Mechanical hydraulic characteristic analysis scheme based on lightweight crowd data in mobile embedded devices
© The Author(s). 2016
Received: 19 May 2016
Accepted: 8 August 2016
Published: 22 August 2016
In order to improve the efficiency of mechanical and hydraulic control of the mechanical equipment, the analysis scheme of mechanical hydraulic characteristics based on lightweight crowd data was proposed in mobile embedded devices. Based on the mobile and embedded machinery equipment, a crowd lightweight data-driven analysis model is proposed to solve the hydraulic mechanical properties of nonlinear filtering with coarse-grained service detection. The engine of the mechanical equipment was connected with the hydraulic control module through the harmonic filter. Based on the output array of hydraulic characteristics and the transmission power of the mobile embedded node, the analysis scheme of mechanical hydraulic characteristics was proposed based on lightweight crowd data in mobile embedded devices. Based on the experiment evaluation result, the hydraulic analysis performance and mechanical equipment support ability of the proposed scheme is better than the static node scheme.
Hydraulic control technology of mechanical equipment has been widely used in mechanical fault detection and robustness protection and so on . How to determine the mechanical hydraulic mechanical transmission system in the structure of the detection scheme ? According to the mechanical condition, setting the parameters of mechanical hydraulic control system and antenna matching is one of the key problems. In the design of mechanical hydraulic control module and the detection node, how to combine the mechanical speed and mechanical equipment working load effectively becomes the main factor that restricts the mechanical power and the economy .
In view of the above problems, a series of research results are obtained. Pattison et al.  reformulated a pyroclastic model to recover hydraulic conductivity with more appropriate fluid-flow boundary conditions. Using an online monitoring system, tests were carried out in article , which could be used to measure the mechanical characteristics of a hydraulic high-voltage circuit breaker. The performance of hydraulic excavator with pump and valve was researched in article , which has been combined separate meter in and meter out circuits. The metaphysics-coupled modeling was proposed and simulated by Bing et al. , which has been used in the hydraulic-operating mechanism for a SF6 high-voltage circuit breaker.
The author of article  provided an in-depth look into how the systems have- or will be changed. An estimator based on the iterated unscented Kalman filter algorithm was proposed to identify model parameters in article . The author in article  presented a fast method for calculating energy savings that would result from installing variable-frequency-drives on the seawater cooling pumps on ships. The distributed generation system managed was proposed by a power converter with reduced number of components . The authors of article  studied the sensor hysteresis modeling with the Preisach model and did the regression analysis with support vector machine.
However, the above research results ignored the relationship of mechanical hydraulic characteristics and system execution efficiency. We proposed the analysis scheme of mechanical hydraulic characteristics based on lightweight crowd data in mobile embedded devices.
2 Lightweight crowd data-driven model
On the analysis network of mobile machinery equipment, we will simplify the machinery and equipment with mobility and embedded technology to solve the problems of hydraulic mechanical properties of nonlinear filtering of coarse-grained service detection.
A crowd lightweight data-driven analysis model with fine-grained characteristics is proposed. The model includes the control protocol of embedded nodes in machinery equipment, the elimination mechanism of interference, the control protocol of transmission power, and the crowd data-driven mechanism.
We assume that the mobile embedded nodes are deployed in a mechanical device with a hop detection signal within the effective sensing radius. The node can sense the hydraulic real-time state of the mechanical equipment. In the characteristic analysis network of the dynamic mechanical equipment, the signal transmission power of the mobile embedded node can be adjusted adaptively according to the size of the crowd data. The effective sensing radius of the mobile embedded node is related to the residual energy of the node. Mobile embedded node adjusts its position and signal transmission power according to the residual energy. When the embedded node forwarding of swarm intelligence data meets the demand characteristic analysis of mechanical hydraulic, adjusting mobile embedded nodes of the perceived distance and signal transmit power, at the edge of the state, achieves lightweight data-driven service push.
Here, E i is the energy consumption of mobile embedded node. S i is the crowd data. M N is the number of mobile crowd nodes. T i is the signal sending power of mobile crowd node. D i is the sending data of mobile embedded node. D ME is the hydraulic characteristic data of mechanical equipment.
3 Mobile embedded machine hydraulic characteristic analysis mechanism
Here, P sending is the transmission power, v sending is the transmission rate, and A HC is the output of the hydraulic characteristics.
Here, S HC represents the weight matrix of hydraulic analysis. E ME represents the efficiency of the hydraulic control system. A antenna represents the antenna array, which can be obtained by differentiating the working time and the maximum power.
4 Performance analysis and verification
Parameter settings of mechanical hydraulic transmission system
Descriptions of system
Weight of mechanical hydraulic transmission system
Speed of transfer
System initialization delay
Air flow rate
Maximum bear weight
Evacuation time of hydraulic pump
Transmission drag coefficient
Motor displacement of hydraulic pump
Parameter settings of mobile embedded node
Descriptions of system
Radio frequency of antenna
Number of antenna
Data frame length
In first experiment, the mobile embedded nodes were deployed in a set of transmission system. The hydraulic analysis performance of the hydraulic drive system is compared with that of the horizontal coordinate.
