Photoelectric Sensor Research Articles

Photoelectric sensor array-based measurement method for the key motion parameters of the small flying object considering non-uniform curve trajectory

Purpose The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It proposes a measurement method and its calculation model of non-uniform curve trajectory using a photoelectric sensor array. Design/methodology/approach First, the basic composition of the measurement system and mechanism of photoelectric sensor array are described, respectively. Second, a non-uniform curve mathematical measurement model is constructed differently from the traditional linear trajectory, taking into account the influence of gravity and air resistance. Third, the measurement error of the system is analyzed through numerical simulation. Finally, the accuracy and feasibility of the approach are verified by live-ammunition experiments. Findings The results show that the systematic error of the hitting point coordinates can be reduced by 9% compared to the traditional linear measurement model. Consequently, this method can meet the higher measurement requirement for the key motion parameters of the small flying object under the non-uniform curve trajectory. Research limitations/implications (if applicable)- although the approach itself is generalizable, the method is unable to detect the motion parameters of multiple small flying objects. Research limitations/implications Although the approach itself is generalizable, the method is unable to detect the motion parameters of the multiple small flying objects. Practical implications It is evident that the proposed non-uniform curve measurement model is more precise in quantifying the essential characteristics of the small flying object, particularly in consideration of the environmental conditions. Social implications The precise measurement of the key motion parameters of the small flying object can facilitate the enhancement of the protective performance of protective materials. Originality/value A novel approach to measurement is proposed, which differs from the conventional uniform trajectory model. To this end, the space construction of the photoelectric sensor array is optimized. The number of the sensors is revised.

Textile Fabric Defect Detection Using Enhanced Deep Convolutional Neural Network with Safe Human–Robot Collaborative Interaction

The emergence of modern robotic technology and artificial intelligence (AI) enables a transformation in the textile sector. Manual fabric defect inspection is time-consuming, error-prone, and labor-intensive. This offers a great possibility for applying more AI-trained automated processes with safe human–robot interaction (HRI) to reduce risks of work accidents and occupational illnesses and enhance the environmental sustainability of the processes. In this experimental study, we developed, implemented, and tested a novel algorithm that detects fabric defects by utilizing enhanced deep convolutional neural networks (DCNNs). The proposed method integrates advanced DCNN architectures to automatically classify and detect 13 different types of fabric defects, such as double-ends, holes, broken ends, etc., ensuring high accuracy and efficiency in the inspection process. The dataset is created through augmentation techniques and a model is fine-tuned on a large dataset of annotated images using transfer learning approaches. The experiment was performed using an anthropomorphic robot that was programmed to move above the fabric. The camera attached to the robot detected defects in the fabric and triggered an alarm. A photoelectric sensor was installed on the conveyor belt and linked to the robot to notify it about an impending fabric. The CNN model architecture was enhanced to increase performance. Experimental findings show that the presented system can detect fabric defects with a 97.49% mean Average Precision (mAP).

On-Chip NADH Detection in Multicellular Models Using an AlGaN/GaN Photodetector Array with Enhanced Sensitivity.

Nicotinamide adenine dinucleotide (NAD) is a pivotal coenzyme, existing in its oxidized form (NAD+) and reduced form (NADH). Both are essential in cellular redox reactions and are implicated in energy production and cancer. Current NADH detection methods often involve complex optical measurements. We propose a miniaturized, on-chip photoelectric sensor array using AlGaN/GaN two-dimensional electron gas (2DEG) photodetectors for NADH quantification. The device exhibits an ultralow dark current and ultrahigh UV light responsivity, enabling sensitive NADH detection. By exploiting the absorbance disparity between NADH and NAD+, our sensor achieves rapid, sensitive detection, surpassing commercial assays. It effectively detects NADH levels in 3D multicellular models, promising cancer screening and monitoring. This sensor platform offers a significant advancement in NADH quantification, with the potential for high-throughput testing and point-of-care diagnostics. Our study presents an efficient approach for NADH sensing, addressing the need for rapid and sensitive detection methods in biomedical research and clinical practice.

