Abstract
Generally, expert systems have been found very useful branch of artificial intelligence that makes extensive use of specialized knowledge to solve complex problems and even in fertilizer plants it has been deployed in handling operations in critical sections, such as material handling systems, online leak detection systems, granulation, air compressor among others. This paper presents research work for steam package boiler expert system for control and maintenance of fertilizer plants using rule-base fuzzy logic hybrid system, which has not been benefited much from expert system. The system handles cause of boiler failures in terms of controlling and maintaining the functional chemical components of the boiler drum and feed water parameters. validation on the system consistency, correctness, and its precision with six (6) steam package boiler parameters test value cases was conducted involving fourteen (14) fertilizer plant boiler domain partitioners. The boiler drum and feed water qualities with less or higher test value worst-cases validates the boiler system, showing each of the parameter’s bar turns red, as displayed on the boiler’s panel, while on test value best-cases, validates the system, displaying green on the boiler’s panel as users entered the right value of parameters per the design specification. We discovered that from 1 to 10 minutes run time for auto system run gives 10.8% errors as compared from 1 to 10 minutes time interval on manual system run that gives 80.2% error, this results to less effort in user interface application usage on auto operations better than manual. The expert system prevents damaged and malfunctioning as control the alkalinity, prevent scaling, both mechanical & chemical corrosion, forming, correct pH values and then the conductivity which deals with the feed boiler water and monitored the level in the boiler drum using the industry measurement parameters (pressure, temperature, level, and flow).
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More From: European Journal of Computer Science and Information Technology
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