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Ship Refrigerated Container Refrigeration System Failure Telemetry And Diagnostic Studies

Posted on:2005-11-18Degree:MasterType:Thesis
Country:ChinaCandidate:X W XiaoFull Text:PDF
GTID:2192360125961092Subject:Refrigeration and Cryogenic Engineering
Abstract/Summary:PDF Full Text Request
Refrigerated containers with high technology can remain the cargoes fresh in a long time. Keeping the fish, meat, vegetable, fruit, and flowers at their optimal temperatures, refrigerated containers can easily be transported to anywhere in the world with a flexible and credible way. So refrigerated containers have rapidly developed as an important way of transportation in the international trade. In order to better the quality of cargo transportation and advance the competitive capacity in the market, shipping companies pay more attention to the transport management of refrigerated containers. But in a long time the transport management of refrigerated containers at sea is dependent on experience and watch keeping at local. The management has not achieved automation at all. At the same time with the proliferating quantity of cargoes that are transported by refrigerated containers, the number of the case related to cargo loss has been increasing. So refrigerated containers require a stable and persistent information technology to distinguish the obligations and decrease the cases. Based on the mentioned condition the dissertation brings forward the remote monitoring system of refrigerated containers for fault diagnose.The dissertation begins with refrigerating transportation, and then introduces refrigerated containers, such as their structure, insulation, specification and so on. Of course the dissertation touches the refrigerating technology of refrigerated containers. And the dissertation pays more attention to refrigerated containers with vapor-compressed refrigeration for the after discussion is based on the containers of this kind.The fault diagnose of the refrigerating unit of refrigerated containers adopts the fault-tree analysis, which is a mature technique among fault diagnoses, to make up some fault-trees of the typical faults. Because refrigerated containers have the character of being transported in the world, it is not easy to get the full data of a specified container. Based on the fault reports and the repair reports on board, we get the frequencies and the repair expenses of the major faults of the refrigerating unit. And we find out that the compressor fault of the refrigerating unit is the most serious fault. Of course we should pay more attention to the fault of sub-health.In order to understand the faults in detail, the dissertation makes a particular discussion about the mechanism of the fault of compressor. And we analyse the inner causes of the faults. Furthermore, the dissertation selects the parameters that we should notice when we monitor the faults.In order to satisfy the diverse load which result from the moving ships the compressors of the refrigerating unit, no matter they are reciprocating compressors, scroll compressors or rotating compressors, should have the same performance parameters. In the interest of the refrigerating unit's economic, non-fault and safe run, it is very important to make a full understand of the performance parameters. So the dissertation does a particular analysis about the performance parameters of the refrigerating unit. Making use of the computer and communication technology and the parameters established in the front discussions the dissertation brings forward the fault diagnose and remote monitoring system of marine refrigerated containers.At last the fault diagnose model of the fault of sub-health is made with BP neural network. And the author constructs the model fault library by collecting the literatures and information. Then the dissertation achieves the fault diagnose by the program written with Visual Basic. The author realizes the alarms to the faults. Making use of the system we can cut down the faults and reduce the cargo loss of refrigerated containers to the greatest extent.
Keywords/Search Tags:refrigerated containers, fault diagnose, remote monitoring system, BP neural network
PDF Full Text Request
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