Systems, methods, and apparatus for corona detection using audio data are provided. In one example embodiment, the method includes obtaining, by one or more computing devices, audio data indicative of audio associated with an electrical system for at least one time interval. The method includes partitioning, by the one or more computing devices, the audio data for the time interval into a plurality of time windows. The method includes determining, by the one or more computing devices, a signal indicative of a presence of corona based at least in part on audio data collected within an identified time window of the plurality of time windows relative to audio data collected for a remainder of the time interval.

A sound pickup method includes splitting a sound pickup signal of a microphone of which sound pickup in a predetermined range is blocked by an acoustic obstacle, into a plurality of sound pickup signals and subjecting at least one sound pickup signal among the plurality of sound pickup signals to band limitation processing, and comparing characteristic amounts of the plurality of sound pickup signals including the sound pickup signal after being subjected to the band limitation processing and controlling a gain of the microphone in accordance with a result of comparing the characteristic amounts.

A headset includes a microphone that detects an acoustic signal, and converts the acoustic signal into a microphone signal, an audio processor that receives the microphone signal, and a twisted pair conductor element coupling the microphone and the audio processor. The twisted pair conductor element self-cancels a radio frequency (RF) field to prevent the RF field from entering the microphone.

A technique for reducing noise in a listening environment. The technique includes dividing the listening environment into a plurality of zones, where each zone is associated with a different active noise cancellation (ANC) system. A boundary between a first zone included in the plurality of zones and a second zone included in the plurality of zones comprises open space. The technique further includes assigning a plurality of acoustic sensors and a plurality of speakers to the ANC system associated with each zone included in the plurality of zones. The technique further includes, for each zone included in the plurality of zones, acquiring acoustic data via the plurality of acoustic sensors, processing the acoustic data, via a processor, to generate noise cancellation signals, and outputting the noise cancellation signals via the plurality of speakers.

The inventive EAL may generally enhance a driver's spatial awareness by providing the driver with intuitive/familiar audible warnings with directionality which can be enhanced with visual warnings as well as other technologies such as ANC and Zoned audio. Thus, the driver can understand the meaning of the warning and where it is coming from so he can react to it faster. In a specific embodiment, a motor vehicle includes a plurality of outside microphones mounted in association with an outer surface of the vehicle. A plurality of loudspeakers are disposed within the passenger compartment of the vehicle. A processing device identifies a sound of interest in microphone signals received from the outside microphones. It is determined from the microphone signals a direction in which the sound of interest is traveling. This may also be done with sensors, GPS, V2X, etc. In response to the identification of the sound of interest, playing at least one of the microphone signals on the loudspeakers is begun such that the sound of interest in the microphone signal and heard by the driver on the loudspeakers is perceived by a driver of the vehicle to be traveling in the determined direction.

A method for masking a vehicle noise includes setting a noise-generated driving region in which the vehicle noise is generated while a vehicle is running; measuring the vehicle noise in the noise-generated driving region; determining a masking sound which cancels the vehicle noise based on the measured vehicle noise; and outputting the determined masking sound into an interior of the vehicle.

A system includes a sound generator (20) that generates sound superimposed to sound to be manipulated. An error sensor (50) measures superimposed sound and outputs a corresponding feedback signal (e′(n)). A signal generator (91) generates a sound signal (y(n)). A controller (92) generates a control signal (λ(n)) representing a value of a sequence of rational numbers. A weighter (93) weights the generated sound signal (y(n)) with the control signal (λ(n)) and inverts it. An adder (94) adds the weighted/inverted sound signal to the feedback signal (e′(n)) and outputs a modified feedback signal (e(n)) to the signal generator (91). A weighter (95) weights the generated sound signal (y(n)) with the difference from one and with the control signal (λ(n)) and outputs the sound signal y′(n). The generated sound signal (y(n)) is a function of the modified feedback signal (e(n)).

Active noise control systems and methods are disclosed that include generating with a first sub-system, anti-noise that is configured to reduce or cancel noise occurring at a listening position. Generating with a second sub-system, anti-noise that is configured to reduce or cancel noise occurring at the listening position. The first active noise control sub-system has a higher robustness than the second active noise control sub-system.

A control system provides centralized active noise control (ANC) and active vibration control (AVC) through a digital network. The control system includes a controller, an audio sub-system, and a vibration sub-system. The audio-sub system includes at least one sound monitoring component and at least one sound outputting component. The vibration sub-system includes at least one vibration monitoring component and at least one vibration actuating component. The controller and the sub-systems are interconnected through the digital network. The controller controls the sub-systems through the digital network to perform the ANC and AVC functions in a holistic approach.

The noise suppression method of individual active noise reduction system comprises the steps that: (1) initial noise digital signals are received and converted to serve as input signals of a BP neural network; (2) the input signals are processed to generate secondary digital signals; (3) the secondary digital signals are output to a loudspeaker and secondary noise is generated; (4) remained noise digital signals obtained by overlapping the initial noise and the secondary noise are received; whether remained noise digital signals is continuously constant for the set times is judged; if yes, the secondary digital signals are kept outputting; (5) if not, BP neural network parameters are optimized and adjusted with the amplitude of the remained noise digital signals being minimum as the optimality principle; remained noise digital signals of previous step are served as new input signals and the step (2) is executed again.