Linear Charge-coupled Device Research Articles

Development of a cost-effective confocal Raman microscopy with high sensitivity

Confocal Raman microscopy is a powerful technique for identifying materials and molecular species; however, the signal from Raman scattering is extremely weak. Typically, handheld Raman instruments are cost-effective but less sensitive, while high-end scientific-grade Raman instruments are highly sensitive but extremely expensive. This limits the widespread use of Raman technique in our daily life. To bridge this gap, we explored and developed a cost-effective yet highly sensitive confocal Raman microscopy system. The key components of the system include an excitation laser based on readily available laser diode, a lens-grating-lens type spectrometer with high throughput and image quality, and a sensitive detector based on a linear charge-coupled device (CCD) that can be cooled down to −30 °C. The developed compact Raman instrument can provide high-quality Raman spectra with good spectral resolution. The 3rd order 1450 cm−1 peak of Si (111) wafer shows a signal-to-noise ratio (SNR) better than 10:1, demonstrating high sensitivity comparable to high-end scientific-grade Raman instruments. We also tested a wide range of different samples (organic molecules, minerals and polymers) to demonstrate its universal application capability.

A two-stage framework for pixel-level pavement surface crack detection

Surface crack is one of the most common distresses of pavement structure, impacting its serviceability and sustainability. Over the past decade, many efforts have been devoted to developing computer vision-based models (e.g., image processing- or deep learning-based) for the automatic detection of pavement surface crack. However, there is a great gap between the public image data taken by the phone or other portable devices and the real-world image data acquired by the linear array charge-coupled device (CCD) camera, which usually is high resolution and contains limited crack pixels per image. To improve the pavement surface crack detection efficiency and accuracy in engineering practice, we propose a novel two-stage framework for automatic pavement surface detection at the pixel level. In stage I, the images concluding pixel cracks are selected using a convolutional neural network (CNN)-based classification network. In stage II, the selected images are processed with our proposed separation-combination strategy and the second version of crack transformer (CTv2) for pavement surface crack detection at the pixel level. Comprehensive experimental investigation and comparison have been conducted on training performance and visualization results, validating the superiority of the developed framework. It paves the way for the large-scale application of automatic pavement crack detection in an efficient manner.

Deflection Basin Detection of Pavements Based on Linear Array Charge-Coupled Device (CCD) Photoelectric Sensors

Deflection is an important indicator of the overall pavement strength, and it is generally detected using the Falling Weight Deflectometer (FWD). In response to the shortcomings of FWD in use, a pavement deflection detection method based on a linear array charge-coupled device (CCD) photoelectric displacement sensor is proposed. Firstly, a detailed description is given of the working principle of the deflection detection photoelectric sensor for the center point of the deflection basin and other points. Secondly, a photoelectric displacement sensor using linear array CCD deflection detection is designed, including a laser, CCD signal processing module, CCD and its driver module, and upper computer communication module. Among them, the EPF10K20TC144-4 device of the FLEX 10K series from ALTERA company is used to generate CCD driving pulses; Two DM54LS245 are selected as the driving interface for CCD photoelectric sensors, and corresponding filtering and signal amplification circuits are designed to address the noise problem of CCD photoelectric signal injection. Finally, the fixed threshold method separates the background and image signals in the CCD photoelectric signal, and the microcontroller is connected to the serial port of the upper computer through the MAX232 chip. The displacement measurement experiment uses the designed linear array CCD photoelectric displacement sensor. The results show that the road deflection basin detection method by the linear array CCD photoelectric displacement sensor fully meets the actual detection requirements and can obtain dynamic deformation information of the tested road surface. It is helpful for a detailed understanding of the changes in the deflection basin of the road surface under load.

In-Loco Optical Spectroscopy through a Multiple Digital Lock-In on a Linear Charge-Coupled Device (CCD) Array.

