Full Text:   <3239>

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CLC number: TP206

On-line Access: 2018-07-02

Received: 2016-10-24

Revision Accepted: 2017-01-27

Crosschecked: 2018-05-10

Cited: 0

Clicked: 6454

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Shu-ting Chen

http://orcid.org/0000-0002-4101-0649

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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.5 P.604-625

http://doi.org/10.1631/FITEE.1601660


An embedded lightweight GUI component library and ergonomics optimization method for industry process monitoring


Author(s):  Da-peng Tan, Shu-ting Chen, Guan-jun Bao, Li-bin Zhang

Affiliation(s):  College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310032, China; more

Corresponding email(s):   shutinren@163.com

Key Words:  Embedded lightweight graphic user interface (GUI), Quasar technology embedded (Qt/E), Industry process monitoring, Multi-thread, Ergonomics performance


Da-peng Tan, Shu-ting Chen, Guan-jun Bao, Li-bin Zhang. An embedded lightweight GUI component library and ergonomics optimization method for industry process monitoring[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(5): 604-625.

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Abstract: 
Developing an efficient and robust lightweight graphic user interface (GUI) for industry process monitoring is always a challenging task. Current implementation methods for embedded GUI are with the matters of real-time processing and ergonomics performance. To address the issue, an embedded lightweight GUI component library design method based on quasar technology embedded (Qt/E) is proposed. First, an entity-relationship (E-R) model for the GUI library is developed to define the functional framework and data coupling relations. Second, a cross-compilation environment is constructed, and the Qt/E shared library files are tailored to satisfy the requirements of embedded target systems. Third, by using the signal-slot communication interfaces, a message mapping mechanism that does not require a call-back pointer is developed, and the context switching performance is improved. According to the multi-thread method, the parallel task processing capabilities for data collection, calculation, and display are enhanced, and the real-time performance and robustness are guaranteed. Finally, the human-computer interaction process is optimized by a scrolling page method, and the ergonomics performance is verified by the industrial psychology methods. Two numerical cases and five industrial experiments show that the proposed method can increase real-time read-write correction ratios by more than 26% and 29%, compared with Windows-CE-GUI and Android-GUI, respectively. The component library can be tailored to 900 KB and supports 12 hardware platforms. The average session switch time can be controlled within 0.6 s and six key indexes for ergonomics are verified by different industrial applications.

面向工业过程监控的嵌入式轻型图形用户界面构件库与人机功效优化方法

摘要:面向工业过程监控的嵌入式轻型图形用户界面(GUI)构件库开发具有较高难度,当前方法在实时任务处理与人机功效等方面存在不足。针对上述问题,提出一种基于嵌入式Qt技术(Qt/E)的轻型GUI构件库设计方法。根据工业过程监控需求,建立构件库实体-关系(E-R)模型,定义系统功能构架与模块数据耦合关系。考虑嵌入式目标系统差异,搭建交叉编译环境以实现Qt/E共享库文件的按需裁剪。基于信号-槽通信接口,提出一种无需回调指针的消息映射方法,优化系统上下文切换性能。结合多线程控制技术,面向数据采集、计算与显示的并行任务处理能力得到强化,从而提高系统实时性与鲁棒性。通过滚动页面方法优化人机交互过程,并利用工业心理学方法验证系统人机功效性能。数值实例模拟与工业现场实验结果表明,与Windows-CE-GUI和Android-GUI相比:实时读写正确率分别提高26%与29%;构件库最小可裁减至900 kB,并可支持12种嵌入式硬件平台;系统平均会话切换时间可控制在0.6 s以内,关键人机功效指标可满足不同工业应用需求。

关键词:嵌入式轻型图形用户界面(GUI);嵌入式Qt技术(Qt/E);工业过程监控;多线程;人机功效

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Acciani G, Fornarelli G, Giaquinto A, 2011. A fuzzy method for global quality index evaluation of solder joints in surface mount technology. IEEE Trans Ind Inform, 7(1):115-124.

[2]Ahn SH, Sul D, Choi SH, et al., 2006. Implementation of lightweight graphic library builder for embedded system. IEEE Int Conf on Advanced Communication Technology, p.166-168.

[3]Barrero F, Toral S, Vargas M, et al., 2010. Internet in the development of future road-traffic control systems. Internet Res, 20(2):154-168.

[4]Cecotti H, 2016. A multimodal gaze-controlled virtual keyboard. IEEE Trans Hum-Mach Syst, 46(4):601-606.

[5]Chen ST, Tan DP, 2018. A SA-ANN-based modeling method for human cognition mechanism and the PSACO cognition algorithm. Complexity, 2018:6264124.

