Nonlinear Error Research Articles

High-Precision large deformation measurement of array SAR based on FBG strain monitoring and initial state reconstruction

Array Synthetic Aperture Radar (SAR) as the novel generation airborne remote sensing system is installed below the wing, has received more attention because it can realize all-weather three-dimensional (3-D) imaging. Its high-precision imaging needs to measure large deformation of wing accurately. The exiting methods based on Fiber Bragg grating (FBG) sensors ignore the effects of wing initial state, which will generate non-negligible non-linear measurement error. To solve this problem, a high-precision large deformation measurement method of array SAR based on FBG strain monitoring and initial state reconstruction is proposed. Firstly, initial angle reconstruction approach is presented to obtain initial state. Then, bending strain measurement method is used to obtain continuous strain. Finally, large deformation model based on initial angle and bending strain is established to achieve large deformation. Experimental results indicate proposed method can effectively measure large deformation, and can acquire the higher displacement accuracy compared to traditional method.

Amplifying Sensing Capabilities: Combining Plasmonic Resonances and Fresnel Reflections through Multivariate Analysis.

Multivariate analysis applied in biosensing greatly improves analytical performance by extracting relevant information or bypassing confounding factors such as nonlinear responses or experimental errors and noise. Plasmonic sensors based on various light coupling mechanisms have shown impressive performance in biosensing by detecting dielectric changes with high sensitivity. In this study, gold nanodiscs are used as metasurface in a Kretschmann setup, and a variety of features from the reflectance curve are used by machine learning to improve sensing performance. The nanostructures of the metasurface generate new plasmonic features, apart from the typical resonance that occurs in the classical Kretschmann mode of a gold thin film, related to the evanescent field beyond total internal reflection. When the engineered metasurface is integrated into a microfluidic chamber, the device provides additional spectral features generated by Fresnel reflections at all dielectric interfaces. The increased number of features results in greatly improved detection. Here, multivariate analysis enhances analytical sensitivity and sensor resolution by 200% and more than 20%, respectively, and reduces prediction errors by almost 40% compared to a standard plasmonic sensor. The combination of plasmonic metasurfaces and Fresnel reflections thus offers the possibility of improving sensing capabilities even in commonly available setups.

Interpolation linearization predistortion technology for FMCW LiDAR.

Frequency-modulated continuous-wave (FMCW) laser ranging technology is an important development direction of light detection and ranging (LiDAR) for the future. It has the advantages of high ranging accuracy, high resolution, wide range, and no ranging blind zone. A distributed feedback laser can be used as a high-quality light source in FMCW laser ranging systems because of its wide frequency modulation range, simple frequency modulation mode, and small package. Aiming at the nonlinear problem of the laser in the frequency modulation process, we present a novel, to our knowledge, predistortion algorithm based on interpolation linear fitting to enhance the linearity of the FMCW laser for LiDAR systems. The sweeping frequency curve of the laser is obtained using the Hilbert transform, and then the sweeping frequency curve is segmented and linearly fitted to calculate the interpolated driving current signals corresponding to linear frequency changes. Using this method, we achieved a nonlinearity error lower than 1e-7 for the swept-frequency signal and demonstrated that the ranging error is less than ±5c m at a distance of 100m in the FMCW system. In addition, we also demonstrated a 3D static object point cloud with high imaging quality. Compared with the iterative predistortion algorithm based on the function fitting, this method avoids fitting errors at the inflection points of the triangular swept-frequency signal and the complexity of multiple iterative calculations. It enables rapid generation of pre-distorted swept-frequency signals, making it particularly suitable for real-time applications of automotive LiDAR systems.

Nonlinear error analysis of fast optical delay lines.

Optical delay lines have wide applications in terahertz time-domain spectroscopy and optical coherence tomography. In this study, a fast-rotating optical delay line (FRODL) with 24 turntable reflection surfaces was designed. By analyzing the working principle of the FRODL, a mathematical model was established for the nonlinear parameter error of the FRODL delay time. By constructing the polarization Michelson interference system and testing the FRODL structure, the error of actual assembly parameters of the FRODL was approximately 0.015 mm, the actual delay time of the FRODL was greater than 43.5 ps, and the linearity was 99.785%.

Design and analysis of parallel six-dimensional force sensor based on near-singular characteristics

The high sensitivity six-dimensional force sensor is the core component of intelligent robot force feedback perception, which is related to the structure of the sensor. This paper proposes a new modeling method to chain the near singular eight-branch Stewart mechanism, which indicates the relationship between structural parameters and sensitivity. The new method gains 16 new configurations by innovating the traditional Stewart institution. A configuration with high sensitivity in Fz, Mx and My directions is selected for further study. The theoretical stiffness model and force mapping model show that the sensitivity of the new structure can be amplified by 4 times in specific degrees of freedom. The results show that the nonlinear error and coupling error are 2.77% and 2.26%, respectively. The proposed method can be widely applied in the field of parallel six-dimensional force sensors.

