An apparatus for detecting a transient event in an operating machine, the apparatus comprising: a controller configured to control performance of the following steps: a measurement step comprising measuring a periodic signal from a machine; a processing step comprising synchronously processing the periodic signal to track the primary frequency; a filtering step comprising removing the primary periodic component and its harmonics from the periodic signal to yield a filtered dataset; an integration step comprising integrating the filtered dataset over the remaining frequencies to yield an integrated dataset representing the periodic energy at frequencies other than the primary frequency and its harmonics; an analysis step comprising identifying a short-term transient in the integrated dataset to identify a transient disruption in the operation of the machine.

Provided is a refrigerator. The refrigerator is characterized by enabling at least a part of a refrigerator door to be selectively transparent by a user's operation, such that the user sees through an inside of the refrigerator while the refrigerator door is closed.

A method for gathering flight load data for a gas turbine engine includes providing a plurality of blocker doors rotatably mounted to a translating sleeve and a plurality of blocker door islands, each blocker door island disposed between circumferentially adjacent blocker doors of the plurality of blocker doors and mounted to at least one mounting point of the translating sleeve, wherein a blocker door island of the plurality of blocker door islands is a data acquisition unit; and connecting the data acquisition unit to at least one sensor in communication with the translating sleeve.

According to one embodiment, a vibration detecting device includes a housing, a vibration sensor, a circuit board, a flexible wiring member, and an elastic member. The vibration sensor is accommodated in the housing. The circuit board is accommodated in the housing, and is provided with a first electric component configured to process a detection signal of the vibration sensor. The wiring member electrically connects the vibration sensor and the circuit board to each other. The elastic member contains a polymer material, and is accommodated in the housing as being in contact with the housing and the circuit board, and being detachable from the housing. The circuit board is held by the housing through the elastic member.

The present disclosure relates to a technical virtual sensing idea of indirectly measuring structural vibration information on an unmeasured point while minimizing the number of sensors attached for actual measurement, and more particularly, to a technique of estimating measurement data of an unmeasured point using a finite element model, synchronized and updated based on experimental data of an actual measurement subject structure, and a virtual sensing algorithm.

A system, method, and non-transitory computer readable medium for diagnosing stator inter-turn faults in a Line Start Permanent Magnet Synchronous Motor (LSPMSM) are described. The method of diagnosing stator inter-turn faults in the LSPMSM includes collecting acoustic signals that are generated from a LSPMSM by a communication device, analyzing via singular spectrum analysis (SSA) the collected acoustic signals for fault detection of the stator inter-turn faults, and determining a fault diagnosis for the fault detection by executing a Fast Fourier Transform (FFT).

A device for measuring a parameter indicative of a rotational speed of a component includes a wired or wireless input configured to receive a vibration signal from a vibration sensor, a boost filter configured to filter the vibration signal, based on a predetermined frequency range, into a sinusoidal signal and, a comparator configured to generate a pulse waveform signal from the sinusoidal signal in order to read the value of the parameter. Also a motor or pump controller including the device.

Apparatus and associated methods relate to a vibrational sensing system (VSS) including an accelerometer and a data processor, which determines an “operational state” of a mechanical drive unit, the processor further employing the “operational state” to gate learning of long-term vibrational data to exclude collection of non-operational data, the long-term data collected to calculate alarm thresholds. For example, vibrations from a target motor are sensed by a coupled accelerometer. Vibrational data from the accelerometer is fed into a data processor which determines the operational state of the motor. The operational state (e.g., on/off indication) may gate data collection such that data is only acquired during on-time, which may advantageously create accurate baselines from which alarm thresholds may be generated, and nuisance alarms may be avoided.

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).