# Investigation of Failure Causes of Oil Pump Based on Operating Conditions
###### Abstract
A thermodynamic model was developed that reproduces engine behavior not only under normal conditions but also under failure conditions [12]. [PERSON] and [PERSON] [13] reported an engine model for onboard engine failure simulation. A physical model was built for engine optimization and diagnostic purposes that can be used onboard ships. The engine model was calibrated using a low-speed marine diesel engine, and the results were successfully verified against the measurement [13]. [PERSON] et al. [14] investigated the impact of marine engine component failures upon an explosion in the starting air manifold. A cause-and-effect analysis of the explosions was performed, and their root causes were identified. In addition, a probabilistic model of an explosion in the starting air manifold of a marine engine was built using a fault tree analysis [14]. [PERSON] et al. [15] investigated the fault monitoring method of marine diesel engines. A hybrid fault monitoring scheme combining manifold learning and anomaly detection was proposed. The results showed that a zero-dimensional marine diesel engine simulation model realistically represented the behavior of the engine with acceptable parameter deviation [15]. [PERSON] et al. [16] investigated the failure of gear teeth fracture of seawater pumps in a diesel engine. The results showed that the root reason of the failure was gear fatigue fracture, which was caused by non-metallic inclusions in the teeth. The condition monitoring and fault diagnosis system (CMFDS) installed on the engine captured some useful information, which provided crucial clues to diagnose and locate the fault [16]. [PERSON] et al. [17] identified diagnostic signals in the composition of exhaust gas from marine four-stroke diesel engines. An active experiment was performed that consisted of measurements conducted during a laboratory-based engine operation with simulated malfunctions [17]. [PERSON] and [PERSON] [18] reported the condition-based maintenance strategy for fault diagnosis for ship engine systems. Certain parameters of the large-sized container ship are collected for the development of the condition-based maintenance strategy. These data were analyzed using an artificial neural network in order to create an engine performance model [18]. A number of related studies have been reported, but a database focused extensively on parts related to pumps, which play an important role in the engine room, has not been developed. Furthermore, it is difficult to find studies that have established an infrastructure capable of evaluating the performance of a pump and analyzed its behavior in normal and abnormal conditions using this infrastructure. In the present study, experimental research was conducted to build a condition-based ship device database. The failure mode was selected by analyzing the failure case and reliability analysis of the pump, which is an essential system. Fault scenarios were derived through several studies on how to test failure modes. The test bed for the land test was established for the fault test. In addition, a performance monitor was used to obtain the actual monitoring and measurement data using the system, and the data characteristics of the time and frequency region were observed using vibration data.