Accurate and reliable measurements of optical properties are crucial for a wide range of industrial and commercial applications. However, external illumination fluctuations can often make these measurements challenging to obtain. This work proposes a new technique based on digital lock-in processing that enables the use of CCD spectrometers in optical spectroscopy applications, even in uncontrolled lighting conditions. This approach leverages digital lock-in processing, performed on each pixel of the spectrometer's CCD simultaneously, to mitigate the impact of external optical interferences. The effectiveness of this method is demonstrated by testing and recovering the spectrum of a yellow LED subjected to other light sources in outdoor conditions, corresponding to a Signal-to-Noise Ratio of -70.45 dB. Additionally, it was possible to demonstrate the method's applicability for the spectroscopic analysis of gold nanoparticles in outdoor conditions. These results suggest that the proposed technique can be helpful for a wide range of optical measurement techniques, even in challenging lighting conditions.

Compact surface plasmon resonance sensor using the digital versatile disc grating as a coupler and a disperser

Compact surface plasmon resonance (SPR) sensors are highly demanded due to their small size, low cost, and wide application scenarios compared with benchtop sensors. To realize high-precision spectral or angular analysis, most compact SPR sensors need spectrometers or rotation stages, which increase the cost of the device. We demonstrate a low-cost and compact SPR sensor by utilizing a single grating as a coupler and a disperser. The polychromatic light emitted from a light-emitting diode was coupled to surface plasmon modes by a grating made from a digital versatile disc-recordable disc. The light was dispersed by the same grating and collected by a linear charge-coupled device. The real-time detection of the SPR spectra and the resonant wavelengths was realized by homemade software based on the laboratory virtual instrument engineering workbench. By measuring different concentrations of glucose solution and sodium chloride solution, we obtain a high refractive index (RI) resolution of 5.52 × 10 − 5 RI unit. This compact SPR sensor can be applied in the areas of food safety, environmental monitoring, medical diagnosis, and so on.

Sugarcane Node Detection Method Based on Photoelectric Sensor Vertical Projection Signal Processing

Highlights A linear array CCD sensor is utilized to obtain the contour signal of the vertical projection of the sugarcane. A method is provided for continuously identifying and locating sugarcane nodes. Examines the impact of scan speed and illumination on the accuracy of identification. The method performs well regarding identification rate, precision, and efficiency. Abstract. In order to achieve continuous and dynamic detection of sugarcane nodes, improve the automatic production efficiency of pre-cut sugarcane seed, and lower the cost of mechanized sugarcane production, a detection method based on linear array charge-coupled device (CCD) photoelectric sensor signal processing was developed. Firstly, the mechanical drive unit was controlled to drive the photoelectric detection system to acquire the signal of the vertical projection of the sugarcane profile. The projection information was then binarized into profile information using the Otsu algorithm. The profile signal was then decomposed using a variable mode decomposition algorithm optimized based on the sparrow search algorithm, and the component reflecting the node content was regarded as the feature signal. Finally, the position of the wave peaks above the judgment threshold in the normalized feature signal was considered the position of the sugarcane nodes. One-way and two-way experiments were conducted to investigate the effects of scan speed and illuminance on identification precision. The results showed that the identification rate, average response time, and average error values were 98.40%, 0.13 s, and 1.36 mm at a scan speed of 75 mm/s and an illuminance of 91.91 lx. Compared to other node identification methods discussed in this article, the proposed method has a high identification rate and accuracy with a high response speed, which can improve the automation efficiency of sugarcane seed production. Keywords: Identification accuracy, Non-contact detection, Photoelectric sensor, Precision agriculture, Seed production, Signal processing, Sugarcane node, Variational mode decomposition.

