A device configured to monitor a vibrating object, the device comprising a common housing holding an accelerometer for sampling vibration signatures of the vibrating object, resulting in vibration samples, and a computing device comprising a data processor and a memory having stored thereon a computer program product for monitoring the vibrating object, the computer program product comprising an input module to receive the vibration samples, an analysis module to analyze the vibration samples to derive asset health scores, a machine learning model to determine asset operating ranges, and an output module to output messages, wherein the computer program product when running on the data processor causes the computing device to receive during a time interval, having an end time t1, the vibration samples from the accelerometer, resulting in a time series vector array, and to analyze the vibration samples comprising deriving from the time series vector array a baseline asset health score and deriving from the time series vector array a time series asset health score, and to subject at least a part of the time series asset health score to the machine learning model for determining at least one asset operating range, and to receive a further vibration sample at a monitor time t2 wherein the monitor time t2 is subsequent to the end time t1, and to derive from the further vibration sample an asset health score, and to determine if the asset health score falls within an operating range determined by the machine learning model, resulting in a monitor result, and to output a message depending on the monitor result, and wherein the device consumes less current than 20 mA.

A wireless and cellular vibration monitoring device (2) comprising a connection structure (6) suitable for attaching the monitoring device (2) to equipment to be monitored is disclosed. The monitoring device (2) comprises a temperature sensor (8) and a vibration sensor (10) configured to remotely monitor vibration and temperature transferred to the monitoring device (2) via the connection structure (6). The device comprises an integrated satellite-based radio-navigation system for location detection. The monitoring device (2) comprises a metal base (4) comprising a body portion (56) comprising a threaded portion (6) constituting the connection structure (6). The threaded portion (6) comprises male threads and protrudes from the body portion (56) of the base (4). The temperature sensor (8) is thermally connected to the body portion (56) of the base (4).

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 analyzes periodic information in digital vibration data associated with a machine. The method involves generating a spectral periodic information plot (PIP) based on the digital vibration data, and locating amplitude peaks in the PIP at frequencies associated with fundamental frequencies of interest. Peaks occurring at fundamental fault frequencies and at related harmonic frequencies are removed from the PIP, while retaining energy values associated with the removed peaks. Remaining peaks in the PIP are classified as synchronous periodic peaks and non-synchronous periodic peaks. The remaining peaks in the PIP are graphically plotted along with the fault frequencies and related harmonic frequencies in different colors or different line styles on a display device to identify different groups of frequencies of interest. The method implements an algorithm that locates peaks in the PIP at frequencies associated with the fundamental frequencies of interest even though frequencies of the located peaks do not precisely match the fundamental frequencies of interest.

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 device for detecting the approach of a vortex ring state for a rotary wing aerodyne, the detection device including a set of vibration sensors configured to be distributed in or on the aerodyne, and a data processing unit configured to receive in real time measurement data from the sensors, process the data in order to calculate in real time the vibration spectrum of the aerodyne, detect in real time, by vibration analysis, the approach of a vortex ring state as a function of the calculated vibration spectrum, and issue an alarm in the event of detection of the approach of a vortex ring state.

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 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.

A method for detecting defects in a rotational element of a machine based on changes in measured vibration energy includes: (a) collecting vibration data over an extended period of time using vibration sensors attached to the machine; (b) processing the vibration data to generate a time waveform comprising processed vibration values sampled during sequential sampling time intervals within the extended period of time; (c) detecting multiple time blocks within the extended period of time during which the processed vibration values exhibit sustained increases at progressively increasing rates; and (d) generating alerts based on detection of the multiple time blocks during which the processed vibration values exhibit sustained increases at progressively increasing rates. The multiple time blocks may include a first time block during which the processed vibration values increase at a first rate, and a second time block occurring after the first time block during which the processed vibration values increase at a second rate that is greater than the first rate.