On-site Bearing Vibration Signal Acquisition and Time-Domain Analysis

When acquiring on-site bearing vibration signals, several critical details require attention. Important factors include signal acquisition locations and recording duration. For different bearing types, we can compute standard time-domain indicators such as Root Mean Square (RMS) value, peak value, and peak-to-peak value. These metrics provide valuable insights into bearing operating conditions, enabling early detection of abnormalities and ensuring equipment reliability. From a programming perspective, vibration signal processing typically involves: - Signal acquisition using sensors (accelerometers) with proper sampling frequency configuration - Data preprocessing including filtering and noise reduction algorithms - Time-domain calculation using mathematical operations: * RMS: sqrt(mean(signal.^2)) * Peak value: max(abs(signal)) * Peak-to-peak: max(signal) - min(signal) Implementation in MATLAB or Python would involve reading sensor data, applying digital filters, and computing these indicators through array operations. Proper signal windowing and averaging techniques ensure statistical reliability of the results.