Zulkifli, Rifki (2020) Perancangan Sistem Diagnosis Kondisi Operasi Gas Turbine Generator berbasis Sistem Pakar. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Gas turbine generator terdiri dari tiga komponen utama yang saling berkaitan satu sama lain yang terdiri dari (kompresor, combustor, dan turbin). Kondisi operasi dari tiap komponen yang berubah – ubah dipengaruhi oleh parameter input – output tiap section. Untuk mengetahui kinerja dari tiap section tersebut perlu sebuah sistem diagnosis mengenai kondisi operasi dari gas turbine generator dengan basis sistem pakar. Sistem pakar terdiri dari database dan mesin penalar. Database berupa analisa kondisi operasi oleh ahli gas turbine generator dan mesin penalar berfungsi untuk membandingkan input berupa data monitoring parameter dari tiap komponen dengan database yang ada. Input parameter harus di-scoring terlebih dahulu agar bisa dibandingkan oleh mesin penalar. Scoring dilakukan dengan cara diskusi dengan ahli gas turbine generator yang ada di PT. SIPL. Hasil diagnosis dari gas turbine generator menggunakan simulasi sistem pakar yang telah dibuat pada Simulink Matlab untuk pengujian saat kondisi operasi normal saat jam operasional 15979 diperoleh kinerja kompresor, combustor dan turbin beroperasi pada keadaan operasional normal untuk beban sebesar 50%, tetapi daya total yang dihasilkan berada dibawah nilai dari ekspektasi. Pengujian sistem pakar yang dilakukan pada saat operasional abnormal gas turbine generator saat jam operasional 16036 diperoleh kesimpulan bahwa kinerja kompresor, combustor dan turbin beroperasi pada keadaan operasional abnormal dan berada dibawah standar range operasional. Kompresor memiliki nilai PCD yang kecil (203,4 kPa) dan kesalahan baca dari nilai input T5 yang dibuktikan dengan nilai T5 yang kecil (37,2°C) , tetapi daya keluaran turbin bernilai 1645 kW yang tidak mungkin terjadi.
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Gas turbine generators consist of three main components which are interrelated to each other which consist of (compressor, combustor, and turbine). The changing operating conditions of each component are affected by the input - output parameters of each section. To find out the performance of each section, we need a diagnosis system based on an expert system. The expert system consists of database and a inference engine. The database in the form of an analysis of operating conditions by a gas turbine generator expert and a inference engine functions to compare the input in the form of monitoring data parameters of each component with an existing database. Input parameters must be scored beforehand so they can be compared by the inference engine. Scoring is done by discussion with gas turbine generator experts in PT. SIPL. The results of the diagnosis of the gas turbine generator using an expert system simulation that was made on Simulink Matlab for testing during normal operating conditions when engine fired hours 15979 obtained the performance of the compressor, combustor and turbine operating under normal operational conditions for a load of 50%, but the total power generated is below the value of expectations. Expert system testing conducted during the operational abnormal gas turbine generator when engine fired hours 16036 concluded that the performance of the compressor, combustor and turbine operates in abnormal operational conditions and is below the standard operating range. The compressor has a small PCD value (203.4 kPa) and a read error of the T5 input value as evidenced by a small T5 value (37.2 ° C), but the turbine output power is 1645 kW which is not possible.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Diagnose, Operation Condition, Gas Turbine Generator, Expert System, Diagnosis, Kondisi Operasi, Gas Turbine Generator, Sistem Pakar |
| Subjects: | Q Science > QA Mathematics > QA336 Artificial Intelligence T Technology > TJ Mechanical engineering and machinery > TJ778 Gas turbines |
| Divisions: | Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis |
| Depositing User: | Rifki Zulkifli |
| Date Deposited: | 31 Aug 2020 06:54 |
| Last Modified: | 09 Jan 2024 07:33 |
| URI: | http://repository.its.ac.id/id/eprint/81666 |
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