Pulse Signal Research Articles

Design of positive pulse measurement while drilling system for mine rotary valve mud

Abstract For the drilling of directional wells and horizontal wells, to ensure that the drilling trajectory is drilled in the coal seam in the direction designed before drilling, it is necessary to transmit information without interrupting the drilling process. The drilling fluid pressure pulse is divided into positive pulse, negative pulse, and continuous wave. The positive pulse transmission system with the mechanical structure of the lifting valve is widely used because of its high pulse signal strength and long propagation distance, which can be used in deep wells. With the increase of the information measured in the formation, the lifting valve can not meet the needs of the current information transmission due to the linear motion of the mechanical structure and the low transmission rate. The rotary valve as the pressure signal generation source can improve the pulse generation rate. Therefore, this paper analyzes the working principle and signal generation principle of the rotary valve positive pulse system, and collects the directional data and natural gamma value of the field test.

Design of FPGA-based data acquisition system for nanoparticle counting

Abstract As one of the effective means to monitor the environment, the number of particles in the air is gradually developing towards smaller nanoparticles. To improve the acquisition speed of nanoparticle signals and the count of the number of particle signals, this paper adopts the FPGA of Altera as the main control chip, combined with the high-speed ADC AD9280. The sampling of the particle pulse signal is realized, and the collected data is transmitted to the host computer through serial communication. Through the designed peak detection algorithm, the algorithm is hardware accelerated to realize real-time continuous processing of particle signal, calculate the number of peaks, and then get the number of particles. In this paper, the hardware circuit and FPGA logic design of the system are described, and the acquisition system is tested. The results show that the system can meet the requirements.

FDS-MOMEDA: optimization-blind deconvolution in finite high-dimensional spaces for extracting pulse signal in rolling bearing fault diagnosis

Rolling bearing fault diagnosis is crucial for ensuring the safe and reliable operation of mechanical equipment. Detecting faults directly from measurement signals is challenging due to severe noise and interference. Blind deconvolution (BD), as a preferred method, effectively recovers periodic pulses from the measured vibration signals of faulty bearings. This study introduces a simulated annealing-based BD approach to enhance the pulse signal components reflecting faults in vibration signals measured on rolling bearings. This method iteratively searches for the optimal coordinates in a high-dimensional orthogonal optimization space, where the optimal coordinates reflect the combination of the inverse filter coefficients. Compared to the generalized spherical optimization space used in the ‘Optimization-Blind Deconvolution’ method in previous works, the proposed finite high-dimensional optimization space helps overcome the problem of inverse filter coefficient convergence, allowing for the design of inverse filters without limit of its shape. To better accommodate the cyclostationarity characteristics of bearing signal measured in reality, the proposed method employs a target vector that allows for uncertainty in pulse occurrence instants, thus overcomes challenges introduced by pseudo-periodic phenomena resulting from bearing slippage. Numerical simulations and experimental results on real bearing vibration signals confirm that the proposed method can design more flexible filters to enhance pulse-like patterns in signals, effectively utilize limited filter resources. Its capacity to tolerate inaccurate fault period estimates, high background noise, and pulse randomness enables it to effectively address vibration measurement signals in real-world scenarios.

Reliable Long-Term Serial Evaluation of Cochlear Function Using Pulsed Distortion-Product Otoacoustic Emissions: Analyzing Levels and Pressure Time Courses.