Design and dynamic analysis of a highly sensitive MEMS gyroscope based on mode localization

Micro-electromechanical systems (MEMS) gyroscopes have important applications in various fields, including aviation, spaceflight, weaponry and automatic driving. To improve the robustness and sensitivity, we design a novel dual-mass MEMS gyroscope based on mode localization in this paper. The gyroscope structure comprises a pair of perturbation systems connected with weakly coupled resonator systems, which eliminates the mode matching and achieves mode localization effects. The dynamic behavior of the MEMS gyroscope is developed using the complex exponential method. The detection characteristics of the amplitude ratio (AR) and amplitude difference (AD) are compared. By combining numerical simulation, we analyzed the influence of critical parameters. It is indicated that the sensitivity can reach up to 40 036.9 ppm/°/s through the AR output, which is two magnitudes higher than the traditional MEMS gyroscope. For the detection of the micro-angular rate, the AD output has advantages in sensitivity, and the AR output has a smaller nonlinearity error. In addition, structural parameters, especially the voltage of the perturbation parallel plates, have a significant impact on the system’s sensitivity. If the breakdown voltage requirement is satisfied, the sensitivity can be enhanced more than ten times by amplifying the voltage, which further broadens the application field of the MEMS gyroscope.

A Proposed Methodology for Determining the Economically Optimal Number of Sample Points for Carbon Stock Estimation in the Canadian Prairies

Soil organic carbon (SOC) sequestration assessment requires accurate and effective tools for measuring baseline SOC stocks. An emerging technique for estimating baseline SOC stocks is predictive soil mapping (PSM). A key challenge for PSM is determining sampling density requirements, specifically, determining the economically optimal number of samples for predictive soil mapping for SOC stocks. In an attempt to answer this question, data were used from 3861 soil organic carbon samples collected as part of routine agronomic soil testing from a 4702 ha farming operation in Saskatchewan, Canada. A predictive soil map was built using all the soil data to calculate the total carbon stock for the entire study area. The dataset was then subset using conditioned Latin hypercube sampling (cLHS), both conventional and stratified by slope position, to determine the total carbon stocks with the following sampling densities (points per ha): 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, and 0.8. A nonlinear error function was then fit to the data, and the optimal number of samples was determined based on the number of samples that minimized soil data costs and the value of the soil carbon stock prediction error. The stratified cLHS required fewer samples to achieve the same level of accuracy compared to conventional cLHS, and the optimal number of samples was more sensitive to carbon price than sampling costs. Overall, the optimal sampling density ranged from 0.025 to 0.075 samples per hectare.

Two Proposals of a Simple Analog Conditioning Circuit for Remote Resistive Sensors with a Three-Wire Connection.

This article proposes and experimentally characterizes two implementations of a novel front-end circuit for three-wire connected resistive sensors with a wire-resistance compensation. The first implementation relies on two twin diodes, whereas the second on a switch; in both cases, those devices are non-remote (i.e., they are placed at the circuit end). The two circuit proposals have a square-wave input excitation so that a constant current with the two polarities is alternatively generated. Then, depending on that polarity, the current goes through either the sensor and the wire parasitic resistances or just the parasitic resistances. This generates a square-wave bipolar output signal whose average value, which is obtained by a low-pass filter, is proportional to the sensor resistance and only depends on the mismatch between two of the three wire resistances involved. Experimental tests applied to resistances related to a Pt100 thermal sensor show a remarkable linearity. For example, the switch-based front-end circuit offers a non-linearity error lower than 0.01% full-scale span, and this is practically insensitive to both the presence and the mismatch between the wire resistances.

Non-Contact Current Measurement for Three-Phase Rectangular Busbars Using TMR Sensors.

This paper proposes a non-contact current measurement method for three-phase rectangular busbars based on TMR (tunneling magneto-resistance) sensors, due to their advantages of large dynamic range, wide bandwidth, light weight, and easy installation. A non-contact current sensor composed of only three TMR sensors is developed and the TMR sensors are respectively placed at a location with a certain distance from the surface of each rectangular busbar to measure the magnetic fields generated by the busbar currents. To calibrate the developed current sensor, i.e., to establish the relationship between the magnetic fields measured by the TMR sensors and the currents flowing in the three-phase rectangular busbars, we designed a thyristor-controlled resistive load as a calibrator, which is connected to a downstream branch of the distribution cabinet. By switching the resistive load, a calibration current, which can be identified from the background current, is generated in one rectangular busbar and its value is measured at the location of the calibrator, and transmitted wirelessly to the location of the TMR sensors. A new and robust method is proposed to extract the voltage components, corresponding to the calibration current, from the voltage waveforms of the TMR sensors. By calculating the proportional coefficients between the calibration currents and the extracted voltage components, online calibration of the current sensor is achieved. We designed and implemented a current measurement system consisting of a current sensor using TMR sensors, a thyristor-controlled resistive load for current sensor calibration, and a data acquisition circuit based on a multi-channel analog-to-digital converter (ADC). Current measurement experiments were performed in a practical distribution cabinet installed in our laboratory. Compared to the measurement results using a commercial current probe with an accuracy of 1%, the relative error of the measured currents in RMS is less than 2.5% and the phase error is less than 1°, while the nonlinearity error of the current sensor is better than 0.8%.