Reduction in Optical Feedback Noise of Atomic Force Microscopy by High-Frequency Current Modulation

Introduction: With the advancement of technology, nanotechnology has emerged as a prominent research field. The Atomic Force Microscope (AFM) serves as a vital tool in nanoscience and technology, playing an indispensable role across various domains. Method: However, in the AFM photoelectric sensing system, the optical feedback noise from the beam deflection method can lead to inaccuracies in signal identification and analysis, impacting the accuracy and reliability of AFM measurements. To mitigate this interference, this study proposes a highfrequency current superposition system aimed at reducing optical feedback noise. By superimposing high-frequency currents, the semiconductor laser transitions from a single-mode to a multi-mode operational state, thereby altering its mode of operation and consequently reducing optical feedback noise during sensing. Initially, mathematical modeling and simulation analysis were conducted on the high-frequency current superposition noise reduction system to examine the impact of high-frequency current on the intensity noise of the semiconductor laser. Subsequently, the design of the high-frequency current superposition noise reduction system was outlined, encompassing the development of a constant current drive circuit, a voltage-controlled oscillator circuit, and a biasing circuit. Finally, the high-frequency current superposition noise reduction system underwent testing. Results: During the high-frequency current superposition noise reduction test, the system's Signal-to-Noise Ratio (SNR) increased from 15.57 dB to 17.81 dB, and the system's noise peak-to-peak value decreased from 8 mV to 6 mV. Analysis of the superposition frequency and noise reduction effect determined the optimal superposition frequency of the AFM photoelectric sensor system to be 400 MHz. Characterization experiments of the high-frequency superposition noise reduction system compared the clarity of Escherichia coli images before and after noise reduction. Conclusion: The aforementioned experimental results demonstrated that high-frequency current superposition is an effective noise reduction method capable of mitigating optical noise in the AFM photoelectric sensing system.

DDPG‐based heliostats cluster control of solar tower power plant

AbstractThe control of heliostat is crucial for the development of solar tower power plant. Currently, most power plants use open‐loop control, which has low cost but low efficiency, closed‐loop control has high concentrating efficiency, but each heliostat requires sensors and has high cost, and Proportional‐Integral‐Derivative (PID) controller has good control effect, but the parameter adjustment is difficult and overshooting problem occurs. In this paper, we propose a DDPG‐based heliostat cluster control aimed at improving the heliostat control effect and reducing the control cost. A leader‐follower strategy is used to control the heliostat, where the whole heliostat field is divided into several groups, each group is assigned a leader heliostat, and the rest of the heliostats follow the leader heliostat to rotate. The leader acquires the control error by means of a photoelectric sensor or a camera device. The following heliographs rotate with the leader to obtain the control signal, so there is no need for sensors, which reduces the number of sensors and lowers the cost. To address the shortcomings of traditional PID, we propose a DDPG‐based PID control algorithm. The algorithm is trained to find out the optimal value at each moment, which ensures that the controller parameters are optimal at each moment. The results show that the tracking error is below 0.0001 rad for both cluster control and individual control. This ensures effective tracking performance while reducing the sensor cost. The controller based on the DDPG algorithm eliminates overshoots, reduces errors, and shortens the stabilization time by 0.5 seconds.

Method of Detecting Liquid Meniscus in Capillary Using Ultraviolet Sensor

The accuracy of determining the physical and chemical properties of a liquid, in particular, assessing the viscosity of the liquid used, is considered an important technical problem in medicine, food, oil, chemical industries, as well as in other areas that determine the quality and safety of human life and activity. For example, assessing the viscosity of the liquid used is a key stage in the design of hydraulic systems. Today, the improvement of methods for determining the viscosity of a liquid is on the path to automation (digitalization) of measurement instruments and methods. In this area, the activities of metrologists and engineers are consistent with the national program «Digital Economy of the Russian Federation» adopted in 2017. The article discusses the capillary method for determining the kinematic viscosity of a liquid as the most accurate of all possible methods at present. The method is based on determining the time of liquid flow between two marks, which are applied to the walls of a glass capillary viscometer forming a measuring tank. One of the main problems of this method is that all stages of measurement are performed by a person, even recording the moment when the liquid meniscus crosses the mark, which is a violation of one of the key principles of process automation – independence of execution, which only implies monitoring the operation of the system. Since ready-made solutions do not fit the laboratory’s measurement tasks, the management decided to develop and conduct a study of an information and measuring system that will carry out the process of detecting the liquid meniscus at the mark level, as well as recalculate the measured time interval into the kinematic viscosity value. The key decision in this development is the choice of a sensor for detecting the liquid meniscus. Based on the literature review, it was decided to use a photoelectric sensor. A study of the transmission spectra of liquids used in this method was conducted to select the wavelength at which the sensor will operate. Thus, a type of photoelectric sensor designed to operate in the UV range has been selected to automate the method of detecting the liquid meniscus when it crosses a mark applied to a capillary tube. The article is addressed to metrologists who perform verification and calibration of glass capillary viscometers, specialists in the field of experimental and theoretical viscometry. The method proposed by the authors can become the basis for further improvement of the method for measuring the kinematic viscosity of a liquid.

