Flight Sensor Data Analysis via Parameter Manipulation Language
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Solution Overview
Problem
Current tools for analyzing flight sensor data require extensive programming knowledge and are complex, making it difficult for engineers and data analysts without programming expertise to perform operations, and are prone to errors leading to increased debugging time and resource usage.
Innovation Solution
The Parameter Manipulation Language (PML) is introduced, which allows users to describe flight sensor parameters and operations at a high level, generating executable code that can be executed by a processor to perform operations on flight sensor data, supporting arithmetic, Boolean, and aggregation operations, and handling null values, thereby reducing the complexity and error rate.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic visualization and analysis tools like Python are used to manipulate flight sensor data, then operational flexibility and analysis capability are improved, but the complexity of the system increases and requires hands-on programming experience
Solution Approach 1:
The patent introduces an intermediary component that automatically generates and executes code based on user specifications. This intermediary translates high-level user requirements into executable code without requiring users to directly write or understand programming syntax, thereby reducing complexity while maintaining analysis capability.
Solution Approach 2:
The system performs self-service by automatically generating, validating, and executing the code needed to manipulate flight sensor data. The code generation module creates appropriate code snippets based on user input, and the execution module runs this code automatically, eliminating the need for users to manually write and debug code.
2Adaptability or versatility
If hands-on programming operations are required to load, clean, and transform flight sensor data, then data manipulation flexibility is improved, but the ease of operation deteriorates for non-programmers
Solution Approach 1:
The patent introduces an intermediary component that automatically generates and executes code based on user specifications. This intermediary translates high-level user requirements into executable code without requiring users to directly write or understand programming syntax, thereby reducing complexity while maintaining analysis capability.
Solution Approach 2:
The system uses templates and predefined code patterns that can be automatically copied and adapted to specific data manipulation tasks. Instead of requiring users to create code from scratch, the system provides reusable code templates that are automatically instantiated and customized based on user requirements.
3Extent of automation
If computer code is generated to perform technical operations on flight sensor data, then automation is improved, but the reliability decreases due to potential errors and debugging requirements
Solution Approach 1:
The system incorporates feedback mechanisms where the execution module monitors code execution and provides feedback to the code generation module. This feedback loop allows the system to learn from execution results, identify errors, and improve code generation accuracy over time, thereby enhancing reliability while maintaining automation.
Solution Approach 2:
The patent implements error handling and validation mechanisms that are built into the code generation process beforehand. The system anticipates potential errors and incorporates defensive programming techniques, error checking, and validation rules into the generated code, cushioning against failures before they occur.
Data Source
AI summary
A method for performing an operation on a flight sensor parameter includes receiving instructions indicating a description of a flight sensor parameter and an operation to be performed on the flight sensor parameter. The method includes generating executable code based on the instructions indicating the description and the operation. The method includes, after generating the executable code, associating the executable code with flight sensor data from one or more sensors. The flight sensor parameter includes a variable of the flight sensor data. The method further includes executing the executable code at a processor using the flight sensor data as an input to generate an output that indicates results of the operation.