Research on the torpedo-shaped biomimetic MEMS vector wake detector

Autonomous Underwater Vehicles (AUVs) are a technological safeguard for executing marine tasks. However, traditional acoustic and optical technologies may fail to provide AUVs with precise near-field perception in complex, turbid environments. Inspired by the lateral line system of fish, a biomimetic MEMS vector wake detector is proposed. Based on the differential pressure sensing mechanism of the canal neuromasts, finite element software is utilized to optimize the shape and resistance performance of the detector's packaging structure. The geometric parameters are determined, and the integration and fabrication of the sensor are performed. The characterization results demonstrate that the detector's sensitivity is 1678 mV/(m/s), with a non-linear error of 3.73 % linearity and a detection threshold of 0.2 m/s. The angle and direction test results verify it possesses vector detection capability and can discern the wake direction. This wake detector could provide a valuable method of cluster perception for underwater vehicles.

Ultra-low power 10-bit 50–90 MSps SAR ADCs in 65 nm CMOS for multi-channel ASICs

The design and measurement results of ultra-low power, fast 10-bit Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) prototypes in 65 nm CMOS technology are presented. Eight prototype ADCs were designed using two different switching schemes of capacitive Digital-to-Analog Converter (DAC), based on MIM or MOM capacitors, and controlled by standard or low-power SAR logic. The layout of each ADC prototype is drawn in 60 μm pitch to make it ready for multi-channel implementation. A series of measurements have been made confirming that all prototypes are fully functional, and six of them achieve very good quantitative performance. Five out of eight ADCs show both integral (INL) and differential (DNL) nonlinearity errors below 1 LSB. In dynamic measurements performed at 0.1 Nyquist input frequency, the effective number of bits (ENOB) between 8.9–9.3 was obtained for different ADC prototypes. Standard ADC versions work up to 80–90 MSps with ENOB between 8.9–9.2 bits at the highest sampling rate, while the low-power versions work up to above 50 MSps with ENOB around 9.3 bits at 40 MSps. The power consumption is linear with the sample rate and at 40 MSps it is around 400 μW for the low-power ADCs and just over 500 μW for the standard ADCs. At 80 MSps the standard ADCs consume about 1 mW.

Theoretical analysis and simulation of FTIR spectrometer based on rotating double-sided reflective mirror

In this study, the FTIR spectrometer-based rotating double-sided reflective mirror (RDRM) is presented. By introducing the RDRM and corner reflector, an optical path difference (Opd) is generated between the two separated light beams. The instrument is highly stable. Spectral restoration is achieved by the scale, which is precalculated using a laser interferogram. This method suppresses the influence of non-linearity and inherent errors on the restored spectrum. We elaborate on this principle through a theoretical analysis and simulation. Based on a set of design parameters, we successfully restored the spectrum with spectral resolution of 0.25 cm−1 through scale in the case of error (average is –13.88 μm and the mean square deviation is 5.7 μm). The relative spectral mean square error (SMSE) is 0.0013 and the spectral correlation coefficient (SCC) is 0.9997.

A Voltage-Assist 16-Channel Electrochemical Biosensor with Linearity Compensation.

Large capacitive loading of electrodes induces massive error current and imperfect settling in the electrochemical signal acquisition process, leading to inaccurate acquisition results. To efficiently mitigate this inaccuracy, this paper presents a current-and-voltage dual-mode acquisition technique in which a voltage front-end (VFE) is employed to acquire the electrode voltage error and compensate the nonlinearity induced by the electrode capacitive loading. Therefore, the gain and bandwidth requirements of the current front end (CFE) can be relaxed to reduce the complexity and power consumption. With a relieved gain requirement, an inverter-based capacitive trans-impedance amplifier (IB-CTIA) is adopted to boost the input transconductance for low-noise design. By reusing the supply current, the IB-CTIA effectively achieves a low input-referred current noise of 3.9 pArms and a dynamic range (DR) of 126 dB with only 18-μW static power. The prototype chip is fabricated in a 180-nm CMOS process. Interleukin-6 immunoassays (IL-6) are implemented to verify the chip's performance. With the proposed nonlinear error compensation, the correlation coefficient of the detection result is improved from 0.951 to 0.980 and the limit of detection (LoD) is reduced from 8.31 pg/mL to 6.90 pg/mL.

