Signal Processing

The objective of this dataset is the fault diagnosis in diesel engines to assist the predictive maintenance, through the analysis of the variation of the pressure curves inside the cylinders and the torsional vibration response of the crankshaft. Hence a fault simulation model based on a zero-dimensional thermodynamic model was developed. The adopted feature vectors were chosen from the thermodynamic model and obtained from processing signals as pressure and temperature inside the cylinder, as well as, torsional vibration of the engine’s flywheel.

Supplementary Material for the paper "Binary Discrete Fourier Transform and its Inversion" by Howard W. Levinson and Vadim A. Markel, published in IEE Transactions on Signal Processing (2021)

 The data set contains 152 measurements of room impulse responses for direction of arrival estimation, using a compact three-channel microphone array. Sources are placed at 10-degree intervals from -90 to 90 degrees in the azimuth plane at range 150 cm. There are also 5 off-grid measurement positions and 6 off-range positions - at ranges 1 m, 2 m, 2.5 m and 3 m. The measurements are performed in a furnished classroom, which is approximately rectangular and of dimensions 9 x 6 x 3 m. The reverberation time is 0.4 s.

Some 6G use cases include augmented reality and high-fidelity holograms, with this information flowing through the network. Hence, it is expected that 6G systems can feed machine learning algorithms with such context information to optimize communication performance. This paper focuses on the simulation of 6G MIMO systems that rely on a 3-D representation of the environment as captured by cameras and eventually other sensors. We present new and improved Raymobtime datasets, which consist of paired MIMO channels and multimodal data.