Drill bit vibration data for lateral, axial, and torsional directions of a drill bit is collected for a simulated or deployed drill bit for visualization of 3D coupled vibration. A frequency converter transforms the drill bit vibration data into frequency vibration data. A drill bit analyzer identifies local maxima (“peaks”) in the frequency vibration data in each of the lateral, axial, and torsional directions. Common peaks across all 3 directions with sufficiently high frequency and sufficiently high bit rotation speed are indicated as 3D coupled vibration. A drill bit data visualizer uses the indications of 3D coupled vibration in addition to the vibration data and frequency vibration data to generate visualizations of 3D coupled vibration in the drill bit.

Drill bit vibration data for lateral, axial, and torsional directions of a drill bit is collected for a simulated or deployed drill bit for visualization of 3D coupled vibration. A frequency converter transforms the drill bit vibration data into frequency vibration data. A drill bit analyzer identifies local maxima (“peaks”) in the frequency vibration data in each of the lateral, axial, and torsional directions. Common peaks across all 3 directions with sufficiently high frequency and sufficiently high bit rotation speed are indicated as 3D coupled vibration. A drill bit data visualizer uses the indications of 3D coupled vibration in addition to the vibration data and frequency vibration data to generate visualizations of 3D coupled vibration in the drill bit.

A computer-implemented method of Condition Monitoring (CM) for rotating machines like motors, a corresponding computer program, computer-readable medium and data processing system for CM for rotating machines as well as a system including the data processing system for CM for rotating machines. M accumulator variables are updated in real-time based on L samples including a current sample sn and at least one preceding sample Sn−1 of input data. Based on the M accumulator variables N spectral features are computed in real-time. A condition of the rotating machine is determined based on the N spectral features.

A system for monitoring and identifying states of a semiconductor device, the system including at least one acoustic sensor for sensing acoustic emission emitted by at least one semiconductor device operating at a voltage of less than or equal to 220 V, the at least one acoustic sensor outputting at least one acoustic emission signal and a signal processing unit for receiving the at least one acoustic emission signal from the at least one acoustic sensor and for analyzing the at least one acoustic emission signal, the signal processing unit providing an output based on the analyzing, the output being indicative at least of whether the at least one semiconductor device is in an abnormal operating state with respect to a normal operating state of the semiconductor device.

A system for monitoring and identifying states of a semiconductor device, the system including at least one acoustic sensor for sensing acoustic emission emitted by at least one semiconductor device operating at a voltage of less than or equal to 220 V, the at least one acoustic sensor outputting at least one acoustic emission signal and a signal processing unit for receiving the at least one acoustic emission signal from the at least one acoustic sensor and for analyzing the at least one acoustic emission signal, the signal processing unit providing an output based on the analyzing, the output being indicative at least of whether the at least one semiconductor device is in an abnormal operating state with respect to a normal operating state of the semiconductor device.

A system for monitoring at least one machine including a plurality of magnetic sensors synchronously sensing magnetic fields emitted by at least one machine, along a corresponding plurality of channels and outputting magnetic field emission signals corresponding to the magnetic fields, a signal analyzer receiving at least a portion of the magnetic field emission signals, performing analysis thereof, and providing an output based on the analysis, the output including at least an indication of a condition of the at least one machine, and a control module receiving the indication of the condition and initiating at least one of a repair event on the at least one machine, an adjustment to a maintenance schedule of the at least one machine and an adjustment to an operating parameter of the at least one machine based on the indication, whereby efficacy of the at least one machine is improved.

A method including measuring vibrations of a rotating machine during its operation, using a vibration sensor. Next, from the signal measured by the sensor, automatically extracting, using an electronic detection device, a first signal representative of components of a first frequency range of the measured vibration signal, and a second signal representative of a second frequency range of the measured vibration signal. Then, from the first signal, calculating a first data set belonging to a time domain of the first signal, and extracting first calculation elements therefrom. Next, from the second signal, calculating a second data set belonging to a frequency domain of the second signal, and extracting second calculation elements therefrom. Lastly, determining a health index of the bearing from each of the extracted calculation elements.

A rail break detection device to which an output waveform from a vibration sensor, which is a first vibration sensor, and an output waveform from a vibration sensor, which is a second vibration sensor, are input, the vibration sensors being mounted on different positions of rails, includes a waveform similarity determination unit to compare impulse waveforms separated from the output waveforms or compare continuous waveforms separated from the output waveforms, and determine similarity therebetween, and detects a break of a rail.

A rail break detection device to which an output waveform from a vibration sensor, which is a first vibration sensor, and an output waveform from a vibration sensor, which is a second vibration sensor, are input, the vibration sensors being mounted on different positions of rails, includes a waveform similarity determination unit to compare impulse waveforms separated from the output waveforms or compare continuous waveforms separated from the output waveforms, and determine similarity therebetween, and detects a break of a rail.

A vibration analysis apparatus includes: a storage unit storing a regression equation indicating correspondence between rotation speed change of a rotation mechanism and a peak occurrence frequency of acceleration of vibration, for each acceleration peak; an analysis unit extracting a peak occurrence frequency of acceleration of vibration for each acceleration peak, based on vibration data of the rotation mechanism and calculating, for each acceleration peak, a waveform area of the acceleration peak by integrating the acceleration peak over a specific frequency section; and an anomaly determination unit determining whether operational anomaly occurs in the rotation mechanism for each acceleration peak. The analysis unit tracks, in accordance with the regression equation, change in peak occurrence frequency due to rotation speed change when vibration of the rotation mechanism is analyzed, and calculates, for each second acceleration peak, the waveform area of the second acceleration peak corresponding to the second vibration frequency tracked.