To date, there is no international standard on how to use distortion-product otoacoustic emissions (DPOAEs) in serial measurements to accurately detect changes in the function of the cochlear amplifier due, for example, to ototoxic therapies, occupational noise, or the development of regenerative therapies. The use of clinically established standard DPOAE protocols for serial monitoring programs appears to be hampered by multiple factors, including probe placement and calibration effects, signal-processing complexities associated with multiple sites of emission generation as well as suboptimal selection of stimulus parameters. Pulsed DPOAEs were measured seven times within 3 months for f2 = 1 to 14 kHz and L2 = 25 to 80 dB SPL in 20 ears of 10 healthy participants with normal hearing (mean age = 32.1 ± 9.7 years). L1 values were computed from individual optimal-path parameters derived from the corresponding individual DPOAE level map in the first test session. Three different DPOAE metrics for evaluating the functional state of the cochlear amplifier were investigated with respect to their test-retest reliability: (1) the interference-free, nonlinear-distortion component level (LOD), (2) the time course of the DPOAE-envelope levels, LDP(t), and (3) the squared, zero-lag correlation coefficient () between the time courses of the DPOAE-envelope pressures, pDP(t), measured in two sessions. The latter two metrics include the two main DPOAE components and their state of interference. Collated over all sessions and frequencies, the median absolute difference for LOD was 1.93 dB and for LDP(t) was 2.52 dB; the median of was 0.988. For the low (f2 = 1 to 3 kHz), mid (f2 = 4 to 9 kHz), and high (f2 = 10 to 14 kHz) frequency ranges, the test-retest reliability of LOD increased with increasing signal to noise ratio (SNR). On the basis of the knowledge gained from this study on the test-retest reliability of pulsed DPOAE signals and the current literature, we propose a DPOAE protocol for future serial monitoring applications that takes into account the following factors: (1) separation of DPOAE components, (2) use of individually optimal stimulus parameters, (3) SNR of at least 15 dB, (4) accurate pressure calibration, (5) consideration of frequency- and level-dependent test-retest reliabilities and corresponding reference ranges, and (6) stimulus levels L2 that are as low as possible with sufficient SNR to capture the nonlinear functional state of the cochlear amplifier operating at its highest gain.

A Fully Self‐Healing Patch of Integrated Bio‐Signal Monitoring Sensors with Self‐Healing Microporous Foam and Au Nanosheet Electrodes

AbstractA fully self‐healing sensor patch consisting of an in‐plane integrated dual‐mode sensor and a pressure sensor with a vertically integrated electrocardiogram (ECG) electrode is reported. For a full‐device self‐healing, interlayer self‐bonding by using self‐healing oxime‐carbamate bond‐based polyurethane and room temperature self‐healing TUEG3 capped Au nanosheet (T‐Au NS) electrodes are devised. Via the use of a self‐healing sensor foam prepared by a coating of a self‐healing composite of polyurethane and polyaniline onto a microporous graphene foam, a self‐healing dual‐mode sensor is fabricated to detect the pressure and temperature simultaneously without interference. Furthermore, the interdigitated self‐healing electrode of T‐Au NS is applied to the pressure sensor to enhance the sensitivity up to 208.62 kPa−1 (<1 kPa), enabling the detection of small pulse signals even after multiple self‐healing events. By using the common self‐healing T‐Au NS electrode vertically integrated onto the sensor patch, ECG signals are also detected. With this sensor patch, skin temperature, wrist pulse, and ECG signals are successfully detected after a simultaneous full‐device self‐healing from complete bisection. This study demonstrates the facile fabrication of a high‐performance, fully self‐healing patch of multi‐sensors via the deliberate selection of sensor design and the associated functional materials, confirming its high potential applicability to highly durable health monitoring systems.

A deep learning-assisted skin-integrated pulse sensing system for reliable pulse monitoring and cardiac function assessment

Long-term pulse monitoring plays a vital role in the prevention and diagnosis of cardiovascular diseases since pulse signals can provide rich characteristics of cardiac conditions. Flexible sensors mounting on the wrist for pulse monitoring have drawn great attention due to the advantages of soft, skin-interfaced and non-invasive features. However, slight wrist movement and transposition of the sensor on skin would dramatically impact the signal quality because of motion artifacts and interfacial properties. Here, we report an intelligent skin-integrated system by combining a sensitive pressure sensor array and a signal enhancement algorithm to provide reliable pulse signal monitoring. The sensors have the advantages of low cost, simple fabrication, reusability and high sensitivity. The multiple sensor channels offer rich information of vital signals, which can facilitate deep learning-based algorithms to denoise and reconstruct pulses more accurately and thus enable precise heart rate monitoring and heart variability assessments. The reported technology suggests a novel approach for pulse waveform detection in static and dynamic conditions, allowing users to more easily achieve reliable pulse monitoring.

AK-MADDPG-Based Antijamming Strategy Design Method for Frequency Agile Radar.

Frequency agility refers to the rapid variation of the carrier frequency of adjacent pulses, which is an effective radar active antijamming method against frequency spot jamming. Variation patterns of traditional pseudo-random frequency hopping methods are susceptible to analysis and decryption, rendering them ineffective against increasingly sophisticated jamming strategies. Although existing reinforcement learning-based methods can adaptively optimize frequency hopping strategies, they are limited in adapting to the diversity and dynamics of jamming strategies, resulting in poor performance in the face of complex unknown jamming strategies. This paper proposes an AK-MADDPG (Adaptive K-th order history-based Multi-Agent Deep Deterministic Policy Gradient) method for designing frequency hopping strategies in frequency agile radar. Signal pulses within a coherent processing interval are treated as agents, learning to optimize their hopping strategies in the case of unknown jamming strategies. Agents dynamically adjust their carrier frequencies to evade jamming and collaborate with others to enhance antijamming efficacy. This approach exploits cooperative relationships among the pulses, providing additional information for optimized frequency hopping strategies. In addition, an adaptive K-th order history method has been introduced into the algorithm to capture long-term dependencies in sequential data. Simulation results demonstrate the superior performance of the proposed method.