Air-based contactless wafer precision positioning system: Contactless sensing using charge coupled devices

This paper presents the development of a contactless sensing system and the dynamic evaluation of an air-bearing based precision wafer positioning system. The contactless positioning stage is a response to the trend seen in the high-tech industry, where the substrates are becoming thinner and larger to reduce the cost and increase the yield. Using contactless handling it is possible to avoid damage and contamination. The system works by floating the substrate on a thin film of air. A viscous traction force is created on the substrate by steering the airflow. A cascaded control design structure has been implemented to the contactless positioning system, where the Inner Loop Controller (ILC) controls the actuator which steers the airflow and the Outer Loop Controller (OLC) controls the position of the substrate by controlling the reference of the ILC. The dynamics of the ILC are evaluated and optimized for the performance of the positioning of the substrate. The vibration disturbances are also handled by the ILC. The bandwidth of the system has been improved to 300 Hz. For the OLC a linear charge-coupled device has been implemented as a contactless sensor. The performance of the sensing system has been analyzed. During control in steady state, this resulted in a position error of the substrate of 12.9 [Formula: see text]m RMS, which is a little more as two times the resolution. The bandwidth of the OLC is approaching 10 Hz.

Air-Based Contactless Wafer Precision Positioning System

This paper presents the development of a contactless sensing system and the dynamic evaluation of an air-bearing-based precision wafer positioning system. The contactless positioning stage is a response to the trend seen in the high-tech industry, where the substrates are becoming thinner and larger to reduce the cost and increase the yield. Using contactless handling it is possible to avoid damage and contamination. The system works by floating the substrate on a thin film of air. A viscous traction force is created on the substrate by steering the airflow. A cascaded control design structure has been implemented on the contactless positioning system, where the inner loop controller (ILC) controls the actuator which steers the airflow and the outer loop controller (OLC) controls the position of the substrate by controlling the reference of the ILC. The dynamics of the ILC are evaluated and optimized for the performance of the positioning of the substrate. The vibration disturbances are also handled by the ILC. The bandwidth of the system has been improved to 300 Hz. For the OLC, a linear charge-coupled device has been implemented as a contactless sensor. The performance of the sensing system has been analysed. During control in steady-state, this resulted in a position error of the substrate of 12.9 μm RMS, which is a little more than two times the resolution. The bandwidth of the OLC is approaching 10 Hz.

Multi-projectiles Target Data Association Algorithm Based on D-S Evidence Theory

In the process of accuracy measurement of multi-projectile intersection target, aiming at the problem of multi-projectile target matching on two imaging planes of linear CCD(Charge Coupled Device), a Time-Dimension ICP(iterative closest point) iterative optimization data association algorithm is designed, and a data association decision algorithm based on D-S(Dempster-Shafer evidence theory) evidence reasoning is proposed. By analyzing the correlation error of multi-projectile target matching, the measure function of ICP iteration optimization is given. According to the basic principle of D-S evidential reasoning and the constraint relationship between two imaging surfaces of a multi-projectile online array camera, the design method of the basic probability assignment function of the number of data association, the mean value of absolute error and the consistency of error are given. According to D-S combination probability distribution, different data association results are reasoned and decided. By designing the distance error function from the point to the polar line, the method is extended to the area array high-speed photographic intersection measurement system. The simulation results show that the proposed algorithm can make effective judgments and give reliable data association results when the projectile data is missing, the projectile data is noisy and the projectile catches up.

Relative radiometric calibration of yaw data without calibration field of hyperspectral images based on harmonic analysis

