Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Active noise control method and system based on fuzzy neural network and armored vehicle driver helmet

A technology of active noise control and fuzzy neural network, applied in the fields of active noise control, noise control, armored vehicle driver helmet, can solve the problems of application limitation, poor control effect of medium and low frequency noise, etc., to reduce the amount of calculation and speed up noise reduction , the effect of improving the convergence speed and learning accuracy

Inactive Publication Date: 2017-10-10
邢优胜
View PDF0 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In conventional armored vehicles, passive noise control in the cabin is carried out by arranging damping and sound-absorbing materials in the cab and passenger compartment, enhancing the sound-absorbing and sound-insulating performance of the floor inside the car, adding engine sound-proof covers, and other physical noise-reduction measures. The measures have better isolation effect on high-frequency noise, but poor control effect on medium and low-frequency noise
[0004] The active noise reduction scheme can effectively reduce the low-frequency noise, while the traditional active noise control scheme can only control the noise below 200Hz, and can only control the noise for a narrow band, so its application is greatly limited

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Active noise control method and system based on fuzzy neural network and armored vehicle driver helmet
  • Active noise control method and system based on fuzzy neural network and armored vehicle driver helmet
  • Active noise control method and system based on fuzzy neural network and armored vehicle driver helmet

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] This embodiment provides an active noise control method based on a fuzzy neural network. see figure 1 Shown is the specific embodiment of the active noise control method based on the fuzzy neural network in this application, and the steps in this embodiment include:

[0031] Step 101: collect the reference noise signal of the reference area by the reference microphone, use it as a reference signal, and output it to the fuzzy controller;

[0032] Step 102: the error microphone collects the residual noise signal in the noise control area as an error signal, and outputs it to the fuzzy controller;

[0033] Step 103: The fuzzy controller analyzes the reference signal and the error signal based on the adaptive filtering RBF (Filter-x RadialBasis Function, hereinafter referred to as FX-RBF) of the fuzzy neural network, and outputs an inverted target sound signal to the speaker.

[0034] Wherein, the fuzzy controllers are two independent fuzzy controllers, which respectivel...

Embodiment 2

[0049] In order to make the description of the present invention clearer and more detailed, and to facilitate the understanding of technical personnel, this embodiment provides an active noise control system based on a fuzzy neural network, see figure 2 Shown is a specific schematic diagram of the active noise control system based on the fuzzy neural network of the present application.

[0050] An active noise control system based on a fuzzy neural network, comprising: a fuzzy controller, a reference microphone, an error microphone and a loudspeaker, wherein:

[0051] The reference microphone is used to collect a reference noise signal in a reference area as a reference signal, and output it to a fuzzy controller;

[0052] The error microphone is used to collect the residual noise signal in the noise control area as an error signal and output it to the fuzzy controller; and

[0053] The fuzzy controller is coupled with the reference microphone and the error microphone, analy...

Embodiment 3

[0056] In order to make the description of the present invention more clear and detailed, and to facilitate the understanding of technical personnel, this embodiment provides an armored vehicle driver's helmet using the active noise control system of the fuzzy neural network described in Embodiment 2. For details, see image 3 As shown in the schematic diagram of the armored vehicle driver's helmet, the active noise control system in Embodiment 2 also includes the driver's helmet main body, and a plurality of miniature microphones are installed on the helmet surface to collect the noise in the noise reference area as a reference signal, as shown in the figure ref.L and ref.R are the reference microphones (such as reference microphones) of the left and right earmuffs respectively; an error microphone (such as an error microphone) is installed in the residual noise control area formed by the earmuffs and the human ear to collect residual noise, As error signals, err.L and err.R i...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an active noise control method and system based on a fuzzy neural network and an armored vehicle driver's helmet. The method includes collecting a reference noise signal in a reference area by a reference microphone, and outputting it to a fuzzy controller as a reference signal; the error microphone collects noise The residual noise signal in the control area is used as an error signal, and is output to a fuzzy controller; and the fuzzy controller is based on an adaptive FX-RBF network training algorithm of a fuzzy neural network, and analyzes the reference signal and the error signal , and output the anti-phase target sound signal to the speaker. The active noise control based on the fuzzy neural network of the present invention has obvious noise reduction effect on noise below 2000 Hz, and the noise reduction effect on low frequency noise below 1000 Hz is particularly significant.

Description

technical field [0001] The invention relates to noise control technology in the field of armored vehicles, in particular to an active noise control method and system based on a fuzzy neural network and an armored vehicle driver's helmet. Background technique [0002] The interior noise of the armored vehicle cab and passenger cabin exceeds the standard, which seriously affects the physical and mental health of the relevant personnel. The design of vibration and noise reduction in the cabin is a relatively important task. The main noise sources in the armored car cabin mainly include: when the vehicle is running at high speed, the air turbulence causes the body structure to vibrate, which generates high-frequency noise in the car; Radiation of medium-frequency noise; vibration of the suspension system when the road surface is uneven causes vibration of the vehicle body structure, resulting in low-frequency noise in the car. [0003] In conventional armored vehicles, passive ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G10K11/178
CPCG10K11/178G10K2210/128G10K2210/3029G10K2210/3038
Inventor 邢优胜
Owner 邢优胜
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products