Analysis of Constraints on the Remote Application of Inverse Synthetic Aperture Laser Radar.

In order to achieve the remote application of inverse synthetic aperture laser radar for high resolution spatial situational awareness, it is essential to analyze the main factors that restrict its remote application. This study combines the range equation of inverse synthetic aperture lidar with the stimulated Brillouin threshold power equation to investigate the variation of laser transmitting power with distance. Additionally, by utilizing the excited Brillouin threshold power equation, laser linewidth formula, and pulse width characteristics of pulse signal, we examine the variation law of laser coherence that meets corresponding power requirements at different distances. The results indicate that a detection distance of 22 km and below can be achieved using continuous fiber lasers without compensation. Coherence compensation is necessary for distances between 22 km and 57 km. For distances ranging from 57 km to 3000 km, pulsed solid-state lasers are used to analyze coherence and conclude that imaging non-cooperative targets within this range is feasible. It is observed that coherence compensation is required from 57 km to 2179 km, becoming more challenging after 2000 km. Furthermore, pulsed solid-state lasers can still be utilized for imaging cooperative targets within a range of 2179-3273 km; however, coherence compensation remains necessary and becomes increasingly difficult. Finally, several coherent length compensation schemes are proposed in order to extend the imaging range of inverse synthetic aperture LiDAR to approximately 3000 km.

#2570 Non-invasive blood pressure monitoring in dialysis patients using pulse wave velocity

Abstract Background and Aims Dialysis patients are at high risk of circulatory dysregulation and hypotension during treatment. Intradialytic hypotension (IDH) is a potentially life-threatening complication. The main causes are high ultrafiltration volumes and high ultrafiltration rates when patients tend to gain a lot of weight between dialysis treatments. A lack of patient compliance with regard to drinking volumes and a lack of residual diuresis are risk factors for this. Close circulatory monitoring and therapy settings to avoid absolute or relatively high UF rates to prevent IDH are frequently used. These are primarily the frequent non-invasive measurement of blood pressure using cuffs, the measurement of relative blood volume and the adjustment of ultrafiltration rates to these values. Prophylactically, the dialysis time can be extended, ultrafiltration profiles or ultrafiltration breaks can be planned, the dialysate temperature can be lowered and the composition of the dialysate can be adjusted. Despite all attempts, however, the incidence of IDH in everyday clinical practice is too high. The non-invasive measurements with cuffs are not carried out frequently enough, the measurement of the relative blood volume only covers a partial range, sudden changes in vascular tension or cardiac output are not recorded. Method The pulse wave velocity (PWV) is a well-known parameter for describing the propagation of the pressure wave after ejection of the heart beat volume in the arteries. The PWV is dependent on blood pressure, vessel wall tension and cardiac output. Changes in blood pressure can therefore be recognised by measuring the PWV. With the help of a measuring device (PESAS) for the ECG signal and peripheral pulse plethysmography, PWV can be measured non-invasively, continuously, for every heartbeat and, above all, hardly noticed by the patient. The PESAS allows the time-synchronised measurement of ECG and peripheral plethysmography curves and thus the determination of PWV. It is an experimental device. We would like to present a study showing the use of a measuring device (PESAS) in 15 prevalent dialysis patients for the detection of IDH. All study participants were examined during 3 dialysis treatments. Results The measurement of PWV in chronic dialysis patients during treatment is technically feasible. The measurement is tolerated by the patients. Changes in PWV could be detected in the patients during the course of dialysis; these were also dependent on the ultrafiltration rates. Individual patient reactions to volume withdrawal varied, with both increases and decreases in PWV being demonstrated. An acute change in PWV was usually associated with a drop in blood pressure. Continuous measurement allowed IDH events to be detected earlier than intermittent blood pressure measurement with cuffs. Sudden drops in blood pressure could be detected better and earlier with the PESAS system than by measuring the relative blood volume. Conclusion The PESAS system is suitable for monitoring dialysis patients to prevent IDH. Further adjustments and optimisation of the evaluation algorithms are necessary.

