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In this work, we propose a real-time noncontact thickness measurement system for conductive materials based on an inductor–capacitor (LC) resonant eddy-current sensor. For the aluminum, copper, stainless steel 304, and carbon steel samples of various thicknesses, the in-phase and quadrature components of the sensor output taken during liftoff scans are found to be a series of quadratic-like curves on the phase versus logarithmic amplitude diagram. These curves can be used to generate the standard phase–amplitude relations for thickness conversion. The phase–amplitude relations of the thickness between the values of standard samples are calculated by cubic spline interpolation. With the standard database of phase–amplitude relations, the noncontact thickness measurement was implemented in real time for the copper foil sample with an error of ±3% when the liftoff distance is less than 5 mm. The liftoff tolerance is as large as 100% of the probe diameter, indicating that the proposed method is useful for online quality inspection of conductor films on flexible substrates. [ABSTRACT FROM AUTHOR]

For the electromagnetic eddy current (EC) testing, various methods have been proposed for reducing the lift-off error on the measurement of samples. In this article, instead of eliminating the measurement error caused by the lift-off effect, an algorithm has been proposed to directly measure the lift-off distance between the sensor and nonmagnetic conductive plates. The algorithm is based on a sample-independent inductance (SII) feature. That is, under high working frequencies, the inductance is found to be sensitive to the lift-off distance and independent of the test piece under an optimal single high working frequency (43.87 kHz). Furthermore, the predicted lift-off distance is used for the thickness prediction of the nonmagnetic conductive samples using an iterative method. Considering the EC skin depth, the thickness prediction is operated under a single lower frequency (0.20 kHz). As the inductance has different sensitivities to the lift-off and thickness, the prediction error of the sample thickness is different from that of the lift-off distance. From the experiments on three different nonmagnetic samples—aluminum, copper, and brass, the maximum prediction error of the lift-off distance and sample thickness is 1.1 mm and 5.42%, respectively, at the lift-off of 12.0 mm. [ABSTRACT FROM AUTHOR]

In high-speed analog-to-digital converters (ADCs), two main factors contribute to high power consumption. The first is the super linear relationship with the sampling rate; i.e., by doubling the sampling rate, the power consumption more than doubles. The second factor arises from the consumption of analog circuitry responsible to mitigate the jitter noise. By employing a multichannel sampling system, one can achieve high sampling rates by incorporating multiple low sampling-rate channels, which results in a linear scaling of power consumption with the number of channels. The main drawback of this system is the timing mismatch between the sampling channels. In this paper, we intend to jointly compensate the jitter noise and the timing mismatch between the channels using statistical methods. We first approximate the acquisition system and derive a stochastic model. Then, we propose an iterative maximum likelihood algorithm to estimate the parameters of the input signal. We further evaluate the Cramér-Rao lower bound (CRLB) for the estimation error to examine the proposed algorithm. Simulation results indicate that our algorithm is capable of closely following the CRLB curve for reasonable values of jitter noise and a wide range of timing mismatch errors. Moreover, it is shown that the mismatch-compensated multichannel sampling system performs almost equivalently to a single-channel high rate sampler without having its shortcomings. [ABSTRACT FROM AUTHOR]

Nonsynchronous sampling conditions are the source of leakage errors in measurements based on digital signal processing. The optimal method to avoid such errors is to generate a synchronous sampling clock, whenever the input signal shows enough period stability to allow this. Such method, however, does not yield a straightforward evaluation of the input signal frequency, which is required in several applications. This paper proposes a modified synchronous clock generator that together with a modified frequency interpolation algorithm provides an accurate measurement of the input signal frequency when the only available information about the sampling clock is a given integer multiple of the input signal fundamental frequency. [ABSTRACT FROM AUTHOR]

This paper introduces a new attitude estimation algorithm for pitch and roll angles. Pitch and roll angles are represented by a unit vector, and its estimation error is estimated in the Kalman filter. The main theoretical contribution is that the error covariance equations are simplified to scalar equations. Thus, the proposed algorithm is computationally efficient. The proposed algorithm is also applied to vertical movement estimation. Simulation and experiment results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Position and orientation system (POS) is widely applied to the various mapping sensors for airborne direct georeferencing. As the accuracy requirements vary in different mapping applications, the POS error analysis is important for the system design. In this paper, an analytical approach to the POS error analysis for ground alignment and constant-velocity flight is proposed. First, the simplified system model is obtained for the error analysis. Then, by applying the two-stage Kalman filter, the analytical relations between the attitude errors and estimation errors of the biases of the inertial sensors are derived. Finally, the experiment is carried out to confirm the effectiveness of the proposed method. The proposed method is not only effective and straightforward but also provides us some new insights into the POS error characteristics. [ABSTRACT FROM AUTHOR]

