CASE STUDIES » SENSOR HEALTH PARAMETER CALCULATION

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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Predictive Maintenance Analytics for Solar Generation Assets

A utility-scale solar plant operator sought to transition from reactive and preventative maintenance practices toward more cost-effective condition-based approaches. The challenge was identifying performance anomalies and equipment issues early enough to reduce energy losses and maintenance costs, while minimizing false alarms that waste operational resources.

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.

Digital Twin Model Development for Industrial Gas Turbines

A client needed to expand their gas turbine monitoring and diagnostic capabilities to cover additional equipment types within their fleet. Existing digital twin models were limited to certain turbine configurations, creating gaps in their ability to perform comprehensive performance analysis across all assets.

Aeroderivative Gas Turbine Digital Twin Development

A power generation operator sought to expand their monitoring and diagnostic capabilities for aeroderivative gas turbines. While digital twin technology had proven valuable for frame-type units, the client needed similar capabilities extended to a different class of equipment, along with support for implementing advanced combustion monitoring techniques.

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.

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