High-performance multi-parameter fiber sensor by grating-enhanced Mach-Zehnder interference.

A multi-parameter dual-core fiber sensor is proposed to realize highly sensitive detection of illumination, temperature, and humidity, separately. Through partial grating etching of a one-side core, the interaction between the core and the external environment is enhanced. Then, combining the Mach-Zehnder effect of the dual core, a higher sensing sensitivity is obtained. Experimental results show the temperature sensitivity is higher than 6.1952 nm/°C. Besides, the humidity and illumination resolution can reach as accurate as 0.041 relative humidity (RH) and 0.025 light units, respectively. To have better multi-parameter sensing and demodulation, the deep learning algorithm of a one-dimensional convolutional neural network (1D-CNN) is used to reach an accuracy of 99.05% with ∼2.00 root mean square error (RMSE). We envision such an excellent multi-parameter sensor can be promising in environmental monitoring and intelligent manufacturing.

Fast structured illumination microscopy with a large dynamic measurement range.

Fast structured illumination microscopy plays an important role in micro-nano detection due to the features of high accuracy, high efficiency, and excellent adaptability. The existing method utilizes the linear region of the axial modulation response curve (AMR), and by building the relationship between the modulation and the real height, achieves topography recovery. However, the traditional method is limited to narrow dynamic measurement range due to the linear region of the AMR being very short. In this paper, a double-differential fast structured illumination microscopy (DDFSIM) is proposed. By introducing two additional detectable branches for building the double-differential axial modulation response curve (DDAMR), the proposed method can obtain a large dynamic measurement range. In the measurement, three charge-coupled devices are respectively placed in and behind and before the focal plane to generate three axial modulation response curves. Three AMRs are used to set up the DDAMR, which has a large dynamic measurement range. Through simulation and experimental verification, the measurement range of DDFSIM is twice that of the conventional method under the same system parameters.

Fast structured illumination microscopy with reflectance disturbance resistibility and improved accuracy.

The conventional fast structured illumination microscopy (FSIM) without vertical scanning has been proposed by Lee for fast surface profiling. Nevertheless, this method is vulnerable to nonuniform surface reflectivity which is generally caused by the different reflection characteristic of hybrid materials and the environmental fluctuations. Consequently, traditional IFSIM cannot be used in the profile measurement for the samples with surface heterogeneity. In this paper, an improved FSIM configuration (IFSIM) is explored for improving the axial accuracy and suppressing the disturbance of the reflectivity. With this technique, a sinusoidal pattern produced by the digital micro-mirror device (DMD) is illuminated onto the sample. The reflected patterns are captured by two charge-coupled devices (CCDs) that are separately placed in and behind or before the focal plane. The subtraction and sum values of the two axial modulation response curves (AMRs) are divided as the new response function, which effectively suppresses the influence of the inhomogeneous reflectivity. Both wide dynamic range and enhanced axial accuracy can be selectively obtained by controlling the defocusing amount of the two differential detectors. The theoretical analysis and experiments are conducted to verify the feasibility of this method.

Accurate surface profilometry using differential optical sectioning microscopy with structured illumination.

A differential optical sectioning microscopy with structured-illumination (DOSM-SI) with enhanced axial precision is explored in this paper for three-dimensional (3D) measurement. As the segment of data on the linear region of the contrast depth response curve (CDR) is very sensitive to variation of the height information, the DOSM-SI introduces a new CDR2 with an axial shift to intersect the linear region of the CDR1, which is achieved by using two charge-coupled detectors (CCDs) in the optical path. The CCD1 is located on the imaging plane and the CCD2 is displaced from the imaging plane. The difference between the CDR1 and CDR2 for each pixel is defined as the differential depth response curve (DCDR). Further, the zero-crossing point of the DCDR for each pixel is accurately extracted using the line-fitting technique, and finally, the sample surface can be reconstructed with a high resolution and precision. Since the slope around the zero-crossing point of the DCDR is apparently larger than that of near the focal position, an enhanced resolution and precision can be realized in DOSM-SI. The experiments and theoretical analysis are elaborated to demonstrate the feasibility of DOSM-SI.

Fast surface profilometry utilizing structured illumination microscopy based on the time-domain phase-shift technique.

Structured illumination microscopy (SIM) has attracted much research interest due to its high accuracy, strong adaptability, and high efficiency. Existing SIM is mainly based on the phase-shift technique, Hilbert transform technique, and global Fourier transform technique. The phase-shift technique is most widely applied for its higher accuracy, and both the phase-shift technique and Hilbert transform technique suffer from lower speed because multiple images are needed to obtain modulation information for each scanning step. The global Fourier transform technique has a higher speed, but the high-frequency information of the sample will inevitably be lost because a filter window is used. As a result, the global Fourier transform technique is limited to smooth surfaces. In this paper, a fast surface profilometry using SIM is proposed. It is based on the time-domain phase-shift technique (SIM-TPT), which combines one-fringe projection and phase shift. In this proposed measurement system, vertical scanning of the object is synchronized with the switching of the phase-shifted fringe pattern. As a result, only one fringe pattern must be projected, which enables a point-to-point processing defined as the local Fourier transform method in this paper to be utilized to extract the modulation information that will preserve the high-frequency information of the image so it can be applied to both smooth and rough surfaces. Compared to conventional SIM, SIM-TPT has a higher speed because it is a simpler system and can be applied to complex structures such as high roughness surfaces and steep edges.

Surface and thickness measurement of transparent thin-film layers utilizing modulation-based structured-illumination microscopy.

In this research, an approach called modulation-based structured-illumination microscopy (MSIM) is proposed to measure the surface and thickness profile of thin film layers. With this method, a sinusoidal fringe pattern generated by digital micro-mirror devices (DMD) is projected on the sample. The modulation estimation of the reflected patterns is implemented for characterizing the surface and thickness profile of the sample. The measurement system is relatively simple and only an ordinary objective is enough to achieve imaging of the sample. In addition, the reflected signals come from the back surface of the film create less disturbance to the front surface compared with white-light interferometry. Consequently, they can be easily distinguished and achieve a successful measurement precisely. Both simulation and experiments are carried out to demonstrate the availability of this MISM method. The results are in excellent agreement with commercial stage profiler and the relative uncertainty is less than 10 nm.

Curiosity model policy optimization for robotic manipulator tracking control with input saturation in uncertain environment.

In uncertain environments with robot input saturation, both model-based reinforcement learning (MBRL) and traditional controllers struggle to perform control tasks optimally. In this study, an algorithmic framework of Curiosity Model Policy Optimization (CMPO) is proposed by combining curiosity and model-based approach, where tracking errors are reduced via training agents on control gains for traditional model-free controllers. To begin with, a metric for judging positive and negative curiosity is proposed. Constrained optimization is employed to update the curiosity ratio, which improves the efficiency of agent training. Next, the novelty distance buffer ratio is defined to reduce bias between the environment and the model. Finally, CMPO is simulated with traditional controllers and baseline MBRL algorithms in the robotic environment designed with non-linear rewards. The experimental results illustrate that the algorithm achieves superior tracking performance and generalization capabilities.