This article demonstrates real-time monitoring of high-speed spindles in CNC machines, indicating innovations in fault diagnosis.
This article addresses the monitoring and diagnosis of high-speed spindles (HSM) used in CNC grinding machines, emphasizing the importance of the real-time evaluation of their dynamic behavior during commissioning. Due to the complexity of these dynamic phenomena, especially at high speeds (up to 150,000 RPM), common faults such as bearing wear, imbalance, or misalignment can lead to catastrophic failures and high repair costs. An original method is proposed, based on synchronous envelope vibration analysis (SEVA) using the Hilbert transform, to detect mechanical defects in both low-frequency domains (imbalance, mechanical looseness) and high-frequency domains (bearing faults). The system includes vibration, temperature, and speed sensors, and the experimental protocol involves step-by-step monitoring from 10,000 to 90,000 RPM. Through synchronous FFT analysis and IFFT, critical frequencies and their impacts on machining quality are identified. The method enables the accurate fault diagnosis of new or refurbished spindles under real industrial conditions, reducing downtime and production losses. The method involves both local and remote real-time monitoring and diagnosis using a remote data center protocol.
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Bîșu et al. (2025) studied this question.
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