High-precision spatiotemporal three-dimensional ultrashort pulse synchronization with optical Kerr effect

In studying the interaction of multiple ultrashort pulses with matter, high requirements are put forward for spatiotemporal synchronization accuracy. Limited by the response time and bandwidth of existing devices, the synchronization of multiple ultrashort pulses still faces significant difficulties. By observing the transient phenomena of the optical Kerr effect, high-precision, three-dimensional (x, y, t) synchronization of ultrashort pulses at different angles was achieved. In the optical Kerr effect, the polarization state of the signal pulse changes only when it coincides with the pump pulse, at which point the signal pulse passes through the analyzer. The changes in the intensity and phase of the signal pulse is positively correlated with the degree of spatiotemporal coincidence. In this study, 10-ps pulses were used in the experiments. By observing the intensity and phase distribution of the signal pulses, a time synchronization accuracy between two pulses of less than 1 ps and spatial synchronization accuracy of ±125 µm and ±3 µm in the x and y directions, respectively, were achieved. Moreover, the synchronization of two pulses at an angle of 90 ° was measured, further proving that the method can achieve the spatiotemporal synchronization of pulses with large angles. Therefore, this method has important application prospects in the study of multi-beam interactions with matter and other ultrafast physical phenomena.

Quantitative Detection for Fatigue Natural Crack in Aero-Aluminum Alloy Based on Pulsed Eddy Current Technique

Aero-space aluminum alloys, as vital materials in aerospace engineering, find extensive application in various aerospace components. However, prolonged usage often leads to the emergence of fatigue natural cracks, posing significant safety risks. Therefore, research on accurate quantitative detection techniques for the cracks in aerospace-aluminum alloys is of vital importance. Firstly, based on the three-points bending experimental model, this paper prepared the fatigue natural crack specimen, and the depth of the natural crack is calibrated. Then, given the complexity of geometric characteristics inherent in natural cracks, the pulsed eddy current signal under the different natural crack depth is acquired and analyzed using an experimental study. Finally, to better exhibit the non-linearity between PEC signal and crack depth, a GA-based BPNN algorithm is proposed. The Latin Hypercube method is considered to optimize the population distribution in the genetic algorithm. The results indicate that the characterization accuracy reaches 2.19% for the natural crack.

An Intelligent Non-Invasive Blood Pressure Monitoring System Based on a Novel Polyvinylidene Fluoride Piezoelectric Thin Film.

Hypertension is a common cause of cardiovascular diseases, closely associated with the high mortality and disability rates of cardiovascular diseases such as stroke and coronary heart disease. Therefore, developing a comfortable and sustainable device for monitoring human pulse signals holds practical significance for the prevention and treatment of hypertension and cardiovascular diseases. PVDF flexible pressure sensors possess the characteristics of high sensitivity, good flexibility, and strong biocompatibility, thereby demonstrating extensive application potential in areas such as health monitoring, wearable devices, and electronic skins. This paper focuses on the development of a modified piezoelectric polymer and its application in an intelligent blood pressure monitoring system, demonstrating its outstanding performance and feasibility through a series of experiments. This research provides innovative material choices for the development of intelligent medical devices and offers beneficial guidance for the design and application of future intelligent health monitoring systems.

IOT based Railway Crossing Gate Status detection and Security Code Generation System based on ESP8266

In rapidly developing nations like India, the railway system plays a pivotal role in facilitating transportation for the population. However, the safety of level crossing gates within this extensive railway network is of utmost importance and requires careful consideration. Unfortunately, due to human oversight, a significant number of accidents occur daily at these junctures, prompting a pressing need for technological interventions to address this issue. This study delves into two key approaches: firstly, the automation of railway gate operations at level crossings to streamline closure processes and reduce human involvement. A practical demonstration of this concept is showcased through a scaled-down model, which effectively tackles the challenge at hand. In this model, strategically positioned sensors near the level crossing gates detect approaching trains at a predetermined distance from the railway track. Subsequently, these proximity sensors relay signal pulses to a controller situated at the level crossing site, triggering motor activation for automated gate closure and opening. Secondly, the focus shifts towards monitoring the status of the crossing gates. Instances occur where gatekeepers unintentionally overlook gate closure and fail to communicate the security code to the station master, potentially leading to accidents. To address this issue, a system is proposed to generate the security code upon detecting the status of the railway gate, utilizing microcontrollers, LCD displays, and proximity sensors. Key Words: Railway Gate, Sensors, Microcontroller, IOT

