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mechmine vibration sensors datamining

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Maschinenüberwachung, neue technologien ermöglichen hohen Automatisierungsgrad (PDF in German) 329kB
Data Mining - das etwas andere Eldorado (PDF in German) 653kB
Mechmine flyer for Hannover Messe 2018 380kB
Is the time right for intelligent machine monitoring? (PDF in German) 275kB
Presentation "Reality check on vibration-based machine monitoring using AI", given May 2019 in Frankfurt (PDF) 2378kB
Mechmine 2019 product flyer 3267kB
"Practical Predictive Maintenance", Polydrive 2/19, (PDF in German) This article compares MEMS and piezo-based sensors and shows analytically, that MEMS are less suited for low RPM applications, i.e. below 500 RPM. It also shows the risk of using RMS data only, like most low-cost IoT systems do, to determine the health state of a bearing. Finally, that information lost early in the machine vibration data acquisition chain cannot be recovered later, also not with AI (e.g. deep neural networks), while appropriate data pre-processing can deliver significant performance gains. 1232kB
Technical Note (PDF in German) under Downloads: On critical aspects when measuring vibrations of very slow turning shafts and its solution. 364kB
Technical Note (PDF in German) under Downloads: On the influence of long cables on the signal bandwidth of IEPE Sensors and its remedy. 312kB
Technical Note (PDF in German) under Downloads: On the weakness of RMS-based machine monitoring to detect even larger bearing defects of machines through smart IoT sensors, and the mechmine way of observing bearing defects in useful time.  541kB
DEFEKTBASIERTE ANOMALIEDETEKTION - Maschinendefekte besser erkennen, Engl. "DEFECT-BASED ANOMALYDETECTION - improve machine defect detection":
It is known that Condition Monitoring can save maintenance costs. But basic IoT sensors, processing RMS measurements such as the RMS velocity, may detect machine defects when they are audible. This puts the whole IoT monitoring into question. However, with higher quality data, one can meet customers expectations of early warning and bearing and gear defect detection. Prior to anomaly detection, it is suggested to apply a defect classification, to improve sensitivity and specificity and meet customer needs. (PDF in German, Magazin Aqua&Gas, Nov2020)
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AUTOMATED RPM CORRECTION (Technical Note in German) - Trending, like following a BPFI defect, ist subject to the precise knowledge of the RPM value. This is usually accomplished with a dedicated tacho impulse sensor at extra cost. Mechmine solved the problem of poorer trends, caused from unknown RPM values, successfully with adanced signal processing methods. 436kB

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