ABSTRACT Radiometric calibration of satellite sensor could be divided into absolute radiometric calibration and relative radiometric calibration. Relative radiometric calibration can greatly reduce the impact of the sensor’s instability due to many factors like failure to perform calibration experiments or satellite post-operative attenuation. One of the methods is to use the 90° yaw data for relative radiation calibration, where the camera or satellite rotates by 90° so that the linear charge-coupled device (CCD) detector is parallel to the flight direction and sequentially passes through the ground uniform field to obtain the same radiance to achieve the satellite in order to achieve relative radiometric calibration of satellite sensor and eliminate stripe phenomenon in image. The orbita hyperspectral satellites (OHS) are commercial hyperspectral remote sensing satellites with the largest image width and the highest spatial resolution in China. It has realized the operation of multiple hyperspectral satellites network for the first time. However, there are still problems such as inaccurate calculation of radiation calibration parameters, difficulty in realizing uniform field ground, and difficulty in achieving full dynamic calibration of the sensor. In this study, the hyperspectral images acquired by OHS satellites were taken as the research object to propose a method to achieve field-free relative radiometric calibration based on harmonic analysis of yaw data. This method combines the advantages of harmonic analysis technology and the least squares theory and is applied to the relative radiation calibration of hyperspectral yaw data. It is called the harmonic analysis radiometric calibration (HARC) algorithm. First, HARC algorithm performed the first-order forward and reverses harmonic analysis on the 86° yaw data of OHS satellites which were pre-processed into the data of the conventional image mode to obtain the theoretical value of the pre-processed yaw data. Then, the actual radiance value of yaw data in column direction would be fitted to the theoretical value using the least squares theory to calculate the offset and gain of radiometric calibration parameter after eliminating the high and low radiance values in yaw data. Finally, the offset and gain parameters were used to carry out relative radiometric calibration on conventional push-broom satellite image. The comparative analysis of the test showed that relative radiometric calibration of all band images of six pieces of CCD arrays in the hyperspectral sensor of OHS satellites was realized based on yaw data without uniform ground calibration field. The HARC algorithm proposed in this paper can overcome the inaccurate calculation of calibration parameters caused by the yaw angle less than 90°. It not only retains the image detail information but also effectively removes various types of thick and thin stripe noise in the sweep direction, and is not limited by the different bands. The algorithm has good universality in applications on various bands. Qualitative and quantitative comparison analyses were conducted between HARC algorithm and classical relative radiometric calibration methods, and the corrected image has a great improvement in image quality and sharpness compared with the original image. The effect of stripe removal and the accuracy of radiation correction of the HARC algorithm are superior to the classical relative radiation calibration method.

A Novel Linear CCD Variable Velocity Two-Dimensional Imaging Approach Based on Adaptive Image Segmentation

Linear charge coupled device (CCD) camera has been widely used in industrial manufacturing and science research because of its capability of high-resolution digital imaging. To reduced imaging distortion caused by scanning velocity variation, a novel linear CCD variable velocity 2-D imaging approach based on adaptive image segmentation is proposed in this article. An adaptive image segmentation algorithm is presented to calculate the size of image segmentation according to variable scanning velocity. A velocity curve fitting based on discrete interpolation is designed to obtain the scanning velocity in each image segment. Then, by using scanning velocity in each segment, compensation coefficient at each segment is calculated and a cubic spline interpolation based pixel interpolation transformation algorithm is designed to obtain the whole corrected image. Finally, the proposed approach is implemented in a printed circuit board (PCB) linear CCD imaging experiments and the results demonstrated its efficiency.

A Novel Position and Orientation Sensor for Indoor Navigation Based on Linear CCDs.

The position and orientation of a mobile agent, such as robot or drone, etc., should be estimated in a timely way during operation in the structured indoor environment, so as to ensure the security and efficiency of task execution. Concerning the problem that the position and orientation are often estimated separately by different kinds of sensors in the off-the-shelf methods, we design a novel position orientation sensor (POS). The POS consists of four pairs of linear charge-coupled devices (CCDs) and cylindrical lenses, which can estimate the 3D coordinate of the anchor in the POS’s field of view. After detecting at least three anchors in its field of vision sequentially, the Rodrigues coordinate transformation algorithm is utilized to estimate the position and orientation of POS simultaneously. Meanwhile, the position and orientation are estimated at the receiver side. Hence there is no privacy concern associated with this system. The architecture of the proposed POS is symmetrical and redundant, even if one of the linear CCDs or cylindrical lens malfunctions, the whole system could still work normally. The proposed method is cost-effective and easily extends to a wide range. The numerical simulation demonstrates the feasibility and high accuracy of the proposed method, and it outperforms the off-the-shelf methods.

