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《對(duì)于發(fā)動(dòng)機(jī)塊振動(dòng)測(cè)量中多個(gè)激力事件的鑒別而做的單點(diǎn)時(shí)頻分析》

作者：威廉，鄧恩，波特查，理查森和金
英國(guó)布賴(lài)頓的蘇塞克斯大學(xué)工程設(shè)計(jì)部
地址：捷豹汽車(chē)有限公司動(dòng)力傳動(dòng)工程，工程中心，修道院路，惠特利，考文垂CV3 4LF ，英國(guó)。


摘要
通過(guò)從振動(dòng)傳感器采集來(lái)的單點(diǎn)加速度數(shù)據(jù)采用短時(shí)傅立葉變換（簡(jiǎn)稱(chēng)STFT）可以用來(lái)識(shí)別發(fā)電機(jī)組的不同振源。研究的重點(diǎn)是利用短期傅里葉變換區(qū)分正常燃燒和異常燃燒，途徑是通過(guò)從其他來(lái)源的激勵(lì)包括閥影響，噴油器脈沖，爆震等等來(lái)區(qū)分。使用單一的方法來(lái)檢測(cè)另一種活動(dòng)可用于前處理的衡量爆震傳感器數(shù)據(jù)基于神經(jīng)網(wǎng)絡(luò)的重建氣缸壓力。這對(duì)于分離各種爆振聲系統(tǒng)中的某些部分也是有用的。通過(guò)一系列試驗(yàn)數(shù)據(jù)孤立這些不同活動(dòng)的3缸汽油發(fā)動(dòng)機(jī)。在每種情況中，測(cè)量數(shù)據(jù)處理采用短時(shí)傅里葉變換，以企圖孤立發(fā)生的特定事件的時(shí)域。有四組實(shí)驗(yàn)要開(kāi)始： （一）沒(méi)有點(diǎn)燃的（馬達(dá)）發(fā)動(dòng)機(jī)，用測(cè)力計(jì)測(cè)驅(qū)動(dòng)力，發(fā)動(dòng)機(jī)安裝了火花塞，然后移開(kāi)，隔離閥的影響; （二）點(diǎn)燃的發(fā)動(dòng)機(jī)在自由狀況下運(yùn)行，然后來(lái)比較空載燃燒和沒(méi)有燃燒; （三）加部分載荷的引擎正常運(yùn)行，然后運(yùn)行一個(gè)噴油器開(kāi)關(guān)的關(guān)閉， （四）讓滿(mǎn)載的發(fā)動(dòng)機(jī)正常運(yùn)行，然后關(guān)閉爆震控制。該研究表明，通過(guò)短時(shí)傅里葉變換一個(gè)單一的時(shí)頻分析方法，如果適當(dāng)?shù)恼{(diào)整分離和使用爆震傳感器數(shù)據(jù)，可以有效地確定發(fā)生這些事件的反應(yīng)時(shí)域。


文章概要
1 、導(dǎo)言
2 、利用短時(shí)傅里葉變換進(jìn)行時(shí)頻分析
3 、發(fā)動(dòng)機(jī)試驗(yàn)方案和實(shí)驗(yàn)數(shù)據(jù)采集
3.1 、實(shí)驗(yàn)測(cè)試方案
3.2 、數(shù)據(jù)采集
參考資料


Time-frequency analysis of single-point engine-block vibration measurements for multiple excitation-event identification
S. Vulli, J.F. Dunne,,, R. Potenza, D. Richardson and P. King
Department of Engineering and Design, The University of Sussex, Falmer, Brighton BN1 9QT, UK
Advanced Powertrain Engineering, Jaguar Cars Limited, Engineering Centre, Abbey Road, Whitley, Coventry CV3 4LF, UK



Abstract
The short-term-Fourier-transform (STFT) is used to identify different sources of IC engine-block vibration from single-point acceleration measurements taken with a commercial knock sensor. Interest is focused on using the STFT to distinguish normal combustion from other sources of excitation including valve impact, injector pulses, and abnormal combustion, such as knocking. Positive identification of these other events using a single method can be useful for pre-processing of measured knock-sensor data for neural-network-based reconstruction of cylinder pressure. It can also be useful separately as part of a fast knock detection system. A series of experiments is discussed to create the data to isolate these different events on a 3-cylinder gasoline engine. In each case, the measured data is processed using the STFT to attempt to isolate the occurrence of particular events in the time domain. Four classes of experiments are undertaken: (i) an un-fired (motored) engine, driven by a dynamometer, with spark plugs fitted, and then removed, to isolate valve impact; (ii) a fired engine running under idle conditions, to contrast no-load combustion with no combustion; (iii) a part-loaded engine running normally, and then running with one injector switched-off, and (iv) a fully-loaded engine running normally, and then running with knock-control switched-off. The paper shows that a single Time-frequency analysis method, applied to knock sensor data in the form of an appropriately-tuned STFT, can effectively identify the occurrence of these events in the time domain if responses are adequately separated and strong enough.
Article Outline
1. Introduction
2. Time-frequency analysis using the STFT
3. Engine test programme and experimental data acquisition
3.1. Experimental test programme
3.2. Data acquisition
Acknowledgements
References