Machine Fault Detection via Drive Power Spectrum Analysis
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Solution Overview
Problem
Existing fault detection methods in machines, such as vibration sensors and electrical parameter monitoring, fail to detect mechanical damage early enough to prevent complex and costly repairs, and are prone to failure or high costs.
Innovation Solution
Analyze the frequency spectrum of electrical power consumption parameters, comparing them to reference spectra to identify anomalies indicative of faults, and generate error detection signals when deviations occur, allowing for early detection and localization of mechanical issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vibration sensors are installed to detect mechanical vibrations, then fault detection capability is improved, but device complexity and installation cost increase
Solution Approach 1:
The patent replaces mechanical vibration sensors with electrical current monitoring to detect faults. By analyzing the frequency spectrum of electrical current consumed by the drive unit, the system detects periodic fluctuations that indicate mechanical faults, thereby eliminating the need for physical sensor installation while maintaining fault detection capability
Solution Approach 2:
The patent uses electrical current as an intermediary parameter to indirectly detect mechanical faults. Instead of directly measuring mechanical vibrations, the system monitors electrical current fluctuations that are coupled to mechanical conditions through the motor's operation, providing a non-contact fault detection method
2Reliability
If current intensity monitoring is used to detect faults, then fault detection is improved, but mechanical damage has already occurred requiring costly repairs
Solution Approach 1:
The patent performs preliminary spectral analysis of electrical current to detect periodic fluctuations that indicate incipient faults before they cause significant mechanical damage. By analyzing the frequency spectrum and comparing it to reference spectra, the system identifies early signs of problems such as unbalanced loads or mechanical defects, enabling preventive maintenance before catastrophic failure occurs
3Measurement precision
If vibration sensors are installed to detect faults, then fault detection accuracy is improved, but sensor damage and installation costs increase
Solution Approach 1:
The patent substitutes electrical current monitoring for mechanical vibration sensing, eliminating the need for physical sensor installation while maintaining fault detection accuracy. The electrical current measurements are obtained non-invasively and processed through spectral analysis to achieve precise fault detection without the costs and risks associated with sensor installation
Solution Approach 2:
The patent creates an electrical copy or representation of mechanical conditions through current spectral analysis. By analyzing the frequency spectrum of electrical current, the system generates an indirect but accurate representation of mechanical fault conditions, eliminating the need for direct mechanical measurement sensors
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 early detection and localization of mechanical faults in machines, facilitating planned maintenance before significant damage occurs, reducing unplanned interruptions and repair costs.
Implementation Method 1
an analysis module (4) by means of which the frequency spectrum of a measured variable (31) characterizing the electrical power consumption of a drive unit (3) is determined and analyzed with regard to anomalies indicating faults
Data Source
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Figure 3~4
Figure 5
AI summary
The invention relates to a method for detecting errors in a machine (1) comprising at least one electric device unit (3) for driving a machine assembly. The frequency spectrum of a measurement variable characterizing the electric power consumption of the drive unit (3) is determined and in an analyzing step, the frequency spectrum evaluates the measurement variable with respect to errors indicating abnormalities.