Rotating Machine Rotor Contact Diagnosis via Elastic Wave Analysis
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Solution Overview
Problem
Existing technologies face challenges in accurately determining contact between rotors and the casing in rotating machines, which can lead to machine breakdowns, and existing methods are not effective in distinguishing between rotor-rotor and rotor-casing contacts.
Innovation Solution
A rotating machine abnormality diagnosing apparatus that includes a sensor to detect elastic waves, performs time-frequency analysis, extracts data representing intensity and time relationships of specific frequency components, and determines contact based on intensity variations corresponding to the rotational cycles of the rotors and the ratio of protrusions to recesses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing diagnostic methods are used to detect elastic waves from rotor contacts, then general contact detection is possible, but accurate distinction between rotor-rotor contact and rotor-casing contact cannot be achieved
Solution Approach 1:
The patent segments the contact detection process into distinct analysis stages: detecting elastic waves from rotor-casing contacts, separately detecting elastic waves from rotor-rotor contacts, and comparing the two datasets. This segmentation enables precise identification of contact types by analyzing them as separate phenomena with distinct characteristic signals.
Solution Approach 2:
The patent applies local quality analysis by examining the specific characteristics of elastic wave signals at different locations and conditions. It analyzes the local signal features (frequency content, amplitude patterns, timing) specific to each contact type - rotor-casing versus rotor-rotor - to distinguish between them accurately.
2Measurement precision
If simple elastic wave detection is used, then the device complexity is low, but the ability to accurately determine contact between rotors and distinguish contact types is insufficient
Solution Approach 1:
The patent performs preliminary actions by pre-defining the diagnostic流程 and analysis methods before actual contact detection occurs. It establishes the framework for detecting elastic waves, analyzing their characteristics, and comparing them against predetermined criteria to determine contact types, enabling accurate diagnosis without requiring overly complex real-time processing.
Solution Approach 2:
The patent introduces intermediary analysis components that mediate between the raw elastic wave signals and the final contact determination. These intermediaries include signal processing units that extract features, compare datasets, and identify contact types, providing a structured approach that manages system complexity while maintaining high measurement precision.
3Reliability
If contact detection focuses only on rotor-casing contact, then the diagnosis is simple, but rotor-rotor contact which causes breakdown cannot be accurately detected
Solution Approach 1:
The patent segments the diagnostic capability into separate detection pathways: one for rotor-casing contact and another for rotor-rotor contact. Each pathway has its own analysis criteria and evaluation methods, enabling reliable detection of both contact types without creating an overly complex integrated system.
Solution Approach 2:
The patent creates a multi-functional diagnostic system that can detect and analyze multiple contact types using a unified elastic wave detection approach. The same basic sensor and signal processing infrastructure serves both rotor-casing and rotor-rotor contact detection, with differentiation achieved through characteristic signal analysis rather than separate dedicated systems.
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 accurate determination of rotor-rotor contact and discriminates between rotor-rotor and rotor-casing contacts, reducing the risk of machine breakdowns by utilizing time-frequency analysis and autocorrelation functions to identify specific intensity variations.
Implementation Method 1
a sensor which detects an elastic wave generating in the rotating machine, and outputs a signal representing intensity and time relationship of the elastic wave
Data Source
AI summary
A rotating machine abnormality diagnosing apparatus for diagnosing an abnormality in a rotating machine includes: an analyzing part which performs a time-frequency analysis to a signal S representing intensity and time relationship of an elastic wave generating in the rotating machine; an extracting part which extracts second data representing intensity and time relationship of a predetermined frequency component from first data obtained by the time-frequency analysis; and a determining part which determines that a first rotor and a second rotor are in contact with each other when the second data contains intensity variation having a cycle represented by T1×b=T2×a, in which a rotational cycle of the first rotor is denoted by T1, a rotational cycle of the second rotor is denoted by T2, and a ratio of a number of protrusions to a number of recesses is denoted by a:b.