Precision livestock farming in the 21st century: Challenges and opportunities for sustainable agriculture

Abstract This study aimed to review the recent development of different technologies in precision livestock farming (PLF), along with their scopes and challenges. PLF is an innovative, contemporary, and fast-expanding approach to agriculture that aims to improve sustainable livestock farming. The growing global population has increased the demand for animal products. To meet this demand, farmers have to increase their production, so without the integration of precision technology, this cannot be achieved. PLF currently employs a variety of technologies. Some of these methods include vision-based solutions, load cells, accelerometers, microphones, thermal cameras, photoelectric sensors, and radio-frequency identification (RFID). Despite the availability of different PLF technologies, their adoption by farmers varies widely on the basis of the cost of investment, ease of operation, availability, and accessibility. These technologies are used to track different activities of livestock farming, such as feeding, drinking, physical behavior, temperature regulation, tracking and identification, estrus detection, disease detection, and milking. PLF contributes significantly to technological advancement, human-animal relationships, environmental sustainability, and increased productivity. It does, however, present a number of obstacles and eventual advantages.

Flexible intelligent fabric composed of pinecone-like microstructure Co-cMOFs/CoZnAl-LDH composite nanomaterial for various types of sensor signals to guide personalized health activities

Multifunctional interfacing is a key aspect of flexible sensor development that facilitates enhanced interaction with the natural environment. However, challenges faced by contemporary multifunctional flexible sensors are structural complexity and high cost. Herein, inspired by the specific structure of pinecone in nature and the microstructured neural networks randomly distributed within human skin, we fabricated Co-cMOFs/CoZnAl-LDH composite nanomaterials with pinecone-like microstructure. Through the mutual verification of finite element simulation and experimental data, the mechanism of high sensitivity of the sensor is dynamically revealed from the structural point of view. The prepared pressure sensors exhibit a detection range (0–120 kPa), high sensitivity (2.35 × 109 kPa−1) and fast response. The photoelectric sensor shows enhanced photoelectric energy conversion, which shows great potential in the detection of sunlight intensity (20–100 mW cm−2). Simultaneously, building a hybrid pressure, acoustic and optical sensing platform and validating its superior performance in human movement and health monitoring applications. Furthermore, a strategy of light intensity feedback system to guide personalized health activities is put forward, so that doctors can guide patients/elderly health activities remotely.

