不同含水率云南松声发射信号特征
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摘要
【目的】研究不同含水率条件下云南松试件声发射信号的传播规律,探讨含水率对声发射信号波形的响应,为云南松声发射源定位提供依据,为木材内部缺陷无损检测提供基础数据。【方法】以云南松为试验材料,采用NI高速数据采集设备和LabVIEW软件构建云南松试件声发射信号采集平台,利用铅芯折断模拟声发射源,对绝干、气干、生材和饱水4种含水率状态下的试件表面进行声发射信号采集,通过时差法计算信号在4种含水率状态下的平均传播速率,并运用小波分析对声发射信号波形进行分解和重构,根据软阈值量化方法消除各通道系数和经阈值量化后的各高频层系数,去除非主能量信号以便从噪声中析取微弱的声发射信号。【结果】试验中传感器均以接收表面波信号为主;随着含水率增加,云南松试件表面声发射信号波形和平均声速均大幅度衰减,绝干状态下声发射信号时域波形幅值达到±5.2 V,平均声速可达4 208.77 m·s~(-1),而饱水状态下信号时域波形幅值仅为±0.6 V,平均声速降至1 414.07 m·s~(-1),气干和生材状态下信号时域波形幅值和平均声速分别为±4、±2 V和3 331.79、2 328.73 m·s~(-1),且各含水率状态之间平均声速差在876.98～1 003.06 m·s~(-1)范围内;小波变换能有效将"淹没"在噪声中的声发射信号析取出来,4种含水率状态下试件声发射信号频域波形范围在40～150 kHz之间,且气干状态下波形峰值出现在110 kHz左右,其余3种均在50 kHz左右达到峰值。【结论】含水率增加可显著改变云南松声发射信号和传播特征,其信号波形和平均声速均与含水率降低呈正比;小波变换在信号降噪处理方面具有明显优势,不仅可去除信号中的大量噪音,而且不会破坏有用信号,保证信号完整性,能更大程度降低对不同含水率云南松试件声发射信号的分析误差,为云南松表面声发射源定位研究及内部无损检测给予试验数据支持;作为一种木材声发射信号采集与分析平台,研究结果可为不同含水率云南松受压变形破坏全过程的声发射特征分析提供必要的基础理论依据。
【Objective】 In this study, Pinus yunnanensis is used as the material to analyze the propagation rule of the acoustic emission(AE)signal in samples under different moisture content conditions, and to discuss the response of moisture content to AE signal waveform, which could provide the basis for the location of AE source of P. yunnanensis and the basic data for nondestructive testing of wood internal defects.【Method】 The most common P. yunnanensis in Yunnan Province, is used as raw material, containing four kinds of water-bearing states,those were, absolute dry, air-dried, green timber and water-saturated. According to the NI high speed data acquisition equipment and the LabVIEW software, the wood AE signal acquisition platform is set up. Then, the AE signal is collected on the surface of four kinds of wood samples by the simulation of AE source under lead core fracture. Meanwhile, the time difference method is used to calculate the average velocity of four kinds of water condition, and wavelet analysis is used to decompose and reconstruct the AE signal waveform, then soft threshold quantization method is applied for removing each channel coefficient and the high frequency coefficients quantized, and removing non-primary energy signals in order to extract the weak acoustic emission signal from the noise.【Result】 In the experiment, the surface wave signals were mainly received by the sensors. With the increase of moisture content, the AE signal waveform and average sound speed of P. yunnanensis are greatly attenuated on the surface. Under absolute dry state, the time domain waveform of AE signal reaches 5.2 V, and the average sound speed can reach 4 208.77 m·s~(-1), while the amplitude of the signal waveform is only 0.6 V, and the average sound speed is decreased to 1 414.07 m·s~(-1) in water-saturated state. The amplitude and average rate of signal waveforms are ±4 V, ±2 V and 2 328.73 m·s~(-1), 3 331.79 m·s~(-1), respectively, in air-dried and green timber states, and the average sound velocity difference between each water bearing state is in the range of 876.98-1 003.06 m·s~(-1). Moreover, the AE signals submerged in noise can be extracted by the method of wavelet analysis. Thus, the AE signal of four kinds of samples is obtained, and the range of frequency waveform is between 40 and 150 kHz, while the peak value of waveform appears at about 110 kHz in the air dry state, and the other three are peaked at about 50 kHz.【Conclusion】 The increase of moisture content significantly changes the AE signal and propagation characteristics of P. yunnanensis, and its signal waveform and average sound speed are positively proportional to the decrease of moisture content. From the comparison of time-frequency diagram of signal before and after wavelet transform, it can be seen that the wavelet transform has obvious advantage in signal noise reduction processing, not only a lot of noise in the signal was removed, but also the useful signal was not damaged, moreover, the signal integrity was guaranteed. On the other hand, to a greater extent, the analysis error is reduced, which gives experimental data support for the research of P. yunnanensis AE source location and internal non-destructive testing. As an AE signal of acquisition and analysis platform, the result of this study could provide the necessary theoretical evidence for the research of AE characteristics of P. yunnanensis with different moisture contents in process of compression deformation and failure.