Real-time Grinding Wheel Condition Monitoring Using Linear Imaging Sensor

Grinding is a widely used process in precision finishing of machined part surfaces. Grinding wheels, the key component of the grinding process, consist of a mixture of abrasive grains and bonding materials with or without a metal core. During the grinding process, the grits are either removed or broken on the wheel surface due to multiple mechanisms. Such tool wear on grinding wheel determines the quality of the ground surface as well as the part dimension accuracy and machining efficiency. This work presents a new method to monitor the health status of the grinding wheel using linear Charge-coupled Device (CCD) sensor, which captures one-dimensional grayscale images of the grinding wheel surface. The statistical features were extracted from the sensor data to estimate the present tool wear. Compared to general camera imaging method, the proposed approach is able to achieve high speed sampling with the CCD sensor to scan across the width of wheel in milliseconds, which enables the method a potential solution for monitoring the wheel condition in real-time. The method was tested by capturing surface images of a silicon carbide wheel on a commercial grinding machine. Statistical features such as standard deviation, kurtosis, and entropy were extracted from the grayscale color intensity of the image data and compared to the measured wheel life represented by the counted grinding cycles. The statistical features were fused by an Artificial Neural Network (ANN) model to estimate the life of the grinding wheel. Experimental results show a good match between the estimated and true wheel life with an average error less than 5%.

Micro-Distortion Detection of Lidar Scanning Signals Based on Geometric Analysis

When detecting micro-distortion of lidar scanning signals, current hardwires and algorithms have low compatibility, resulting in slow detection speed, high energy consumption, and poor performance against interference. A geometric statistics-based micro-distortion detection technology for lidar scanning signals was proposed. The proposed method built the overall framework of the technology, used TCD1209DG (made by TOSHIBA, Tokyo, Japan) to implement a linear array CCD (charge-coupled device) module for photoelectric conversion, signal charge storage, and transfer. Chip FPGA was used as the core component of the signal processing module for signal preprocessing of TCD1209DG output. Signal transmission units were designed with chip C8051, FT232, and RS-485 to perform lossless signal transmission between the host and any slave. The signal distortion feature matching algorithm based on geometric statistics was adopted. Micro-distortion detection of lidar scanning signals was achieved by extracting, counting, and matching the distorted signals. The correction of distorted signals was implemented with the proposed method. Experimental results showed that the proposed method had faster detection speed, lower detection energy consumption, and stronger anti-interference ability, which effectively improved micro-distortion correction.

Geometric Calibration for the Aerial Line Scanning Camera GFXJ

The Gao Fen Xiang Ji (GFXJ) is the first Chinese self–developed airborne three–line array charge-coupled devices (CCD) camera and is designed to meet 8 cm ground sample distance (GSD), 0.5 m planimetry accuracy, and 0.28 m elevation accuracy for ground three-dimensional (3D) points at a flight height of 2000 m. These values also meet the 1:1000 scale mapping requirements in China. However, the original direct geopositioning accuracy of the GFXJ is approximately 4 m in the planimetry direction and 6 m in the elevation direction. To meet the ground 3D point accuracy requirements and improve the direct geopositioning accuracy of the GFXJ, this paper carries out a deep investigation on the GFXJ geometric calibration. This geometric calibration includes two main parts: the Global Navigation Satellite System (GNSS) lever arms and inertial measurement unit (IMU) boresight misalignment calibration, and the camera lens and CCD line distortion calibration. First, a brief introduction is given on the imaging properties of the GFXJ camera. Then, the GNSS lever arms and IMU boresight misalignment calibration models are built for the GFXJ camera. Next, a piecewise self-calibration model based on the CCD viewing angle is established for the GFXJ lens and CCD line distortion calibration. Subsequently, an iterative two-step calibration scheme is proposed for the geometric calibration. Finally, experiments were implemented using multiple flight blocks obtained in the Songshan remote sensing comprehensive field and the Hegang area of Heilongjiang Province. Through calibration experiments, geometric calibration values were obtained for the GNSS lever arms and IMU boresight misalignment. Reliable CAM files were independently generated for the forward, nadir, and backward line arrays. The experiments showed that the proposed GNSS lever arms and IMU boresight misalignment calibration models and the piecewise self-calibration model had good applicability and effectiveness for the GFXJ camera. The proposed two-step calibration scheme can significantly enhance the geometric positioning accuracy of the GFXJ camera. The original direct geopositioning accuracy of the GFXJ is approximately 4 m in the planimetry direction and 6 m in the elevation direction. Using the GNSS lever arms and the IMU boresight misalignment calibration values and the CAM files, the positioning accuracy of the GFXJ camera can fulfill the 3D point accuracy requirements and the 1:1000 mapping accuracy requirements at a 2000 m flight height after aerial triangulation with only several ground control points. The planimetry accuracy is approximately 0.2 m, and the elevation accuracy is less than 0.28 m. In addition, the calibration models and calibration scheme established in this paper can provide a reference for calibration studies on other airborne linear array CCD cameras.

