[1]吕云蕾,刘亚秋,黄英来*.基于FMEA的MDF连续平压板厚诊断与控制失效信息表达方法[J].林业工程学报,2019,4(06):127-135.[doi:10.13360/j.issn.2096-1359.2019.06.018]
　LYU Yunlei,LIU Yaqiu,HUANG Yinglai*.FMEA-based MDF continuous flat press panel thickness diagnosis and control failure information expression method[J].Journal of Forestry Engineering,2019,4(06):127-135.[doi:10.13360/j.issn.2096-1359.2019.06.018]
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基于FMEA的MDF连续平压板厚诊断与控制失效信息表达方法()
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《林业工程学报》[ISSN:2096-1359/CN:32-1862/S]

卷:
4
期数:
2019年06期
页码:
127-135
栏目:
装备与信息化 执行主编：周宏平
出版日期:
2019-11-20

文章信息/Info

Title:
FMEA-based MDF continuous flat press panel thickness diagnosis and control failure information expression method
文章编号:
2096-1359(2019)06-0127-09
作者:
吕云蕾; 刘亚秋; 黄英来*
东北林业大学信息与计算机工程学院,哈尔滨 150040
Author(s):
LYU Yunlei;  LIU Yaqiu;  HUANG Yinglai*
School of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China
关键词:
故障模式及影响分析;  中密度纤维板;  连续平压;  板厚纠偏;  诊断与控制;  海明编码
Keywords:
failure mode and effects analysis;  medium density fiberboard;  continuous flat pressure;  thickness correction;  diagnostic control;  Hamming code
分类号:
S777; S781.5
DOI:
10.13360/j.issn.2096-1359.2019.06.018
文献标志码:
A
摘要:
连续热压是中密度纤维板(MDF)生产中最重要的工序之一,由于连续平压机作为整条生产线的核心设备,因此,对其运行控制的精准性、可靠性将会直接影响整线的生产能力和产品品质。利用失效模式和影响分析(FMEA)方法,针对连续平压过程中易出现的板厚控制失效和板厚偏差缺陷消隐问题,提出了一种MDF连续平压板厚诊断与控制失效信息表达方法,根据该方法潜在失效性与海明编码的方法相结合,并通过海明编码对连续热压定厚段控制执行组单元压缸阵列进行诊断表达,用以分析MDF热压生产过程中潜在的定厚失效模式,并给出板厚缺陷和板材的偏差等级消隐工艺控制决策规则。通过海明编码和逻辑或运算算法结合测试分析表明,设计提出的MDF连续平压板厚诊断与纠偏控制失效信息表达方法符合MDF连续平压生产的全工况过程信息的表达,能够满足连续平压机的敏捷生产和可靠运行要求,并对实现MDF厚度偏差诊断与控制提供了理论基础,为后续生产过程提供了安全保障。
Abstract:
Continuous hot pressing is one of the most important processes in the production of medium density fiberboard(MDF).Since the continuous flat press is the key equipment of the whole production line, the accuracy and reliability of its operation control will directly affect the operation efficiency, production capacity and product quality.As one of the major raw materials in the furniture industry, the thickness deviation of MDF panel plays a critical role in determining the furniture quality.Thus, it is important to control the panel thickness during the MDF production to obtain panels with even thickness.In this study, the failure mode and influence analysis(FMEA)method was used to solve the problem of panel thickness control failure and panel thickness deviation defect blanking, which were prone to occur in the continuous flat pressing process.This study proposed a method combining the method of potential failure with the Hamming coding method, using the Hamming code to diagnose the expression of the continuous hot-pressed thick-section control execution unit cylinder array and to analyze the potential deviation of the MDF hot-pressing production process.This proposed method utilized the fixed thickness failure mode and provided the panel defect and thickness deviation level of the sheet blanking process control decision rules.The combination of Hamming coding and logical OR algorithm showed that the MATLAB simulation experiment was combined with the actual operation in the field and the data obtained by the simulation experiment was encoded by the Haiming coding to obtain different MDF deviation level information.Therefore, it was concluded that the MDF continuous flat press panel thickness diagnosis and rectification control failure information expression method proposed in this study conformed to the full working condition process information of the production of the MDF continuous flat press, which can meet the smart production and reliable operation requirements of the continuous flat press.The results of this study can provide a theoretical basis for realizing the smart diagnosis and control of MDF thickness deviation, improving production efficiency and guaranteeing the quality of MDF panels in the production process.