We studied the three sets of transmission system in the second experiment. The analysis network was composed of three mobile embedded nodes, for studying the hydraulic monitoring time and natural stop transfer ratio, which record the pressure characteristics of the hydraulic system to carry out a comparative analysis of the situation.
Y-axis of Fig. 7 is a natural stop ratio. Figure 7 gives the comparison analytical results of the natural stop ratio based on the mechanical and hydraulic properties of embedded mobile node with mechanical hydraulic characteristic analysis (W-MHCA) and hydraulic characteristic analysis of mechanical transmission system (WO-MHCA). We completed a 100-min test of mechanical transmission system.
Through hydraulic machinery characteristic analysis of embedded mobile node, the situation of hydraulic transmission system could be accurately predicted. The cavities B, C, and D would be adaptively adjusted. The transmission system always maintain the best working condition based on the above issues, which would improve work efficiency and load capacity.
The analysis scheme of mechanical hydraulic characteristics was proposed based on lightweight crowd data in mobile embedded devices to solve the mechanical hydraulic equipment control and improve the efficiency of mechanical work. Firstly, a population intellectual lightweight data-driven analysis model was proposed with the mobile embedded machinery and equipment, which was used to solve the hydraulic mechanical properties of nonlinear filtering of coarse-grained service detection. Secondly, we studied the engine of the mechanical equipment with the hydraulic control module through the harmonic filter. Then, we designed the mobile embedded node by considering the output array of hydraulic characteristics and the transmission power. Based on the above basis, the analysis scheme of mechanical hydraulic characteristics was proposed based on lightweight crowd data in mobile embedded devices. Based on the experiment evaluation result, the hydraulic analysis performance and mechanical equipment support ability of the proposed scheme is better than the static node scheme and without analysis state.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- OH Souza, N Barbieri, AHM Santos, Study of hydraulic transients in hydropower plants through simulation of nonlinear model of penstock and hydraulic turbine model [J]. IEEE Trans. Power Syst. 14(4), 1269–1272 (1999)View ArticleGoogle Scholar
- W Liao, S Chen, C Chen et al., Research of negative flow control characteristics for axial piston pump based on hydraulic and mechanical co-simulation[C]// International Conference on System Science, Engineering Design and Manufacturing Informatization. Chengdu, China, (IEEE Press, 2012), pp. 79–83Google Scholar
- M Noulhiane, S Samson, S Clémenceau et al., High-accuracy range detection radar sensor for hydraulic cylinders [J]. Sensors J. IEEE 14(3), 734–746 (2014)View ArticleGoogle Scholar
- AJ Pattison, M Mcgarry, JB Weaver et al., Spatially-resolved hydraulic conductivity estimation via poroelastic magnetic resonance elastography [J]. IEEE Trans. Med. Imaging 33(6), 1373–80 (2014)View ArticleGoogle Scholar
- C Wang, C Liu, Experimental study of the online monitoring of the mechanical characteristics of a hydraulic high-voltage circuit breaker[C]// International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Changsha, China, (IEEE Press, 2015), pp. 2706–09Google Scholar
- L Ge, Z Dong, W Huang et al., Research on the performance of hydraulic excavator with pump and valve combined separate meter in and meter out circuits[C]// International Conference on Fluid Power and Mechatronics. Harbin, China, (IEEE Press, 2015), pp. 37–41Google Scholar
- B Xu, R Ding, J Zhang et al., Multiphysics-Coupled Modeling: Simulation of the Hydraulic-Operating Mechanism for a SF6 High-Voltage Circuit Breaker[J]. IEEE/ASME Trans. Mechatron. 21, 379–93 (2016)Google Scholar
- B Sarlioglu, CT Morris, More electric aircraft: review, challenges, and opportunities for commercial transport aircraft [J]. IEEE Trans. Transportation Electrification 1(1), 54–64 (2015)View ArticleGoogle Scholar
- H Huang, M Yang, W Zang et al., In vitro identification of four-element windkessel models based on iterated unscented Kalman filter [J]. IEEE Trans. Biomed. Eng. 58(9), 2672–80 (2011)View ArticleGoogle Scholar
- CL Su, WL Chung, KT Yu, An energy-savings evaluation method for variable-frequency-drive applications on ship central cooling systems [J]. IEEE Trans. Ind. Appl. 50(50), 1286–1294 (2014)Google Scholar
- ECD Santos, CB Jacobina, N Rocha et al., Single-phase to three-phase four-leg converter applied to distributed generation system [J]. IET Power Electron. 3(6), 892–903 (2010)View ArticleGoogle Scholar
- C Yang, C Li, The application of support vector machine in the hysteresis modeling of silicon pressure sensor [J]. IEEE Sensors J. 11(9), 2022–2026 (2011)View ArticleGoogle Scholar