Force-velocity profiling in elite luge athletes during the simulated luge start

Introduction & Purpose The idea of some athletes having high strength levels but being too slow for a particular movement while others are fast but not strong enough for the demands of their sport exists among many coaches. Therefore, planning decisions are often based on the measurement results of speed and force capabilities and the interest in the relationships between additional load, force, velocity and power during the required movement is high. The luge start is a ballistic movement that requires both high forces and velocities to reach maximal performance (i.e. fast starting times). Examining the load, force, velocity and power capabilities of elite luge athletes during the luge start could deliver insights for training prescription to improve individual weak points and improve performance. This study investigated the relationship between the calculated maxima of force-velocity (FV), load-velocity (LV) and power-velocity (PV) profiles during a simulated luge start and on-ice start times in elite luge athletes. Methods Eleven Austrian national luge team athletes (1 female, 10 male, 25 [4.4] y, 182.4 [7.3] cm, 86.65 [10.4] kg) participated in this study. Measurements were conducted during a single testing session on a specially designed start simulator. Each athlete performed starts against 5 increasing resistances relative to their bodyweight (0%, 25%, 50%, 75%, 100%). For each pull, relative maximum force (Fmax), maximum power (Pmax) and maximum velocity (Vmax) were calculated using the measurements of a linear position transducer (GymAware PowerTool). An experimental approach was used to create the FV-, LV- and PV-profiles showing the highest R2. On-ice start times [s] were measured by photoelectric sensors (ALGE). A correlation matrix (p < 0.05) was used to analyze the relationships between the theoretical Pmax, Fmax (i.e. theoretical isometric maximum force), theoretically unloaded Vmax (Vmax(F0)), theoretical relative maximum loads (Lmax(V0)) and starting times obtained from the profiles. Results Ten linear FV profiles and 11 exponential LV were created (Figure 1; FV: R2mean = 0.9532 ± 0.06; LV: R2mean = 0.9918 ± 0.01). There were significant negative relationships between Vmax(F0) and on-ice starting times (r(9) = -.74, p < .05; r(9) = -.71, p < .05; r(9) = -.74, p < .05) and significant positive correlations between Lmax(V0) and ice start times (r(9) = .71, p < .05; r(9) = .71, p < .05; r(9) = .72, p < .05). Discussion The FV relationship during a simulated luge start can be represented mostly through a linear regression line, supporting the findings of former studies which showed a quasilinear relationship between force and velocity in multi-joint movements (Bobbert, 2012; Jaric, 2015). In line with earlier approaches, PV relationships could be represented quite accurately by use of second-degree polynomial regressions (Allison et al., 2013; Padulo et al., 2017). Contradictory to the linear LV relationships found in other movements (García-Ramos et al., 2018), the luge start LV profile can be better represented by exponential regression curves which could be due to the minimized friction in the luge start setup. Conclusion The abilities of accelerating high external loads and producing high velocities both affect luge start time.

Laser-induced in-situ electrohydrodynamic jet printing of micro/nanoscale hierarchical structure

With the rapid advancement of micro/nanoscale devices, there is a growing demand for hierarchical micro/nano porous-structure, particularly in fields of high-performance sensors, electrochemical energy storage, and photocatalysis. The fabrication methods for hierarchical micro/nano-porous structures have been limited by complex processes and high costs, making further development and application difficult. In this paper, a novel strategy of laser-induced in-situ electrohydrodynamic jet (E-Jet) printing of hierarchical micro/nano-porous structures was proposed. Based on the mechanism of high-energy laser beam induction on the jet, it successfully fabricated hierarchical porous ZnO structures from nanoscale to dozens of microns. The jet size focusing and solidification behavior were analyzed by combining experimental and simulative exploration. The resultant effects of the thermal field, flow field, and laser field on the spatial temperature distribution and the jetting morphology were examined. Furthermore, the laser-induced influence on the morphology of the printed micro/nano-porous ZnO structures was explored. Meanwhile, the performance of micro/nano-porous ZnO photoelectric sensors printed by E-Jet under different laser powers was investigated. The laser-induced in-situ E-Jet printing method provided an innovative pattern for the high-resolution additive manufacturing of hierarchical porous structures, demonstrating its potential for applications in advanced material and high-performance devices.

Synergistically enhanced PVDF-based nanofiber membranes randomly embedded with ZnWO4@PDA nanorods for self-powered sensors with multi-mode free switching

In spite of the high level of attention paid to multifunctional sensors, the flexible and multifunctionality are still intractable challenges to be tackled. Herein, we design a flexible, hydrophobic and stable multifunctional sensing material by electrostatic spinning of PVDF/ZnWO4@PDA (PZP). The incorporation of ZnWO4@PDA into PVDF nanofibers can act as an effective nucleating agent and photosensitizer, which increases the polar crystalline phase and photovoltaic properties of PVDF. With the synergy of PVDF and ZnWO4@PDA, PZP based piezoelectric sensors offer significantly superior electrical output (28.4 V, 600 nA) and high sensitivity (1.04 V/kPa). Moreover, it is particularly surprising that photoelectric sensor based on PZP textiles has excellent optical properties, as confirmed by the response/recovery time (0.6 s/0.66 s) of simulated sunlight detection. Piezoelectric photoelectric effect exists in PZP textiles, as evidenced by the significant increase in the strain output current of photoelectric sensor when irradiated with sunlight. Furthermore, based on the coupling of piezoelectric effect and triboelectric effect of PZP composite, the contact out nano-triboelectric generator has enhanced the electrical output and electromechanical conversion efficiency. Therefore, this work has successfully prepared multifunctional sensing materials that integrate pressure sensing, audio recognition, underwater communication, optoelectronic detection and triboelectric energy collection, paving a new way for the flexible multifunctional sensors.

