A measuring rod (1) with a longitudinal axis (A) for insertion in the flow cross section of a tube and for the verification of a flowing medium in this tube having at least one first sender unit (2) for the transmission of a first acoustic or electromagnetic measuring signal (3) and at least one first receiver unit (4) for receiving the first measuring signal, wherein the first sender unit (2) and the first receiver unit (4) define a measuring section, wherein the first sender unit (2) is arranged in such a manner that the first measuring signal (3) crosses the measuring section and wherein the first receiver unit (4) is arranged in such a manner that it, at least during operation without flow, receives the first measuring signal (3) after crossing the measuring section.

A measuring rod (1) with a longitudinal axis (A) for insertion in the flow cross section of a tube and for the verification of a flowing medium in this tube having at least one first sender unit (2) for the transmission of a first acoustic or electromagnetic measuring signal (3) and at least one first receiver unit (4) for receiving the first measuring signal, wherein the first sender unit (2) and the first receiver unit (4) define a measuring section, wherein the first sender unit (2) is arranged in such a manner that the first measuring signal (3) crosses the measuring section and wherein the first receiver unit (4) is arranged in such a manner that it, at least during operation without flow, receives the first measuring signal (3) after crossing the measuring section.

A sensor device is coupled to a mechanical machine. The sensor device detects vibrations of the mechanical machine and transmits the vibration data to a remote processing device. The vibration data may be compressed prior to transmission. The remote processing device receives the data and generates a reconstructed version of the vibration data. The remote processing device includes a machine learning model trained to examine vibration data and to identify a motion pattern associated with an error condition. The machine learning model is applied to the reconstructed vibration data and detects an occurrence of an error condition in the mechanical machine. An alert indicating that an error condition has been detected is transmitted to a human operator. The human operator verifies the status of the mechanical machine and confirms that an error condition has occurred. In response to receipt of the confirmation, the machine learning model is further trained on training data updated to include the vibration data generated by the mechanical machine.

A sensor device is coupled to a mechanical machine. The sensor device detects vibrations of the mechanical machine and transmits the vibration data to a remote processing device. The vibration data may be compressed prior to transmission. The remote processing device receives the data and generates a reconstructed version of the vibration data. The remote processing device includes a machine learning model trained to examine vibration data and to identify a motion pattern associated with an error condition. The machine learning model is applied to the reconstructed vibration data and detects an occurrence of an error condition in the mechanical machine. An alert indicating that an error condition has been detected is transmitted to a human operator. The human operator verifies the status of the mechanical machine and confirms that an error condition has occurred. In response to receipt of the confirmation, the machine learning model is further trained on training data updated to include the vibration data generated by the mechanical machine.

Apparatus is provided having an acoustic-based air probe with an acoustic source configured to provide an acoustic signal into a mixture of concrete; and an acoustic receiver configured to be substantially co-planar with the acoustic source, to respond to the acoustic signal, and to provide signaling containing information about the acoustic signal injected into the mixture of concrete.

Apparatus is provided having an acoustic-based air probe with an acoustic source configured to provide an acoustic signal into a mixture of concrete; and an acoustic receiver configured to be substantially co-planar with the acoustic source, to respond to the acoustic signal, and to provide signaling containing information about the acoustic signal injected into the mixture of concrete.

Combinations of multiple analytic techniques may be used to identify changes to a structure based on changes in characteristics of acoustic signals traveling along the structure. Acoustic signals traveling along the structure may be monitored to detect changes in characteristics of the acoustic signal from baseline signal characteristics. The changes in characteristics of the acoustic signals may be processed using multiple analytic techniques to provide analyses of the change in time-domain, in frequency-domain, and in mixed time-frequency-domain. The change to the structure may be identified based on a combination of the results of the analysis in time-domain, in frequency-domain, and in mixed time-frequency-domain.

Combinations of multiple analytic techniques may be used to identify changes to a structure based on changes in characteristics of acoustic signals traveling along the structure. Acoustic signals traveling along the structure may be monitored to detect changes in characteristics of the acoustic signal from baseline signal characteristics. The changes in characteristics of the acoustic signals may be processed using multiple analytic techniques to provide analyses of the change in time-domain, in frequency-domain, and in mixed time-frequency-domain. The change to the structure may be identified based on a combination of the results of the analysis in time-domain, in frequency-domain, and in mixed time-frequency-domain.

Provided herein are systems and methods for real time processing of signals from an array of transducers for detecting transient elastic waves originating from unknown locations in a body, which may propagate in a dispersive fashion. The systems and methods allow real time combination and analysis of signals, including decisions regarding storage as new data is received. The methods described herein include designing arrays of detectors and methods for processing signals in real time given the constraints of the body under test determining whether to store the set of information while a new set of information is received for processing within a real time environment. The methods described herein include methods which result in the determination or small time shifts which place all signals into a coherent time base which are then combined achieving a composite waveform that possesses an increased signal-to-noise ratio over any single element.

Provided herein are systems and methods for real time processing of signals from an array of transducers for detecting transient elastic waves originating from unknown locations in a body, which may propagate in a dispersive fashion. The systems and methods allow real time combination and analysis of signals, including decisions regarding storage as new data is received. The methods described herein include designing arrays of detectors and methods for processing signals in real time given the constraints of the body under test determining whether to store the set of information while a new set of information is received for processing within a real time environment. The methods described herein include methods which result in the determination or small time shifts which place all signals into a coherent time base which are then combined achieving a composite waveform that possesses an increased signal-to-noise ratio over any single element.