基于特征映射平面的塔机塔身钢结构损伤快速识别方法

摘要
图/表
参考文献(15)
相关文章 (15)

全文: PDF (1623 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要为有效地提高塔机运行状态在线监测效率，提出一种塔机塔身损伤状态快速判别方法。构建塔身不同损伤位置组合状态下的塔机结构，并采集恒定载荷工况各损伤状态下的塔机回转一周时的塔身顶端空间位置数据集；将空间位置数据进行3个弦函数和拟合，提取拟合得到的正弦函数的幅值、频率、相位等特征向量集；将各损伤状态在x轴和y轴方向上拟合的特征向量集作为三角形顶点构建特征平面集，并以完好状态下的特征平面作为参考平面，计算其他平面与参考平面在两坐标轴方向的夹角；采用夹角值作为损伤状态评判依据，并将各状态对应的夹角值映射到平面内，对损伤结果进行可视化处理。采用该方法对塔机实体模型和物理模型状态数据进行分析，验证了该算法在塔机塔身损伤状态识别上的快速、有效性。
关键词：塔机塔身；损伤状态判别；角度；特征映射平面

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	杨蕊1
	宋世军1
	宋连玉2
	安增辉1
	臧泓源1
	张会敏3

关键词 ：塔机塔身, 损伤状态判别, 角度, 特征映射平面

Abstract：A fast-discriminating method of tower crane damage state was proposed for effectively improving the online monitoring efficiency of tower crane running state. The tower crane structures under the combination of different damage positions of the tower were constructed, and the spatial position data sets of the tower top when the tower crane rotates once under the condition of constant load were collected. The spatial position data were fitted with the sum of 3 sinusoidal functions, and the amplitude, frequency, phase and other feature vector sets of the sine function obtained by fitting were extracted. The feature vector sets in the X-axis and Y-axis directions under each damage state were used as triangle vertices to construct the feature plane set. The characteristic plane in good condition was taken as the reference plane, and the Angle between other planes and the reference plane in the direction of two coordinate axes was calculated. Angle values were used to construct the point cloud images of each state in the plane, which was used as the basis for damage state evaluation. The mapping relationship between damage state and single feature point established in this paper provides a fast and reliable basis for tower crane state identification.
Key words: Tower crane; Damage state discrimination; Angle; Feature mapping plane

Key words： Tower crane Damage state discrimination Angle Feature mapping plane

收稿日期: 2021-09-17 出版日期: 2022-12-15

引用本文:

杨蕊1,宋世军1,宋连玉2,安增辉1,臧泓源1,张会敏3. 基于特征映射平面的塔机塔身钢结构损伤快速识别方法[J]. 振动与冲击, 2022, 41(23): 315-321.
YANG Rui1, SONG Shijun1, SONG Lianyu2, AN Zenghui1, ZANG Hongyuan1, ZHANG Huimin3. Fast damage identification method of tower crane steel structure based on feature mapping plane. JOURNAL OF VIBRATION AND SHOCK, 2022, 41(23): 315-321.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2022/V41/I23/315

