In a measuring arrangement for determining properties of a material to be extruded while an extrusion process is being carried out in an extruder, at least one extruder screw is rotatably mounted in a tubular guide in a barrel and is connected to a rotary drive. Material to be extruded is fed to the tubular guide at one end and is removed as finish-extruded material at an oppositely arranged discharge. Arranged at measuring positions at predeterminable defined intervals on the wall of the tubular guide along the longitudinal axis of the extruder screw are multiple first sound transducers, which are designed for the detection of sound waves that are generated during the extrusion process by the extrusion process as process noises and/or are emitted by a second sound transducer, arranged at one end of the tubular guide, in the direction of the longitudinal axis of the extruder screw and into the material to be extruded that is conveyed through a mixing chamber present in the tubular guide.

In a measuring arrangement for determining properties of a material to be extruded while an extrusion process is being carried out in an extruder, at least one extruder screw is rotatably mounted in a tubular guide in a barrel and is connected to a rotary drive. Material to be extruded is fed to the tubular guide at one end and is removed as finish-extruded material at an oppositely arranged discharge. Arranged at measuring positions at predeterminable defined intervals on the wall of the tubular guide along the longitudinal axis of the extruder screw are multiple first sound transducers, which are designed for the detection of sound waves that are generated during the extrusion process by the extrusion process as process noises and/or are emitted by a second sound transducer, arranged at one end of the tubular guide, in the direction of the longitudinal axis of the extruder screw and into the material to be extruded that is conveyed through a mixing chamber present in the tubular guide.

A “periodic signal parameter” (PSP) indicates periodic patterns in an autocorrelated vibration waveform and potential faults in a monitored machine. The PSP is calculated based on statistical measures derived from an autocorrelation waveform and characteristics of an associated vibration waveform. The PSP provides an indication of periodicity and a generalization of potential fault, whereas characteristics of the associated waveform indicate severity. A “periodic information plot” (PIP) is derived from a vibration signal processed using two analysis techniques to produce two X-Y graphs of the signal data that share a common X-axis. The PIP is created by correlating the Y-values on the two graphs based on the corresponding X-value. The amplitudes of Y-values in the PIP is derived from the two source graphs by multiplication, taking a ratio, averaging, or keeping the maximum value.

A “periodic signal parameter” (PSP) indicates periodic patterns in an autocorrelated vibration waveform and potential faults in a monitored machine. The PSP is calculated based on statistical measures derived from an autocorrelation waveform and characteristics of an associated vibration waveform. The PSP provides an indication of periodicity and a generalization of potential fault, whereas characteristics of the associated waveform indicate severity. A “periodic information plot” (PIP) is derived from a vibration signal processed using two analysis techniques to produce two X-Y graphs of the signal data that share a common X-axis. The PIP is created by correlating the Y-values on the two graphs based on the corresponding X-value. The amplitudes of Y-values in the PIP is derived from the two source graphs by multiplication, taking a ratio, averaging, or keeping the maximum value.

Methods and devices are provided for analyzing a tubular structure including at least two electromagnetic-acoustic transducers (EMAT) and, called sensors, attachable or attached in, on or in the vicinity of the tubular structure; and computation and/or memory resources, that are accessed locally and/or remotely and that are configured to determine, for the pair of sensors, a function representing the impulse response of the tubular structure on the basis of the diffuse acousto-elastic noise present in the structure. Developments describe the use of rings supporting the sensors; translation and/or rotation movements; permanent or temporary installations; hinged rings; various computation modes, e.g., intercorrelation, a passive inverse filter, or correlation of the coda of the correlation; the use of artificial noise sources, imaging (e.g., tomography) for determining the existence of one or more defects in the structure. Software aspects are described.

Methods and devices are provided for analyzing a tubular structure including at least two electromagnetic-acoustic transducers (EMAT) and, called sensors, attachable or attached in, on or in the vicinity of the tubular structure; and computation and/or memory resources, that are accessed locally and/or remotely and that are configured to determine, for the pair of sensors, a function representing the impulse response of the tubular structure on the basis of the diffuse acousto-elastic noise present in the structure. Developments describe the use of rings supporting the sensors; translation and/or rotation movements; permanent or temporary installations; hinged rings; various computation modes, e.g., intercorrelation, a passive inverse filter, or correlation of the coda of the correlation; the use of artificial noise sources, imaging (e.g., tomography) for determining the existence of one or more defects in the structure. Software aspects are described.

The present disclosure provides methods and systems for the characterization of a potential microtexture region (MTR) of a sample, component, or the like. The methods may include determining a threshold width of spatial correlation coefficient and/or a threshold spatial correlation coefficient slope for an actual MTR, characterizing a potential MTR as an actual MTR or a defect, characterizing an actual MTR as an acceptable MTR or not, and/or characterizing various components with potential MTRs as defective or not. The characterization may include calculating a width of spatial correlation coefficient and/or a spatial correlation coefficient slope of the potential MTR and comparing the width of spatial correlation coefficient to a threshold width of spatial correlation coefficient and/or comparing the spatial correlation coefficient slope to a threshold spatial correlation coefficient slope for the potential MTR to be characterized as an actual MTR or a defect (crack).

The present disclosure provides methods and systems for the characterization of a potential microtexture region (MTR) of a sample, component, or the like. The methods may include determining a threshold width of spatial correlation coefficient and/or a threshold spatial correlation coefficient slope for an actual MTR, characterizing a potential MTR as an actual MTR or a defect, characterizing an actual MTR as an acceptable MTR or not, and/or characterizing various components with potential MTRs as defective or not. The characterization may include calculating a width of spatial correlation coefficient and/or a spatial correlation coefficient slope of the potential MTR and comparing the width of spatial correlation coefficient to a threshold width of spatial correlation coefficient and/or comparing the spatial correlation coefficient slope to a threshold spatial correlation coefficient slope for the potential MTR to be characterized as an actual MTR or a defect (crack).

Methods, systems, and computer-readable storage media for providing high-resolution assessment of the condition of pipes of a fluid distribution down to the individual pipe stick. An acoustic sensor is placed in acoustical communication with a pipe at one end of a target segment. An acoustical wave is generated in the pipe at a first out-of-bracket excitation location while signal data is recorded from the acoustic sensor. Timing information regarding the arrival at the acoustic sensor of reflections of the acoustic wave from pipe joints in the target segment is extracted from the recorded signal data, and a time delay between reflections from consecutive pipe joints is computed. An acoustic propagation velocity in a pipe stick between the consecutive pipe joints is then computed based on the time delay and a length of the pipe stick. A condition of the pipe stick is determined based on the computed acoustic propagation velocity.

This application relates to an apparatus and method for detecting a microcrack using orthogonality analysis of a mode shape vector and a principal plane in a resonance point. The apparatus may include a measurement unit comprising multiple sensors and configured to measure whether a crack exists at a measurement target, and an analysis unit configured to determine whether a crack exists, on the basis of measurement values of the respective sensors. The measurement unit includes a fixing jig configured to fix the measurement target, an excitation means configured to apply a predetermined impact to the measurement target, and multiple acceleration sensors attached at predetermined locations on the measurement target. The analysis unit may further calculate frequency responses of the measurement target to the impact applied by the excitation means, and determine whether a crack exists by analyzing the number of resonance points and independence of the resonance points.