PFSA-Based Oscillatory Instability Detection in Turbulent Systems

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Solution Overview

Problem

Existing methods fail to effectively predict and prevent oscillatory instabilities in turbulent systems, leading to performance degradation and structural damage, as they often rely on post-instability detection and require high energy consumption or overlook nonlinear dynamics.

Innovation Solution

A system and method using probabilistic Finite State Automata (PFSA) to analyze symbolic time series signals from dynamic state variables, enabling the prediction of oscillatory instability onset and allowing for proactive control measures to prevent instability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional pressure fluctuation measurement methods are used to detect oscillatory instability, then instability detection is achieved, but high energy consumption and requirement for external actuators occur

Engineering Contradiction:

Improveinstability detection reliabilityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system uses the device's own operational parameters (pressure, temperature, flow rate) to detect instability onset through automated analysis, eliminating the need for external actuators and reducing energy consumption while maintaining reliable detection

Inventive Principle:

Principle #25Self-service

2Reliability

If conventional delayed control signals are used to control oscillatory instability, then active control is achieved, but damage to the device may already occur by the time control is initiated

Engineering Contradiction:

Improvecontrol effectivenessVSAvoidresponse time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of operational parameters to detect early signs of instability onset before full instability occurs, enabling proactive control measures to be initiated in advance and preventing device damage

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors operational parameters and provides real-time feedback on stability status, allowing dynamic adjustment of control actions based on current system state to maintain effective control

Inventive Principle:

Principle #23Feedback

3Reliability

If frequency domain approach is used to detect oscillatory instability, then instability onset detection is enabled, but noise in the device reduces detection reliability

Engineering Contradiction:

Improvedetection capabilityVSAvoiddetection reliability in noisy environment

Core Design Contradiction:

ReliabilityVSDifficulty of detecting and measuring

Solution Approach 1:

The system transforms the analysis from frequency domain to time domain by analyzing the temporal evolution of correlation coefficients of operational parameters, which provides better noise immunity and more reliable detection in noisy environments

Inventive Principle:

Principle #35Parameter changes

4Reliability

If autocorrelation of pressure signals is used to predict stability margin, then stability monitoring is achieved, but nonlinear dynamic characteristics prior to instability are overlooked

Engineering Contradiction:

Improvestability prediction accuracyVSAvoidnonlinear dynamic information

Core Design Contradiction:

ReliabilityVSLoss of information

Solution Approach 1:

The system dynamically computes correlation coefficients between multiple operational parameters (pressure, temperature, flow rate) to capture the evolving nonlinear relationships and dynamic characteristics of the system as it approaches instability, preserving information that linear autocorrelation would miss

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS10095247B2System and method for controlling oscillatory instabilities in a device

Publication Date: 2018.10.09 INDIAN INST OF TECH MADRAS

AI summary

A method for detecting onset of oscillatory instability in a device is described. The method includes obtaining a symbolic time series of a time series signal corresponding to a dynamic state variable of the device. The method further includes detecting the onset of oscillatory instability in the device based on the symbolic time series.