A sensory–neuromorphic interface capable of environmental perception, sensory coding, and biological stimuli

AbstractThe sensory–neuromorphic interface is key to the application of neuromorphic electronics. Artificial spiking neurons and artificial sensory nerves have been created, and a few studies showed a complete neuromorphic system through cointegration with synaptic electronics. However, artificial synaptic devices and systems often do not work in real environments, which limits their ability to provide realistic neural simulations and interface with biological nerves. We report a sensory–neuromorphic interface that uses a fiber synapse to emulate a biological afferent nerve. For the first time, a sensing–neuromorphic interface is connected to a living organism for peripheral nerve stimulation, allowing the organism to establish a connection with its surrounding environment. The interface converts perceived environmental information into analog electrical signals and then into frequency‐dependent pulse signals, which simplify the information interface between the sensor and the pulse‐data processing center. The frequency of the interface shows a sublinear dependence on strain amplitude at different stimulus intensities, and can deliver increased frequency spikes at potentially damaging stimulus intensities, similar to the response of biological afferent nerves. To verify the application of this interface, a system that monitors strain and provides an overstrain alarm was constructed based on this afferent neural circuit. The system has a response time of <2 ms, which is compatible with the response time in biological systems. The interface can be potentially extended to process signals from almost any type of sensors for other afferent senses, and these results demonstrate the potential for neuromorphic interfaces to be applied to bionic sensory interfaces.

Study on joint effects of modal dispersion, mode-dependent loss and noise by unified density-matrix formalism

We generalize the density-matrix formalism to provide a simple and unified framework for the study of modal dispersion (MD), mode-dependent loss (MDL) and noise in mode-division-multiplexing communication systems. Fundamental concepts and formulas in the original formalism are generalized, while new elements and associated equations are introduced and/or derived. Due to the ability of the density operator to characterize partially-coherent fields, the generalized density-matrix formalism is particularly useful for analyzing the field propagation in presence of noise. Combining the unified density-matrix formalism and the stochastic-process theory, we conduct detailed numerical simulation and analysis on the modal properties of a randomly-perturbed 6-mode fiber with loss and noise. We find that although the MDL only slightly affects the statistics of the group delays, it can cause significant non-orthogonality among the principal modes, which might induce extra crosstalk and temporal spreading in the signal pulses. Furthermore, with the coherency of fields in the fiber being reduced by the noise, the MDL can induce substantial fluctuation in the field coherency even though it does not significantly affect the averaged field coherency.

A model-based sliding mode control with intelligent distribution for a proportional valve driven by digital valve arrays

Parallel-connected digital valve arrays are commonly utilized in the pilot stage of the proportional directional valve to enhance dynamic performance and reliability. However, when the digital valve array is driven by a digital signal, it is difficult to optimally assign the signal pulses to each valve. If the assignment is not well executed, it can significantly reduce the switching uniformity of the digital valves or lead to performance degradation of the system. In this paper, a model-based sliding mode control strategy based on the intelligent distribution of control law is proposed and successfully applied to a proportional valve driven by digital valve arrays. The intelligent distribution strategy encompasses a logic distribution algorithm and a circular sliding distribution algorithm that automatically assigns control laws to different valves based on the rolling of the PWM signal cycle. Experimental results confirm that the proposed strategy not only simultaneously reduces the total number of valve switches and enhances the switching uniformity among the valves, but also adapts to the variation in the number of valves. The proposed strategy is not limited to the application of digital valve arrays, it is also applicable in other fields of multi-actuators driven by digital signals, and can simultaneously improve the control accuracy, lifetime, and maintenance friendliness.

Hybrid optimal-FOPID based UPQC for reducing harmonics and compensate load power in renewable energy sources grid connected system.

