基于阻抗的结构健康监测中损伤度量的统计过程控制

Q. Nomelini, J. W. Silva, C. A. Gallo, R. M. F. Neto, José Dos Reis Vieira de Moura Junior, J. E. Ramos
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引用次数: 1

摘要

统计过程控制(SPC)因使用控制图和可重复性和再现性(R&R)技术而脱颖而出。本工作旨在将其应用于结构监测的预处理方面。实验采用完全随机设计(CRD),有两个变异源:8根带有压电片的铝梁,5种损伤类型(D1 =基线,D2 = 0.6g, D3 = 1.1g, D4 = 1.6g, D5 = 2.2g)。所有测量在30℃下收集,每种情况重复20次,产生损伤度量。在R&R研究中,重复性变化较小(9.84%),但再现性较高(72.39%),表明每种情况下损伤指标相似,但梁和损伤之间差异较大。基于这一评估,控制图有助于验证在哪些梁和损伤中发现了这些最大的变化。总之,均值和个体测量的控制图以及R&R研究是测量误差检测的原始数据预处理步骤的有趣工具。
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STATISTICAL PROCESS CONTROL (SPC) OF DAMAGE METRICS IN THE IMPEDANCE-BASED STRUCTURAL HEALTH MONITORING
 ABSTRACT: Statistical Process Control (SPC) stands out for the use of control charts and for repeatability and reproducibility (R&R) techniques. This work aimed at its applications in the aspects of pre-processing of structural monitoring. The experiment was carried out in a completely randomized design (CRD) with two sources of variation: eight aluminum beams with piezoelectric patches and five types of damage (D1 = baseline, D2 = 0.6g, D3 = 1.1g, D4 = 1.6g, D5 = 2.2g). All measurements were gathered at 30C and with 20 repetitions for each condition case, producing a damage metric. In the R&R study, a low variation of repetition was observed (9.84%), but a high reproducibility (72.39%), representing that the damage metrics were similar for each situation, but a high variation among beams and damages. Based on this evaluation, the control charts helped to verify in which beams and damages these greatest variabilities were found. Concluding, the control charts for mean and individual measures as well as the R&R study were interesting tools for raw data preprocessing step for measurement error detection. 
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来源期刊
Revista Brasileira de Biometria
Revista Brasileira de Biometria Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
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审稿时长
53 weeks
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