Accurate Position Sensor Research Articles

A comparative analysis between deep neural network-based 1D-CNN and LSTM models to harness the self-sensing property of the shape memory alloy wire actuator for position estimation

The article presents a performance-based comparative analysis of popular deep neural network (DNN) models such as 1-dimensional convolutional neural network (1D-CNN) and long short-term memory (LSTM) for position estimation of shape memory alloy (SMA)-based wire actuator. These DNN models utilize the self-sensing property (SSP) for position estimation of the SMA actuator. The phase-dependent electrical resistivity of SMA wire acts as SSP, where the electrical resistivity in the form of SMA wire resistance acts as inputs to the proposed models for precise estimation of the current position of the SMA actuator. For effective position control of the SMA actuator, accurate position sensor feedback is required, utilizing SSP results in the elimination of this external sensor. This will improve the overall system in terms of compactness and reduced interface complexity. Coming to DNN models, 1D-CNN has been meagerly explored in the current literature landscape for self-sensing estimation of SMA actuators. These 1D-CNN models are becoming quite popular for time series prediction for various applications and are emerging as an alternative to widely used LSTM models. In this paper, a novel implementation of a 1D-CNN model for SMA actuator position estimation has been done. A comparative analysis between 1D-CNN and LSTM has been done for prediction capability and inference speed based on performance measures such as Mean Square Error (MSE), Mean Absolute Error (MAE), symmetric Mean Absolute Percentage Error (sMAPE), data distribution, and average inference speed. The proposed comparative results show that 1D-CNN has a matching performance with the LSTM model with respect to prediction capability, however, 1D-CNN offers faster inference speed. The analysis of the proposed work can be useful for choosing a suitable DNN model for deployment on low computing platforms such as microcontrollers for SMA actuator-based real-time applications where time latency is a critical parameter.

A Novel Linear Resolver Proposal and Its Performance Analysis Under Healthy and Asymmetry Air-Gap Fault

A novel linear resolver (L-Resolver) is proposed in this article. The excitation and signals windings are placed on the mover, and the stator structure is designed by a certain number of teeth/slots per the mover length. Therefore, the proposed structure is more simple compared to other resolver types and causes a low price structure. A flexible magnetic equivalent circuit (MEC) is used for analysis due to its capability, introducing various structures. The resolver performance under healthy and faulty cases is evaluated, where the position error under asymmetry air-gap fault is obtained. The performed analysis shows that the proposed resolver has less than 100- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mathrm {\mu m}}$ </tex-math></inline-formula> position error. Hence, it can be a proper alternative as an accurate position sensor. The simple structure and high-accurate position estimation are the advantages of the proposed resolver compared to other types. Finally, the effectiveness of the proposed resolver is validated by experimental results.

A Low-Cost, Highly Customizable Solution for Position Estimation in Modular Robots

Abstract Accurate position sensing is important for state estimation and control in robotics. Reliable and accurate position sensors are usually expensive and difficult to customize. Incorporating them into systems that have very tight volume constraints such as modular robots are particularly difficult. PaintPots are low-cost, reliable, and highly customizable position sensors, but their performance is highly dependent on the manufacturing and calibration process. This paper presents a Kalman filter with a simplified observation model developed to deal with the nonlinearity issues that result in the use of low-cost microcontrollers. In addition, a complete solution for the use of PaintPots in a variety of sensing modalities including manufacturing, characterization, and estimation is presented for an example modular robot, SMORES-EP. This solution can be easily adapted to a wide range of applications.

Direct Torque Control Scheme for DC Voltage Regulation of the Standalone DFIG-DC System

This paper deals with a standalone doubly fed induction generator-direct current (DFIG-dc) system, where stator and rotor are connected to an isolated dc load, via diode rectifier and voltage-source inverter, respectively. A direct torque control scheme is proposed for dc voltage regulation, where the dc voltage is regulated by a torque controller, while stator frequency is maintained at a nearly rated frequency, by achieving constant dc voltage to rotor flux ratio. An innovative switching strategy is developed to incorporate the phase sequence change in rotor current from subsynchronous speed to supersynchronous speed. Variable switching due to a hysteresis controller provides a reduction in the harmonic content of stator current. This control is simple in implementation, and less parameter dependent. There is no requirement of exact position sensing, while the speed measurement is sufficient, which also reduces the cost and maintenance of an accurate position sensor. Sensing of stator voltage and current is not required in this scheme, and control is done with a minimum number of sensors. As the number of turns on the stator is higher than the rotor, to have common dc link and to exploit rated stator MMF, roles of stator and rotor are interchanged. Performance of the control scheme is verified experimentally on a 4 kW DFIG, and results are reported.

