Compressor Failure Prediction via Pressure Volume Cycle Analysis
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Solution Overview
Problem
Equipment in chemical and petrochemical plants, such as compressors, deteriorate over time, leading to decreased efficiency and potential failure due to environmental stresses and operational issues like surge, which can result in reduced performance and shortened lifespan, necessitating predictive maintenance and efficient control systems.
Innovation Solution
A system comprising sensors, a data collection platform, and a data analysis platform that predicts part failures in compressors by analyzing pressure and volume compression cycle data, allowing for adjustments to system control valves to prevent damage and optimize operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If continuous operation of compressor is maintained, then productivity is improved, but equipment reliability deteriorates due to deterioration and potential failure
Solution Approach 1:
The system performs preliminary action by predicting compressor failures before they occur through analysis of pressure and volume compression cycle data. The data analysis platform identifies trends and patterns that indicate impending failures, allowing maintenance to be scheduled in advance rather than waiting for actual failure, thus maintaining continuous operation while preventing reliability deterioration.
Solution Approach 2:
The system implements feedback by continuously monitoring compressor performance through sensors that collect pressure and volume data during compression cycles. This feedback loop provides real-time information to the data analysis platform, which compares actual performance against expected patterns to detect deviations indicating deterioration, enabling proactive maintenance decisions that balance continuous operation with reliability preservation.
2Duration of action of stationary object
If predictive maintenance is implemented, then equipment lifespan is extended, but device complexity increases due to additional sensors and data analysis systems
Solution Approach 1:
The system applies universality by designing the data collection platform and data analysis platform to serve multiple functions. These platforms not only predict compressor failures but also monitor overall equipment performance, track maintenance schedules, and provide operational insights. This multi-functionality justifies the added complexity by delivering comprehensive value beyond simple failure prediction, thereby extending equipment lifespan through proactive maintenance.
Solution Approach 2:
The system implements self-service by enabling the compressor system to monitor and diagnose its own condition through integrated sensors and analysis platforms. The equipment essentially performs self-diagnosis by analyzing its own pressure and volume compression cycle data, identifying potential failures, and triggering maintenance alerts without requiring external inspection systems, thus extending lifespan while managing complexity through autonomous operation.
3Reliability
If system control valve adjustment is made to reduce pressure, then compressor damage is prevented, but process efficiency decreases
Solution Approach 1:
The system applies preliminary anti-action by taking preventive measures through control valve adjustment before compressor damage occurs. The data analysis platform predicts failures and triggers automated control valve adjustments to reduce pressure and prevent catastrophic damage. This preliminary protective action maintains reliability by preventing damage while the system schedules maintenance during planned downtime rather than forcing continuous operation at reduced efficiency.
Solution Approach 2:
The system performs preliminary action by proactively adjusting the control valve based on predicted failure trends rather than waiting for actual damage. This allows the system to maintain protective pressure reduction measures in advance, preventing compressor damage while planning maintenance activities during scheduled downtime, thus balancing reliability protection with process efficiency considerations.
Data Source
AI summary
A plant or refinery may include equipment such as condensers, regenerators, distillation columns, rotating equipment, compressors, pumps, turbines, or the like. Different operating methods may impact deterioration in equipment condition, thereby prolonging equipment life, extending production operating time, or providing other benefits. Mechanical or digital sensors may be used for monitoring equipment to determine whether problems are developing. For example, sensors may be used in conjunction with one or more system components to perform invariant mapping, monitor system operating characteristics, and/or predict pressure, volume, surges, reactor loop fouling, gas quality, or the like. An operating condition (e.g., of one or more pieces of equipment in the plant or refinery) may be adjusted to prolong equipment life or avoid equipment failure.