Abstract:Citation flight simulator has many systems, compared with the real aircraft, the maintenance manual rules are simple,but the maintenance technical requirements are high. According to the existing maintenance manual, it is difficult to accurately judge the fault components, and quickly complete the disassembly and replacement of the fault components. To solve this problem, the Maintenance Simulation Model (MSM) is proposed and established by analyzing the system structure of the flight simulator with awards, and the MSM Model framework is constructed. The three elements of the MSM Model are defined: state, migration and constraint conditions. The various states of maintenance components are defined based on state, the trigger conditions of maintenance implementation are defined based on migration, and the restriction relationship between state and trigger conditions is established based on constraint conditions. The rendering drive and switching of virtual scene of MSM model are also described. Finally, the disassembly of voice control components in the simulation maintenance platform is taken as an example to verify the effectiveness of the simulation maintenance management model.

Abstract:A surface navigation platform model needs to conduct self-propelled test in open water, and the experimenters need to control the four thruster motors and four rotary motors of the model on shore, so as to control the movement of the model. Because the model is small in volume and can carry small weight.Aiming at this problem, a set of simple structure and low cost control system is designed.The system is based on Modbus RTU protocol and controls the motor through serialport. The actual test result shows that the system can control the rotation speed and angle of the servo motor in real time,the maximum control distance is about 1km, and the control error is within 3%, which shows the system can meet the needs of the test.

Abstract:The traditional wireless monitoring system based on Zig Bee has many problems, such as limited data transmission distance and high power consumption. A low-power medical monitoring system based on Lora technology is designed. According to the different functions, the whole monitoring system can be divided into three parts, each part realizes data interaction through Lora wireless network. The core device of the detection end is the infrared photoelectric sensor, which sends the acquired dropping speed and liquid medicine margin to the hand-held end through Lora wireless network on the one hand, and to the patient through voice broadcast and LCD display on the other hand, and the detection end is also responsible for receiving the patient information sent from the hand-held end and the rear end. The backstage end is responsible for monitoring patients and nurses in an all-round way. The experimental results show that the medical drip monitoring system designed in this paper has strong anti-interference ability, can realize data long-distance transmission, not only low power consumption, but also easy to network, and has a wide range of application prospects.

Abstract:In order to realize the high reliability and low-cost application of the space two-dimensional turntable in orbit, as well as the ability of low-speed smooth motion, high-precision tracking and 360 degree full range continuous operation, a vector control system of stepper motor based on FPGA chip is established. The 128 subdivision precision control of stepping motor is realized by PWM chopping adjustment of current sine table. A 21 bit photoelectric encoder used as position feedback and a harmonic reducer used as mechanism drive to realize open-loop control, real-time speed adjustment and tracking control, optimal path planning control and motion timeout protection . The influence of MOSFET on chopping frequency and maximum subdivision is analyzed. The experimental results show that the tracking accuracy of the two axes is better than 0.005 degrees at 3σ, the speed stability is less than 5%, and the servo control bandwidth is more than 4Hz, and it has the ability of continuous zero crossing. The control system can simplify the hardware design, increase the applicability of software, more suitable for ultra-low speed motion, and meet the requirements of two-dimensional turntable for servo control system.

Abstract:The deep-sea in-situ nuclear radiation detector can operate in the in-situ environment by itself after being configured by the mother ship. At the same time, after the instrument is salvaged and recovered, the mother ship needs to complete the docking and data recovery functions, and the data readout between the detector and the host computer on the mother ship becomes a key issue. Aiming at the compatibility and scalability problems existing in the current spectrometer readout equipment, this paper designs a data read-out method for the deep-sea in-situ nuclear radiation detector. The RS485 and LVDS physical layer are used in hardware to ensure the stable and reliable data readout spectrometer. The MODBUS protocol application layer is used to improve compatibility and scalability spectrometer. By building a laboratory test platform, the overall function of the system, and the bit error rate, eye diagram of the physical layer are tested. The results show that the method can realize the stable and reliable data readout of the deep-sea in-situ gamma detector. In the low-speed mode and high-speed mode, the reading data rate of the detection instrument system is 115200bps and 40Mbps respectively.

