Acoustic Engine Diagnostics for Real-Time Process Attribute Detection
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Solution Overview
Problem
Existing engine monitoring systems lack real-time and accurate methods to assess process attributes and control engine operations based on acoustic signatures, leading to potential deviations and inefficiencies.
Innovation Solution
A system utilizing acoustic sensors to generate time-dependent data signals, processed by a computing device to transform into frequency-domain spectra, enabling identification of process attributes and controlling engine components through correlation analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic sensors and frequency-domain analysis are implemented, then measurement precision of process attributes is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical sensing systems with acoustic field-based detection. Instead of using multiple mechanical sensors for different process attributes, the system uses acoustic sensors to capture sound waves that naturally propagate through the engine, extracting multiple process attributes (temperature, pressure, flow rate, component wear) from the acoustic signal's frequency-domain characteristics. This substitution reduces system complexity while improving measurement precision.
Solution Approach 2:
The acoustic sensing system serves multiple functions simultaneously. A single acoustic sensor array can detect various process attributes (temperature, pressure, flow rate, component wear, blockages) by analyzing different frequency bands of the acoustic signal. This multi-functionality eliminates the need for separate specialized sensors for each parameter, thereby reducing device complexity while maintaining high measurement precision across all detected attributes.
2Productivity
If real-time acoustic monitoring is implemented, then productivity is improved, but use of energy increases
Solution Approach 1:
The system employs periodic acoustic sampling rather than continuous monitoring. The acoustic sensors capture sound waves during specific cycles of engine operation, and the processing system analyzes the frequency-domain spectrum at these periodic intervals. This periodic action enables real-time monitoring capability while significantly reducing energy consumption compared to continuous monitoring, as the system only processes data when new acoustic cycles are captured.
Solution Approach 2:
The patent extracts only the essential information needed for process attribute determination from the acoustic signal. By transforming the acoustic signal into the frequency domain and identifying specific frequency bands associated with different attributes, the system extracts only the relevant spectral characteristics rather than processing the entire time-domain signal continuously. This extraction approach enables real-time monitoring while minimizing energy consumption by focusing computational resources only on the most informative frequency components.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables real-time monitoring and control of engine operations, reducing deviations and improving efficiency by accurately detecting component wear, blockages, and process variations.
Implementation Method 1
at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal. The acoustic signal is generated by an engine performing a process
Implementation Method 2
an acoustic data signal processing module configured to receive the at least one time-dependent acoustic data signal, and transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum
Data Source
AI summary
An example system includes at least one acoustic sensor configured to generate at least one time-dependent acoustic data signal indicative of an acoustic signal generated by an engine performing a process possessing a plurality of process attributes, and a computing device including an acoustic data signal processing module configured to receive the at least one time-dependent acoustic data signal, and transform the at least one time-dependent acoustic data signal to a frequency-domain spectrum, wherein each process attribute of the plurality of process attributes is associated with at least one respective frequency band, and a correlation module configured to determine a process attribute of the plurality of process attributes by identifying at least one characteristic of the frequency-domain spectrum.