Research on CNC programming and machining process based on CAD/CAM technology

Abstract Focusing on CNC process data, this paper provides an in-depth analysis, characterization and mining of macro machining processes by associating CAD and CAM models. The article introduces a Bayesian inference method to construct an association relationship between the manufacturing features of the query part and the macroscopic process of the manufactured part, which avoids the need for a direct similarity comparison between the geometry of the query part and the part to be manufactured. In addition, the study calculated the overall similarity between the query part and the CNC programming process data instances through the guidance of the process skeleton, thus realizing the precise evaluation from the CNC programming perspective. The algorithm for generating tool trajectories in multi-axis CNC programming is analyzed. By selecting representative surfaces and performing tool processing calculations, this study explores the process planning and tool parameter selection of usual parts of surfaces in multi-axis CNC programming machining. It optimizes the nonlinear error in tool trajectory processing by combining CAD/CAM technology. The results show that the optimized process proposed in this paper significantly improves the machining efficiency by 36.94%. In the cutting at tool corners, the maximum cutting force generated by the optimized machining process is only 190.3N, which is only 67.2% of the leading cutting force of the Cimatron process. In addition, when the engagement frequency is 780 Hz, the optimized process proposed in this paper has the smallest vibration amplitude, which is only 21.4% of the Cimatron strategy. Therefore, this study significantly improves the machining efficiency while ensuring the machining quality, which has important practical application value.

In-field calibration of triaxial accelerometer based on PE-ANGO

Abstract This paper presents a new method for in-field calibration of accelerometers to address the problems of low efficiency and high cost associated with traditional calibration methods. A nonlinear mathematical model of the accelerometer is established, and the cost function is analysed and deduced the cost function. Then, an adaptive Northern Goshawk Optimisation (NGO) algorithm based on prior knowledge enhancement is introduced. A method of collecting multi-position data with a hand-held accelerometer is introduced, and the proposed algorithm is used to in-field calibrate nine parameters of the accelerometer’s nonlinear error model. In addition, simulation is used to compare the results of calibrating the accelerometer using the proposed algorithm and the original algorithm, demonstrating the superiority of the proposed algorithm. Finally, experimental results confirm that the proposed method can rapidly calibrate accelerometer error parameters without relying on complex equipment and with greater accuracy than traditional methods.

Measurement Accuracy Improvement of Homodyne Laser Diode Interferometer by Real-Time Nonlinear Error Suppressing

Measurement Accuracy Improvement of Homodyne Laser Diode Interferometer by Real-Time Nonlinear Error Suppressing

General Self-Correction Algorithm for Nonlinear Errors Based on the Real-Time Generative Look-Up-Table

General Self-Correction Algorithm for Nonlinear Errors Based on the Real-Time Generative Look-Up-Table

A Real-Time Determination Method for Homodyne Grating Interferometer Signal Nonlinear Error Based on Duty Cycle Measurement of States

A Real-Time Determination Method for Homodyne Grating Interferometer Signal Nonlinear Error Based on Duty Cycle Measurement of States

Visual Heading-Aided Pedestrian Navigation Method Based on Factor Graph in Indoor Environment

The main error in traditional inertial pedestrian navigation is caused by unobservable heading errors with only zero velocity constraints. In this paper, a human posture model aided optimized fusion framework based on dominant events for pedestrian navigation is proposed to precisely locate pedestrians. Optimization is performed only at the moment of dominant events to reduce computational effort and improve the robustness. This model can fit the preferred heading information between two dominant events for fusion to improve accuracy. The optimization-based framework can also reduce the non-linear error by re-linearizing the state and associating constraints to the historical state to estimate the biases better. Besides, a hybrid visual heading angle estimation method is proposed by leveraging the Manhattan World hypothesis to obtain a drift-free heading angle with a monocular camera. The hypothesis is searched in the designated region based on histogram quality assessment that can improve the robustness and significantly reduce the computational amount. With low-cost devices, the multiple indoor experiments show that the proposed method can achieve 0.11% positioning accuracy comparable to traditional algorithms which require numerous conditions to be met in good environments. And achieving over 70% improvement in accuracy over traditional methods in complex environments.

Nonlinear error compensation algorithm for signal resolution of chromatic confocal measurements

The mechanisms of the nonlinear error, primarily stemming from the deviation of the polynomial model fitting the wavelength-distance mapping relationship in chromatic confocal measurement, have been elucidated. A compensation method is proposed for the nonlinear error, based on a regression tree model. Through calibration experiments using our chromatic confocal sensor, an impressive improvement of over 40 % in precision could be achieved by our proposed compensation method, which advances from ±1 μm to ±0.6 μm within a 4 mm measurement range.