非接触电导检测土壤养分离子的谱峰自动识别方法  

Automatic Identification Method for Spectral Peaks of Soil Nutrient Ions Using Contactless Conductivity Detection

作　　者：唐超礼[1] 李浩 王儒敬[2,3] 王乐 黄青 王大朋[2,3] 张家宝 陈翔宇[2,3] TANG Chaoi;LI Hao;WANG Rujing;WANG Le;HUANG Qing;WANG Dapeng;ZHANG Jiabao;CHEN Xiangyu(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,Chi‐na;Hefei Institutes of Physical Science,Chinese Academy of Sciences,Institute of Intelligent Machines,Intelligent Agri‐culture Engineering Laboratory of Anhui Province,Hefei 230031,China;Agricultural Sensors and Intelligent Percep‐tion Technology Innovation Center of Anhui Province,Zhongke Hefei Institutes of Collaborative Research and Innovation for Intelligent Agriculture,Hefei 231131,China;University of Science and Technology of China,Hefei 230026,China)

机构地区：[1]安徽理工大学电气与信息工程学院,安徽淮南232001 [2]中国科学院合肥物质科学研究院,智能机械研究所,安徽省智慧农业工程实验室,安徽合肥230031 [3]中科合肥智慧农业协同创新研究院,农业传感器与智能感知安徽省技术创新中心,安徽合肥231131 [4]中国科学技术大学,安徽合肥230026

出　　处：《智慧农业（中英文）》2024年第1期36-45,共10页Smart Agriculture

基　　金：国家重点研发计划项目(2023YFD1701800,2021YFD2000204,2023YFD1702104);国家自然科学基金项目(12304236,32301688);安徽省自然科学基金项目(2308085QA19,1908085QE202);安徽省科技特派团项目(S2022t06010123);中国科学院合肥物质科学研究院院长基金(YZJJ2024QN38)。

摘　　要：[目的/意义]电容耦合非接触式电导检测(Capacitively Coupled Contactless Conductivity Detection,C4D)在农业土壤养分离子检测方面发挥着重要作用。对C4D信号中离子特征峰的有效识别,有利于后续对离子特征峰的定性和定量分析,为加强农业土壤养分管理提供依据。然而,C4D信号的特征峰检测仍然存在无法自动精准识别、人工操作复杂、效率低等缺点。[方法]提出一种基于连续小波变换结合粒子群优化(Particle Swarm Optimization,PSO)和最大类间方差法(Otsu)的谱峰自动识别算法,旨在实现准确、高效、自动化的C4D信号峰识别。采用C4D检测样品溶液,得到离子谱图信号,对谱图信号进行连续小波变换,得到小波变换系数矩阵。通过搜索小波系数变换系数矩阵极值,识别出脊线和谷线。将小波系数矩阵转换为灰度图像,结合PSO和Otsu寻找最佳阈值,进一步对灰度图像的背景和目标分割,再结合原始谱图中的脊谷线识别谱图中的特征峰。[结果与讨论]测试含有41、61和102个峰的数据集,以受试者工作特性(Receiver Operating Characteristic,ROC)曲线和度量值作为评估峰值检测算法性能的准则。与其他方法相比,基于连续小波变换结合粒子群优化的最大类间方差法分割图像(Continuous Wavelet Transform C.ombined with Particle Swarm Optimization of Otsu to Segment Image,CWTSPSO)的谱峰自动识别算法的ROC曲线均保持在0.9以上,度量值分别为0.976、0.915和0.969。CWTSPSO能够有效检测出更多弱峰和重叠峰,同时检测出更少的假峰,有利于提升C4D信号的谱峰识别率和精准性。[结论]本研究提出的CWTSPSO能为非接触式电导检测农业土壤养分离子信号分析提供有力支持。[Objective]Capacitive coupled contactless conductivity detection(C4D)plays an important role in agricultural soil nutrient ion detec‐tion.Effective identification of characteristic ion peaks in C4D signals is conducive to subsequent qualitative and quantitative analysis of characteristic ion peaks,which provides a basis for improving agricultural soil nutrient management.However,the detection of characteristic peaks in C4D signals still has shortcomings,such as the inability of automatic and accurate identification,complicated manual operation,and low efficiency.[Methods]In this study,an automatic spectral peak identification algorithm based on continuous wavelet transform combined with par‐ticle swarm optimization(PSO)and maximum interclass variance method(Otsu)was proposed to achieve accurate,efficient and auto‐mated identification of C4D signal peaks.Capillary electrophoresis(CE)combined with a C4D device(CE-C4D)was used to detect the standard ions and soil sample solutions to obtain the C4D ion signal spectra,which were simulated according to the characteristics of the real C4D signal spectra to obtain the C4D simulated signals containing single Gaussian peaks and multi-Gaussian peaks.The contin‐uous wavelet transform was performed on the C4D spectrogram signal to obtain the wavelet transform coefficient matrix.The local maxima and local minima of the continuous wavelet transform coefficient matrix were searched by the staircase scanning method,and the local maxima and local minima were connected to form ridges and valleys.The wavelet coefficient matrix was converted to a gray-scale image by logistic mapping to visualize the data.The number of particle populations in PSO was set to 15,the gray scale thresh‐old of 15 particles was set to a random integer within the gray scale level of 0~255,and the initial velocity of the particles was set to 5.The combination of PSO and Otsu calculated the fitness(variance value)of each particle,updated the individual best position and the global best position,furth

关 键 词：非接触式电导检测 连续小波变换 粒子群优化算法 最大类间方差法 谱峰识别 

分 类 号：O657.11[理学—分析化学]