Fuzzy neural network-based active noise control method, system and tank helmet

A technology of active noise control and fuzzy neural network, applied in the field of tanks, to achieve the effect of speeding up noise reduction, improving convergence speed and learning accuracy, and improving noise reduction effect

Inactive Publication Date: 2017-10-03
邢优胜
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional noise control technologies such as sound absorption, sound insulation, and noise reduction are more effective for high-frequency noise. Existing active noise reduction solutions generally can only control noise below 200 Hz, and can only control noise for narrow bands

Method used

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  • Fuzzy neural network-based active noise control method, system and tank helmet
  • Fuzzy neural network-based active noise control method, system and tank helmet
  • Fuzzy neural network-based active noise control method, system and tank helmet

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Experimental program
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Embodiment 1

[0029] 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:

[0030] 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;

[0031] 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;

[0032] 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.

[0033] Wherein, the fuzzy controllers are two independent fuzzy controllers, which respectivel...

Embodiment 2

[0048] 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.

[0049] 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:

[0050] 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;

[0051] 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

[0052] The fuzzy controller is coupled with the reference microphone and the error microphone, analy...

Embodiment 3

[0055] 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 a tank 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 tank helmet, the active noise control system in Embodiment 2 also includes the main body of the tank crew helmet, 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, ref. L and ref.R are the reference microphones (such as the reference microphone) of the left and right earmuffs respectively; the error microphone (such as the error microphone) is installed in the residual noise control area formed by the earmuffs and the human ear to collect the residual noise as the error signal, err.L and err.R in the figure are the left and right error mi...

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PUM

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Abstract

The invention discloses an active noise control method and system based on a fuzzy neural network, and a tank helmet. The method includes collecting a reference noise signal in a reference area by a reference microphone as a reference signal, and outputting it to a fuzzy controller; the error microphone collects a noise control area The residual noise signal, as error signal, and output to fuzzy controller; And described fuzzy controller is based on the self-adaptive FX-RBF net training algorithm of fuzzy neural network, described reference signal and described error signal are analyzed, and Outputting the target sound signal in reverse phase to the loudspeaker, the active noise control based on the fuzzy neural network of the present invention has obvious noise reduction effect on noise below 2000 Hz, especially the noise reduction effect on low frequency noise below 1000 Hz.

Description

technical field [0001] The invention relates to the noise control technology in the field of tanks, in particular to an active noise control method and system based on a fuzzy neural network and a tank helmet. Background technique [0002] Modern warfare pays more and more attention to the maneuverability of tanks. In the process of tank development, the engine power of tanks needs to be continuously improved. With the increase of engine power, the noise in the tank cabin is also increasing. The noise in the cabin seriously affects the working ability and physical and mental health of the tank crew, affecting the combat effectiveness of the troops. [0003] For the mechanical noise of the power system such as the engine and the transmission box, the noise generated by the interaction between the track and the ground, and the noise formed by the vibration of the vehicle body caused by the engine working, etc., are mostly concentrated in the low-to-medium frequency range. Tra...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04G10K11/178
CPCG05B13/042G10K11/178
Inventor 邢优胜
Owner 邢优胜
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