Control Loop Oscillation Diagnosis Using IOCAD Autocorrelation

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Solution Overview

Problem

Existing methods for detecting and diagnosing oscillations in control loops are often cumbersome, require reference models, and are not efficient in real-time monitoring, especially in complex industrial processes.

Innovation Solution

The method involves creating an Input-Output Cross Autocorrelation Diagram (IOCAD) using the autocorrelation of control actions and process variables, combined with indicators like ITAE, R2, and Levene's statistical test, to diagnose oscillations and assess control loop performance without requiring a reference model.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If rule-based oscillation detection methods are used, then oscillation detection capability is improved, but device complexity and difficulty of implementation increase

Engineering Contradiction:

Improveoscillation detection capabilityVSAvoidimplementation complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the oscillation detection process into distinct functional modules: autocorrelation calculation module, oscillation detection module, and performance assessment module. Each module performs a specific function, making the overall system more manageable and easier to implement while maintaining high detection capability through the systematic application of autocorrelation analysis.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent uses autocorrelation to create a simplified representation (copy) of the control loop behavior. By analyzing the autocorrelation function of the control signal and process variable, the system captures essential oscillation characteristics without requiring complex models or reference data, thus reducing implementation complexity while preserving detection accuracy.

Inventive Principle:

Principle #26Copying

2Measurement precision

If reference models are required for performance assessment, then assessment accuracy is improved, but ease of operation and adaptability deteriorate

Engineering Contradiction:

Improveperformance assessment accuracyVSAvoidease of implementation

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent implements a self-service approach where the control loop assesses its own performance using its own historical data. The autocorrelation analysis is performed on the actual control signal and process variable from the loop itself, eliminating the need for external reference models. This makes the system easier to operate and more adaptable to different processes while maintaining assessment accuracy through statistical analysis of the loop's own behavior patterns.

Inventive Principle:

Principle #25Self-service

3Device complexity

If visual inspection methods are used, then simplicity is maintained, but productivity and coverage deteriorate

Engineering Contradiction:

Improvemethod simplicityVSAvoidinspection efficiency

Core Design Contradiction:

Device complexityVSProductivity

Solution Approach 1:

The patent replaces the mechanical visual inspection process with an automated computational system. Instead of manually examining control loop behaviors, the system automatically calculates autocorrelation functions and analyzes oscillation patterns using computer algorithms. This substitution dramatically improves productivity and coverage, enabling assessment of hundreds or thousands of control loops while maintaining the simplicity of the underlying detection principle through straightforward autocorrelation computation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of information

If autocorrelation analysis is applied to both control action and process variable, then diagnostic capability is improved, but use of energy and computational load increase

Engineering Contradiction:

Improvediagnostic information completenessVSAvoidcomputational energy consumption

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

The patent merges the analysis of control action and process variable into a unified diagnostic framework. By computing autocorrelation for both signals and comparing their characteristics, the system obtains comprehensive diagnostic information about oscillation sources and loop performance. The merging of these two analysis streams allows efficient use of computational resources while maximizing the information gained, as the combined perspective reveals diagnostic insights that neither signal alone could provide.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20250138520A1Methods for diagnosing and auditing control loops and method for comparing the performance of a current control loop

Publication Date: 2025.05.01 PETROLEO BRASILEIRO SA PETROBRAS

AI summary

The present invention refers to an audit method and a diagnostic method in industrial control loops through the detection of oscillations in time series originating from the control action and the controller output, through a technique based on autocorrelation, wherein an Input-Output Cross Autocorrelation Diagram (IOCAD) is developed to monitor the performance of control loops. Specifically, with the sensor signal of the manipulated variable (MV) and the sensor signal of the controlled variable (PV), autocorrelations of the MV and PV are calculated, generating the IOCAD. In this way, indicators are generated that allow auditing and diagnosing control loops. The invention further relates to a method for comparing the performance of a current control loop with a reference control loop through the IOCAD.