Abstract:Aiming at the problems of low labor efficiency and inaccurate management in the maintenance process of expressway electromechanical equipment, an intelligent monitoring system of expressway electromechanical equipment based on FPGA is designed. At first, the system uses FPGA as the main control chip, and combines STM32 module to collect a variety of sensor data for equipment status information, in which the signal output by the sensor is conditioned by the amplification filter circuit. Secondly, hierarchical convolution deep learning is used to analyze the collected state data of electromechanical equipment. By replacing traditional feature extraction network with residual network and establishing loss function model of candidate region, intelligent fault detection of electromechanical equipment is realized. Experimental results show that, compared with other monitoring methods, the system's failure alarm rate under noise interference is greatly reduced to only 0.16%, which meets the requirements of automatic management.

Abstract:Electric signal transmission in the drilling oil-based drilling fluid environment is one of the current research hotspots. To solve this problem, a high-frequency inductive coupling transmission device is designed to solve the problem. The core transmission part is an inductive coupling transmission coil.In this paper, through HFSS simulation and laboratory model testing, an inductive magnetic coupling transmission coil structure is designed, which can be used to solve the problem of inductive coupling trans-mission of complex drilling tools downhole. The simulation model establishes a multi-coil transmission model to study the law of induction transmission characteristics of different turns in different media conditions. Based on this law, a corresponding physical model is designed. The results of actual measurement show that the transmission gain effect is good. High gain(-20dB)is obtained both in simulating water-based drilling fluid and the case of oil-based drilling fluids, and conventional modulation and demodulation circuits can be used to realize signal transmission and processing, and have conditions for inductive transmission in a variety of media. Therefore, the device lays a foundation for the complex drilling tool induction transmission and the measurement while drilling signal transmission in a variety of media conditions, which is of great significance for engineering applications.

Abstract:In this paper, a closed-loop feedback control system for the measured ammonia gas pressure is designed based on Bernoulli's principle, and the high-resolution spectral characteristics of NH3 under low pressure conditions are studied. The system takes the measured ammonia absorption tank pressure as the control object, uses CDG800 pressure sensor to measure the absorption tank air pressure, one of the VT317 solenoid valve controls the high pressure standard concentration ammonia source to increase the air pressure in the absorption tank, and the other VT317 solenoid valve controls the vacuum pump extraction The gas in the absorption cell reduces the pressure to form a low-pressure gas circuit for NH3 spectrum detection; and a closed-loop feedback control circuit for pressure measurement, solenoid valve and vacuum pump with Arduino UNO microcontroller as the core is designed. The experimental results show that the designed air pressure control system can maintain a stable time for more than 72 hours, and the air pressure fluctuates within 1 torr. A single absorption spectrum signal in the NH3 mid-infrared band 1103.4cm-1 is obtained, and the calculated line intensity is consistent with the center line of the HITRAN database. The strong data deviation is between 2.71% and 4.71%.

Abstract:In the progress of servo testing, the actual servo-angle signal is needed to be acquired for the calibration and performance evaluation of the servo system. The traditional servo-angle acquisition system is composed of PCI-based acquisition board and IPC, which has high-cost and needs special computer. For the requirement of a low-cost and universal servo-angle acquisition system in servo testing, a lower computer based on STM32F103 is designed to instead of traditional PCI-based acquisition board. The lower computer communicates with PC via USB interface. The PC software based on LabWindows/CVI is designed for communication and human-computer interaction. This system features low-cost,high reliability,high flexibility,and it has been successfully applied in servo testing. The experiment results demonstrate the outstanding achievement of the system.

Abstract:Aiming at the problem of motor rolling bearing fault diagnosis accuracy, a motor fault diagnosis method based on wavelet packet analysis and artificial fish (AFSA) optimized support vector machine (SVM) was proposed. Wavelet packet multi-resolution analysis method was used to decompose and reconstruct the motor vibration signals, and the time-frequency diagrams of different frequency bands were obtained. Then, AFSA algorithm is used to optimize the parameter penalty parameter(C) and kernel parameter() in the support vector machine. Finally, the fault diagnosis model of AFSA-SVM is established, and the frequency band energy value in the signal time-frequency graph is extracted as the input feature vector of AFSA-SVM for learning and testing. Finally, the simulation experiment verifies that the fault diagnosis accuracy is up to 98.7%, and compared with the particle swarm optimization support vector machine (PSO-SVM) and the unoptimized support vector machine, the results show that the proposed method has a higher fault diagnosis and recognition effect.

