This article presents results of a quality evaluation study, considering voice transmission in a 6 kV medium voltage cable network using the BPL (Broadband over Power Line) communication system. The tests are carried out under real mining conditions for the selected power cable without voltage, earthed at both sides. Such a method of monitoring work conditions is of great importance, especially during a disaster. Power cables are potentially resistant to mechanical damage and, thus, ensure continuity of transmission, also, in cases of electricity stoppage and partial damage (interruption) of the phase conductors. The voice transmission quality is tested for a relatively low bitrate of 8 kbps–48 kbps using both induction and mixed induction-capacitive coupling with the power cable. Such a solution should provide both reliable and high-quality services, considering clear and understandable voice messages to people. The quality evaluation is carried out on a group of 15 people aged between 25–35 years old. The tested signal samples consist of voice messages in British English, German, and Polish. On the basis of the investigated results, respective conclusions are formulated.
A reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems. The air quality prediction data were collected from the Central Pollution Control Board (CPCB) from four cities in India: Bangalore, Chennai, Hyderabad, and Cochin. Normalization is performed using Min-Max Normalization and fills the missing values in the dataset. A Convolutional Neural Network (CNN) is applied to provide deep representation of the input dataset. The BSMO technique selects the relevant features based on the balancing factor and provides the relevant features for the Bi-directional Long Short-Term Memory (Bi-LSTM) model. The Bi-LSTM model provides the time series prediction of air quality for four cities. The BSMO model obtained higher feature selection performance compared to existing techniques in air quality prediction. The BSMO-BILSTM model obtained 0.318 MSE, 0.564 RMSE, and 0.224 MAE, whereas Attention LSTM reached 0.699 MSE, 0.836 RMSE, and 0.892 MAE. Our solution may be of particular interest to various governmental and non-governmental institutions focused on maintaining high Quality of Life (QoL) on the local or state level.
To use lithium-iron-phosphate battery packs in the supply systems of any electric mining equipment and/or machines, the required conditions of work safety must be met. This applies in particular to coal mines endangered by fire and/or explosion. To meet the spark-safety conditions, the cells (together with the battery management system—BMS) must be isolated from the influence of the environment, and therefore placed in special fire-tight housings. This significantly degrades the heat dissipation, thus affecting the operating conditions of the cell-packs. Therefore, their usage without the so-called BMS is not recommended, as shown in the authors’ preliminary research. In practice, various BMS are used, most often with the so-called passive balancing. However, their application in mines is uncertain, due to the effect of heating under operation. When it comes to active BMS, they usually possess a quite complex structure and hence, are relatively expensive. Therefore, the authors conducted research for two specially developed active and one commercial passive BMS cooperating with selected lithium-iron-phosphate (LiFePO4) batteries when used in a suspended mining vehicle type PCA-1. The tests were carried out under environmental temperatures ranging from +5 °C to +60 °C. The effect of mismatching (12.5% to 37.5% of total cells number) of the cell parameters on the temperature distribution and voltage fading at the terminals of individual cells was checked. As a result of the investigations, the practical usefulness of the developed active BMS was determined, enabling the extension of the lithium-iron-phosphate battery life under onerous mine conditions, for a single recharge, which is a novelty. On the basis of the obtained results, appropriate practical conclusions were formulated.
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