High-speed implementation of MultiMCW entropy estimation method

2017 ◽  
Author(s):  
Wontae Kim ◽  
Hojoong Park ◽  
Yongjin Yeom ◽  
Ju-Sung Kang
Keyword(s):  
High Speed ◽  
Estimation Method ◽  
Entropy Estimation

Estimation of Track Irregularity Based on Genetic Algorithm and Unscented Kalman Filtering

2012 ◽  
Author(s):  
Hongmei Shi ◽  
Zujun Yu
Keyword(s):  
Genetic Algorithm ◽  
Kalman Filtering ◽  
High Speed ◽  
Measurement Data ◽  
Estimation Method ◽  
Coupling Model ◽  
Dynamic Responses ◽  
The Real ◽  
True Value ◽  
Track Irregularity

Track irregularity is the main excitation source of wheel-track interaction. Due to the difference of speed, axle load and suspension parameters between track inspection train and the operating trains, the data acquired from the inspection car cannot completely reflect the real status of track irregularity when the operating trains go through the rail. In this paper, an estimation method of track irregularity is proposed using genetic algorithm and Unscented Kalman Filtering. Firstly, a vehicle-track vertical coupling model is established, in which the high-speed vehicle is assumed as a rigid body with two layers of spring and damping system and the track is viewed as an elastic system with three layers. Then, the static track irregularity is estimated by genetic algorithm using the vibration data of vehicle and dynamic track irregularity which are acquired from the inspection car. And the dynamic responses of vehicle and track can be solved if the static track irregularity is known. So combining with vehicle track coupling model of different operating train, the potential dynamic track irregularity is solved by simulation, which the operating train could goes through. To get a better estimation result, Unscented Kalman Filtering (UKF) algorithm is employed to optimize the dynamic responses of rail using measurement data of vehicle vibration. The simulation results show that the estimated static track irregularity and the vibration responses of vehicle track system can go well with the true value. It can be realized to estimate the real rail status when different trains go through the rail by this method.

scholarly journals A Deterministic Sensor Deployment Method for Target Coverage

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Ye Jiang ◽  
Shuyan Xiao ◽  
Jian Liu ◽  
Bo Chen ◽  
Bangbang Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Gas Sensors ◽  
Estimation Method ◽  
Weather Conditions ◽  
Pso Algorithm ◽  
Gas Diffusion ◽  
Optimization Criterion ◽  
Sensor Deployment ◽  
Entropy Estimation ◽  
Gas Leakage

In order to monitor the gas leakage, the gas sensors are deployed conventionally in chemical industry park, with little considerations given to the gas characteristics and weather conditions, which give rise to the problems of coverage hole and coverage repetition. To solve the problems, this paper proposes a deterministic sensor deployment method with the gas diffusion models which takes into account wind speed and direction and then studies the influence of wind speed and direction on the monitoring error of gas sensors. Then, we research the deterministic deployment method of gas sensors in condition of the main wind speed and direction somewhere. Firstly, we use the CFD theory to simulate the gas diffusion situation so as to obtain the concentration value of the relevant points. Secondly, we put forward a new optimization criterion, namely, the more alarm concentration points covered by gas sensors, the coverage performance is better, and the deployment method is better. Accordingly, a new objection function is built. Thirdly, we obtain the weight values of the function using entropy estimation method. Finally, we deploy the gas sensors determinately using particle swarm optimization (PSO) algorithm. The simulation results show that the proposed method can improve the monitoring efficiency and the coverage performance of gas sensor network.

scholarly journals A dynamic zone estimation method using cumulative voxels for autonomous driving

2017 ◽  
Vol 14 (1) ◽  
pp. 172988141668713 ◽  
Author(s):  
Seongjo Lee ◽  
Seoungjae Cho ◽  
Sungdae Sim ◽  
Kiho Kwak ◽  
Yong Woon Park ◽  
...  
Keyword(s):  
High Speed ◽  
Moving Objects ◽  
Three Dimensional ◽  
Estimation Method ◽  
Autonomous Driving ◽  
Significant Feature ◽  
Data Set ◽  
Ground Truth Data ◽  
Unmanned Vehicle ◽  
Space Data

Obstacle avoidance and available road identification technologies have been investigated for autonomous driving of an unmanned vehicle. In order to apply research results to autonomous driving in real environments, it is necessary to consider moving objects. This article proposes a preprocessing method to identify the dynamic zones where moving objects exist around an unmanned vehicle. This method accumulates three-dimensional points from a light detection and ranging sensor mounted on an unmanned vehicle in voxel space. Next, features are identified from the cumulative data at high speed, and zones with significant feature changes are estimated as zones where dynamic objects exist. The approach proposed in this article can identify dynamic zones even for a moving vehicle and processes data quickly using several features based on the geometry, height map and distribution of three-dimensional space data. The experiment for evaluating the performance of proposed approach was conducted using ground truth data on simulation and real environment data set.

