Search

Background Pretreatment is a critical step required for efficient conversion of woody biomass into biofuels and platform chemicals. Fungal pretreatment is regarded as one of the most promising technology for woody biomass conversion but remains challenging for industrial application. The exploration of potential fungus strain with high efficient delignification and less processing time for woody biomass pretreatment will be valuable for development of biorefinery industry. Here, a newly isolated white-rot basidiomycete Peniophora incarnate T-7 was employed for poplar wood pretreatment. Results The chemical component analysis showed that cellulose, hemicellulose and lignin from poplar wood declined by 16%, 48% and 70%, respectively, after 7 days submerged fermentation by P. incarnate T-7. Enzymatic saccharification analysis revealed that the maximum yields of glucose and xylose from 7 days of P. incarnate T-7 treated poplar wood reached 33.4% and 27.6%, respectively, both of which were enhanced by sevenfold relative to the untreated group. Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), X-ray diffraction (XRD) and pyrolysis gas chromatography–mass spectrometry (Py-GC/MS) characterization confirmed that lignocellulosic structure of poplar wood was largely broken by P. incarnate T-7, including delignification and de-crystalline of cellulose. Meanwhile, lignin component of poplar wood was selectively degraded by P. incarnate T-7, and G-type unit of lignin was preferentially attacked by the strain. Furthermore, quantitative proteomic analysis revealed that a considerable amount of lignocellulolytic enzymes were detected in the secretory proteins of P. incarnate T-7, especially with high abundance of lignin-degrading enzymes and hemicellulases. Combination of quantitative proteomic with transcriptomic analysis results showed that most of those lignocellulolytic enzymes were highly upregulated on poplar wood substrate compared to glucose substrate. Conclusions This study showed that P. incarnate T-7 could selectively delignify poplar wood by submerged fermentation with short time of 7 days, which greatly improved its enzymatic saccharification efficiency. Our results suggested that P. incarnate T-7 might be a promising candidate for industrial woody biomass pretreatment.

The existing analytical gradient models in phase measuring deflectometry (PMD) usually suffer in the ambiguous problem. To solve this problem, simplification/assumption is often given to the surface shape, which causes non-ignorable measurement error in certain situations. In order to analyze the relation between the surface shape and measurement error when simplification/assumption is used, a ray tracing simulation model is developed in this paper. For any given PMD system setup, the relation between the height/slope variations of test surface and measurement accuracy can be carried out. The corresponding experiment work proves the correctness of this simulation model. The increasing of either the height or slope of object will lead to the exponential aggravating of measurement error. For our experiment setup, the measurement gradient error will be less than 0.5% if the ratio of the distance between the LCD (Liquid Crystal Display) screen and the reference plane and the STD (standard derivation) of object height is larger than 200. Keywords: Phase measuring deflectometry, Optical 3D measurement, Error analysis, Ray tracing model

With the rapid development of electronic industry, higher and higher requirements are placed on the surface quality of optical components in electronic devices. Structured-Light Modulation Analysis Technique (SMAT) was recently proposed to detect the contamination and defects on specular surfaces. In this paper, the proposed mechanisms and mathematical models of SMAT are analyzed and established based on the theory of photometry and the optical characteristics of contamination and defects for the first time. What's more, a novel transmission system adopting SMAT is especially designed for the defect detection of transparent objects. For both reflection and transmission system, simulations and experiments were conducted, and comparative studies with uniform planar illumination were also carried out. Simulations on the influence of incident light source region showed that SMAT can eliminate the interference of ambient light while uniform planar illumination technique cannot. Experiments on samples with specular surface and transparent material demonstrated that the modulation values at the contamination and defects are much less than that at clean and intact place, and defects and contaminations were clearly distinguished based on SMAT, while they were almost indiscernible with uniform planar illumination. Therefore, SMAT can be applied to the whole-field inspection of optical components in industrial environments.

The fringe reflection technique (FRT) has been one of the most popular methods to measure the shape of specular surface these years. The existing system calibration methods of FRT usually contain two parts, which are camera calibration and geometric calibration. In geometric calibration, the liquid crystal display (LCD) screen position calibration is one of the most difficult steps among all the calibration procedures, and its accuracy is affected by the factors such as the imaging aberration, the plane mirror flatness, and LCD screen pixel size accuracy. In this paper, based on the deduction of FRT analytical phase–slope description, we present a novel calibration method with no requirement to calibrate the position of LCD screen. On the other hand, the system can be arbitrarily arranged, and the imaging system can either be telecentric or non-telecentric. In our experiment of measuring the 5000mm radius sphere mirror, the proposed calibration method achieves 2.5 times smaller measurement error than the geometric calibration method. In the wafer surface measuring experiment, the measurement result with the proposed calibration method is closer to the interferometer result than the geometric calibration method.

In modern industrial manufacturing, the demand for the surface inspection of specular objects has become more and more urgent. In this paper, a novel defect detection method with eliminating dust is systematically proposed to inspect surface defects of specular objects. The proposed approach can be applied to the defect detection of silicon wafers, optical lens, cell phone cover glass, etc. Structured-Light Modulation Analysis Technique (SMAT) is adopted to detect defects and dust simultaneously. Meanwhile, according to the discrepancy of polarization states between dust and other places, polarized illumination and a linear polarizer are exploited to photograph dust image exclusively. The dust image is used to remove dust from the modulation image; thus, the purified defect distribution can be obtained. Relevant experiments are also performed to prove the effectiveness of this proposed approach.

