CAJ | 학술논문

为了在传感器测量锂电池非连续性膜厚前不需测量C型机构的固有频率和扫描振动频率，采用3层小波-阈值判断-稀疏分解信号处理去噪方法，进行了理论分析和实验验证。该方法不需固有频率和扫描振动频率的先验知识，在不同C型机构扫描速率模式下，通过迭代选取最佳匹配的原子序列保留锂电池薄膜厚度分布，滤除局部噪声波动，实现稀疏迭代去噪。结果表明，相对于小波算法，在缺乏先验知识的条件下，稀疏分解算法具有较好的去噪性能，其均方差值达5μm～7μm，是一种操作简单、可行有效的方法。
위료재전감기측량리전지비련속성막후전불수측량C형궤구적고유빈솔화소묘진동빈솔，채용3층소파-역치판단-희소분해신호처리거조방법，진행료이론분석화실험험증。해방법불수고유빈솔화소묘진동빈솔적선험지식，재불동C형궤구소묘속솔모식하，통과질대선취최가필배적원자서렬보류리전지박막후도분포，려제국부조성파동，실현희소질대거조。결과표명，상대우소파산법，재결핍선험지식적조건하，희소분해산법구유교호적거조성능，기균방차치체5μm～7μm，시일충조작간단、가행유효적방법。
In order to avoid measuring the inherent frequency and the scanning vibration frequency of C -dynamic scanning system before measuring discontinuous film thickness of lithium battery with laser sensors , the 3-layer wavelet-threshold judgment-sparse decomposition signal processing de-noising method was used . Theoretical analysis and experimental verification were made . Without prior knowledge of the inherent frequency and the scanning vibration frequency and under different C-dynamic scanning mode , the best-matching atomic sequence was selected by iteration and the film thickness distribution of lithium battery was reserved , fluctuations of the local noise were filtered and sparse iterative de-noising was realized .The results show that comparing with the wavelet algorithm and in the absence of the prior knowledge , sparse decomposition algorithm has better de-noising performance and is a simple , practical and effective method.Mean square error of sparse decomposition algorithm is 5μm~7μm.