【Objective】 In this study, Pinus yunnanensis is used as the material to analyze the propagation rule of the acoustic emission(AE)signal in samples under different moisture content conditions, and to discuss the response of moisture content to AE signal waveform, which could provide the basis for the location of AE source of P. yunnanensis and the basic data for nondestructive testing of wood internal defects.【Method】 The most common P. yunnanensis in Yunnan Province, is used as raw material, containing four kinds of water-bearing states,those were, absolute dry, air-dried, green timber and water-saturated. According to the NI high speed data acquisition equipment and the LabVIEW software, the wood AE signal acquisition platform is set up. Then, the AE signal is collected on the surface of four kinds of wood samples by the simulation of AE source under lead core fracture. Meanwhile, the time difference method is used to calculate the average velocity of four kinds of water condition, and wavelet analysis is used to decompose and reconstruct the AE signal waveform, then soft threshold quantization method is applied for removing each channel coefficient and the high frequency coefficients quantized, and removing non-primary energy signals in order to extract the weak acoustic emission signal from the noise.【Result】 In the experiment, the surface wave signals were mainly received by the sensors. With the increase of moisture content, the AE signal waveform and average sound speed of P. yunnanensis are greatly attenuated on the surface. Under absolute dry state, the time domain waveform of AE signal reaches 5.2 V, and the average sound speed can reach 4 208.77 m·s~(-1), while the amplitude of the signal waveform is only 0.6 V, and the average sound speed is decreased to 1 414.07 m·s~(-1) in water-saturated state. The amplitude and average rate of signal waveforms are ±4 V, ±2 V and 2 328.73 m·s~(-1), 3 331.79 m·s~(-1), respectively, in air-dried and green timber states, and the average sound velocity difference between each water bearing state is in the range of 876.98-1 003.06 m·s~(-1). Moreover, the AE signals submerged in noise can be extracted by the method of wavelet analysis. Thus, the AE signal of four kinds of samples is obtained, and the range of frequency waveform is between 40 and 150 kHz, while the peak value of waveform appears at about 110 kHz in the air dry state, and the other three are peaked at about 50 kHz.【Conclusion】 The increase of moisture content significantly changes the AE signal and propagation characteristics of P. yunnanensis, and its signal waveform and average sound speed are positively proportional to the decrease of moisture content. From the comparison of time-frequency diagram of signal before and after wavelet transform, it can be seen that the wavelet transform has obvious advantage in signal noise reduction processing, not only a lot of noise in the signal was removed, but also the useful signal was not damaged, moreover, the signal integrity was guaranteed. On the other hand, to a greater extent, the analysis error is reduced, which gives experimental data support for the research of P. yunnanensis AE source location and internal non-destructive testing. As an AE signal of acquisition and analysis platform, the result of this study could provide the necessary theoretical evidence for the research of AE characteristics of P. yunnanensis with different moisture contents in process of compression deformation and failure.