In this paper, a new generating technique of sinusoidal fringes for 3D shape measurement is presented. Specifically, a sinusoidal fringe is generated by expanding the inverted image of a filled binary sinusoidal pattern in a specified direction, and further, the phase shift is realized by switching the backlight sources of a set of sinusoidal patterns. In theory, sinusoidal fringes can be formed whether the projection is focused or defocused. Moreover, the technique has the potential for high frame rates due to the way the phase shift is performed. In particular, since the high shape precision of the binary sinusoidal pattern and the high accuracy of the phase shift can be easily realized by the photolithography process, the technique is very easy to implement.

Phase Measuring Deflectometry (PMD) is an effective metrology technique for specular surfaces, but it is hard to achieve rapid measurement precisely with prevenient fringe analysis methods. Inspired by recent successes of deep learning techniques for fringe analysis, we demonstrate for the first time that deep learning can be used to achieve high-precision three-dimensional (3D) measurement of specular surfaces with a single frame. In this research, it is proposed to use depthwise separable convolution to optimize measured results. Experimental results proved that this proposed method has better performance than the existing fringe analysis method employing deep learning.

The fringe projection profilometry (FPP) has obtained increasing popularity in the field of industrial automation, inverse engineering and graphics. Recent literature reveals that the non-ideal system point spread function (PSF) in FPP will cause phase error in the area around the discontinuous edge. Existing error reduction methods need to detect the location of all the edges accurately first, which are hard to accomplish when the camera is defocused. Meanwhile, the corrected data in the error area relies heavily on the data in its nearest unaffected area, which makes the corrected data unreliable. We prove that the non-ideal system PSF will also induce phase error in the area of surface details, and this is a problem seldom discussed in FPP. In this work, the relationships between the PSF-induced phase error and system parameters are deduced mathematically and numerically. Additionally, a deconvolution-based method is proposed to reduce the PSF-induced phase error in this paper. The proposed method can overcome the shortcomings of the existing approaches. Both simulation and experiment results show that our proposed method can reduce the Root Mean Square phase/height error by up to 4 times, and can also improve the measured 3D details significantly.

In recent years, phase measuring deflectometry (PMD) has become a popular method to measure the shapes of specular surfaces. However, the inherent slope-height ambiguity problem, which indicates the phase of the recorded fringe pattern is determined by both the height and slope of the test surface, causes considerable ambiguity errors in the measurement results. Existing error reduction methods usually require the initial shape information of the test surface or additional equipment to assist the measurement. These requirements make measurement inflexible in some situations. In this paper, the slope-height ambiguity problem in PMD is modelled and analyzed analytically for the first time, and the system geometry requirements of minimizing the ambiguity error are carried out accordingly. To meet these requirements, a co-axis optical path setup with a telecentric imaging system is proposed. In our simulation and experiment, this system reduces the phase and height errors by up to two orders of magnitude, compared to those from the normally employed system geometry setup.

The ability to accurately estimate the location and geometry of holes is often required in the field of quality control and automated assembly. Projected fringe profilometry is a potentially attractive technique on account of being non-contacting, of lower cost, and orders of magnitude faster than the traditional coordinate measuring machine (CMM). However, we demonstrate in this paper that fringe projection is susceptible to significant (hundreds of µm) measurement artefacts in the neighbourhood of hole edges, which give rise to errors of a similar magnitude in the estimated hole geometry. A mechanism for the phenomenon is identified based on the finite size of the imaging system’s point spread function and the resulting bias produced near to sample discontinuities in geometry and reflectivity. A mathematical model is proposed, from which a post-processing compensation algorithm is developed to suppress such errors around the holes. The algorithm includes a robust and accurate sub-pixel edge detection method based on a Fourier descriptor of the hole contour. The proposed algorithm was found to reduce significantly the measurement artefacts near the hole edges. As a result, the errors in estimated hole radius were reduced by up to one order of magnitude, to a few tens of µm for hole radii in the range 2-15 mm, compared to those from the uncompensated measurements.

Calibration is a crucial step in fringe projection profilometry, which establishes the relationship between unwrapped phase and (FPP) three-dimensional (3-D) shape data (X,Y,h). For an arbitrarily arranged FPP system, a simple geometrical model and mathematical descriptions of the relationships among phase, height distribution, and transverse coordinate are presented. Based on this, a flexible global calibration method is presented to reconstruct 3-D shape by just using a checkerboard with known separation and alternating white and blue. The calibration board is placed at several random positions to determine the relationship between phase and height, and the relationship between pixel position and X, Y coordinates. To get high accuracy, distortion for each pixel is considered. The validity, flexibility, and practicality of this system and calibration technique are verified by experiments.

A color-encoded fringe reflection technique is presented for dynamic specular surface measurement. Only one color-encoded fringe pattern is required in this method. In comparison with the reported dynamic specular surface measuring method (the composite fringe pattern method), the proposed color-encoded fringe technique has higher phase accuracy. The color intensity crosstalk problem between the three channels is discussed. As a result, this problem will seldom affect the phase accuracy of the proposed method. This turns out to be the main reason why the presented method can achieve a higher measuring accuracy than the existing dynamic measurement method. In addition, the proposed color-encoded fringe technique is proven to be more suitable than the existing method for the complex tested surface. The vibrating measuring experiment of a wafer proves the ability of the proposed method to achieve dynamic measurement.