Integration of renewable energy sources (RES) to the grid in today's electrical system is being encouraged to meet the increase in demand of electrical power and also overcome the environmental related problems by reducing the usage of fossil fuels. Power Quality (PQ) is a critical problem that could have an effect on utilities and consumers. PQ issues in the modern electric power system were turned on by a linkage of RES, smart grid technologies and widespread usage of power electronics equipment. Unified Power Quality Conditioner (UPQC) is widely employed for solving issues with the distribution grid caused by anomalous voltage, current, or frequency. To enhance UPQC performance, Fractional Order Proportional Integral Derivative (FOPID) is developed; nevertheless, a number of tuning parameters restricts its performance. The best solution for the FOPID controller problem is found by using a Coati Optimization Algorithm (COA) and Osprey Optimization Algorithm (OOA) are combined to make a hybrid optimization CO-OA algorithm approach to mitigate these problems. This paper proposes an improved FOPID controller to reduce PQ problems while taking load power into account. In the suggested model, a RES is connected to the grid system to supply the necessary load demand during the PQ problems period. Through the use of an enhanced FOPID controller, both current and voltage PQ concerns are separately modified. The pulse signal of UPQC was done using the optimal controller, which analyzes the error value of reference value and actual value to generate pulses. The integrated design mitigates PQ issues in a system at non-linear load and linear load conditions. The proposed model provides THD of 12.15% and 0.82% at the sag period, 10.18% and 0.48% at the swell period, and 10.07% and 1.01% at the interruption period of non-linear load condition. A comparison between the FOPID controller and the traditional PI controller was additionally taken. The results showed that the recommended improved FOPID controller for UPQC has been successful in reducing the PQ challenges in the grid-connected RESs system.

Influence Assessment of Distance to the Source of Pulse Signals With Harmonic Components on the Temporal Distortion of Their Forms

Within the scope of this article, periodic pulse signal typical samples with harmonic components have been analyzed, including their spectral fluctuations, changes in their frequency range, and the form of signal typical samples depending on the distance. Collected statistical information regarding changes in the duration of typical samples affected by distance change from the signal source to the sensor based on data collected during field experiments. Signal features by which typical samples can be recognized have been outlined and their duration effectively measured. The dynamics of frequency spectrum change and duration of repetitive typical samples have been presented depending on the distance to the signal source. Additionally, the frequency range and average duration range of the researched typical samples, and their variations have been provided based on the gathered statistics data.

Weak signal detection method based on nonlinear differential equations

With the rapid development of computer network technology, it is often necessary to collect weak signals to collect favorable information. The development of signal detection technology is ongoing; however, various issues arise during the detection process. These issues include low efficiency and a high signal noise threshold. However, many problems will be encountered in the process of detection. In order to solve these problems, the nonlinear chaos theory is introduced to detect signals, and the simulation experiments of weak pulse signals and weak partial discharge signals are carried out respectively. The experimental results showed that the detection effect was remarkable in the quasi periodic state, and it had a good detection effect for weak pulse signals. At a signal-to-noise ratio of -25 dB, double coupling system, two-way ring coupling system, and single ring coupling system displayed detection success rates exceeding 98%. Meanwhile, the detection success rate of the strong coupling system was only 12%. Even at a noise signal ratio as low as -40 dB, the dual coupling system still maintained a detection success rate above 80%. The simulation results of partial discharge signal detection showed that there was a high fluctuation only at 2 ms, and the rest was basically stable at about 0 V, indicating that the system had a strong suppression effect on Gaussian white noise. When comparing the simulation results of the detection of the new chaotic system and the double coupling system, it was found that the new chaotic system has a superior impact in detecting weakly attenuated partial discharge signals. Through analysis of the system’s dynamic behavior, the research confirms its rich dynamic characteristics and sheds light on the reasons for phase state mutation and missed detection. The noise system is utilized for comparing the performance of various systems, with the goal of enhancing the system’s detection capability.

Tunable Negative and Positive Photoconductance in Van Der Waals Heterostructure for Image Preprocessing.

The processing of visual information occurs mainly in the retina, and the retinal preprocessing function greatly improves the transmission quality and efficiency of visual information. The artificial retina system provides a promising path to efficient image processing. Here, graphene/InSe/h-BN heterogeneous structure is proposed, which exhibits negative and positive photoconductance (NPC and PPC) effects by altering the strength of a single wavelength laser. Moreover, a modified theoretical model is presented based on the power-dependent photoconductivity effect of laser: , which can reveal the internal physical mechanism of negative/positive photoconductance effects. The present 2D structure design allows the field effect transistor (FET) to exhibit excellent photoelectric performance (RNPC=1.1× 104AW-1, RPPC=13AW-1) and performance stability. Especially, the retinal pretreatment process is successfully simulated based on the negative and positive photoconductive effects. Moreover, the pulse signal input improves the device responsivity by 167%, and the transmission quality and efficiency of the visual signal can also be enhanced. This work provides a new design idea and direction for the construction of artificial vision, and lay a foundation for the integration of the next generation of optoelectronicdevices.