[6]Chevalier A, Kicka M, 2006. Web designers and web users: influence of the ergonomic quality of the web site on the information search. Int J Hum-Comput Stud, 64(10): 1031-1048.

[7]Dalheimer MK, Hansen S, 2002. Embedded systems: embedded development with qt/embedded. Dr Dobbs J, 27(3):48-54.

[8]Drossu R, Obradovic Z, Fletcher J, 1996. A flexible graphical user interface for embedding heterogeneous neural network simulators. IEEE Trans Edu, 39(3):367-374.

[9]Du F, 2008. GUI Design Based on Ergonomics. MS Thesis, Nanjing University of Aeronautics and Astronautics, Nanjing, China (in Chinese).

[10]Ji SM, Xiao FQ, Tan DP, 2010. Analytical method for softness abrasive flow field based on discrete phase model. Sci China Technol Sci, 53(10):2867-2877.

[11]Ji SM, Weng XX, Tan DP, 2012. Analytical method of softness abrasive two-phase flow field based on 2D model of LSM. Acta Phys Sin, 61(1):010205.

[12]Ji SM, Ge JQ, Tan DP, 2017. Wall contact effects of particle-all collision process in a two-phase particle fluid. J Zhejiang Univ-Sci A (Appl Phys & Eng), 18(12):958-973.

[13]Jin F, Wu ZH, 2008. Lightweight graphics device driver and graphical user interface based on embedded Linux. Trans Beijing Inst Technol, 28(3):233-236.

[14]Li C, Ji SM, Tan DP, 2012. Study on machinability and the wall region of solid-liquid two phase softness abrasive flow. Int J Adv Manuf Technol, 61(9-12):975-987.

[15]Li C, Ji SM, Tan DP, 2013. Multiple-loop digital control method for 400Hz inverter system based on phase feedback. IEEE Trans Power Electron, 28(1):408-417.

[16]Li J, Ji SM, Tan DP, 2017. Improved soft abrasive flow finishing method based on turbulent kinetic energy enhancing. Chin J Mech Eng, 30(2):301-309.

[17]Li X, Horie M, Kagawa T, 2014. Pressure-distribution methods for estimating lifting force of a swirl gripper. IEEE/ASME Trans Mechatron, 19(2):707-718.

[18]Li X, Li N, Tao GL, 2015. Experimental comparison of Bernoulli gripper and vortex gripper. Int J Prec Eng Manuf, 16(10):2081-2090.

[19]Liao YX, Li X, Zhong W, et al., 2016. Study of pressure drop-flow rate and flow resistance characteristics of heated porous materials under local thermal non-equilibrium conditions. Int J Heat Mass Transf, 102:528-543.

[20]Lin ZS, Yu SM, Lu JH, 2015. Design and ARM-embedded implementation of a chaotic map-based real-time secure video communication system. IEEE Trans Circ Syst Video Technol, 25(7):1203-1216.

[21]Mazzei D, Vozzi F, Cisternino A, et al., 2008. A high-throughput bioreactor system for simulating physiological environments. IEEE Trans Ind Electron, 55(9):3273-3280.

[22]Park J, Lee J, 2011. A beacon color code scheduling for the localization of multiple robots. IEEE Trans Ind Inform, 7(3):467-475.

[23]Ramos MA, Penteado RAD, 2008. Embedded software revitalization through component mining and software product line techniques. J Univ Comput Sci, 14(8):1207-1227.

[24]Rehault F, 2010. Windows mobile advanced forensics: an alternative to existing tools. Dig Invest, 7(1-2):38-47.

[25]Riskedal E, 2008. Qt and Windows CE. Dr Dobbs J, 33(6): 30-45.

[26]Saponara S, Petri E, Fanucci L, et al., 2011. Sensor modeling, low-complexity fusion algorithms, and mixed-signal IC prototyping for gas measures in low-emission vehicles. IEEE Trans Instrum Meas, 60(2):372-384.

[27]Steblovnik K, Zazula D, 2011. A novel agent-based concept of household appliances. J Intell Manuf, 22(1):73-88.

[28]Su LJ, Zheng NG, Yao M, et al., 2014. A computational model of the hybrid bio-machine MPMS for ratbots navigation. IEEE Intell Syst, 29(6):5-13.

[29]Tan DP, Zhang LB, 2014. A WP-based nonlinear vibration sensing method for invisible liquid steel slag detection. Sensor Actuat B Chem, 202:1257-1269.