参考文献/References:

[1] 陈德旺.连续平压法生产MDF的热压工艺[J].林产工业, 2005, 32(4): 32-34, 38.DOI: 10.3969/j.issn.1001-5299.2005.04.009.
CHEN D W.Hot pressing technology for MDF production with continuous press process[J].China Forest Products Industry, 2005, 32(4): 32-34, 38.
[2] 朱良宽, 王子博, 刘亚秋, 等.基于RBF神经网络的中密度纤维板连续热压板厚动态面控制[J].东北林业大学学报, 2016, 44(6): 68-74.DOI: 10.13759/j.cnki.dlxb.20160510.003.
ZHU L K, WANG Z B, LIU Y Q, et al.MDF continuous hot pressing plank thickness dynamic surface control by RBF neural network[J].Journal of Northeast Forestry University, 2016, 44(6): 68-74.
[3] WANG W Z, LIU X W, QIN Y, et al.A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral[J].Safety Science, 2018, 110: 152-163.DOI: 10.1016/j.ssci.2018.08.009.
[4] CATELANI M, CIANI L, VENZI M.Failure modes, mechanisms and effect analysis on temperature redundant sensor stage[J].Reliability Engineering and System Safety,2018, 180(C): 425-433.DOI: 10.1016/j.ress.2018.08.013.
[5] 吴凤明, 刘家祥, 殷璨.基于FMEA的设备风险分级管控研究[J].价值工程, 2018, 37(27): 94-96.DOI: 10.14018/j.cnki.cn13-1085/n.2018.27.037.
WU F M, LIU J X, YIN C.Research on equipment risk classification control based on FMEA[J].Value Engineering, 2018, 37(27): 94-96.
[6] 刘博.FMEA分析法在C公司电子产品组装生产线中的应用研究[D].苏州: 苏州大学, 2017.
LIU B.Application of FMEA in C company electronic product line[D].Suzhou: Soochow University, 2017.
[7] GHEIBI M, KARRABI M, EFTEKHARI M.Designing a smart risk analysis method for gas chlorination units of water treatment plants with combination of Failure Mode Effects Analysis, Shannon Entropy, and Petri Net Modeling[J].Ecotoxicology and Environmental Safety, 2019, 171: 600-608.DOI: 10.1016/j.ecoenv.2019.01.032.
[8] 武曲, 吕博.光学计算机对称三值数据海明校验研究[J].长春理工大学学报(自然科学版), 2015, 38(4): 87-92.DOI: 10.3969/j.issn.1672-9870.2015.04.020.
WU Q, LYU B.Hamming specification for symmetric ternary data of optical computer[J].Journal of Changchun University of Science and Technology, 2015, 38(4): 87-92.
[9] 潘兴明, 石倩, 路胜杰, 等.基于海明编码的EEPROM数据存取功能的实现[J].电子设计工程, 2015, 23(7): 162-165.DOI: 10.14022/j.cnki.dzsjgc.2015.07.056.
PAN X M, SHI Q, LU S J, et al.Implementation of EEPROM data access function based on HAIMING code[J].Electronic Design Engineering, 2015, 23(7): 162-165.
[10] 李康, 张毛毛, 杨忠, 等.基于神经网络的人造板装饰纸表面色泽特征分类研究[J].林业工程学报, 2018, 3(1): 16-20.DOI:10.13360/j.issn.2096-1359.2018.01.003.
LI K, ZHANG M M, YANG Z, et al.Classification for decorative papers of wood-based panels using color and glossiness parameters in combination with neural network method[J].Journal of Forestry Engineering, 2018, 3(1): 16-20.
[11] 邵小东.MDF连续热压机板厚控制液压系统位置跟踪控制研究[D].哈尔滨: 东北林业大学, 2015.
SHAO X D.Study of position tracking control of MDF continuous hot-press plank thickness control hydraulic system[D].Harbin: Northeast Forestry University, 2015.
[12] 孙海云.FMEA在汽车车桥中的应用研究[D].青岛: 青岛理工大学, 2014.
SUN H Y.Application research of FMEA in automobile axle[D].Qingdao: Qingdao Technology University, 2014.
[13] 姚灿江, 魏领会, 王海龙, 等.基于FTA和FMEA的RV减速器可靠性分析[J].现代制造工程, 2018(1): 136-140.DOI: 10.16731/j.cnki.1671-3133.2018.01.026.
YAO C J, WEI L H, WANG H L, et al.Reliability analysis of RV reducer on FTA and FMEA[J].Modern Manufacturing Engineering, 2018(1): 136-140.
[14] SEITI H, HAFEZALKOTOB A, NAJAFI S E, et al.A risk-based fuzzy evidential framework for FMEA analysis under uncertainty: an interval-valued DS approach[J].Journal of Intelligent & Fuzzy Systems, 2018, 35: 1419-1430.DOI: 10.3233/JIFS-169684.
[15] YANG C S, ZOU Y N, LAI P H, et al.Data mining-based methods for fault isolation with validated FMEA model ranking[J].Applied Intelligence, 2015, 43(4): 913-923.DOI: 10.1007/s10489-015-0674-x.
[16] WANG W Z, LIU X W, QIN Y, et al.A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral[J].Safety Science, 2018, 110: 152-163.DOI: 10.1016/j.ssci.2018.08.009.
[17] 武曲.MDF连续平压板厚自动纠偏协同控制研究[D].哈尔滨: 东北林业大学, 2013.
WU Q.Synergetic control for slab thickness deviation rectification of MDF continuous press[D].Harbin: Northeast Forestry University, 2013.

备注/Memo

备注/Memo:
收稿日期:2019-02-14 修回日期:2019-04-09基金项目:国家自然科学基金(31370565)。作者简介:吕云蕾,女,研究方向为模式识别与智能控制。通信作者:黄英来,男,副教授。E-mail:nefuhyl@163.com
更新日期/Last Update: 2019-11-10