In high-speed and continuously running packaging equipment, the drive shaft is the core component of power transmission, and its health status directly affects the stability of the production line. Traditional vibration monitoring technology mostly uses a threshold alarm mechanism, which is difficult to capture early hidden fault characteristics. This study proposes a shaft system health monitoring method based on vibration spectrum analysis, which achieves accurate identification of fault initiation by establishing a multidimensional feature matrix.
Technical principle
This solution deploys three-axis acceleration sensors at both ends of the drive shaft to collect vibration signals in the range of 0.5-10kHz. Through the improved fast Fourier transform (FFT) algorithm, the time domain signal is converted into a three-dimensional spectrum diagram: the horizontal axis is frequency (0-5kHz), the vertical axis is amplitude (0-20g), and the color scale represents energy density (dB/Hz). Focus on monitoring three characteristic frequency bands:
.Baseband (±5% of the corresponding frequency of shaft speed): sudden changes in amplitude reflect shaft imbalance
.Double frequency band: harmonic energy growth indicates coupling misalignment
.High frequency resonance band (>3kHz): discrete peaks indicate micro cracks in the bearing raceway
The system has a built-in self-learning module that can dynamically establish a device fingerprint library. When it is detected that the energy density of a certain frequency band exceeds the baseline value by 15%, a three-level response mechanism is automatically triggered:
·Level 1: Adjust the output torque of the drive motor (±5% range) for dynamic compensation
·Level 2: Call the backup transmission path to maintain production
·Level 3: Locate the fault coordinates and generate a maintenance strategy tree
Industrial verification
In a 3720-hour continuous test on a dairy packaging line, the system successfully warned of 7 types of faults, including journal wear (412 hours in advance) and keyway cracking (83 hours in advance). Compared with traditional monitoring methods, this technology reduces the false alarm rate to 1.2% (the industry average is 8.7%), and the average fault location time is shortened to 18 minutes. Especially when dealing with instantaneous overload conditions, its dynamic torque compensation function stabilizes the vibration amplitude of the shaft system in the range of 76%-92% of the safety threshold.
Engineering Value
The core breakthrough of this technology is to upgrade vibration analysis from single threshold monitoring to state trend management. By establishing a three-dimensional time-frequency-energy model of shaft vibration, three dimensions have been improved:
. Fault detection sensitivity: can identify shaft bending deformation at the level of 0.05mm
. Remaining life prediction: The calculation error based on the Weibull distribution model is ≤12%
. Maintenance decision optimization: Increase the proportion of planned maintenance from 38% to 71%
Currently, this technology has formed a modular solution that supports installation without stopping the equipment. Engineering practice has proved that its unique resonant frequency dynamic compensation algorithm can increase the MTBF (mean time between failures) of the drive shaft system to 18,000 hours, 2.3 times higher than traditional solutions, providing a new technical paradigm for predictive maintenance of packaging equipment.