[30]Tan DP, Ji SM, Li PY, et al., 2010. Development of vibration style ladle slag detection method and the key technologies. Sci China Technol Sci, 53(9):2378-2387.

[31]Tan DP, Ji SM, Jin MS, 2013a. Intelligent computer-aided instruction modeling and a method to optimize study strategies for parallel robot instruction. IEEE Trans Edu, 56(3):268-273.

[32]Tan DP, Li PY, Ji YX, et al., 2013b. SA-ANN-based slag carry-over detection method and the embedded WME platform. IEEE Trans Ind Electron, 60(10):4702-4713.

[33]Tan DP, Ji SM, Fu YZ, 2016a. An improved soft abrasive flow finishing method based on fluid collision theory. Int J Adv Manuf Technol, 85(5-8):1261-1274.

[34]Tan DP, Yang T, Zhao J, et al., 2016b. Free sink vortex Ekman suction-extraction evolution mechanism. Acta Phys Sin, 65(5):054701.

[35]Tan DP, Zhang LB, Ai QL, 2016c. An embedded self-adapting network service framework for networked manufacturing system. J Intell Manuf, in press.

[36]Tan DP, Li L, Zhu YL, et al., 2017a. An embedded cloud database service method for distributed industry monitoring. IEEE Trans Ind Inform, in press.

[37]Tan DP, Ni YS, Zhang LB, 2017b. Two-phase sink vortex suction mechanism and penetration dynamic characteristics in ladle teeming process. J Iron Steel Res Int, 24(7): 669-677.

[38]Veltcheva AD, Soares CG, 2012. Analysis of abnormal wave groups in Hurricane Camille by the Hilbert Huang transform method. Ocean Eng, 42:102-111.

[39]Wang J, Li DJ, Yang CJ, et al., 2015. Developing a power monitoring and protection system for the junction boxes of an experimental seafloor observatory network. Front Inform Technol Electron Eng, 16(12):1034-1045.

[40]Wu ZH, Zheng NG, Zhang SW, et al., 2016. Maze learning by a hybrid brain-computer system. Sci Rep, 6:31746.

[41]Wulf V, Pipek V, Won M, 2008. Component-based tailorability: enabling highly flexible software applications. Int J Hum Comput Stud, 66(1):1-22.

[42]Xu LD, Viriyasitavat W, Ruchikachorn P, et al., 2012. Using propositional logic for requirements verification of service workflow. IEEE Trans Ind Inform, 8(3):639-646.

[43]Yao MQ, Yang K, Xu CY, et al., 2015. Design of a novel RTD-based three-variable universal logic gate. Front Inform Technol Electron Eng, 16(8):694-699.

[44]Yin S, Wang G, Gao H, 2015. Data-driven process monitoring based on modified orthogonal projections to latent structures. IEEE Trans Contr Syst Technol, 24(4):1480-1487.

[45]Zeng X, Ji SM, Tan DP, et al., 2013. Softness consolidation abrasives material removal characteristic oriented to laser hardening surface. Int J Adv Manuf Technol, 69(9-12): 2323-2332.

[46]Zeng X, Ji SM, Jin MS, et al., 2016. Research on dynamic characteristic of softness consolidation abrasives in machining process. Int J Adv Manuf Technol, 82(5-8):1115-1125.

[47]Zhang K, Kang JU, 2011. Real-time numerical dispersion compensation using graphics processing unit for Fourier-domain optical coherence tomography. Electron Lett, 47(5):309-310.

[48]Zhang M, Jiang JZ, Liu CH, 2013. Development of a multi-function gateway node oriented environment monitoring in greenhouse. Sens Lett, 11(6-7):1236-1239.

[49]Zheng NG, Wu Z, Lin M, et al., 2010a. Enhancing battery efficiency for pervasive health-monitoring systems based on electronic textiles. IEEE Trans Inform Technol Biomed, 14(2):350-359.

[50]Zheng NG, Wu ZH, Lin M, et al., 2010b. Infrastructure and reliability analysis of electric networks for E-textiles. IEEE Trans Syst Man Cybern Part C, 40(1):36-51.

[51]Zheng NG, Su LJ, Zhang DQ, et al., 2015. A computational model for ratbot locomotion based on cyborg intelligence. Neurocomputing, 170(C):92-97.

[52]Zhou HJ, Xiang R, 2013. MicroWindows-based multi-device support intelligent Chinese input system. J Comput Appl, 33(7):2067-2070.

[53]Zhuo XF, Fan JB, Chen B, 2002. Application of Linux multilineality in GUI programming. J Southwest Univ Sci Technol, 17(3):21-24.

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