Performance of cascade refrigeration with liquid refrigerant by-pass

Niu, Baolian

doi:10.3901/jme.2007.08.192

Cited by 2 publications

(3 citation statements)

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“…Therefore, the faults of RSGCs are diverse, the correlation between the faults is strong, and the complexity is high. [17][18][19] This makes the manual diagnosis process more difficult, so the diagnosis process not sufficiently timely. The accuracy of the diagnosis results largely depends on the experience and knowledge of the diagnosis expert.…”

Section: Introductionmentioning

confidence: 99%

Multisensor information fusion method for intelligent fault diagnosis of reciprocating compressor in shale gas development

Tang

Yang

Liu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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To address the problems of the poor feature extraction ability and weak data generalization ability of traditional fault diagnosis methods in reciprocating shale gas compressor fault diagnosis applications, in this study, a fault diagnosis method for reciprocating shale gas was developed. This method uses a novel optimized learning method, free energy in persistent contrastive divergence, in deep belief network learning and training. It solves the problem of the deep belief network classification ability degradation in long-term training. The root mean square error is used as the fitness function to search for the optimal parameter combination of the DBN network by using the sparrow search algorithm. At the same time, the learning rate and batch size of the deep belief network, which have a large impact on the training error, are selected for optimization. Then, the original vibration signal is preprocessed by calculating 13 different time domain indicators, and feature-level data and decision-level data are fused in a parallel superposition method to obtain a fused time domain index dataset. Finally, combined with the powerful adaptive feature extraction and nonlinear mapping ability of deep learning, the constructed sample dataset is input to the deep belief network for training, and the deep belief network based on reciprocating shale gas compressor fault diagnosis model is established.

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Section: Introductionmentioning

confidence: 99%

Multisensor information fusion method for intelligent fault diagnosis of reciprocating compressor in shale gas development

Tang

Yang

Liu

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part O:

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show abstract

“…Considering the increase in load requirements of air-conditioning and refrigeration systems in application conditions and limitations in the serviceable range of system equipment, equipment combinations such as cascade refrigeration systems, multi-stage compression refrigeration systems, and parallel compressor refrigeration systems have been widely employed. Therefore, analyzing the impact of each application condition on the system performance [1][2][3][4][5] is vital for selection the optimal system for system equipment combination.…”

Section: Introductionmentioning

confidence: 99%

“…Several scholars from China and other countries have conducted extensive numerical simulations and experimental studies on the compressor performance and refrigerant selection [3][4][5][6][7][8][9][10][11][12]. Niu et al [3] proposed a liquid bypass refrigeration system which regulates the refrigeration capacity by adjusting the flow of refrigerant entering the evaporator. The system effectively reduces the compressor discharge temperature without the risk of liquid hammer.…”

Section: Introductionmentioning

confidence: 99%

Experimental Analysis of the Performances of Unit Refrigeration Systems Based on Parallel Compressors with Consideration of the Volumetric and Isentropic Efficiency

Shen¹,

Gui²,

Xia³

et al. 2020

Fluid Dynamics &Amp; Materials Processing

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The performances of a refrigeration unit relying on compressors working in parallel have been investigated considering the influence of the compressor volumetric efficiency and isentropic efficiency on the compression ratio. Moreover, the following influential factors have been taken into account: evaporation temperature, condensation temperature and compressor suction-exhaust pressure ratio for different opening conditions of the compressor. The following quantities have been selected as the unit performance measurement indicators: refrigeration capacity, energy efficiency ratio (COP), compressor power consumption, and refrigerant flow rate. The experimental results indicate that the system refrigeration capacity and COP decrease with a decrease in evaporation temperature, increase of condensation temperature, and increase in pressure ratio. The refrigerant flow rate increases with the increase in evaporation temperature, decrease in condensing temperature and increase in pressure ratio. The compressor power consumption increases with the increase in condensing temperature and increase in pressure ratio, but is not significantly affected by the evaporation temperature.

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Performance of cascade refrigeration with liquid refrigerant by-pass

Cited by 2 publications

References 0 publications

Multisensor information fusion method for intelligent fault diagnosis of reciprocating compressor in shale gas development

Multisensor information fusion method for intelligent fault diagnosis of reciprocating compressor in shale gas development

Experimental Analysis of the Performances of Unit Refrigeration Systems Based on Parallel Compressors with Consideration of the Volumetric and Isentropic Efficiency

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