Turbo Machine Reliability Forecasting via Geospatial Data

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Turbo machines, such as gas turbines, face maintenance challenges due to environmental factors like temperature, humidity, and particulates, which affect their reliability and require timely maintenance to avoid premature failure and reduce operational costs.

Innovation Solution

A method and system that utilize geospatial data and operating factors to determine a reliability forecast for turbo machines, incorporating environmental factors like precipitation, dust, and sulfur dioxide levels, to inform maintenance schedules and extend operational life.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If maintenance is performed at regular intervals to ensure reliability, then component failure is prevented, but operational time is reduced and operational costs increase

Engineering Contradiction:

Improveturbo machine reliabilityVSAvoidoperational time

Core Design Contradiction:

ReliabilityVSDuration of action of moving object

Solution Approach 1:

The system performs preliminary assessment of maintenance needs by analyzing environmental factors (precipitation, dust, sulfur dioxide) and operating factors (load cycles, temperature) before actual maintenance is required. This allows predicting remaining useful life and scheduling maintenance only when necessary, rather than following fixed intervals, thus extending operational time while maintaining reliability

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors environmental conditions and operating parameters, using this feedback to dynamically adjust maintenance predictions. By incorporating real-time data from geospatial environmental sources and machine operating sensors, the system adapts maintenance scheduling to actual conditions, preventing both premature and delayed maintenance

Inventive Principle:

Principle #23Feedback

2Duration of action of moving object

If maintenance is delayed to extend operational time, then operational costs are reduced, but risk of premature component failure increases

Engineering Contradiction:

Improveoperational timeVSAvoidcomponent failure risk

Core Design Contradiction:

Duration of action of moving objectVSReliability

Solution Approach 1:

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides advance warning of potential reliability issues by predicting remaining useful life based on accumulated environmental and operating stressors. This allows operators to prepare for maintenance before components actually fail, cushioning against the risk of premature failure while maximizing operational time

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

3Measurement precision

If environmental factors are monitored to improve maintenance timing, then maintenance precision is improved, but system complexity increases

Engineering Contradiction:

Improvemaintenance timing accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system uses environmental factors (precipitation, dust, sulfur dioxide levels) and operating factors (load cycles, temperature) as intermediary indicators of component stress and degradation. These measurable environmental parameters serve as proxies for internal component condition, allowing indirect but accurate assessment of maintenance needs without requiring complex internal sensors or direct component monitoring

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system replaces complex mechanical monitoring of component wear and degradation with environmental and operational data analysis. By using geospatial environmental data and operating parameters to predict remaining useful life, the system substitutes direct mechanical assessment with computational modeling, reducing the need for complex diagnostic equipment

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS9557246B2Method and system for determining power plant machine reliability

Publication Date: 2017.01.31 GE INFRASTRUCTURE TECH LLC

AI summary

Disclosed are methods and systems to determine a power plant machine reliability forecast. In an embodiment, a method may comprise obtaining an environmental factor of a power plant machine based on geospatial data of a first area and location data of a second area, obtaining an operating factor of the power plant machine, and determining a reliability forecast based on the obtained environmental factor and the obtained operating factor.