Application of Metal Halide Perovskite in Internet of Things.

The Internet of Things (IoT) technology connects the real and network worlds by integrating sensors and internet technology, which has greatly changed people's lifestyles, showing its broad application prospects. However, traditional materials for the sensors and power components used in the IoT limit its development for high-precision detection, long-term endurance, and multi-scenario applications. Metal halide perovskite, with unique advantages such as excellent photoelectric properties, an adjustable bandgap, flexibility, and a mild process, exhibits enormous potential to meet the requirements for IoT development. This paper provides a comprehensive review of metal halide perovskite's application in sensors and energy supply modules within IoT systems. Advances in perovskite-based sensors, such as for gas, humidity, photoelectric, and optical sensors, are discussed. The application of indoor photovoltaics based on perovskite in IoT systems is also discussed. Lastly, the application prospects and challenges of perovskite-based devices in the IoT are summarized.

Comparative kinematic analysis of high-speed treadmill vs. overground sprinting across athletic levels and sex.

This investigation aimed to dissect the kinematic differences in sprinting between high-speed treadmill and overground conditions, examining how these variations are influenced by the athlete's training status and biological sex. A total of 40 participants, 20 NCAA Division 1 sprinters and 20 recreational runners, performed a series of maximal sprints on a high-speed treadmill and on a standardized competition overground track. Sprinting kinematic variables such as stride length, stride frequency, contact time, and flight time were collected via photoelectric sensors. Maximal sprinting kinematics were analyzed by linear mixed-effects models, considering the impacts of sprinting environment (treadmill vs. overground), training level, and sex, with leg length as fixed factors and individual athletes as random effects. Statistical significance was set at a significance level of 0.05. The statistical analysis revealed that high-speed treadmill sprinting significantly affects all measured kinematic variables, leading to increased stride frequency and contact time. Elite sprinters demonstrated enhanced kinematic efficiency over recreational runners, characterized by increased stride length and frequency and reduced contact time. Sex-based kinematic distinctions also emerged, with male athletes exhibiting superior stride length and frequency compared to female athletes. Leg length significantly influenced stride frequency, and an interaction effect was observed for flight time between sprint type and athletic group. These findings elucidate the distinct biomechanical profiles across sprinting modalities and athlete demographics, emphasizing the need for sprint training customization. This study's insights offer a valuable reference for coaches and athletes to refine training and performance assessment in varied sprinting environments.

Ferroelectric, flexoelectric and photothermal coupling in PVDF-based composites for flexible photoelectric sensors.

A ferroelectric polyvinylidene fluoride (PVDF) film with excellent flexibility possesses great potential for photodetection and wearable devices. However, the relatively weak photo-absorption and the consequent small photocurrent limit its photofunctional properties. Herein, we embedded a strongly visible-light active material system, 0.5Ba(Zr0.08Ti0.8Mn0.12)O3-0.5(Ba0.7Ca0.3)TiO3 (BZTM-BCT) loaded with Ag and Au nanoparticles, into a PVDF film, which demonstrates a significantly higher photovoltaic response in the whole visible light range with a β-phase content of over 90%. In a state of "bending + poling", the PVDF/BZTM-BCT:Au film presents an optimal response for photoelectric properties by exhibiting a photocurrent that is 57 times higher than that of a pure PVDF film when illuminated with 405 nm LED light at 100 mW cm-2. Photoexcitation and thermal excitation jointly contribute to the generation of free carriers, while the flexoelectric and ferroelectric coupling electric field provides a greater driving force for carrier separation and transport. More interestingly, composite film-based photoelectric sensors can simultaneously respond to light and the movement and deformation of contacted things, indicating its potential in versatile applications. Overall, this work puts forward a new route for designing new flexible multifunctional photoelectric devices.

