VIBRATION MONITORING
VIBRATION MONITORING
Safe Operation with SMART MARINE Service of Digital Health Vibro-Monitoring Set
Predictive maintenance is the most effective strategy today. It is with our reliable SMART Service.
Advanced techniques such as vibration monitoring for machinery. Long-term analysis determines when maintenance is truly necessary.
We offer a reliable and convenient market solution: vibration data collection by onboard personnel with expert analysis conducted remotely by our accredited lab. Reliable service for safe navigation in simple way!
Service with Digital Health Vibro-Monitoring Set
- Simple & Remote Analysis of vibration data
- Simple to have data on regular basis for condition trending
- KPIs for Fleet Managers: Insights into performance, wear trends and maintenance forecasting.
For fleet monitoring, we include an extra module called «Business analytics and fleet KPIs», designed specifically for superintendents and fleet managers.
SMART MARINE Service with In-depth analytics of fleet is your choice!
The Digital Health Vibro-Monitoring Set provides a comprehensive hardware-software-service solution under a single contract, featuring a yearly subscription model without the need to buy a vibration meter. Clients achieve an impressive 15:1 Return-on-Investment starting from the first year.
Machinery condition report is based on detailed narrowband analysis of recorded time waveforms and processed spectrums of velocity, acceleration and demodulated acceleration, and supervised Machine Learning algorithm.
- High Frequency up to 10,000 Hz Time waveform analysis
- Low Frequency up to 1000 Hz Spectrum analysis
- High Frequency up to 10,000 Hz Spectrum analysis
- Demodulation analysis (Vibration demodulation or envelope analysis is useful to detect bearing early damage detection. Demodulation is a signal process to identify high vibration frequencies.)
- Crest factor (It is a parameter of a waveform, showing the ratio of peak values to the effective value. In other words, crest factor indicates how extreme the peaks are in a waveform.)
- Spectral kurtosis (It is a statistical parameter indicating how the impulsiveness of a signal varies with frequency. Since faults in rolling element bearings give rise to a series of short impulse responses as the rolling elements strike faults on the races, the SK is potentially useful for determining the frequency bands dominated by the bearing fault signals, usually containing resonance frequencies excited by the faults.)
- Pulsation index for reciprocating compressors (Pressure pulsation are generated in reciprocating compressors, not just at run speed but at multiples of run speed up to as high as 250 Hz. Pulsation generated at low compression ratio operating conditions, which are typical of pipeline installations, tend to be particularly severe. High pulsation at the compressor valves can adversely affect compressor performance and valve life.)
- Autocorrelation curve analysis (Autocorrelation, also known as serial correlation, is a statistical concept that measures the degree of similarity between a given time series and a lagged version of itself over successive time intervals. It describes the relationship between a variable's current value and its past values in a time series. Autocorrelation is used to understand the underlying patterns or structure in a time series, which can reveal information about trends, seasonality, and cycles.)
Fault indicators and limiting values are continuously monitored by the machine learning algorithm and the algorithm is updated automatically.
A wide range of machinery problems are detected at an early stage:
- bearing wear or defects;
- gear defects;
- lack of lubrication;
- pump impeller wear and cavitation defects;
- misalignment;
- unbalance;
- mounting problems;
- resonance vibration.