引文
陈春谏,赵耀江,郭胜亮,等.2018.不同含水率煤岩声发射特性试验研究.煤矿安全,49(5):40-46.(Chen C J,Zhao Y J,Guo S L,et al.2018.Experimental study on acoustic emission characteristics of coal with different moisture content.Safety in Coal Mines,49(5):40-46.[in Chinese])
丁小康,张祥雪,郝燕华,等.2012.木材干燥过程中声发射信号分析.木材工业,26(3):40-43.(Ding X K,Zhang X X,Hao Y H,et al.2012.Acoustic emission analysis during small thin wood samples.China Wood Industry,26(3):40-43.[in Chinese])
范博楠,王海斗,徐滨士,等.2015.强背景噪声下微弱声发射信号提取及处理研究现状.振动与冲击,34(16):147-155.(Fan B N,Wang H D,Xu B S,et al.2015.Present research situation of the extraction and processing of weak acoustic emission signals under strong background noise.Journal of Vibration and Shock,34(16):147-155.[in Chinese])
范文俊,涂登云,彭冲,等.2015.热处理对毛白杨木材力学性能的影响机理.东北林业大学学报,43(10):88-91.(Fan W J,Tu D Y,Peng C,et al.2015.Influence of heat treatment on mechanical properties of Populus tomentosa wood.Journal of Northeast Forestry University,43(10):88-91.[in Chinese])
黄金波,王志刚,刘昌明.2013.基于小波变换的镁碳质耐火材料受压损伤声发射特征分析.材料导报,27(16):139-142.(Huang J B,Wang Z G,Liu C M.2013.Analysis of the acoustic emission characteristics of MgO-C Refractory damage under compressive load based on wavelet transform.Materials Review,27(16):139-142.[in Chinese])
廖立,涂登云,李重根,等.2013.热处理对尾赤桉木材物理力学性能的影响.中南林业科技大学学报,33(5):128-131.(Liao L,Tu D Y,Li C G,et al.2013.Effects of heat treatment on physical-mechanical properties of E.urophylla×E.camaldulensis.Journal of Central South University of Forestry,33(5):128-131.[in Chinese])
林兰英,秦理哲,傅峰.2015.微观力学表征技术的发展及其在木材科学领域中的应用.林业科学,51(2):121-128.(Ling L Y,Qin L Z,Fu F.2015.Development of micromechanical technique and application on wood science.Scientia Silvae Sinicae,51(2):121-128.[in Chinese])
刘昊,高建民.2014.含水率和密度对木材应力波传播速度的影响.北京林业大学学报,36(6):154-158.(Liu H,Gao J M.2014.Effects of moisture content and density on the stress wave velocity in wood.Journal of Beijing Forestry University,36(6):154-158.[in Chinese])
彭辉,蒋佳荔,詹天翼,等.2016.木材密度和含水率对其轴向超声波传播速度的影响.林业科学,52(10):117-124.(Peng H,Jiang J L,Zhan T Y,et al.2016.Influence of density and moisture content on ultrasound velocities along the longitudinal direction in wood.Scientia Silvae Sinicae,52(10):117-124.[in Chinese])
邵卓平,陈品,查朝生,等.2009.木材损伤断裂过程的声发射特性与Felicity效应.林业科学,45(2):86-91.(Shao Z P,Chen P,Zha C S,et al.2009.Acoustic emission characteristics of damage and fracture process of wood and felicity effect.Scientia Silvae Sinicae,45(2):86-91.[in Chinese])
申珂楠,丁馨曾,赵海龙,等.2015a.木材表面声发射信号源的三角形定位方法.东北林业大学学报,43(4):77-81.(Shen K N,Ding X Z,Zhao H L,et al.2015a.Acoustic emission signal source localization in wood surface with triangle positioning method.Journal of Northeast Forestry University,43(4):77-81.[in Chinese])
申珂楠,赵海龙,丁馨增,等.2015b.基于 LabVIEW 的木材声发射信号采集与小波析取.中南林业科技大学学报,35(4):125-129.(Shen K N,Zhao H L,Ding X Z,et al.2015b.Wood acoustic emission signal acquisition and wavelet extraction based on LabVIEW.Journal of Central South University of Forestry,35(4):125-129.[in Chinese])
申珂楠,赵海龙,丁馨曾,等.2015c.木材损伤断裂过程声发射信号小波析取.河南科技大学学报:自然科学版,36(3):33-37.(Shen K N,Zhao H L,Ding X Z,et al.2015c.Acoustic emission signal wavelet disjunction in wood damage and fracture process.Journal of Henan University of Science and Technology:Natural Science,36(3):33-37.[in Chinese])
孙丽萍,张冬妍.2013.基于分层信息融合的木材干燥过程含水率在线检测.农业工程学报,29(s1):257-263.(Sun L P,Zhang D Y.2013.Online testing of lumber drying moisture based on layered information fusion.Transactions of the Chinese Society of Agricultural Engineering,29(s1):257-263.[in Chinese])
文圣勇,韩立军,宗义江,等.2013.不同含水率红砂岩单轴压缩试验声发射特征研究.煤炭科学技术,41(8):46-48.(Wen S Y,Han L J,Zong Y J,et al.2013.Study on acoustic emission characteristics of sandstone uniaxial compression test with different moisture content.Coal Science and Technology,41(8):46-48.[in Chinese])
许江,耿加波,彭守建,等.2015.不同含水率条件下煤与瓦斯突出的声发射特性.煤炭学报,40(5):1047-1054.(Xu J,Geng J B,Peng S J,et al.2015.Acoustic emission characteristics of coal and gas outburst under different moisture contents.Journal of China Coal Society,40(5):1047-1054.[in Chinese])
许中林,李国禄,董天顺,等.2014.声发射信号分析与处理方法研究进展.材料导报,28(9):56-60.(Xu Z L,Li G L,Dong T S,et al.2014.Overview on development of acoustic emission signal analysis technique and processing.Materials Review,28(9):56-60.[in Chinese])
张安斌,刘祥鑫,张艳博,等.2017.不同含水率泥质粉砂岩破裂声发射特性试验研究.地下空间与工程学报,13(3):591-597.(Zhang A B,Liu X X,Zhang Y B,et al.2017.Experimental research on acoustic emission characteristics of argillaceous siltstone failure under different moisture contents.Chinese Journal of Underground Space and Engineering,13(3):591-597.[in Chinese])
Baensch F,Sause M G R,Brunner A J,et al.2015.Damage evolution in wood-Pattern recognition based on acoustic emission(AE)frequency spectra.Holzforschung,69(3):357-365.