Research on high-precision encoder based on optical-magnetic combination structure to measure absolute angle

As a kind of sensor for real-time feedback and dynamic monitoring of angular velocity and angular displacement of the system, the common photoelectric encoder is widely used in many fields such as new energy electric vehicles, servo closed-loop control systems, industrial control, security monitoring. In order to improve the resolution and accuracy, a kind of optical and magnetic combined encoder which combines photoelectricity and multi-pole magnetoelectricity is designed in this paper, where the light-blocking disk of photoelectric sensor is designed according to the pseudo-random sequence, and the photoelectric coding is used to determine the magnetic interval of multi-pole. The absolute angle is calculated according to the number of multiple circles plus the angle of single circle. The experimental results at different temperatures (−40 °C∼100 °C) show that the accuracy of the proposed combined encoder can reach ±0.08°, which is improved by 0.37° compared with that of the single-pole encoder. Finally, the combined encoder was applied to the pan-tilt-zoom (PTZ) camera of a video surveillance enterprise, and the experiment showed that its repeated positioning accuracy reached ±0.02°, which is greatly improved compared with single-pole encoder.

Spectrophotometric-Based Sensor for the Detection of Multiple Fertilizer Solutions

The online detection of fertilizer solution information is a crucial link in the implementation of intelligent and precise variable fertilization techniques. However, achieving simultaneous rapid online detection of multiple fertilizer components is still challenging. Therefore, a rapid detection method based on spectrophotometry for qualitative and quantitative identification of four fertilizers (typical N, P, and K fertilizers: KNO3, (NH4)2SO4, KH2PO4, and K2SO4) was proposed in this work. Full-scan absorption spectra of fertilizer solutions at varying concentrations were obtained using a UV–visible/near-infrared spectrophotometer. By assessing the linear fit between fertilizer concentration and absorbance at each wavelength within the characteristic band, the characteristic wavelengths for KNO3, (NH4)2SO4, KH2PO4, and K2SO4 were identified as 214 nm, 410 nm, 712 nm, and 1708 nm, respectively. The identification method of fertilizer type and the prediction model of concentration were constructed based on characteristic wavelength and the Lambert–Beer law. Based on the above analysis, a four-channel photoelectric sensor was designed with four LEDs emitting wavelengths closely matched to characteristic wavelengths for fertilizer detection. A detection strategy of “qualitative analysis followed by quantitative detection” was proposed to realize the online detection of four fertilizer types and their concentrations. Evaluation of the sensor’s performance showed its high stability, with an accuracy of 81.5% in recognizing fertilizer types. Furthermore, the relative error of the sensor detection was substantially less than ±15% for the fertilizer concentrations not exceeding 80 mg/L. These results confirm the capability of the sensor to meet the practical requirements for online detection of four fertilizer types and concentrations in the field of agricultural engineering.

Bio-Inspired Photoelectric Dual-Mode Sensor Based on Photonic Crystals for Human Motion Sensing and Monitoring.

Photoelectric dual-mode sensors, which respond to strain signal through photoelectric dual-signals, hold great promise as wearable sensors in human motion monitoring. In this work, a photoelectric dual-mode sensor based on photonic crystals hydrogel was developed for human joint motion detection. The optical signal of the sensor originated from the structural color of photonic crystals, which was achieved by tuning the polymethyl methacrylate (PMMA) microspheres diameter. The reflective peak of the sensor, based on 250 nm PMMA PCs, shifted from 623 nm to 492 nm with 100% strain. Graphene was employed to enhance the electrical signal of the sensor, resulting in a conductivity increase from 9.33 × 10-4 S/m to 2 × 10-3 S/m with an increase in graphene from 0 to 8 mg·mL-1. Concurrently, the resistance of the hydrogel with 8 mg·mL-1 graphene increased from 160 kΩ to 485 kΩ with a gauge factor (GF) = 0.02 under 100% strain, while maintaining a good cyclic stability. The results of the sensing and monitoring of finger joint bending revealed a significant shift in the reflective peak of the photoelectric dual-mode sensor from 624 nm to 526 nm. Additionally, its resistance change rate was measured at 1.72 with a 90° bending angle. These findings suggest that the photoelectric dual-mode sensor had the capability to detect the strain signal with photoelectric dual-mode signals, and indicates its great potential for the sensing and monitoring of joint motion.

