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Guixiong Liu
School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, People’s Republic of China

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Article
Published: 23 November 2019 in Advances in Manufacturing
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Currently, direct braking-force measurement under dynamic conditions requires a considerable modification to the vehicles and has poor compatibility because there are many types of vehicles. Thus, in this paper, an indirect measurement method of new-energy vehicles’ braking force under dynamic braking conditions is proposed. The mechanical wheel and axle model at low/idling/high speeds is established using the piston-pressure formula, force transfer in the brake-wheel cylinder, relative movement between the wheel and the roller, among others. On this basis, the relationship between wheel braking force and roller-linear acceleration is further derived. Our method does not alter existing vehicle structures or sensor types. The standard sealing bolt is temporarily replaced with a hydraulic sensor for coefficient calibration. Afterward, the braking force can be indirectly calculated using the roller-linear velocity data. The method has characteristics of efficiency and high accuracy without refitting vehicles.

ACS Style

Sen-Ming Zhong; Gui-Xiong Liu; Jia-Jian Wu; Bo Zeng. Indirect measurement technology of new energy vehicles’ braking force under dynamic braking conditions. Advances in Manufacturing 2019, 7, 389 -400.

AMA Style

Sen-Ming Zhong, Gui-Xiong Liu, Jia-Jian Wu, Bo Zeng. Indirect measurement technology of new energy vehicles’ braking force under dynamic braking conditions. Advances in Manufacturing. 2019; 7 (4):389-400.

Chicago/Turabian Style

Sen-Ming Zhong; Gui-Xiong Liu; Jia-Jian Wu; Bo Zeng. 2019. "Indirect measurement technology of new energy vehicles’ braking force under dynamic braking conditions." Advances in Manufacturing 7, no. 4: 389-400.

Journal article
Published: 01 September 2019 in Symmetry
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In recent years, electromagnetic interference (EMI) of new energy vehicles, including difference mode symmetric interference and common mode asymmetry interference, has attracted the attention of many scholars. So far, EMI tests for new energy vehicles under steady conditions cannot reflect the actual EMI of the running vehicle. The results of EMI test methods based on fast Fourier transform (FFT) under dynamic conditions have worse frequency resolutions, and frequency/amplitude accuracy has low precision. Therefore, this paper proposes an EMI test method based on FFT and dot frequency scanning (DFS) for new energy vehicles under dynamic conditions. The identification method for accelerating, sliding, and braking conditions is studied. A comprehensive EMI key evaluation index system for new energy vehicles is built, including characteristic points with maximum amplitude, area, ratio, and density coefficients for high-amplitude characteristic points. Among them, the maximum amplitude is an index to evaluate extreme values. The ratio of high-amplitude characteristic points is a comprehensive index to evaluate the overall region. The density coefficient is an index to evaluate the local region. Finally, this method is applied to three vehicles. With the same instruments, by reducing the FFT frequency span, the frequency resolution and frequency accuracy increase. The results indicate that the EMI of new energy vehicles can be tested under dynamic conditions with high accuracy according to the operable evaluation indexes.

ACS Style

Guixiong Liu; Senming Zhong; Liu. Research on an Electromagnetic Interference Test Method Based on Fast Fourier Transform and Dot Frequency Scanning for New Energy Vehicles under Dynamic Conditions. Symmetry 2019, 11, 1092 .

AMA Style

Guixiong Liu, Senming Zhong, Liu. Research on an Electromagnetic Interference Test Method Based on Fast Fourier Transform and Dot Frequency Scanning for New Energy Vehicles under Dynamic Conditions. Symmetry. 2019; 11 (9):1092.

Chicago/Turabian Style

Guixiong Liu; Senming Zhong; Liu. 2019. "Research on an Electromagnetic Interference Test Method Based on Fast Fourier Transform and Dot Frequency Scanning for New Energy Vehicles under Dynamic Conditions." Symmetry 11, no. 9: 1092.

