A pump monitoring system for use in wellbore operations can determine whether an indication of a failure is due to an actual pump issue or a failed sensor. The pump monitoring system includes a sensor on a fluid end of a pump to measure properties associated with the pump and a vibration detector. A computing device executes instructions to receive the sensor signal and the vibration signal and identify an irregularity in the sensor signal. The processor then determines whether an operational signal component is present in the vibration signal, and displays an indication that the sensor has failed when the operational signal component is not present in the vibration signal. If the operational signal component is present in the vibration signal, the irregularity is likely caused by a pump problem such as a failed valve.

A pump monitoring system for use in wellbore operations can determine whether an indication of a failure is due to an actual pump issue or a failed sensor. The pump monitoring system includes a sensor on a fluid end of a pump to measure properties associated with the pump and a vibration detector. A computing device executes instructions to receive the sensor signal and the vibration signal and identify an irregularity in the sensor signal. The processor then determines whether an operational signal component is present in the vibration signal, and displays an indication that the sensor has failed when the operational signal component is not present in the vibration signal. If the operational signal component is present in the vibration signal, the irregularity is likely caused by a pump problem such as a failed valve.

A statistical method is used to separate periodic from non-periodic vibration peaks in machine vibration spectra. Generally, a machine vibration spectrum is not normally distributed because the amplitudes of periodic peaks are significantly large and random relative to the generally Gaussian noise. In a normally distributed signal, the statistical parameter Kurtosis has a value of 3. The method sequentially removes each largest amplitude peak from the peaks in a frequency region of interest in the spectrum until the Kurtosis has a value of three or less. The removed peaks, which are all considered to be periodic, are placed into a candidate peak list. As the process of building the candidate peak list proceeds, if the kurtosis of the remaining peaks in the frequency region of interest falls to three or less, the process stops and the candidate peak list is defined.

Drones are engineered with sensors for use in insurance applications. After locating an object of interest, a drone performs an investigation by probing the object of interest. Sensors receive feedback from the object of interest. An electronic fingerprint of the drone is produced. Afterward, perils are computed based on the feedback and the fingerprint of the drone is used in insuring the object of interest. The act of probing includes thumping, drumming, or radiating ultrasound waves against the object of interest. The sensors can be turned off when they are within a geographic zone of prohibited operations.

An electronic device and a method are disclosed. The electronic device includes a sensor, a memory, a processor, and a communication interface. The sensor is configured to detected vibrations of a burner system including any component of a burner system. The memory is configured to store the detected vibrations. The processor is configured to record the detected vibrations caused by the burner system at a predetermined time interval. The processor is also configured to generate a report of the recorded vibrations caused by a burner component to indicate the operational status of the burner, wherein the generated report includes at least two recorded vibrations. The communication interface configured to transmit the generated report.

In some embodiments, a LIDAR system may include at least one processor configured to control at least one light source for projecting light toward a field of view and receive from at least one first sensor first signals associated with light projected by the at least one light source and reflected from an object in the field of view, wherein the light impinging on the at least one first sensor is in a form of a light spot having an outer boundary. The processor may further be configured to receive from at least one second sensor second signals associated with light noise, wherein the at least one second sensor is located outside the outer boundary; determine, based on the second signals received from the at least one second sensor, an indicator of a magnitude of the light noise; and determine, based on the indicator the first signals received from the at least one first sensor and, a distance to the object.

In some embodiments, a LIDAR system may include at least one processor configured to control at least one light source for projecting light toward a field of view and receive from at least one first sensor first signals associated with light projected by the at least one light source and reflected from an object in the field of view, wherein the light impinging on the at least one first sensor is in a form of a light spot having an outer boundary. The processor may further be configured to receive from at least one second sensor second signals associated with light noise, wherein the at least one second sensor is located outside the outer boundary; determine, based on the second signals received from the at least one second sensor, an indicator of a magnitude of the light noise; and determine, based on the indicator the first signals received from the at least one first sensor and, a distance to the object.

A method of identifying a fault in a synchronous reluctance electric machine, the method including carrying out a first vibration measurement on a stator in a first radial direction of the stator; carrying out a second vibration measurement on the stator in a second radial direction of the stator; determining, on the basis of at least one of the first vibration measurement and the second vibration measurement, a first vibration frequency; determining, on the basis of the first vibration measurement and the second vibration measurement, a mode shape of the vibration at the first vibration frequency; and determining, on the basis that the first vibration frequency f.sub.b and the mode shape m fulfil the following barrier fault conditions:

f.sub.b=f.sub.r, and m=1

where f.sub.r is a rotation frequency of a rotor, that a flux barrier of the rotor is defect.

A monitoring device for condition assessment of a packaging machine for producing packages of liquid food comprises a signal interface for connection to a plurality of vibration sensors in the packaging machine. The monitoring device includes logic to: receive measurement signals from the vibration sensors and obtain an event timing signal, IVIES, indicative of predefined work events of the packaging machine, wherein the respective work event corresponds to a mechanical action by a respective component in the packaging machine when operating to produce the packages. The monitoring device further includes logic to: identify, by use of the IVIES and in the measurement signals, signal values associated with the respective component, and evaluate the signal values for condition assessment of the respective component. The provision and use of the MES thus facilitates condition assessment of individual components in a packaging machine.

A monitoring device for condition assessment of a packaging machine for producing packages of liquid food comprises a signal interface for connection to a plurality of vibration sensors in the packaging machine. The monitoring device includes logic to: receive measurement signals from the vibration sensors and obtain an event timing signal, IVIES, indicative of predefined work events of the packaging machine, wherein the respective work event corresponds to a mechanical action by a respective component in the packaging machine when operating to produce the packages. The monitoring device further includes logic to: identify, by use of the IVIES and in the measurement signals, signal values associated with the respective component, and evaluate the signal values for condition assessment of the respective component. The provision and use of the MES thus facilitates condition assessment of individual components in a packaging machine.