This paper presents a wearable sensor approach to motion measurements of human lower limbs, in which subjects perform specified walking trials at self-administered speeds so that their level walking and stair ascent capacity can be effectively evaluated. After an initial sensor alignment with the reduced error, quaternion is used to represent 3-D orientation and an optimized gradient descent algorithm is deployed to calculate the quaternion derivative. Sensors on the shank offer additional information to accurately determine the instances of both swing and stance phases. The Denavit-Hartenberg convention is used to set up the kinematic chains when the foot stays stationary on the ground, producing state constraints to minimize the estimation error of knee position. The reliability of this system, from the measurement point of view, has been validated by means of the results obtained from a commercial motion tracking system, namely, Vicon, on healthy subjects. The step size error and the position estimation accuracy change are studied. The experimental results demonstrated that the extensively existed sensor misplacement and sensor drift problems can be well solved. The proposed self-contained and environment-independent system is capable of providing consistent tracking of human lower limbs without significant drift. [ABSTRACT FROM AUTHOR]

Resistive chemical sensors, such as metal oxide (MOX) devices, usually exhibit resistance values within a wide range, from tens of kilohms to tens of gigohms. This is due, for example, to the different sensor material, manufacturing, working temperature, and so on. Electronic interfaces based on the resistance-to-time conversion (RTC) technique are widely used to handle such sensors, thanks to the low-cost, low-noise, and wide-range characteristics; in fact, time intervals are easier to measure within several decades without the need of scaling factors. However, the main limit of the RTC-based schemes is the variable and long measuring time, from microseconds (tens of kilohms) to quite a lot of seconds (tens of gigohms), impeding, for instance, a fine analysis of fast transients. This work proposes an innovative circuit based on the combination of the RTC method with the use of the least mean square interpolation algorithm. The implemented prototype allows the sensor resistance to be estimated with a constant measuring time of 10 ms within the range 10\ \k\Omega \div 100\ \G\Omega. The proposed implementation has shown a relative estimation error less than 10% (about 1% within 100\ \k\Omega \div 100\ \G\Omega). In addition, the system is capable to estimate the parasitic effect of the sensor (modeled with a capacitance up to 50 pF in parallel with the resistive component), showing a linearity error around 0.3% full scale (FS). A new tool has been also provided to estimate the uncertainty of the proposed approach due to rapid resistance changes, such as fast sensor transients. The simulation tool has been also used to prove performance improvement in the capacitance estimation, with respect to previously proposed solutions. Experimental results conducted using different real MOX sensors show the suitability of the proposed system for applications in which the sensor behavior need to be accurately analyzed, even in presence of fast dynamics. [ABSTRACT FROM PUBLISHER]

This paper proposes a Kalman filter-based attitude (i.e., roll and pitch) estimation algorithm using an inertial sensor composed of a triaxial accelerometer and a triaxial gyroscope. In particular, the proposed algorithm has been developed for accurate attitude estimation during dynamic conditions, in which external acceleration is present. Although external acceleration is the main source of the attitude estimation error and despite the need for its accurate estimation in many applications, this problem that can be critical for the attitude estimation has not been addressed explicitly in the literature. Accordingly, this paper addresses the combined estimation problem of the attitude and external acceleration. Experimental tests were conducted to verify the performance of the proposed algorithm in various dynamic condition settings and to provide further insight into the variations in the estimation accuracy. Furthermore, two different approaches for dealing with the estimation problem during dynamic conditions were compared, i.e., threshold-based switching approach versus acceleration model-based approach. Based on an external acceleration model, the proposed algorithm was capable of estimating accurate attitudes and external accelerations for short accelerated periods, showing its high effectiveness during short-term fast dynamic conditions. Contrariwise, when the testing condition involved prolonged high external accelerations, the proposed algorithm exhibited gradually increasing errors. However, as soon as the condition returned to static or quasi-static conditions, the algorithm was able to stabilize the estimation error, regaining its high estimation accuracy. [ABSTRACT FROM AUTHOR]