Compact two-coordinate digital autocollimator

The paper describes a compact two-coordinate photoelectric digital autocollimator made using a single linear charge-coupled photosensitive device and a special type of autocollimation mark. The autocollimator allows us to measure angles in the horizontal and vertical planes in the range of ±10′. In this case, the maximum error in measuring the angle in the horizontal plane does not exceed ±0.7′′, and in the ±7.5′ angle measurement range, it does not exceed ±0.5′′. The maximum error in measuring the angle in the vertical plane does not exceed ±5′′. The frequency of the output of digital angle measurement data by the autocollimator is 30 Hz.

Optical liquid-level sensor based on a designed light guide plate

An optical liquid-level sensor based on a designed light guide plate (LGP) is proposed and experimentally demonstrated. Light transmits between the two surfaces of the LGP as in an optical waveguide. The front surface of the LGP is planar and contacts the liquid, and the back surface is designed with microstructures to uniform the light distribution by scattering. The uniform light intensity that escapes from the LGP abruptly decreases at the liquid level. A linear charge-coupled device (CCD) near the back surface is used to detect the liquid level by detecting the abrupt decrease in the light intensity. The feasibility of the proposed sensor is proved by a ray-tracing simulation and an experiment. The sensor shows high linearity and accuracy with a measurement error of 0.12 mm. The measurement range can be extended flexibly.

Single-mode fiber-optic Fabry–Perot interferometry sensor based on optical cross-correlation demodulation

A single-mode fiber-optic Fabry–Perot interferometry (FPI) sensor based on optical cross-correlation demodulation is presented, with advantages of both low cost and small size. The sensor mainly consists of a light-emitting diode, a glass wafer, a linear charge-coupled device, a cylindrical lens, a fiber-optic coupler, a sensing head, and a circuit board. The cavity length of the FPI sensor is demodulated by the optical cross-correlation relationship between the glass wafer and the Fabry–Perot cavity. When the cavity length changes, the pixel number corresponding to the peak value of the cross-correlation image shifts accordingly. To optimize the demodulation parameters, a simulation model is established. The experimental results show that the resolution and variation range of cavity length measurement are achieved to be 0.6 nm and ±4 μm, respectively. The proposed fiber-optic sensor is promising for the temperature and pressure measurements in circumstances of intense electromagnetic interference and long distance.

Resonant Wavelength Shift Detection System Based on a Gradient Grating Period Guided-Mode Resonance

A resonant wavelength detection system based on a gradient grating period guided-mode resonance (GGP-GMR) filter and a linear charge-coupled device is demonstrated. The GGP-GMR used in this work consists of a subwavelength grating structure with a grating period that varies from 250 to 550 nm in increments of 2 nm. We successfully demonstrate that by using this system, we can monitor the shift in a sensor's dip wavelength caused by different sucrose concentrations. This technology has the potential to replace the spectrometer used in most optical biosensor systems. Given its compactness, the system can be integrated with lab-on-a-chip systems for numerous biosensing applications.

General Model of Photon-Pair Detection with an Image Sensor.

We develop an analytic model that relates intensity correlation measurements performed by an image sensor to the properties of photon pairs illuminating it. Experiments using an effective single-photon counting camera, a linear electron-multiplying charge-coupled device camera, and a standard CCD camera confirm the model. The results open the field of quantum optical sensing using conventional detectors.