estimating RUL based on SOM and KNNR respectively are proposed. Finally, an ensemble method by combining the output of all aforementioned algorithms is proposed and tested. Principal components analysis and statistical process control were implemented to create T^2 and Q metrics, which were proposed to be used as health indicators reflecting degradation processes and were employed for direct RUL estimation for the first time. It was shown that even when RUL is relatively short due to instantaneous nature of failure mode, it is feasible to perform good RUL estimates using the proposed techniques
Methodology Of Experimental Investigations Of Valve Operation
Tightness, as well as the reliability of the valve plate, is a complex property of the effective operation of compressor cylinders of the first stage and, in general, gas-engine reciprocating compressors. The issue of valve plate tightness is a subject of independent study, since technical and economic efficiency depends on their work. In this connection, only some data obtained under operating conditions are presented in this work.As a research result, it is found that, taking into account the identified requirements for the gas lift system, in order to effectively increase the operating hours of valves with increased tightness of the plate, it is necessary to check and purge the valves. Therefore, each valve in the gas lift compressor station, without subjecting them to cleaning, is first recommended to check for leaks. To confirm the feasibility of checking valve tightness, special equipment is offered for each gas-lift compressor station, a purge chamber, on which the tightness of valve plates is checked.The usefulness and importance of the purge chamber is in preparation of the valve at the gas lift compressor station, which contributes to increased efficiency, safe operation, normal tightness and reliability of its operation
Maintaining model efficiency, avoiding bias and reducing input parameter volume in compressor fault classification
With the exponential growth in data collection and storage and the necessity for timely prognostic health monitoring of industrial processes traditional methods of data analysis are becoming redundant. Big data sets and huge volumes of inputs give rise to equally massive computational requirements. In this paper the differences in input parameter selection using a subset of the original variables and using data reduction techniques are compared. Each selection procedure being illustrated by both statistical methods and machine learning techniques. It is shown that the subsequent classification models are highly comparable. Finally the merits of a combined multivariate statistical and wavelet decomposition approach is considered. Techniques are applied to output signals from an experimental compressor rig
Applications of machine learning to reciprocating compressor fault diagnosis: a review
Operating condition detection and fault diagnosis are very important for reliable operation of reciprocating compressors. Machine learning is one of the most powerful tools in this field. However, there are very few comprehensive reviews which summarize the current research of machine learning in monitoring reciprocating compressor operating condition and fault diagnosis. In this paper, the recent application of machine learning techniques in reciprocating compressor fault diagnosis is reviewed. The advantages and challenges in the detection process, based on three main monitoring parameters in practical applications, are discussed. Future research direction and development are proposed
new efficiency opportunities arising from intelligent real time control tools applications the case of compressed air systems energy efficiency in production and use
Abstract Most of the production facilities in Europe make use of compressed air to drive equipment for manufacturing and Compressed Air Systems (CAS) account for about 10% of the total electrical energy consumption of European industries. Therefore, reducing CAS energy consumption is a crucial task to meet the European goals of improving energy efficiency and reducing environmental impact of the industrial sector. This work is part of a wider research activity aimed at developing a strategy to optimize the energy use in CAS. In particular, this paper shows the importance of monitoring energy consumption and control energy use in compressed air generation, to enable energy saving practices, enhance the outcomes of energy management projects, and to guide industries in energy management. We propose a novel procedure in which measured data are compared to a baseline obtained through mathematical modelling (i.e. regression functions) to enable faults detection and energy accounting, through the use of control charts (i.e. variations' control and the Cumulative Sums). The effectiveness of the proposed methodology is demonstrated in a case study, namely the compressed air system of a pharmaceutical manufacturing plant
Profitability, reliability and condition based monitoring of LNG floating platforms: a review
The efficiency and profitability of Floating, Production, Storage and Offloading platform (FPSO) terminals depends on various factors such as LNG liquefaction process type, system reliability and maintenance approach. This review is organized along the following research questions: (i) what are the economic benefit of FPSO and how does the liquefaction process type affect its profitability profile?, (ii) how to improve the reliability of the liquefaction system as key section? and finally (iii) what are the major CBM techniques applied on FPSO. The paper concluded the literature and identified the research shortcomings in order to improve profitability, efficiency and availability of FPSOs
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