Model-Based Correction of Velocity Measurements in Navigated 3-D Ultrasound Imaging During Neurosurgical Interventions

In neurosurgery, information of blood flow is important to identify and avoid damage to important vessels. Three-dimensional intraoperative ultrasound color-Doppler imaging has proven useful in this respect. However, due to Doppler angle-dependencies and the complexity of the vascular architecture, clinical valuable 3-D information of flow direction and velocity is currently not available. In this work, we aim to correct for angle-dependencies in 3-D flow images based on a geometric model of the neurovascular tree generated on-the-fly from free-hand 2-D imaging and an accurate position sensor system. The 3-D vessel model acts as a priori information of vessel orientation used to angle-correct the Doppler measurements, as well as provide an estimate of the average flow direction. Based on the flow direction we were also able to do aliasing correction to approximately double the measurable velocity range. In vitro experiments revealed a high accuracy and robustness for estimating the mean direction of flow. Accurate angle-correction of axial velocities were possible given a sufficient beam-to-flow angle for at least parts of a vessel segment . In vitro experiments showed an absolute relative bias of 9.5% for a challenging low-flow scenario. The method also showed promising results in vivo, improving the depiction of flow in the distal branches of intracranial aneurysms and the feeding arteries of an arteriovenous malformation. Careful inspection by an experienced surgeon confirmed the correct flow direction for all in vivo examples.

Low-cost capacitive sensing for precision alignment of mirrors

Piezoelectric actuators are often used to align mirrors in high-precision optical systems; however they are highly hysteretic and are therefore not repeatable. Closed-loop control is a reliable way to correct for this, but requires an accurate position sensor for feedback. We present a capacitive sensor that is capable of measuring the tilt of a mirror with a noise density of 10 milliarcsec Hz−1/2 and repeatability of better than ±17 milliarcsec (corresponding to a distance of ±4 nm) over a range of more than 6 arcmin. This enables the correction of hysteresis with much better performance at low frequencies than feedforward algorithms or charge controllers. Low cost (a hundredth of the cost of similar systems) and ease of construction and integration with commercially available mirror mounts are its primary advantages. The effect of temperature on the mirror mount was significant, with a change of several arcsec per degree Celsius. However, it was possible to obtain stable performance over periods of several hours in a lab without sophisticated temperature control.

Characterization of Accelerometers Using Nonlinear Kalman Filters and Position Feedback

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, we describe a method to test and characterize accelerometers using an accurate position sensor and nonlinear Kalman filters. The method is designed to estimate parameters in nonlinear accelerometers and could be a simpler alternative to methods using centrifuges or vibrational testing. The method makes it possible to do real-time parameter estimation. In addition, the method can be integrated into an inertial tracking or navigation system with sufficiently accurate position measurements. The estimation filters have been implemented and successfully tested using Monte Carlo simulations. An experimental setup has been built, and its functionality has been verified. </para>

Azim: Direction-Based Service System for Both Indoors and Outdoors

SUMMARY In this paper, we propose an advanced location-based service that we call a direction-based service, which utilizes both the position and direction of a user. The direction-based service enables a user to point to an object of interest for command or investigation. We also describe the design, implementation and evaluations of a direction-based service system named Azim. With this system, the direction of the user can be obtained by a magnetic-based direction sensor. The sensor is also used for azimuthbased position estimation, in which a user’s position is estimated by having the user point to and measure azimuths of several markers or objects whose positions are already known. Because this approach does not require any other accurate position sensors or positive beacons, it can be deployed costeffectively. Also, because the measurements are naturally associated with some degree of error, the position is calculated as a probability distribution. The calculation considers the error of direction measurement and the pre-obtained field information such as obstacles and magnetic field disturbance, which enables robust position measurements even in geomagnetically disturbed environments. For wide-area use, the system also utilizes a wireless LAN to obtain rough position information by identifying base stations. We have implemented a prototype system for the proposed method and some applications for the direction-based services. Furthermore, we have conducted experiments both indoors and outdoors, and exemplified that positioning accuracy by the proposed method is precise enough for a direction-based service.

The Coast Guard's Differential GPS Programme

The US Coast Guard has a project to provide a differential global positioning system service for harbour and harbour approach (HHA) areas of the coastal United States. The Great Lakes, Puerto Rico and most of Alaska and Hawaii will also be covered by the service. The Coast Guard's DGPS system will fulfil the 8–20 metre navigation accuracy requirement for HHA with an availability of up to 999 percent. The Coast Guard intends to provide this service to the general public and other government agencies, as well as use the system for its own missions. This capability is expected to enhance maritime safety in keeping with the National Transportation Policy by providing an all-weather radionavigation service to supplement existing radar and visual techniques, as well as a highly accurate position sensor for future electronic chart displays. This paper describes the Coast Guard's programme. Background and historical information on the development of pseudorange differential GPS is presented first, followed by a description of currently available technology. Various aspects of the Coast Guard's plan for implementing DGPS are then described, concluding with a rough project time line and a statement concerning Federal DGPS policy.

The Coast Guard's Differential GPS Program

The U.S. Coast Guard has undertaken a project to provide Differential Global Positioning System service for harbor and harbor approach (HHA) areas of the coastal United States. The Great Lakes, Puerto Rico and most of Alaska and Hawaii will also be covered by the service. The Coast Guard’s DGPS system will fulfill the 8- 20 meter navigation accuracy requirement for HHA with an availability of up to 99.9%. The Coast Guard intends to provide this service to the general public and other government agencies, as well as use the system for its own missions. This capability is expected to enhance maritime safety in keeping with the National Transportation Policy by providing an all-weather radionavigation service to supplement existing radar and visual techniques, as well as a highly accurate position sensor for future electronic chart displays. This paper describes the Coast Guard’s program. Background and historical information on the development of pseudorange differential GPS is presented first, followed by a description of currently available technology. Various aspects of the Coast Guard’s plan for implementing DGPS are then described, concluding with a rough project time line and a statement concerning Federal DGPS policy.