Journal article
Published: 03 August 2019 in Symmetry
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Chassis assembly quality is a necessary step to improve product quality and yield. In recent years, with the continuous expansion of deep learning method, its application in product quality detection is increasingly extensive. The current limitations and shortcomings of existing quality detection methods and the feasibility of improving the deep learning method in quality detection are presented and discussed in this paper. According to the characteristics of numerous parts and complex types of chassis assembly components, a method for chassis assembly detection and identification based on deep learning component segmentation is proposed. In the proposed method, assembly quality detection is first performed using the Mask regional convolutional neural network component instance segmentation method, which reduces the influence of complex illumination conditions and background detection. Next, a standard dictionary of chassis assembly is built, which is connected with Mask R-CNN in a cascading way. The component mask is obtained through the detection result, and the component category and assembly quality information is extracted to realize chassis assembly detection and identification. To evaluate the proposed method, an industrial assembly chassis was used to create datasets, and the method is effective in limited data sets of industrial assembly chassis. The experimental results indicate that the accuracy of the proposed method can reach 93.7%. Overall, the deep learning method realizes complete automation of chassis assembly detection.

ACS Style

Guixiong Liu; Binyuan He; Siyuang Liu; Jian Huang. Chassis Assembly Detection and Identification Based on Deep Learning Component Instance Segmentation. Symmetry 2019, 11, 1001 .

AMA Style

Guixiong Liu, Binyuan He, Siyuang Liu, Jian Huang. Chassis Assembly Detection and Identification Based on Deep Learning Component Instance Segmentation. Symmetry. 2019; 11 (8):1001.

Chicago/Turabian Style

Guixiong Liu; Binyuan He; Siyuang Liu; Jian Huang. 2019. "Chassis Assembly Detection and Identification Based on Deep Learning Component Instance Segmentation." Symmetry 11, no. 8: 1001.

Journal article
Published: 16 May 2019 in Symmetry
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Image deblurring can improve visual quality and mitigates motion blur for dynamic visual inspection. We propose a method to deblur saturated images for dynamic visual inspection by applying blur kernel estimation and deconvolution modeling. The blur kernel is estimated in a transform domain, whereas the deconvolution model is decoupled into deblurring and denoising stages via variable splitting. Deblurring predicts the mask specifying saturated pixels, which are then discarded, and denoising is learned via the fast and flexible denoising network (FFDNet) convolutional neural network (CNN) at a wide range of noise levels. Hence, the proposed deconvolution model provides the benefits of both model optimization and deep learning. Experiments demonstrate that the proposed method suitably restores visual quality and outperforms existing approaches with good score improvements.

ACS Style

Bodi Wang; Guixiong Liu; Junfang Wu; Wang; Liu; Wu. Blind Deblurring of Saturated Images Based on Optimization and Deep Learning for Dynamic Visual Inspection on the Assembly Line. Symmetry 2019, 11, 678 .

AMA Style

Bodi Wang, Guixiong Liu, Junfang Wu, Wang, Liu, Wu. Blind Deblurring of Saturated Images Based on Optimization and Deep Learning for Dynamic Visual Inspection on the Assembly Line. Symmetry. 2019; 11 (5):678.

Chicago/Turabian Style

Bodi Wang; Guixiong Liu; Junfang Wu; Wang; Liu; Wu. 2019. "Blind Deblurring of Saturated Images Based on Optimization and Deep Learning for Dynamic Visual Inspection on the Assembly Line." Symmetry 11, no. 5: 678.

Journal article
Published: 05 May 2019 in Electronics
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Multidirected acyclic graph (DAG) workflow scheduling is a key problem in the heterogeneous distributed environment in the distributed computing field. A hierarchical heterogeneous multi-DAG workflow problem (HHMDP) was proposed based on the different signal processing workflows produced by different grouping and scanning modes and their hierarchical processing in specific functional signal processing modules in a multigroup scan ultrasonic phased array (UPA) system. A heterogeneous predecessor earliest finish time (HPEFT) algorithm with predecessor pointer adjustment was proposed based on the improved heterogeneous earliest finish time (HEFT) algorithm. The experimental results denote that HPEFT reduces the makespan, ratio of the idle time slot (RITS), and missed deadline rate (MDR) by 3.87–57.68%, 0–6.53%, and 13–58%, respectively, and increases relative relaxation with respect to the deadline (RLD) by 2.27–8.58%, improving the frame rate and resource utilization and reducing the probability of exceeding the real-time period. The multigroup UPA instrument architecture in multi-DAG signal processing flow was also provided. By simulating and verifying the scheduling algorithm, the architecture and the HPEFT algorithm is proved to coordinate the order of each group of signal processing tasks for improving the instrument performance.

ACS Style

Yuzhong Li; Wenming Tang; Guixiong Liu. HPEFT for Hierarchical Heterogeneous Multi-DAG in a Multigroup Scan UPA System. Electronics 2019, 8, 498 .

