Disclosed herein is a submersible having one or more sensors configured to collect a signal from an interior area of a liquid carrying channel, and a processor configured to obtain the signal from the one or more sensors, calculate a diameter and a circumference of the liquid carrying channel according to the signal. determine whether an irregularity is present on an inner surface of the liquid carrying channel according to the diameter and the circumference, and generate a notification to notify an irregularity has been detected on the inner surface.

Acoustic optical integrity detection system architectures and methods can be used to detect optical integrity of an optical component by detecting a discontinuity on and/or in the optical component (e.g., on the optical surface and/or within the bulk of the optical component). In some examples, integrity detection can be used to ensure safety compliance of an optical system, optionally including a laser. Acoustic integrity detection can utilize transducers (e.g., piezoelectric transducers) to transmit ultrasonic waves along an optical surface and/or through the thickness of an optical component. A discontinuity of the optical surface can interact with the transmitted wave causing attenuation, redirection and/or reflection of at least a portion of the transmitted wave. Portions of the transmitted wave energy after interaction with the discontinuity can be measured to determine discontinuity location, type, and/or severity.

Detecting and classifying damage to a vehicle. One example system includes a microphone positioned to detect sound waves inside the vehicle, one or more sensors positioned on the vehicle and configured to sense a characteristic of a windshield of the vehicle, and an electronic processor communicatively coupled to the one or more sensors and the microphone. The electronic processor is configured to receive sensor information from the one or more sensors and to receive an electrical signal from the microphone. The electronic processor is configured to determine, based on the sensor information, whether a crack event has occurred. The electronic processor is configured to, in response to determining that a crack event has occurred, determine a cause of the crack event based on the electrical signal received from the microphone. The electronic processor is configured to execute a mitigation action based on the cause of the crack event.

A method of battery state monitoring includes: (1) providing a battery cell and at least one ultrasonic actuator and at least one ultrasonic sensor mounted to the battery cell; (2) using the ultrasonic actuator, generating a guided wave that propagates in-plane of the battery cell; (3) using the ultrasonic sensor, receiving an arriving wave corresponding to the guided wave; and (4) determining a state of the battery cell based on the arriving wave.

A method for measuring health of a motor includes: (a) measuring, by an electrocardiogram sensor, vibration of the motor to obtain at least two electrical signals with each of the at least two electrical signals representing a harmonic of the vibration of the motor; (b) comparing each of the at least two electrical signals with a corresponding baseline; (c) based on the comparison, determining whether any one of the at least two electrical signals includes one or more artifacts wherein an artifact in a respective one of the at least two electrical signals is a deviation from a respective one of the corresponding baseline; and (d) based on any one of the at least two electrical signals including the one or more artifacts, providing an estimated time to failure for the motor.

A machine learning device which learns fault prediction of one of a main shaft of a machine tool and a motor driving the main shaft, including a state observation unit observing a state variable including at least one of data output from a motor controller controlling the motor, data output from a detector detecting a state of the motor, and data output from a measuring device measuring a state of the one of the main shaft and the motor; a determination data obtaining unit obtaining determination data upon determining one of whether a fault has occurred in the one of the main shaft and the motor and a degree of fault; and a learning unit learning the fault prediction of the one of the main shaft and the motor in accordance with a data set generated based on a combination of the state variable and the determination data.

A method is disclosed. In one example, the method includes bonding a first panel of a first material to a base panel in a first gas atmosphere, wherein multiple hermetically sealed first cavities encapsulating gas of the first gas atmosphere are formed between the first panel and the base panel. The method further includes bonding a second panel of a second material to at least one of the base panel and the first panel, wherein multiple second cavities are formed between the second panel and the at least one of the base panel and the first panel.

A damage evaluation device includes: a phased array probe that irradiates an ultrasonic signal from a surface of an inspection metal toward an inside of the inspection metal and detects a reflection signal reflected in a predetermined region inside the inspection metal; and an arithmetic processor. The arithmetic processor sets planes parallel to each other in an inspection region, calculates pixel data by quantifying the reflection signal from segments set in each of the planes; calculates a scattering degree of the pixel data, and evaluates damage of the inspection metal based on the scattering degree.

A device is configured to operate a Heating, Ventilation, and Air Conditioning (HVAC) system. The device is further configured to determine that the speed of a combustion air inducer has exceeded a speed threshold value. The device is further configured to receive an audio signal from a microphone while operating the HVAC system, to identify an audio signature for the combustion air inducer from an audio signature library, and to determine the audio signature for the combustion air inducer is present within the audio signal. The device is further configured to determine a fault type based on the determination that the audio signature for the combustion air inducer is present within the audio signal, to identify a component identifier for a component of the HVAC system that is associated with fault type, and to output a recommendation identifying the component identifier.

Provided are a waveform analysis method and a waveform analysis device capable of preventing, in advance, a breakage accident during operation and preventing stoppage due to breakdown of machinery and performing efficient maintenance work by specifying a degraded part from among the parts that constitute the machinery. A waveform analysis device 30 is provided with; a signal analysis unit 31 for performing fast Fourier transform for a signal transmitted from a sensor 28 that detects a physical phenomenon in the machinery an impulse extraction unit 32 for extracting an impulse component from spectrum data generated by the signal analysis unit 31; a display unit 35 for displaying waveform data including the impulse component extracted by the impulse extraction unit 32; and a data editing unit 33 for editing, from data of a waveform including the impulse component displayed by the display unit 35, waveform data in a range selected via an input unit 36 by a worker, generating a graph displaying a frequency, a time, and the intensity of the impulse component, and displaying the graph on the display unit 35.