Smart grid power quality monitoring and regulation based on photoelectric sensors and optical system signal processing

With the rapid development of smart grids, power quality monitoring and regulation have become an important task to ensure the stable operation of the power grid. Traditional power quality monitoring methods have problems such as low monitoring accuracy and poor real-time performance. Therefore, this article proposes a smart grid power quality monitoring and adjustment method based on photoelectric sensors and optical system signal processing to improve monitoring accuracy and real-time performance. This article uses photoelectric sensors to monitor the power quality in the power grid in real-time, and transmits the monitoring data to the optical system. Signal processing of monitoring data through optical systems to extract key parameters related to power quality. Finally, by adjusting the relevant equipment of the smart grid, the regulation and optimization of power quality can be achieved. The experimental results show that the smart grid power quality monitoring and adjustment method based on photoelectric sensors and optical system signal processing can effectively improve monitoring accuracy and real-time performance. Through real-time monitoring and regulation of power quality, the stability and reliability of the power grid have been significantly improved.

Photoelectrochemical sensor for hypochlorous acid detection based on the MWNTs doped PEDOT loaded with BP5 functionalized gold nanoparticles

Hypochlorous acid concentration anomaly may cause many serious diseases, so the development method to detect HClO high sensitivity and selectivity is of great significance in clinical diagnosis. Among many methods for detecting HClO, photoelectric chemical sensor has the advantages of high sensitivity and strong anti-interference ability, and has been widely used in the field of detecting HClO. Herein, a simple and specific photoelectrochemical sensor was constructed using A1/B1-type pillar[5]arene functionalized Au NPs and multi-walled carbon nanotube-polythiophene composites for the detection of hypochlorous acid. This approach was based on a sulfhydryl-borate ester modified A1/B1 type pillar[5]arene (BP5) as the main body, hypochlorous acid (HClO) as the guest, multi-walled carbon nanotube (MWNTs) conducting polymers doped with poly(3,4-ethylenedioxythiophene) (PEDOT) as the transport bridge and signal amplifier, as well as spherical gold nanoparticles act as the signal reporter. Specifically, the photoelectrochemical efficiency was further enhanced by the localized surface plasmon resonance effect (LSPR) of gold nanoparticles (Au NPs) and the host-guest complexation between BP5 and HClO. The large specific surface area of MWNTs doped with PEDOT significantly enhanced the electrical conductivity and chemical stability of PEDOT, facilitating accelerated electron transfer and mitigating the recombination of the photogenerated electron-hole pairs. Benefiting from the combination of Au NPs, BP5, MWNTs and PEDOT, the sensor exhibited excellent sensitivity with detection range of 0.5–340 μM and a detection limit of 0.17 μM, and distinguished selectivity against 6 interfering substances. Due to the adsorption and removal effects of pillar[5]arenes on heavy metal ions and pollutants in water, as well as their effective catalytic performance, we anticipate that this composite material also has great potential in photoelectrochemical detection, catalysis, and adsorption.

Bifacial Photovоltaic Sensor for Insolation Energy Resource Monitoring

Accurate and reliable measurements of the total solar radiation flux make it possible to evaluate the efficiency of using stand-alone photovaltaic systems in various meteorological conditions. These measurements allow more accurately predict in time the energy production volume, accumulator and capacitive storage devices parameters and the payback period. Research purpose was to study the possibility of creating a photoelectric sensor and a method of uninterrupted measurement based on this sensor which allows to measure total solar radiation flux including its direct, diffused and reflected components simultaneously. The photovaltaic sensor with bifacial photosensitivity was manufactured and applied, which is low-inertia comparing to traditional thermoelectric pyranometers, and its spectral sensitivity is quite close to the same parameter of photovoltaic power supply system. It creates the possibility to estimate the insolation level capable to be completely converted into electrical energy without an ineffective heat-generating long-wavelength part of the solar spectrum. A laboratory measuring stand was made to test the sensor's operability. Modeling and experiments’ the sensor parameters were carried out and confirmed its operability. The bifacial photosensitivity sensor allows to control simultaneously direct, diffused and reflected from the earth's surface components of solar radiation, what gives more complete information about the energy potential of the photovoltaic power supply system location.