CASE STUDIES » AI/ML TECHNOLOGIES

Case Studies

Explore how Turbine Logic helps companies like yours optimize the performance of your assets through advanced analytics, diagnostics, and engineering expertise.

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Other Studies

Bifacial Solar Module Performance Analysis

A client sought to better understand the real-world performance benefits of bifacial photovoltaic modules compared to traditional monofacial installations. With growing industry interest in bifacial technology, there was a need for rigorous, data-driven analysis to quantify actual performance gains and identify the factors that most significantly influence energy production from these advanced solar modules.

Sensor Health Monitoring for Gas Turbine Operations

Gas turbine monitoring and diagnostics centers frequently encounter false alarms that consume valuable time and resources. Many of these false alarms stem from issues within the instrumentation chain: sensors that have drifted, failed, or produced corrupted data during transmission or storage.

Digital Twin Framework Development for the Power Generation Industry

A client in the power generation sector recognized that digital twin technologies were being developed inconsistently across their organization, leading to duplicated efforts and challenges in deploying these tools effectively. Without a standardized approach, teams struggled to leverage real-world operational data, create adaptable models, and integrate emerging technologies like AI and machine learning into their workflows.

Combustion Dynamics Monitoring Implementation

A power generation company sought to enhance their gas turbine fleet monitoring capabilities, particularly around combustion dynamics. They needed a solution that could provide early detection of anomalous behavior related to instrumentation issues, tuning problems, and potential hardware damage before these issues led to costly unplanned outages or equipment damage.

Legacy Software Modernization for Continued Platform Compatibility

A client faced a growing compatibility challenge with a critical performance monitoring tool that had been in use for years. The software relied on older architecture that was becoming increasingly incompatible with modern computing environments as industry standards evolved.

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