AMA Style

Yuzhong Li, Wenming Tang, Guixiong Liu. HPEFT for Hierarchical Heterogeneous Multi-DAG in a Multigroup Scan UPA System. Electronics. 2019; 8 (5):498.

Chicago/Turabian Style

Yuzhong Li; Wenming Tang; Guixiong Liu. 2019. "HPEFT for Hierarchical Heterogeneous Multi-DAG in a Multigroup Scan UPA System." Electronics 8, no. 5: 498.

Journal article
Published: 21 February 2019 in Sensors
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Multi-group scanning of ultrasonic phased arrays (UPAs) is a research field in distributed sensor technology. Interpolation filters intended for fine delay modules can provide high-accuracy time delays during the multi-group scanning of large-number-array elements in UPA instruments. However, increasing focus precision requires a large increase in the number of fine delay modules. In this paper, an architecture with fine delay modules for time division scheduling is explained in detail. An improved bound fit (IBF) algorithm is proposed, and an analysis of its mathematical model and time complexity is provided. The IBF algorithm was verified by experiment, wherein the performances of list, longest processing time, bound fit, and IBF algorithms were compared in terms of frame data scheduling in the multi-group scan. The experimental results prove that the scheduling algorithm decreased the makespan by 8.76–21.48%, and achieved the frame rate at 78 fps. The architecture reduced resource consumption by 30–40%. Therefore, the proposed architecture, model, and algorithm can reduce makespan, improve real-time performance, and decrease resource consumption.

ACS Style

Yuzhong Li; Wenming Tang; Guixiong Liu. Improved Bound Fit Algorithm for Fine Delay Scheduling in a Multi-Group Scan of Ultrasonic Phased Arrays. Sensors 2019, 19, 906 .

AMA Style

Yuzhong Li, Wenming Tang, Guixiong Liu. Improved Bound Fit Algorithm for Fine Delay Scheduling in a Multi-Group Scan of Ultrasonic Phased Arrays. Sensors. 2019; 19 (4):906.

Chicago/Turabian Style

Yuzhong Li; Wenming Tang; Guixiong Liu. 2019. "Improved Bound Fit Algorithm for Fine Delay Scheduling in a Multi-Group Scan of Ultrasonic Phased Arrays." Sensors 19, no. 4: 906.

Journal article
Published: 16 October 2017 in Sensors
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High data transmission efficiency is a key requirement for an ultrasonic phased array with multi-group ultrasonic sensors. Here, a novel FIFOs scheduling algorithm was proposed and the data transmission efficiency with hardware technology was improved. This algorithm includes FIFOs as caches for the ultrasonic scanning data obtained from the sensors with the output data in a bandwidth-sharing way, on the basis of which an optimal length ratio of all the FIFOs is achieved, allowing the reading operations to be switched among all the FIFOs without time slot waiting. Therefore, this algorithm enhances the utilization ratio of the reading bandwidth resources so as to obtain higher efficiency than the traditional scheduling algorithms. The reliability and validity of the algorithm are substantiated after its implementation in the field programmable gate array (FPGA) technology, and the bandwidth utilization ratio and the real-time performance of the ultrasonic phased array are enhanced.

ACS Style

Wenming Tang; Guixiong Liu; Yuzhong Li; Daji Tan. An Improved Scheduling Algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors. Sensors 2017, 17, 2355 .

AMA Style

Wenming Tang, Guixiong Liu, Yuzhong Li, Daji Tan. An Improved Scheduling Algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors. Sensors. 2017; 17 (10):2355.

Chicago/Turabian Style

Wenming Tang; Guixiong Liu; Yuzhong Li; Daji Tan. 2017. "An Improved Scheduling Algorithm for Data Transmission in Ultrasonic Phased Arrays with Multi-Group Ultrasonic Sensors." Sensors 17, no. 10: 2355.

Journal article
Published: 26 April 2016 in Frontiers of Mechanical Engineering
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The identification of targets varies in different surge tests. A multi-color space threshold segmentation and self-learning k-nearest neighbor algorithm (k-NN) for equipment under test status identification was proposed after using feature matching to identify equipment status had to train new patterns every time before testing. First, color space (L*a*b*, hue saturation lightness (HSL), hue saturation value (HSV)) to segment was selected according to the high luminance points ratio and white luminance points ratio of the image. Second, the unknown class sample S r was classified by the k-NN algorithm with training set T z according to the feature vector, which was formed from number of pixels, eccentricity ratio, compactness ratio, and Euler’s numbers. Last, while the classification confidence coefficient equaled k, made S r as one sample of pre-training set T z ′. The training set T z increased to T z+1 by T z if T z was saturated. In nine series of illuminant, indicator light, screen, and disturbances samples (a total of 21600 frames), the algorithm had a 98.65%identification accuracy, also selected five groups of samples to enlarge the training set from T 0 to T 5 by itself.

