DC-inverter split air-conditioner is widely used in Chinese homes as a result of its high-efficiency and energy-saving. Recently, the researches on its outdoor unit have focused on the influence of surrounding structu...DC-inverter split air-conditioner is widely used in Chinese homes as a result of its high-efficiency and energy-saving. Recently, the researches on its outdoor unit have focused on the influence of surrounding structures upon the aerodynamic and acoustic performance, however they are only limited to the influence of a few parameters on the performance, and practical design of the unit requires more detailed parametric analysis. Three-dimensional computational fluid dynamics（CFD） and computational aerodynamic acoustics（CAA） simulation based on FLUENT solver is used to study the influence of surrounding structures upon the aforementioned properties of the unit. The flow rate and sound pressure level are predicted for different rotating speed, and agree well with the experimental results. The parametric influence of three main surrounding structures（i.e. the heat sink, the bell-mouth type shroud and the outlet grille） upon the aerodynamic performance of the unit is analyzed thoroughly. The results demonstrate that the tip vortex plays a major role in the flow fields near the blade tip and has a great effect on the flow field of the unit. The inlet ring＇s size and throat＇s depth of the bell-mouth type shroud, and the through-flow area and configuration of upwind and downwind sections of the outlet grille are the most important factors that affect the aerodynamic performance of the unit. Furthermore, two improved schemes against the existing prototype of the unit are developed, which both can significantly increase the flow rate more than 6 %（i.e. 100 m3·h～（-1）） at given rotating speeds. The inevitable increase of flow noise level when flow rate is increased and the advantage of keeping a lower rotating speed are also discussed. The presented work could be a useful guideline in designing the aerodynamic and acoustic performance of the split air-conditioner in engineering practice.展开更多
In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accele...In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.展开更多
Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors:Smartphone heterogeneity and smaller data lengths.The use of multifarioussmartphones cripp...Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors:Smartphone heterogeneity and smaller data lengths.The use of multifarioussmartphones cripples the performance of such approaches owing to the variability of the magnetic field data.In the same vein,smaller lengths of magnetic field data decrease the localization accuracy substantially.The current study proposes the use of multiple neural networks like deep neural network(DNN),long short term memory network(LSTM),and gated recurrent unit network(GRN)to perform indoor localization based on the embedded magnetic sensor of the smartphone.A voting scheme is introduced that takes predictions from neural networks into consideration to estimate the current location of the user.Contrary to conventional magnetic field-based localization approaches that rely on the magnetic field data intensity,this study utilizes the normalized magnetic field data for this purpose.Training of neural networks is carried out using Galaxy S8 data while the testing is performed with three devices,i.e.,LG G7,Galaxy S8,and LG Q6.Experiments are performed during different times of the day to analyze the impact of time variability.Results indicate that the proposed approach minimizes the impact of smartphone variability and elevates the localization accuracy.Performance comparison with three approaches reveals that the proposed approach outperforms them in mean,50%,and 75%error even using a lesser amount of magnetic field data than those of other approaches.展开更多
An indoor positioning system( IPS) is designed to realize positioning and tracking of mobile targets,by taking advantages of both the visible light communication( VLC) and inertial measurement unit( IMU). The platform...An indoor positioning system( IPS) is designed to realize positioning and tracking of mobile targets,by taking advantages of both the visible light communication( VLC) and inertial measurement unit( IMU). The platform of the IPS is designed,which consists of the light-emitting diode( LED)based transmitter,the receiver and the positioning server. To reduce the impact caused by measurement errors,both inertial sensing data and the received signal strength( RSS) from the VLC are calibrated. Then,a practical propagation model is established to obtain the distance between the transmitter and the receiver from the RSS measurements. Furthermore,a hybrid positioning algorithm is proposed by using the adaptive Kalman filter( AKF) and the weighted least squares( WLS)trilateration to estimate the positions of the mobile targets.Experimental results show that the developed IPS using the proposed hybrid positioning algorithm can extend the localization area of VLC,mitigate the IMU drifts and improve the positioning accuracy of mobile targets.展开更多
基金Supported by Program for Changjiang Scholars and Innovative Research Team in University,Ministry of Education of China(PCSIRT)
文摘DC-inverter split air-conditioner is widely used in Chinese homes as a result of its high-efficiency and energy-saving. Recently, the researches on its outdoor unit have focused on the influence of surrounding structures upon the aerodynamic and acoustic performance, however they are only limited to the influence of a few parameters on the performance, and practical design of the unit requires more detailed parametric analysis. Three-dimensional computational fluid dynamics（CFD） and computational aerodynamic acoustics（CAA） simulation based on FLUENT solver is used to study the influence of surrounding structures upon the aforementioned properties of the unit. The flow rate and sound pressure level are predicted for different rotating speed, and agree well with the experimental results. The parametric influence of three main surrounding structures（i.e. the heat sink, the bell-mouth type shroud and the outlet grille） upon the aerodynamic performance of the unit is analyzed thoroughly. The results demonstrate that the tip vortex plays a major role in the flow fields near the blade tip and has a great effect on the flow field of the unit. The inlet ring＇s size and throat＇s depth of the bell-mouth type shroud, and the through-flow area and configuration of upwind and downwind sections of the outlet grille are the most important factors that affect the aerodynamic performance of the unit. Furthermore, two improved schemes against the existing prototype of the unit are developed, which both can significantly increase the flow rate more than 6 %（i.e. 100 m3·h～（-1）） at given rotating speeds. The inevitable increase of flow noise level when flow rate is increased and the advantage of keeping a lower rotating speed are also discussed. The presented work could be a useful guideline in designing the aerodynamic and acoustic performance of the split air-conditioner in engineering practice.
