机械工程学报
機械工程學報
궤계공정학보
CHINESE JOURNAL OF MECHANICAL ENGINEERING
2010年
3期
71-75,82
,共6页
声发射%模糊熵%有效性系数%信号识别
聲髮射%模糊熵%有效性繫數%信號識彆
성발사%모호적%유효성계수%신호식별
Acoustic emission%Fuzzy entropy%Effectiveness coefficient%Signal recognition
利用模糊熵理论来度量转子碰摩声发射信号的特征参数相对于不同碰摩状态识别模式的不确定度.根据碰摩声发射信号的特点,选用平均信号电平、幅度、幅度动态范围以及小波包分解信号前四个节点重构信号的能量值作为声发射信号识别的特征参数,由训练样本确定各特征参数针对不同碰摩类别的基于高斯形式的隶属度函数,并由隶属函数得到特征参数与类别之间的模糊关系矩阵.由于各特征参数对于声发射信号识别的有效性不同,因此在计算模糊关系矩阵时引入有效度系数,提出一种利用模糊熵定义有效度系数的方法.结合该系数得到修正的模糊关系矩阵并计算综合评价模糊集合,选择隶属度最大的类别作为识别结果.在转子试验台上采集的不同碰摩状态的声发射信号进行验证,试验结果表明,模糊综合评价方法是一种有效的声发射识别手段,并可以利用参数有效性的差异来提高识别效率.
利用模糊熵理論來度量轉子踫摩聲髮射信號的特徵參數相對于不同踫摩狀態識彆模式的不確定度.根據踫摩聲髮射信號的特點,選用平均信號電平、幅度、幅度動態範圍以及小波包分解信號前四箇節點重構信號的能量值作為聲髮射信號識彆的特徵參數,由訓練樣本確定各特徵參數針對不同踫摩類彆的基于高斯形式的隸屬度函數,併由隸屬函數得到特徵參數與類彆之間的模糊關繫矩陣.由于各特徵參數對于聲髮射信號識彆的有效性不同,因此在計算模糊關繫矩陣時引入有效度繫數,提齣一種利用模糊熵定義有效度繫數的方法.結閤該繫數得到脩正的模糊關繫矩陣併計算綜閤評價模糊集閤,選擇隸屬度最大的類彆作為識彆結果.在轉子試驗檯上採集的不同踫摩狀態的聲髮射信號進行驗證,試驗結果錶明,模糊綜閤評價方法是一種有效的聲髮射識彆手段,併可以利用參數有效性的差異來提高識彆效率.
이용모호적이론래도량전자팽마성발사신호적특정삼수상대우불동팽마상태식별모식적불학정도.근거팽마성발사신호적특점,선용평균신호전평、폭도、폭도동태범위이급소파포분해신호전사개절점중구신호적능량치작위성발사신호식별적특정삼수,유훈련양본학정각특정삼수침대불동팽마유별적기우고사형식적대속도함수,병유대속함수득도특정삼수여유별지간적모호관계구진.유우각특정삼수대우성발사신호식별적유효성불동,인차재계산모호관계구진시인입유효도계수,제출일충이용모호적정의유효도계수적방법.결합해계수득도수정적모호관계구진병계산종합평개모호집합,선택대속도최대적유별작위식별결과.재전자시험태상채집적불동팽마상태적성발사신호진행험증,시험결과표명,모호종합평개방법시일충유효적성발사식별수단,병가이이용삼수유효성적차이래제고식별효솔.
Fuzzy entropy is used to determine the uncertainty of characteristic parameters of rub-impact acoustic emission (AE) signal in the different rub-impact modes. Average signal level, amplitude, dynamic amplitude range and energies of four nodes reconstruction signals decomposition by wavelet packets are chosen as the characteristic parameters of recognition of AE signal. The membership function of each characteristic parameter belonged to different rub-impact mode based on Gaussian model is obtained from the training samples respectively. Subsequently the fuzzy relation matrix of characteristic parameters and modes is calculated with membership functions. According to different effectiveness in recognizing AE signal by the characteristic parameters, an algorithm based on fuzzy entropy is presented to calculate effectiveness coefficient. The integrated evaluate fuzzy sets is calculated with the new fuzzy relation matrix modified by effectiveness coefficient, and the mode which has the most degree of membership is chosen as the recognition results. The experiments indicate that the integrated fuzzy evaluation is effective in analysis and recognition of AE, and the differences of parameter effectiveness can be used to improve recognition efficiency.