ACS Style

Jian Huang; Gui-Xiong Liu. Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification. Frontiers of Mechanical Engineering 2016, 11, 311 -315.

AMA Style

Jian Huang, Gui-Xiong Liu. Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification. Frontiers of Mechanical Engineering. 2016; 11 (3):311-315.

Chicago/Turabian Style

Jian Huang; Gui-Xiong Liu. 2016. "Multi-color space threshold segmentation and self-learning k-NN algorithm for surge test EUT status identification." Frontiers of Mechanical Engineering 11, no. 3: 311-315.

Journal article
Published: 23 January 2015 in Energies
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Direct Current (DC) electrical resistivity is a material property that is sensitive to temperature changes. In this paper, the relationship between resistivity and local temperature inside steel shell battery cells (two commercial 10 Ah and 4.5 Ah lithium-ion cells) is innovatively studied by Electrical Resistance Tomography (ERT). The Schlumberger configuration in ERT is applied to divide the cell body into several blocks distributed in different levels, where the apparent resistivities are measured by multi-electrode surface probes. The investigated temperature ranges from −20 to 80 °C. Experimental results have shown that the resistivities mainly depend on temperature changes in each block of the two cells used and the function of the resistivity and temperature can be fitted to the ERT-measurement results in the logistical-plot. Subsequently, the dependence of resistivity on the state of charge (SOC) is investigated, and the SOC range of 70%–100% has a remarkable impact on the resistivity at low temperatures. The proposed approach under a thermal cool down regime is demonstrated to monitor the local transient temperature.

ACS Style

Xiaobin Hong; Nianzhi Li; Jinheng Feng; Qingzhao Kong; Guixiong Liu. Multi-Electrode Resistivity Probe for Investigation of Local Temperature Inside Metal Shell Battery Cells via Resistivity: Experiments and Evaluation of Electrical Resistance Tomography. Energies 2015, 8, 742 -764.

AMA Style

Xiaobin Hong, Nianzhi Li, Jinheng Feng, Qingzhao Kong, Guixiong Liu. Multi-Electrode Resistivity Probe for Investigation of Local Temperature Inside Metal Shell Battery Cells via Resistivity: Experiments and Evaluation of Electrical Resistance Tomography. Energies. 2015; 8 (2):742-764.

Chicago/Turabian Style

Xiaobin Hong; Nianzhi Li; Jinheng Feng; Qingzhao Kong; Guixiong Liu. 2015. "Multi-Electrode Resistivity Probe for Investigation of Local Temperature Inside Metal Shell Battery Cells via Resistivity: Experiments and Evaluation of Electrical Resistance Tomography." Energies 8, no. 2: 742-764.

Journal article
Published: 15 February 2012 in Procedia Engineering
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In order to improve the self-recognition capability of the IEEE 1451 smart sensor and enhance the level of sensor's intelligence and application flexibility, this paper presents a SPWD (sorting pulse width difference) based IEEE 1451.2 smart sensor self-recognition mechanism. The mechanism realizes baud rate self-adaption of IEEE 1451.2 serial interface first adopting the SPWD method. It also utilizes TEDS (transducer electronic data sheet) definition and configuration technique and virtual TEDS parsing algorithm to achieve smart sensor self-recognition. Then, an IEEE 1451 smart weighing sensor system is constructed using this mechanism and its self-recognition properties are tested. The experiment results show that, when the baud rate is 28800 bit/s, SPWD based IEEE 1451.2 smart sensor's recognition rate is 99.07% and its average recognition time is 1.20 s.

ACS Style

Guixiong Liu; Gengxin Chen; Yuebin Zhou. SPWD Based IEEE 1451.2 Smart Sensor Self-Recognition Mechanism and Realization. Procedia Engineering 2012, 29, 2501 -2505.

AMA Style

Guixiong Liu, Gengxin Chen, Yuebin Zhou. SPWD Based IEEE 1451.2 Smart Sensor Self-Recognition Mechanism and Realization. Procedia Engineering. 2012; 29 ():2501-2505.

