Abstract:
The gas sampling system on LNG vessels plays an important role in detecting the
presence of methane gas. However, during operation, it may experience flow disturbances
(flow faults) that can reduce system performance and require manual intervention by
operators. This condition indicates the need for a system capable of automatically
cleaning the gas sampling line. This study aims to design an auto blowing system
prototype as an automated method for cleaning gas sampling lines using a pressure sensor
and an ESP32 microcontroller. The research method employed in this study was Research
and Development (R&D) using the ADDIE model, which consists of the analysis, design,
development, implementation, and evaluation stages. The developed prototype utilizes an
ESP32 microcontroller integrated with a pressure sensor to detect pressure changes as an
indication of flow disturbances. The system was designed to automatically activate the
auto blowing mechanism when the pressure reaches a threshold value of -5 kPa, with a
blowing duration of 10 seconds. The product testing results showed that the system was
able to distinguish between normal and disturbed conditions based on pressure changes
detected by the sensor. When the pressure reached or fell below the threshold value of -5
kPa, the system automatically activated the auto blowing process. Functional testing
results also demonstrated that all major components, including the pressure sensor, OLED
display, ESP32, relay, solenoid valve, and mini pump, operated according to their
intended functions. Validation results from two expert validators produced an average
score of 88%, categorized as “Highly Appropriate,” while assessments from seafarer
respondents ranged from 84% to 96% within the same category. These results indicate
that the developed prototype meets the feasibility requirements in terms of design,
functionality, effectiveness, consistency, and safety. Therefore, this study successfully
developed an auto blowing system prototype capable of detecting indications of flow
disturbances and automatically cleaning the sampling line as a preventive measure. The
system has the potential to be further developed to improve operational efficiency and
reduce dependence on manual cleaning procedures in LNG vessel gas sampling systems.