基金Project(61301181) supported by the National Natural Science Foundation of China
文摘In this paper, we integrate inertial navigation system (INS) with wireless sensor network (WSN) to enhance the accuracy of indoor localization. Inertial measurement unit (IMU), the core of the INS, measures the accelerated and angular rotated speed of moving objects. Meanwhile, the ranges from the object to beacons, which are sensor nodes with known coordinates, are collected by time of arrival (ToA) approach. These messages are simultaneously collected and transmitted to the terminal. At the terminal, we set up the state transition models and observation models. According to them, several recursive Bayesian algorithms are applied to producing position estimations. As shown in the experiments, all of three algorithms do not require constant moving speed and perform better than standalone ToA system or standalone IMU system. And within them, two algorithms can be applied for the tracking on any path which is not restricted by the requirement that the trajectory between the positions at two consecutive time steps is a straight line.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2019-2016-0-00313)supervised by the IITP(Institute for Information&communication Technology Promotion)+1 种基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT and Future Planning(2017R1E1A1A01074345).
文摘Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors:Smartphone heterogeneity and smaller data lengths.The use of multifarioussmartphones cripples the performance of such approaches owing to the variability of the magnetic field data.In the same vein,smaller lengths of magnetic field data decrease the localization accuracy substantially.The current study proposes the use of multiple neural networks like deep neural network(DNN),long short term memory network(LSTM),and gated recurrent unit network(GRN)to perform indoor localization based on the embedded magnetic sensor of the smartphone.A voting scheme is introduced that takes predictions from neural networks into consideration to estimate the current location of the user.Contrary to conventional magnetic field-based localization approaches that rely on the magnetic field data intensity,this study utilizes the normalized magnetic field data for this purpose.Training of neural networks is carried out using Galaxy S8 data while the testing is performed with three devices,i.e.,LG G7,Galaxy S8,and LG Q6.Experiments are performed during different times of the day to analyze the impact of time variability.Results indicate that the proposed approach minimizes the impact of smartphone variability and elevates the localization accuracy.Performance comparison with three approaches reveals that the proposed approach outperforms them in mean,50%,and 75%error even using a lesser amount of magnetic field data than those of other approaches.
基金The National Natural Science Foundation of China(No.61741102,61471164,61601122)the Fundamental Research Funds for the Central Universities(No.SJLX_160040)
文摘An indoor positioning system( IPS) is designed to realize positioning and tracking of mobile targets,by taking advantages of both the visible light communication( VLC) and inertial measurement unit( IMU). The platform of the IPS is designed,which consists of the light-emitting diode( LED)based transmitter,the receiver and the positioning server. To reduce the impact caused by measurement errors,both inertial sensing data and the received signal strength( RSS) from the VLC are calibrated. Then,a practical propagation model is established to obtain the distance between the transmitter and the receiver from the RSS measurements. Furthermore,a hybrid positioning algorithm is proposed by using the adaptive Kalman filter( AKF) and the weighted least squares( WLS)trilateration to estimate the positions of the mobile targets.Experimental results show that the developed IPS using the proposed hybrid positioning algorithm can extend the localization area of VLC,mitigate the IMU drifts and improve the positioning accuracy of mobile targets.