Dunegan H L,Harris D O,Tatro C A.1968.Fracture analysis by use of acoustic emission.Engineering Fracture Mechanics,1(1):105-110.
Lamy F,Takarli M,Angellier N,et al.2015.Acoustic emission technique for fracture analysis in wood materials.International Journal of Fracture,192(9):57-70.
Ritschel F,Brunner A J,Niemz P.2013.Nondestructive evaluation of damage accumulation in tensile test specimens made from solid wood and layered wood materials.Composite Structures,95(1):44-52.
Ritschel F,Yang Z,Brunner A J,et al.2014.Acoustic emission analysis of industrial plywood materials exposed to destructive tensile load.Wood Science & Technology,48(3):1-21.
Wolkerstorfer S V,Rosner S,Hietz P.2012.An improved method and data analysis for ultrasound acoustic emissions and xylem vulnerability in conifer wood.Physiologia Plantarum,146(2):184-191.
丁小康,张祥雪,郝燕华,等.2012.木材干燥过程中声发射信号分析.木材工业,26(3):40-43.(Ding X K,Zhang X X,Hao Y H,et al.2012.Acoustic emission analysis during small thin wood samples.China Wood Industry,26(3):40-43.[in Chinese])
范博楠,王海斗,徐滨士,等.2015.强背景噪声下微弱声发射信号提取及处理研究现状.振动与冲击,34(16):147-155.(Fan B N,Wang H D,Xu B S,et al.2015.Present research situation of the extraction and processing of weak acoustic emission signals under strong background noise.Journal of Vibration and Shock,34(16):147-155.[in Chinese])
范文俊,涂登云,彭冲,等.2015.热处理对毛白杨木材力学性能的影响机理.东北林业大学学报,43(10):88-91.(Fan W J,Tu D Y,Peng C,et al.2015.Influence of heat treatment on mechanical properties of Populus tomentosa wood.Journal of Northeast Forestry University,43(10):88-91.[in Chinese])
黄金波,王志刚,刘昌明.2013.基于小波变换的镁碳质耐火材料受压损伤声发射特征分析.材料导报,27(16):139-142.(Huang J B,Wang Z G,Liu C M.2013.Analysis of the acoustic emission characteristics of MgO-C Refractory damage under compressive load based on wavelet transform.Materials Review,27(16):139-142.[in Chinese])
廖立,涂登云,李重根,等.2013.热处理对尾赤桉木材物理力学性能的影响.中南林业科技大学学报,33(5):128-131.(Liao L,Tu D Y,Li C G,et al.2013.Effects of heat treatment on physical-mechanical properties of E.urophylla×E.camaldulensis.Journal of Central South University of Forestry,33(5):128-131.[in Chinese])
林兰英,秦理哲,傅峰.2015.微观力学表征技术的发展及其在木材科学领域中的应用.林业科学,51(2):121-128.(Ling L Y,Qin L Z,Fu F.2015.Development of micromechanical technique and application on wood science.Scientia Silvae Sinicae,51(2):121-128.[in Chinese])
刘昊,高建民.2014.含水率和密度对木材应力波传播速度的影响.北京林业大学学报,36(6):154-158.(Liu H,Gao J M.2014.Effects of moisture content and density on the stress wave velocity in wood.Journal of Beijing Forestry University,36(6):154-158.[in Chinese])
彭辉,蒋佳荔,詹天翼,等.2016.木材密度和含水率对其轴向超声波传播速度的影响.林业科学,52(10):117-124.(Peng H,Jiang J L,Zhan T Y,et al.2016.Influence of density and moisture content on ultrasound velocities along the longitudinal direction in wood.Scientia Silvae Sinicae,52(10):117-124.[in Chinese])
邵卓平,陈品,查朝生,等.2009.木材损伤断裂过程的声发射特性与Felicity效应.林业科学,45(2):86-91.(Shao Z P,Chen P,Zha C S,et al.2009.Acoustic emission characteristics of damage and fracture process of wood and felicity effect.Scientia Silvae Sinicae,45(2):86-91.[in Chinese])
