Calculation of Skin Depths and Eddy-Current Power Losses for Magnetic Position Sensors

We present a theoretic model to calculate skin depths and eddy-current power losses for a magnetic position sensor. Eddy-current, arised from the operation of an alternating-current excitation, induces secondary currents and fields between magnetic material and magnetic position sensor. In this paper, a magnetic position sensor system is simplified to be an outer-winding coil along the axial direction of a low carbon steel bar. The analytical model is derived from basic field and circuit theory considering a linear approximation for a nonlinear permeability. Thus the skin depths and eddy-current power losses from the model in eddy-current modeling techniques at various frequencies of an excited current source can be calculated. The proposed configuration is capable of predicting the skin depths and eddy-current power losses for a magnetic position sensor and has a consistence with experiments.

In Vivo Dosimetry of an Anthropomorphic Phantom Using the RADPOS for Proton Beam Therapy

The radiation positioning system (RADPOS) combines an electromagnetic positioning sensor with metal oxide semiconductor field-effect transistor (MOSFET) dosimetry, enabling simultaneous online measurement of dose and spatial position. Evaluation points can be determined with the RADPOS. The accuracy of in-vivo proton dosimetry was evaluated using the RADPOS and an anthropomorphic head and neck phantom. MOSFET doses measured at 3D positions obtained with the RADPOS were compared with treatment plan values calculated using a simplified Monte Carlo (SMC) method. MOSFET responses, which depend strongly on the linear energy transfer of the proton beam, were corrected using the SMC method. The SMC method was used to calculate only dose deposition determined by the experimental depth-dose distribution and lateral displacement of protons due to the multiple scattering effect in materials and incident angle. This method thus enabled rapid calculation of accurate doses in even heterogeneities. In vivo dosimetry using the RADPOS, as well as MOSFET doses, agreed with SMC calculations in the range of ?3.0% to 8.3%. Most measurement errors occurred because of uncertainties in dose calculations due to the 1-mm position error. The results indicate that uncertainties in measurement position can be controlled successfully within 1 mm when using the RADPOS with in-vivo proton dosimetry.

ASSESSING THE DYNAMIC ERRORS OF COORDINATE MEASURING MACHINES

The main factors affecting the dynamic errors of coordinate measuring machines are analyzed. It is pointed out that there are two main contributors to the dynamic errors: One is the rotation of the elements around the joints connected with air bearings and the other is the bending of the elements caused by the dynamic inertial forces. A method for obtaining the displacement errors at the probe position from dynamic rotational errors is presented. The dynamic rotational errors are measured with inductive position sensors and a laser interferometer. The theoretical and experimental results both show that during the process of fast probing, due to the dynamic inertial forces, there are not only large rotation of the elements around the joints connected with air bearings but also large bending of the weak elements themselves.

A position sensor based on grating projection with spatial filtering and polarization modulation

A position sensor based on grating projection with spatial filtering and polarization modulation is presented. A grating is projected onto the object to be measured through a 4f optical system with a spatial filter. After reflected by the object, the grating projection is imaged on a detection grating through another 4f optical system to form moiré fringes, The polarization modulated moiré signal is detected to obtain the position information of the object. In the position sensor, the moiré signal varies sinusoidally with the position of object. The measurement is independent of the incident intensity on the projection grating and the reflectivity of the object to be measured, In experiments, the effectiveness of the position sensor is proved, and the root mean square （RMS） error at each measurement position is less than 13 nm.

Efficient closed-form solution for target localization using TDOA measurements in the presence of sensor position errors

An efficient solution for locating a target was proposed, which by using time difference of arrival （TDOA） measurements in the presence of random sensor position errors to increase the accuracy of estimation. The cause of position estimation errors in two-stage weighted least squares （TSWLS） method is analyzed to develop a simple and effective method for improving the localization performance. Specifically, the reference sensor is selected again and the coordinate system is rotated according to preliminary estimated target position by using TSWLS method, and the final position estimation of the target is obtained by using weighted least squares （WLS）. The proposed approach exhibits a closed-form and is as efficient as TSWLS method. Simulation results show that the proposed approach yields low estimation bias and improved robustness with increasing sensor position errors and thus can easily achieve the Cramer-Rao lower bound （CRLB） easily and effectively improve the localization accuracy.

A Novel Adaptive Cooperative Location Algorithm for Wireless Sensor Networks

To overcome the disadvantages of the location algorithm based on received signal strength indication(RSSI) in the existing wireless sensor networks(WSNs),a novel adaptive cooperative location algorithm is proposed.To tolerate some minor errors in the information of node position,a reference anchor node is employed.On the other hand,Dixon method is used to remove the outliers of RSSI,the standard deviation threshold of RSSI and the learning model are put forward to reduce the ranging error of RSSI and improve the positioning precision effectively.Simulations are run to evaluate the performance of the algorithm.The results show that the proposed algorithm offers more precise location and better stability and robustness.