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Analisa Predictive Berbasis Supervised Machine Learning Terhadap Kerusakan Peralatan Pembangkit Marte Ardhianto, Mochamad; Sumarwanto, Rudi
Jurnal Teknologi Elekterika Vol. 19 No. 2 (2022): Nopember
Publisher : Jurusan Teknik Elektro Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/elekterika.v6i2.3690

Abstract

Predictive maintenance is a treatment for the actual operation of the equipment to optimize the company's operations. The output of predictive program maintenance is data, this treatment includes the type of "condition based maintenance" where changes in the condition of the machine or equipment are detected so that proactive actions are taken before the occurrence of machine damage. The K-nearest Neighbor (K-NN) algorithm is a simple supervised machine learning algorithm that is used to solve problems based on classification and regression. K-NN works by finding the query distance and all database examples, selecting a certain number of examples (K) adjacent to the query, then selecting the frequent label (in classification) or the average label (in regression). The purpose of this algorithm is to classify new object conditions based on attributes and samples from the training database. So that a predictive analysis is carried out on the damage to generating equipment using the machine learning application method of the Nearest Neighbor type or the classification of conditions used to predict the age or condition of an equipment by modeling according to the standard Operation & Maintenance of equipment. By doing predictive analysis, maintenance will lead to condition based maintenance so that the KPI (Key Performance Indicator) of operating performance in the form of increasing values, such as Capacity Factor (CF), Equivalent Availbility Factor (EAF) becomes optimal and prevents the generator from tripping suddenly. which is called sudden outage frequency (SdOF), as well as more efficient maintenance costs.
Handling Water Leaking on The Turbine Pit ULPLTA Bakaru due to Damage of the Guide Vane Part using Automatic Method with Motorized Valve Ardhianto, Mochamad Marte; Sumarwanto, Rudi
INTEK: Jurnal Penelitian Vol 8 No 2 (2021): October 2021
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/intek.v8i2.2994

Abstract

The Bakaru PLTA is the largest hydroelectric power plant in South Sulawesi with a capacity of 126 MW. To generate that much power, a lot of water is required, therefore, the Bakaru hydropower dam is designed to be able to accommodate a lot of water. In operation, the Bakaru hydropower plant consists of 2 units. However, not all units operate normally, such as unit 2. In unit 2, there is a leak that occurs in the Turbine Pit. This leak is caused by abrasion of the u-packing guide vane. With a leak in the turbine pit, more approaches are needed to dispose of the water in the turbine pit to the pit drainage. Which later developed into an infusion system that utilizes gravity to discharge water from the turbine pit in basement 2 to the drainage pit in basement 3. However, in its development, it turns out that the volume of water discharged cannot be controlled so that, it can cause a condition where one day the infusion hose does not flow and causes an increase in the water level in the turbine pit. This rise in the level of the turbine pit is dangerous for the unit. This is because water can enter the breathing hole of the bearing turbine tank and contaminate the oil so the bearing temperature is high and causes a trip or in the worst case, causing equipment damage. However, in reality, using an infusion system using human labor is still often constrained in terms of time efficiency, consistency and cost. Because every time this activity is carried out, the workers who do it are not always the same person and scheduled. Therefore the efficiency is still low. The purpose of this study was to determine the optimal method of handling the increase in water level in the turbine pit so that unit trips do not occur caused by the increase in the water level in the turbine pit. Finally, it is interesting to discuss and find a solution by relocating the handling of leaks by "using an automatic method with a motorized valve by installing a Motorized Valve on the Turbine Pit, so there are financial and non-financial benefits to be obtained. From the results of using the automatic method with a motorized valve, the results obtained are faster cycle times for handling leaks in the turbine pit so there is no stop unit due to leakage disturbances in the turbine pit.