Chicago/Turabian Style

Guixiong Liu; Gengxin Chen; Yuebin Zhou. 2012. "SPWD Based IEEE 1451.2 Smart Sensor Self-Recognition Mechanism and Realization." Procedia Engineering 29, no. : 2501-2505.

Book chapter
Published: 01 January 2012 in Advances in Intelligent and Soft Computing
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IEEE1451.5 standard standardizes wireless communication modes and data formats of intelligent sensor such as Blue Tooth, WiFi, Zigbee. Networked Intelligent Sensor is designed based on IEEE 1451.5, using low power consumption MSP430F2410 as the core of the signal data acquisition and processing and TEDS data storage, ZigBee-based chip CC2530 realize wireless data communication between STIM to NCAP, and implement plug and play function of network intelligent sensor finally by the LabVIEW. Using it for gas flow measurement and which have been achieved satisfying test results.

ACS Style

Jiang Shifen; Liu Guixiong. Design of Networked Intelligent Sensor Module Based on IEEE1451.5. Advances in Intelligent and Soft Computing 2012, 627 -633.

AMA Style

Jiang Shifen, Liu Guixiong. Design of Networked Intelligent Sensor Module Based on IEEE1451.5. Advances in Intelligent and Soft Computing. 2012; ():627-633.

Chicago/Turabian Style

Jiang Shifen; Liu Guixiong. 2012. "Design of Networked Intelligent Sensor Module Based on IEEE1451.5." Advances in Intelligent and Soft Computing , no. : 627-633.

Book chapter
Published: 01 January 2012 in Advances in Intelligent and Soft Computing
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The paper puts forward an embedded voice inquiry experimental platform which is practiced on the Internet of things. With the high-performance chip STM32 as its main control chip and together with wireless communication module Q2687, the platform controls the module of measurement and utilizes GSM network to realize the function of sending measurement data by playing voice in specific telephone. It doesn’t need background system to realize functions of alarming and remote temperature and humidity inquiring with voice. It is characterized with its small volume, low cost, low-power dissipation and easy utilization. The result of the test shows that the platform is stable and has good compatibility and practicality. As an experimental and educational platform for IOT technology and embedded technology, it has high application value.

ACS Style

Songbin Zhou; Guixiong Liu; Chuanglu Lin. An Embedded Voice Inquiry Experimental Platform for Temperature and Humidity Measurement on the Internet of Things. Advances in Intelligent and Soft Computing 2012, 533 -539.

AMA Style

Songbin Zhou, Guixiong Liu, Chuanglu Lin. An Embedded Voice Inquiry Experimental Platform for Temperature and Humidity Measurement on the Internet of Things. Advances in Intelligent and Soft Computing. 2012; ():533-539.

Chicago/Turabian Style

Songbin Zhou; Guixiong Liu; Chuanglu Lin. 2012. "An Embedded Voice Inquiry Experimental Platform for Temperature and Humidity Measurement on the Internet of Things." Advances in Intelligent and Soft Computing , no. : 533-539.

Book chapter
Published: 01 January 2012 in Advances in Intelligent and Soft Computing
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This paper aims to clarify the information flow for the vehicles operating safety states monitoring (VOSM) system and optimize VOSM system performance. Based on analyzing VOSM system structure and information sequence, the information model for VOSM system is built by automata theory. The relationship among three key parameters including vehicle’s motion attitude parameter (MAP), dynamic load parameter (DLP) and braking performance parameter (BPP) is analyzed and described in this paper. The results indicate that VOSM system model based on automata can effectively describe VOSM system information sequence, and reflects the process of the system state change. Through the model, it will be able to achieve intelligent scheduling in VOSM system, and provide theory basis and reference model for future development and optimization work.

ACS Style

Jianlong Xu; Guixiong Liu; Yi Gao. Vehicle Operating Safe State Monitoring System Modeling Method Based on Automata. Advances in Intelligent and Soft Computing 2012, 369 -376.

AMA Style

Jianlong Xu, Guixiong Liu, Yi Gao. Vehicle Operating Safe State Monitoring System Modeling Method Based on Automata. Advances in Intelligent and Soft Computing. 2012; ():369-376.

Chicago/Turabian Style

Jianlong Xu; Guixiong Liu; Yi Gao. 2012. "Vehicle Operating Safe State Monitoring System Modeling Method Based on Automata." Advances in Intelligent and Soft Computing , no. : 369-376.