vibratsioonianalüüsi

Vibratsioonianalüüsi, English: vibration analysis, is a set of techniques used to measure, interpret, and evaluate the vibrational characteristics of mechanical systems. By detecting changes in frequency, amplitude, or phase of vibrations, engineers can assess the health of components such as motors, gearboxes, bearings, and structural assemblies. The primary aim of vibration analysis is to predict potential failures, optimize maintenance schedules, and improve overall system reliability.

The origins of vibratsioonianalüüsi can be traced back to the early 20th century when seismology and machinery troubleshooting overlapped. In the 1960s and 1970s, the development of digital signal processing and fast Fourier transform (FFT) algorithms expanded the technique’s applicability across industrial sectors. Today, it integrates with condition‑based maintenance strategies, predictive analytics, and the Internet of Things (IoT).

Key methods include time‑domain analysis, where raw acceleration signals are examined for spikes or trends; frequency‑domain analysis, where signals are transformed via FFT to reveal resonant peaks; and advanced time‑frequency methods such as wavelet transforms that capture transient events. Common hardware consists of accelerometers, velocity sensors, and data acquisition units that feed data into software platforms.

Applications range from manufacturing—monitoring rotating machinery—to aerospace, where turbine engines undergo rigorous vibrational profiling, and to civil engineering, where bridges and buildings are inspected for dynamic stresses. The discipline is governed by standards from organizations such as ISO, IEC, and ASME, which provide guidelines for sensor placement, data interpretation, and reporting.

Ongoing research focuses on machine learning integration, automated fault detection, and the use of MEMS sensors, aiming to deliver real-time diagnostics and reduce operational downtime.