[1] ZHANG N Q, YU M, ZHANG X, FU J, WU H S. Enhancing Tower Crane Safety Using Condition Monitoring System [J]. Applied Mechanics and Materials, 2013, 418: 80-83.
[2] 朱小丰, 周桦,胡健锋. 塔式起重机塔身失效研究[J]. 科学与财富, 2014, 6: 28-28.
ZHU Xiao-feng, ZHOU Hua, HU Jian-feng. Study on Tower Body Failure of Tower Crane [J]. Science and Wealth, 2014, 6: 28-28.
[3] 虞江波. 起重机械事故风险因素分析和安全管理探讨[J]. 智能城市, 2020, 006 (009): 88-89.
YU Jiang-bo. Analysis on Risk Factors of Crane Accidents and Discussion on Safety Management [J]. Smart City, 2020, 006 (009): 88-89.
[4] 陶蓉, 关哲. 塔式起重机安全装置功能分析[J]. 智慧时代, 2016, 03X: 231.
TAO Rong, GUAN Zhe. Functional Analysis of Safety Device of Tower Crane[J]. Age of wisdom, 2016, 03X: 231.
[5] 张伟. 钢结构焊缝超声探伤检测方法及缺陷评定[J]. 质量探索, 2013, 3: 43-44.
ZHANG Wei. Ultrasonic Flaw Detection Method and Defect Evaluation of Steel Structure Welds [J]. Quality Exploration, 2013, 3: 43-44.
[6] RAGHAVAN A C, CESNIK C. Review of Guided-Wave Structural Health Monitoring[J]. Shock and Vibration Digest, 2007, 39 (2): 91-114.
[7] 张健奎, 王宁, 卢萍, 简克彬. 辨识振动环境中两点螺栓连接状态的REE声发射指标[J]. 振动与冲击, 2013, (08): 179-182.
ZHANG Jian-kui, WANG Ning, LU Ping, JIAN Ke-bin. REE Acoustic Emission Index for Identifying the State of Two-point Bolt Connection in Vibration Environment[J]. Vibration and Shock, 2013, (08): 179-182.
[8] WILLBERG C, DUCZEK. Simulation Methods for Guided Wave-Based Structural Health Monitoring[J]. Applied Mechanics Reviews: An Assessment of the World Literature in Engineering ences, 2015, 67(1/6):010803-1.
[9] 聂彦平, 毛崎波,张炜. 基于曲率模态与柔度曲率的损伤识别[J]. 机械研究与应用, 2012, 002: 19-21.
NIE Yan-ping, MAO Qi-bo, ZHANG Wei. Damage Identification based on Curvature Mode and Flexibility Curvature[J]. Mechanical Research and Application, 2012, 002: 19-21.
[10] 王新刚, 杨禄杰, 张鑫垚,马瑞敏. 基于刚度退化的振动传递路径系统的可靠性分析[J]. 振动与冲击, 2020, 39, (20): 266-273.
WANG Xin-gang, YANG Lu-jie, ZHANG Xin-yao, MA Rui-min. Reliability Analysis of Vibration Transmission Path System based on Stiffness Degradation[J]. Vibration and Shock, 2020, 39, (20): 266-273.
[11] 杨斌, 程军圣. 基于振动传递率函数和奇异值熵的结构损伤检测方法[J]. 中国机械工程, 2013, 24 (017): 2382-2385.
YANG Bin, CHENG Jun-sheng. Structural Damage Detection Method based on Vibration Transfer Rate Function and Singular Value Entropy [J]. China Mechanical Engineering, 2013, 24 (017): 2382-2385.
[12] 熊仲明, 王超, 林涛. 基于神经网络的大跨钢结构缺陷损伤的定位研究[J]. 振动与冲击, 2011, (09): 198-203.
XIONG Zhong-ming, WANG Chao, LIN Tao. Research on Defect Damage Location of Long-span Steel Structure based on Neural Network[J]. Vibration and Shock, 2011, (09): 198-203.
[13] 李西平, 谷立臣, 寇雪芹. 基于超声时序神经网络目标识别的塔机安全预警[J]. 中国机械工程, 2016, 27 (016): 2190-2195.
LI Xi-ping. GU Li-chen, KOU Xue-qin. Tower Crane Safety Early Warning based on Ultrasonic Time Series Neural Network Target Recognition [J]. China Mechanical Engineering, 2016, 27 (016): 2190-2195.
[14] 张会敏，宋世军. 基于图谱特征的塔式起重机塔身损伤判断方法研究[J]. 中国工程机械学报, 2021, 19 (3): 268-272.
ZHANG Hui-min, SONG Shi-jun. Research on Damage Judgment Method of Tower Crane Body based on Spectrum Characteristics[J]. Chinese Journal of Construction Machinery, 2021, 19 (3): 268-272.
[15] 张会敏. 基于图谱特征的塔身结构损伤诊断模型研究 [D]. 山东建筑大学, 2016: 9-16.
ZHANG Hui-min. Research on damage diagnosis model of tower structure based on spectrum characteristics [D]. Shandong jianzhu university, 2016: 9-16.