New Aptamer/MoS2/Ni-Fe LDH Photoelectric Sensor for Bisphenol A Determination

Here, a new type of PEC aptamer sensor for bisphenol A (BPA) detection was developed, in which visible-light active MoS2/Ni-Fe LDH (layered double hydroxide) heterostructure and aptamer were used as photosensitive materials and biometric elements, respectively. The combination of an appropriate amount of MoS2 and Ni-Fe LDH enhances the photocurrent response, thereby promoting the construction of the PEC sensor. Therefore, we used a simple in situ growth method to fabricate a MoS2/Ni-Fe LDH sensor to detect the BPA content. The aptasensor based on aptamer/MoS2/Ni-Fe LDH displayed a linear range toward a BPA of 0.05–10 to 50–40,000 ng L−1, and it has excellent stability, selectivity and reproducibility. In addition, the proposed aptamer sensor is effective in evaluating real water samples, indicating that it has great potential for detecting BPA in real samples.

Comparative Study on Characteristics of Partial Discharge Optical Pulse and UHF Pulse in Switch Equipment

The article explores the performance of the new silicon photoelectric sensor in partial discharge detection, and compares the measured optical pulse with the traditional UHF pulse. Through optical and electrical synchronous partial discharge experiments, the article analyzes and discusses the detection performance, working characteristics and statistical characteristics of various sensors, and explores the advantages and feasibility of silicon photoelectric partial discharge sensors in actual discharge monitoring; In addition, the statistical performance of the two physical phenomena of partial light radiation and electromagnetic radiation was obtained through the analysis of optical and electrical synchronous monitoring data. Compared with UHF sensor, silicon photoelectric sensor under the optimal working voltage has a higher signal-to-noise ratio (SNR); Under the electromagnetic interference of the high-frequency motor, silicon photoelectric sensor exhibits better anti-electromagnetic interference ability; Discharge phase interval and characteristics reflected by the PRPD obtained by two detection methods maintain good consistency; Pulse repetition rate has the same trend with applied voltage, but statistical frequency of optical pulses obtained is higher than that of electromagnetic pulses because silicon photoelectric sensor has a higher SNR and single-photon sensitivity.

Digital Garbage System using Arduino NANO

Garbage bins or dust bins are those that are put in public places in cities and are currently overflowing due to an increase in waste every day. It harms people's health by spreading deadly infections. To avoid this, smart bins will be designed with sensors such as an infrared sensor, a weight sensor, a photoelectric sensor, and radio frequency identification (RFID) card reader. If someone throws trash into the smart bins, a photoelectric sensor will identify the clear representation objects, and a weight sensor will be positioned beneath the smart bin to calculate the percentage of garbage present it will forward the information to the authorities in charge of that specific location. As a result, the relevant authorities can get messages until the bin is squished, and each bin is assigned a unique ID, which will appear on the screen of the respected officer, allowing them to take fast action. If a person is within two meters radius of the bin that contains an RFID CARD READER, the RFID reader will read all of that person's information and send a message to him about what they placed into the bin, as well as an appreciation message for using the bin. Keywords: Arduino NANO, GSM Module, Smart Dustbin, IoT, Arduino Uno.

Progress in ZnO Nanosensors

Developing various nanosensors with superior performance for accurate and sensitive detection of some physical signals is essential for advances in electronic systems. Zinc oxide (ZnO) is a unique semiconductor material with wide bandgap (3.37 eV) and high exciton binding energy (60 meV) at room temperature. ZnO nanostructures have been investigated extensively for possible use as high-performance sensors, due to their excellent optical, piezoelectric and electrochemical properties, as well as the large surface area. In this review, we primarily introduce the morphology and major synthetic methods of ZnO nanomaterials, with a brief discussion of the advantages and weaknesses of each method. Then, we mainly focus on the recent progress in ZnO nanosensors according to the functional classification, including pressure sensor, gas sensor, photoelectric sensor, biosensor and temperature sensor. We provide a comprehensive analysis of the research status and constraints for the development of ZnO nanosensor in each category. Finally, the challenges and future research directions of nanosensors based on ZnO are prospected and summarized. It is of profound significance to research ZnO nanosensors in depth, which will promote the development of artificial intelligence, medical and health, as well as industrial, production.

