Motor Failure Detection Using Acceleration Current Frequency Analysis
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Solution Overview
Problem
Conventional failure symptom detection methods for electric motor-provided equipment are inaccurate due to noise interference from inverter driving and load variations, leading to erroneous detection of abnormality.
Innovation Solution
A failure symptom detection device and method that utilizes current detection, frequency analysis of q-axis current during the acceleration period of the electric motor, and comparison with reference values to accurately identify abnormality without additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If current and voltage signals are analyzed continuously for failure detection, then monitoring capability is improved, but measurement precision deteriorates due to noise from inverter driving and load variations
Solution Approach 1:
The patent segments the current signal analysis by extracting only the acceleration period current characteristics from the overall operation cycle. This segmentation isolates the diagnostic information from noise-contaminated steady-state operation, thereby maintaining monitoring capability while improving measurement precision through selective signal analysis.
Solution Approach 2:
The patent applies preliminary action by performing frequency analysis on current signals during the acceleration period before the motor reaches steady state. This timing captures diagnostic information before load variations and inverter noise fully manifest, enabling accurate failure detection without continuous monitoring of noisy operational phases.
2Reliability
If additional sensors are installed for constant monitoring, then detection reliability is improved, but device complexity increases
Solution Approach 1:
The patent implements self-service by utilizing the electric motor's existing current signals for diagnostic purposes. The motor's own operational characteristics during acceleration provide sufficient information for failure detection, eliminating the need for external sensors and maintaining detection reliability while avoiding increased device complexity.
Solution Approach 2:
The patent applies universality by making the current detection unit serve dual functions: both controlling motor operation and providing diagnostic information for failure detection. This multi-functionality maintains detection reliability using existing infrastructure, thereby avoiding the need for additional specialized sensors and reducing device complexity.
Data Source
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AI summary
This failure symptom detection device includes: a diagnosis calculation unit (91) which calculates index values for abnormality-presence/absence determination for electric motor-provided equipment (1), from a detection result of current flowing from a driving device (4) to an electric motor (3); and a diagnosis determination unit (92) which determines presence/absence of abnormality of the electric motor-provided equipment (1) from a calculation result of the diagnosis calculation unit (91). The diagnosis calculation unit (91) includes a starting current extraction unit (911) which, from detected current, extracts current in an acceleration period until a constant rotational speed is reached after starting of the electric motor (3), a data generation unit (914) which divides current data in the acceleration period extracted by the starting current extraction unit (911), into pieces of data, and a frequency analysis unit which performs frequency analysis on each piece of data divided by the data generation unit (914).