A computer-implemented process determines, based on bearing fault frequencies, optimum values for the maximum frequency (F.sub.max) and the number of lines of resolution (N.sub.lines) to be used in collecting machine vibration data so as to adequately distinguish between spectral peaks for identifying faults in machine bearings. The process can be extended to any other types of fault frequencies that a machine may exhibit, such as motor fault frequencies, pump/fan fault frequencies, and gear mesh fault frequencies. Embodiments of the process also ensure that the time needed to acquire the waveform is optimized. This is particularly useful when collecting data using portable vibration monitoring devices.

A computer-implemented process determines, based on bearing fault frequencies, optimum values for the maximum frequency (F.sub.max) and the number of lines of resolution (N.sub.lines) to be used in collecting machine vibration data so as to adequately distinguish between spectral peaks for identifying faults in machine bearings. The process can be extended to any other types of fault frequencies that a machine may exhibit, such as motor fault frequencies, pump/fan fault frequencies, and gear mesh fault frequencies. Embodiments of the process also ensure that the time needed to acquire the waveform is optimized. This is particularly useful when collecting data using portable vibration monitoring devices.

A method of detecting corrosion in a conduit or container comprises measuring the thickness of a wall of the conduit or container with one or more pulse-echo ultrasound devices, wherein the method comprises the following steps: (i) receiving signals indicative of A-scan data from the one or more pulse-echo ultrasound devices, wherein the A-scan data comprises a plurality of A-scan spectra; (ii) determining which of the A-scan spectra have a distorted waveform such that a reliable wall thickness measurement cannot be determined; (iii) analysing the A-scan spectra identified in step (ii) as having a distorted waveform to determine one or more A-scan spectral characteristics of each spectrum that are causing the distortion; (iv) resolving the waveform characteristics based on the determined spectral characteristics causing the waveform distortion so as to produce modified A-scan spectra; (v) determining thickness measurements of the wall based on the modified A-scan spectra; and (vi) determining the extent to which the wall has been corroded based on the thickness measurements determined in step (v) and additional thickness determined from A-scan spectra.

A method of detecting corrosion in a conduit or container comprises measuring the thickness of a wall of the conduit or container with one or more pulse-echo ultrasound devices, wherein the method comprises the following steps: (i) receiving signals indicative of A-scan data from the one or more pulse-echo ultrasound devices, wherein the A-scan data comprises a plurality of A-scan spectra; (ii) determining which of the A-scan spectra have a distorted waveform such that a reliable wall thickness measurement cannot be determined; (iii) analysing the A-scan spectra identified in step (ii) as having a distorted waveform to determine one or more A-scan spectral characteristics of each spectrum that are causing the distortion; (iv) resolving the waveform characteristics based on the determined spectral characteristics causing the waveform distortion so as to produce modified A-scan spectra; (v) determining thickness measurements of the wall based on the modified A-scan spectra; and (vi) determining the extent to which the wall has been corroded based on the thickness measurements determined in step (v) and additional thickness determined from A-scan spectra.

Embodiments herein generally relate to systems and methods to determine the composition, properties, and morphology of a liquid in a liquid handling structure. Aspects disclosed include exploiting spatiotemporal constraints of zero-group-velocity modes for non-contact, non-invasive, liquid sensing applications.

The present invention discloses a boom monitoring method and engineering machinery comprising a boom monitoring system. The method comprises obtaining a boom damage signal monitored in boom operation by a piezoelectric sensing network formed by a plurality of piezoelectric sensors arranged at different points on a boom, and determining a damage position of the boom and a corresponding first boom damage value such that when the first boom damage value reaches a preset starting value of an optical fiber sensing network formed by a plurality of optical fiber sensors arranged at the different monitoring points on the boom, optical wave values of the corresponding monitoring points are obtained and a boom crack signal is determined. A second boom damage value is calculated according to the boom crack signal, which comprises a crack change factor and a crack length. According to the present invention, the boom is monitored with improved efficiency.

An asphalt density estimation system includes a measurement device configured to output a measurement signal; a time synchronization unit configured to sample the measurement signal to obtain a sampled measurement signal and identify periodic sampling points of the sampled measurement signal across a plurality of periods. The system also includes a time synchronous averaging unit configured to construct a modified measurement signal in the time domain by: for at least one sampling point within the period, averaging a plurality of the periodic sampling points across periods to obtain an average periodic data point for the at least one sampling point, and constructing the modified measurement signal using the average periodic data point for the at least one sampling point. The system further includes a density calculation unit configured to determine asphalt density values based on the modified measurement signal; and a display unit configured to display the determined asphalt density values.

This disclosure generally relates to the field of structural health monitoring, and, more particularly, to a method and system for evaluating residual life of components made of composite materials. Existing methods require performing computational methods such as Finite Element Analysis (FEA) on the results of Non-Destructive Testing (NDT) every time a component is inspected. This makes the process expensive and time-consuming. Thus, embodiments of present disclosure provide a method wherein NDT is performed using different sensing methods such as ultrasound, ultrasound pulse echo, thermography to determine type of defect, location of defect and depth of defect in a test component which are then fed into a pre-trained machine learning model to predict residual life of the component. Testing time is greatly reduced since the pre-trained machine learning model is trained offline using results of the computational methods.

The disclosure relates to methods and apparatus for identifying rheological properties of liquids from acoustic signals generated by liquid flow through a pipe. Example embodiments include a method of identifying a rheological property of a liquid flowing in a pipe (101), the method comprising: detecting an acoustic signal generated by the liquid flowing in the pipe using a sensor (105) attached to a rod (104) extending from a wall of the pipe (101) into the liquid; sampling the acoustic signal to provide a sampled acoustic signal; transforming the sampled acoustic signal to generate a sampled frequency spectrum; correlating the sampled frequency spectrum with a stored frequency spectrum from a database of stored frequency spectra of liquids having predetermined rheological properties; and identifying a rheological property of the liquid based on the stored frequency spectrum.

This present disclosure describes an ultrasound image display method and apparatus, a storage medium, and an electronic device. The method includes acquiring, by a device, an input signal by performing detection on a to-be-detected object, the input signal comprising a three-dimensional (3D) radio-frequency (RF) signal. The device includes a memory storing instructions and a processor in communication with the memory. The method also includes performing, by the device, a modulus calculation on the 3D RF signal to obtain envelope information in a 3D ultrasound image, the modulus calculation being at least used for directly acquiring a 3D amplitude of the 3D RF signal; and displaying, by the device, the envelope information in the 3D ultrasound image, the envelope information being at least used for indicating the to-be-detected object.