申珂楠,丁馨曾,赵海龙,等.2015a.木材表面声发射信号源的三角形定位方法.东北林业大学学报,43(4):77-81.(Shen K N,Ding X Z,Zhao H L,et al.2015a.Acoustic emission signal source localization in wood surface with triangle positioning method.Journal of Northeast Forestry University,43(4):77-81.[in Chinese])
申珂楠,赵海龙,丁馨增,等.2015b.基于 LabVIEW 的木材声发射信号采集与小波析取.中南林业科技大学学报,35(4):125-129.(Shen K N,Zhao H L,Ding X Z,et al.2015b.Wood acoustic emission signal acquisition and wavelet extraction based on LabVIEW.Journal of Central South University of Forestry,35(4):125-129.[in Chinese])
申珂楠,赵海龙,丁馨曾,等.2015c.木材损伤断裂过程声发射信号小波析取.河南科技大学学报:自然科学版,36(3):33-37.(Shen K N,Zhao H L,Ding X Z,et al.2015c.Acoustic emission signal wavelet disjunction in wood damage and fracture process.Journal of Henan University of Science and Technology:Natural Science,36(3):33-37.[in Chinese])
孙丽萍,张冬妍.2013.基于分层信息融合的木材干燥过程含水率在线检测.农业工程学报,29(s1):257-263.(Sun L P,Zhang D Y.2013.Online testing of lumber drying moisture based on layered information fusion.Transactions of the Chinese Society of Agricultural Engineering,29(s1):257-263.[in Chinese])
文圣勇,韩立军,宗义江,等.2013.不同含水率红砂岩单轴压缩试验声发射特征研究.煤炭科学技术,41(8):46-48.(Wen S Y,Han L J,Zong Y J,et al.2013.Study on acoustic emission characteristics of sandstone uniaxial compression test with different moisture content.Coal Science and Technology,41(8):46-48.[in Chinese])
许江,耿加波,彭守建,等.2015.不同含水率条件下煤与瓦斯突出的声发射特性.煤炭学报,40(5):1047-1054.(Xu J,Geng J B,Peng S J,et al.2015.Acoustic emission characteristics of coal and gas outburst under different moisture contents.Journal of China Coal Society,40(5):1047-1054.[in Chinese])
许中林,李国禄,董天顺,等.2014.声发射信号分析与处理方法研究进展.材料导报,28(9):56-60.(Xu Z L,Li G L,Dong T S,et al.2014.Overview on development of acoustic emission signal analysis technique and processing.Materials Review,28(9):56-60.[in Chinese])
张安斌,刘祥鑫,张艳博,等.2017.不同含水率泥质粉砂岩破裂声发射特性试验研究.地下空间与工程学报,13(3):591-597.(Zhang A B,Liu X X,Zhang Y B,et al.2017.Experimental research on acoustic emission characteristics of argillaceous siltstone failure under different moisture contents.Chinese Journal of Underground Space and Engineering,13(3):591-597.[in Chinese])
Baensch F,Sause M G R,Brunner A J,et al.2015.Damage evolution in wood-Pattern recognition based on acoustic emission(AE)frequency spectra.Holzforschung,69(3):357-365.
Dunegan H L,Harris D O,Tatro C A.1968.Fracture analysis by use of acoustic emission.Engineering Fracture Mechanics,1(1):105-110.
Lamy F,Takarli M,Angellier N,et al.2015.Acoustic emission technique for fracture analysis in wood materials.International Journal of Fracture,192(9):57-70.
Ritschel F,Brunner A J,Niemz P.2013.Nondestructive evaluation of damage accumulation in tensile test specimens made from solid wood and layered wood materials.Composite Structures,95(1):44-52.
Ritschel F,Yang Z,Brunner A J,et al.2014.Acoustic emission analysis of industrial plywood materials exposed to destructive tensile load.Wood Science & Technology,48(3):1-21.
Wolkerstorfer S V,Rosner S,Hietz P.2012.An improved method and data analysis for ultrasound acoustic emissions and xylem vulnerability in conifer wood.Physiologia Plantarum,146(2):184-191.
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