An Improved Sum of Squared Difference Algorithm for Automated Distance Measurement

In recent years, with improvement of photoelectric conversion efficiency and accuracy, photoelectric sensor was arranged to simulate binocular stereo vision for 3D measurement, and it has become an important distance measurement method. In this paper, an improved sum of squared difference (SSD) algorithm which can use binocular cameras to measure distance of vehicle ahead was proposed. Firstly, consistency matching calibration was performed when images were acquired. Then, Gaussian blur was used to smooth the image, and grayscale transformation was performed. Next, the Sobel operator was used to detect the edge of images. Finally, the improved SSD was used for stereo matching and disparity calculation, and the distance value could be obtained corresponding to each point. Experimental results showed that the improved SSD algorithm had an accuracy rate of 95.06% when stereo matching and disparity calculation were performed. This algorithm fully meets the requirements of distance measurement.

Design and Simulation Analysis of Simultaneous Localization and Mapping System for Robot Using Multi Photoelectric Sensors

Robot technology integrates motion control, information fusion and wireless communication technology. Among them, simultaneous localization and mapping (SLAM) technology is the key to realize robot autonomous navigation. In this exploration, multi photoelectric sensors are used for information fusion to solve the nonlinear and uncertain problems of robot navigation system in obstacle avoidance. The acoustic optical sensor and photoelectric sensor are integrated to collect the information of the surrounding environment. The photoelectric encoder of the drive motor is used to control the direct current machine with fuzzy PID closed-loop control. The methods of extended Kalman filter based SLAM (EKF-SLAM) and particle filter based SLAM (PF-SLAM), which are commonly used in navigation problems, are studied and compared. The proposed SLAM system adopts ARM11 high performance processor structure of S3C6410. ARM processor is responsible for task management, input and output, acoustic optical sensor can provide distance and position information, and photoelectric sensor can provide two-dimensional plane information. Their information fusion helps to restore the three-dimensional information of the environment around the robot. In the simulation analysis, the robot moves in a circular way on the horizontal ground. SLAM algorithm based on the information fusion of multi photoelectric sensors can help the robot better perceive the surrounding environment in unknown environment, increase the movement distance and reduce the overall positioning error; the robot can avoid obstacles well in autonomous mode after hardware and algorithm debugging. In the remote control mode, the movement of the robot can be adjusted by controlling the direction.

Photoelectric Sensor Circuit and Image Segmentation Method for Radar System

In this exploration, based on the principle and system parameters of laser three-dimensional (3D) radar imaging technology, the corresponding photoelectric sensor circuit scheme is formulated. The sense circuit of avalanche photon diode (APD) converts the signal through the transresistance amplifier circuit. Then, LMH6629 is selected as a precision amplifier with low input noise voltage and low input error current. The capacitance is used as a compensation element to compensate the phase. For the power supply scheme, choosing the mode of switching power supply and LDO to work together can improve the efficiency of power supply and reduce the output of current ripple. At the same time, semantic segmentation is carried out for the obtained photoelectric images. Based on the traditional spatial pyramid pooling algorithm, the fusion of mean intersection over union and cross information entropy loss function is introduced to improve the weight of local image region. In the experiment, Multisim software is used to simulate the circuit. The APD reverse bias voltage is set to 90 V, and the multiplication coefficient is 98.7. The feedback resistance, bandwidth, phase compensation capacitance and other parameters are further calculated. It is found that there is obvious self-excited phenomenon in the output waveform of the transresistance amplifier without phase compensation capacitor. When the feedback capacitance reaches 0.8 pF, the oscillation phenomenon is obviously reduced; further calculation shows that the bandwidth of transresistance amplifier is 230 MHz, and the noise of APD power supply is mainly caused by BUCK switching power supply switch when the bottom noise of oscilloscope is ignored. However, the noise is suppressed under the action of the back-end LDO device; after the loss function is introduced, the contour of the photoelectric image is preserved completely, and then the more accurate segmentation results are obtained.

Application of Photoelectric Sensor in Control of Industrial Robot

Indoor positioning and automatic charging technology of the robot is an important indicator to test intelligent control of robot. The surrounding condition is collected by acousto-optic sensor and photoelectric sensor, and the closed-loop control of DC motor is realized based on Fuzzy PID. The system integrates multiple photoelectric sensors and uses high-performance processor, S3C6410 ARM11, as the core instead of PC, reducing the power consumption and cost, so as to complete the acquisition of ranging information. And the environment image is obtained for image processing. The infrared docking method is adopted in the docking process, that is, three infrared transmitting tubes in the charging dock emit different positions, and the position relative to the charging dock is judged according to the number of received signals. In the experiment, the positioning error of industrial robot is about 1%, which can meet the requirements of indoor positioning. The docking success rate of automatic charging is more than 98%, and the time spent is less than 65 seconds, which satisfies with the requirements of automatic charging.