Although the discrete wavelet transform has been used for diagnosing bearing faults for two decades, most work in this field has been done with test rig data. Since field data starts to be made more available, there is a need to shift into application studies.
The choice of mother wavelet, ie, the predefined shape used to analyse the signal, has previously been investigated with simulated and test rig data without consensus of optimal choice in literature. Common between these investigations is the use of the wavelet coefficients' Shannon entropy to find which mother wavelet can yield the most useful features for condition monitoring.
This study attempts to find the optimal mother wavelet selection using the discrete wavelet transform. Datasets from wind turbine gearbox accelerometers, consisting of enveloped vibration measurements monitoring both healthy and faulty bearings, have been analysed. The bearing fault frequencies' excitation level has been analysed with 130 different mother wavelets, yielding a definitive measure on their performance. Also, the applicability of Shannon entropy as a ranking method of mother wavelets has been investigated.
The results show the discrete wavelet transforms ability to identify faults regardless of mother wavelet used, with the excitation level varying no more than 4%. By analysing the Shannon entropy, broad predictions to the excitation level could be drawn within the mother wavelet families but no direct correlation to the main results. Also, the high computational effort of high order Symlet wavelets, without increased performance, makes them unsuitable.
Maintenance operations have significant influence on the economy and performance of mining companies. Unpredicted repairs cause interruptions and breakdowns in production. This means economic losses but, in some cases, also increasing environmental emissions in off-gases and wastewater. Condition based maintenance (CBM) can significantly reduce maintenance costs. Sensors and measurement devices offer a lot of data and assist workers to identify upcoming maintenance needs in advance. Typical measurement variables are for example vibration, temperature, different speeds and pressures. DEVICO project aims to develop a framework for solutions and combine condition monitoring and process data to integrate CBM to control and timing of the maintenance actions. On-line and periodic CM measurements can be combined with process measurements by using signal processing and feature extraction. Case study is conducted in Pyhäsalmi mine with Sandvik load haul dump (LHD) machinery. The condition monitoring system is installed on LHD front axle. The choice for the installation position was made based on the feedback and maintenance data gathered from mining companies. This information indicates that the axles are among the most critical parts in LHD machines.
In this work, two different types of evacuation situations were studied in order to provide validation data for some aspects of the evacuation modeling. The first type was evacuation drills which are normally carried out as part of the safety training of the staff in public buildings and offices. The second type was actual evacuations which occur every now and then. The main techniques used for the observation of evacuation events were video cameras, Radio Frequency Identification (RFID), and surveillance cameras. A large amount of information was obtained and the problems in the application of the observation techniques were identified. In particular, the results show that when the RFID technique is used, the placement of the antennas and tags is very important. With careful placement of the antennas and tags, the reliability of the RFID technique as applied in the current work may be sufficient for scientific purposes. In the observation of an actual evacuation of a large shopping centre, the recordings of the surveillance cameras were used to measure the flow rates of people. The results are very promising and indicate that the collection of surveillance camera recordings from large evacuations should be started.
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