Combined Back-EMF Estimator with High-Frequency Signal Injection for Wide Speed Range Sensorless Control of PMLSM

2013 ◽  
Vol 753-755 ◽  
pp. 1405-1408
Author(s):  
Hua Cai Lu ◽  
Xuan Yu Yao ◽  
Juan Ti
Keyword(s):  
High Frequency ◽  
High Speed ◽  
Sensorless Control ◽  
Estimation Method ◽  
Detection Algorithm ◽  
Estimation Accuracy ◽  
High Frequency Signal ◽  
Weighting Method ◽  
Transition Speed ◽  
Signal Injection

This paper describes a composite sensorless position and speed detection algorithm designed for permanent magnet linear synchronous motor (PMLSM). A high-frequency voltage signal injection method is used at starting and low speed, and a back-EMF integrate method is used at high speed, and the two kinds of method are fused by weighting method in the transition speed area. Simulation results show that estimation accuracy of this composite estimation method is satisfactory, and the sensorless control system based on this method has good dynamic response characteristics within full speed.

scholarly journals A Low-Cost, High-Precision Method for Ripple Voltage Measurement Using a DAC and Comparators

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 586
Author(s):  
Jincheng Liu ◽  
Jiguang Yue ◽  
Li Wang ◽  
Chenhao Wu ◽  
Feng Lyu
Keyword(s):  
High Precision ◽  
High Speed ◽  
Low Cost ◽  
Estimation Method ◽  
Electronic System ◽  
Voltage Measurement ◽  
Pass Filter ◽  
Switched Mode Power Supply ◽  
Dc Component ◽  
Microcontroller Unit

As the core of electronic system, the switched-mode power supply (SMPS) will lead to serious accidents and catastrophes if it suddenly fails. According to the related research, the monitoring of ripple can acquire the health degree of SMPS indirectly. To realize low-cost, high-precision, and automatic ripple measurement, this paper proposes a new ripple voltage (peak-to-peak value) measuring scheme, utilizing a DAC and two high-speed comparators. Within this scheme, the DC component of SMPS output is blocked by a high-pass filter (HPF). Then, the filtered signal and the reference voltage from a DAC together compose the input of a high-speed comparator. Finally, output pulses of the comparator are captured by a microcontroller unit (MCU), which readjusts the output of the DAC by calculation, and this process is repeated until the DAC output is exactly equal to the peak (or valley) value of ripple. Moreover, in order to accelerate the measurement process, a peak estimation method is specially designed to calculate the output ripple peak (or valley) value of buck topology through merely two measurements. Then the binary search method is utilized to obtain a more exact value on the basis of estimative results. Additionally, an analysis of the measurement error of this ripple measurement system is executed, which shows that the theoretical error is less than 0.5% where the ripple value is larger than 500 mV. Furthermore, appropriate components are selected, and a prototype is manufactured to verify the validity of the proposed theory.

The Performance Correlation Hilbert Time-Delay Estimation for Passive Detection

2014 ◽  
Vol 602-605 ◽  
pp. 1768-1771
Author(s):  
Feng Wang ◽  
Mei Quan Liu ◽  
Jiang Wei Fan
Keyword(s):  
Time Delay ◽  
High Speed ◽  
Time Lag ◽  
Estimation Method ◽  
Time Delay Estimation ◽  
Time Difference ◽  
Delay Estimation ◽  
Main Peak ◽  
Zero Crossing ◽  
Passive Detection

Passive time difference detection method is distance, high speed and good concealment which has broad military application prospects. One of the key technologies for passive detection is to extract the time lag through effective signal processing. Relevant method is the most basic method to estimate the time difference and is the basic theory of all correlative time-delay estimation algorithms. The method is simple. But good results rely on the spectrum characteristics of signal and noise is ideal. Time delay estimation based on Hilbert transform is the expansion of the generalized correlation time-delay estimation method which changes the correlation function from accidentally symmetry into odd symmetry. Detecting correlation peak is converted into zero crossing detection. The method sharps the main peak value point and improved the precision of time delay estimation which gets better time-delay estimation performance in the narrowband signal.

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