基于BP神經(jīng)網(wǎng)絡(luò )的多傳感器信息融合研究

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基于BP神經(jīng)網(wǎng)絡(luò )的多傳感器信息融合研究
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作者單位:(1.鹽城工學(xué)院 電氣工程學(xué)院,江蘇 鹽城 224051;2.東南大學(xué) 信息科學(xué)與工程學(xué)院,南京 210096)
作者簡(jiǎn)介:夏菽蘭(1969), 女,江蘇鹽城人,副教授,碩士,主要從事電子技術(shù)與信息檢測技術(shù)方向的研究。[FQ)]
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基金項目:國家自然科學(xué)基金項目資助(60472058)。

Research of Multi-sensor Information Fusion Based on BP Neural Networks

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(1.School of Electrical Engineering, Yancheng Institute of Technology, Yancheng 224051, China; ;2.College of Information Science and Engineering ,Southeast University, Nanjing 210096,China)

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摘要:

BP網(wǎng)絡(luò )是應用最廣的一種人工神經(jīng)網(wǎng)絡(luò ),將BP神經(jīng)網(wǎng)絡(luò )應用到壓力檢測領(lǐng)域的溫度等非線(xiàn)性補償,具有重要的實(shí)用價(jià)值,對壓力檢測精度的改進(jìn)效果顯著(zhù)；從傳感器信息融合的角度看,神經(jīng)網(wǎng)絡(luò )就是一個(gè)融合系統；通過(guò)對神經(jīng)網(wǎng)絡(luò )基本理論的闡述,針對研究對象將BP神經(jīng)網(wǎng)絡(luò )原理與多傳感器信息融合技術(shù)有機集合起來(lái),提出了基于BP神經(jīng)網(wǎng)絡(luò )的二傳感器信息融合模型及改進(jìn)算法,建立了BP神經(jīng)網(wǎng)絡(luò )訓練標準樣本庫,并對該網(wǎng)絡(luò )模型進(jìn)行主要技術(shù)指標的測試和仿真工作,測試結果表明構建的模型及其改進(jìn)算法能很好地滿(mǎn)足了高精度壓力檢測儀的指標要求。

Abstract:

BP network is a kind of the most widely used artificial neural network, it is applied to temperature nonlinear compensation of pressure detecting, has important practical value, and significantly on the improvement of detection accuracy. From the point of view of the sensor information fusion, neural network is a fusion system. Through the exposition of the basic theory of neural network, and based on the principle of BP neural network and multi sensor information fusion technology, the model and the improved algorithm of two sensor information fusion based on BP neural network have been proposed, and training sample database of BP neural network has been established. The main technical parameters of the network model have been tested and simulated, and the results show that the constructed model and its improved algorithm can well meet the requirement of high accuracy pressure detector index.

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夏菽蘭,趙力.基于BP神經(jīng)網(wǎng)絡(luò )的多傳感器信息融合研究計算機測量與控制[J].,2015,23(5):1823-1826.

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