Abstract:As a modern means of transportation, the maglev train has a non-linear and unstable levitation system. According to the characteristics of the system, the stability problem is researched and discussed. According to the mechanical structure of the suspension track, a physical model of the suspension system with nonlinear properties is established. In order to facilitate understanding and research, the nonlinear system is linearized by the feedback linearization method of the inverse system, and the pseudo-linear system equation of the rail train suspension system after compensation will be obtained. Analyze the characteristics of the pseudo-linear system and design a closed-loop simple and robust controller. Use the Simulink toolbox in MATLAB software to simulate the control system. The simulation results show that the train suspension system under the action of the controller has strong robustness and good suspension stability. It has strong immunity to external interference and can better meet the requirements of stable suspension control.

Abstract:In view of the current situation that the basic accuracy is generally adopted as the final technical indicator of the instrument in the process of measuring and using precise digital measuring instrument, the paper has analysed the principle of precise digital measuring instrument and the factors that affect the measurement accuracy, elaborated the calculation method of the maximum permissible errors of the digital measuring instrument in detail, and proposed the “point-by-point calculation scheme” of capacitance parameter by taking E4980A as a typical model. and finally found the calculation result of the same measurement point is ±11.95% different from the traditional calculation method. The result shows that the calculation method in this article can be used as an accurate method for evaluating performance indicators of AC digital bridges, which can better guide users to correctly use the technical indicators of each measurement point. At the same time, it can also avoid the misjudgment of measurement personnel and has a higher practicability.

Abstract:VHF communication is widely used in civil aviation, but it is highly susceptible to various noise interferences. The traditional method has poor denoising effect and does not eliminate inherent interference, this paper proposes an adaptive Kalman filter algorithm based on wavelet analysis. In this algorithm, a new threshold function is proposed in the wavelet analysis, and in the adaptive Kalman filter algorithm, an adaptive factor is added to adjust the window length to adjust the filter gain, which can effectively avoid the filter divergence. This paper randomly selects VHF speech signals of four different frequencies in a certain period of time and filtered by the proposed algorithm. The signal-to-noise ratio, root mean square error, signal waveform and spectrogram are analyzed. The results show that the algorithm can effectively remove the noise in VHF speech signal, obtain higher signal-to-noise ratio and smaller root mean square error, and further improve the quality of speech.

Abstract:Pointing to the problem that slam well logging system cannot realize rapid and real-time acquisition of large volume data under the limit of transmitting bandwidth of logging cable at present, a down-hole telemetry transmitting sub dedicated to slam logging is designed in this paper. Based on the correlation analysis of sampling data, depth aligned two dimensional data array is formed by up-loaded data frames buffering according to sampling time from different tools in combination of slam logging. According to image lossless compression theory, adaptive predicting model based on CALIC algorithm are utilized to up load data array after lossless compression by hardware circuit design and embedding programming development. Simulation experimental result is that data compression ratio is improved by about 30% compared with current mainstream compression method-LZW on actual data of slam logging from 4 wells of SL oilfield. Application testing result is that efficiency of new slam logging is improved by about 22% on actual slam logging operations of 5 wells from SL oilfield. Result shows that efficiency is greatly improved by new hardware design and data compression and transmitting algorithm which realizes high-speed data acquisition and insures huge economical advantage of slam logging in saving the cost of exploring and developing oilfields.

Abstract:To solve the problem of worse feasibility, lower resolution of continuous curve without thin beds information in stratum of traditional data pre-processing methods in through casing resistivity logging, a new data pre-processing method is designed in this paper. Abnormal values on same depth are eliminated by data cleaning theory and the sparse representing coefficients of signal are solved by optimizing algorithm and constraints through constructing observation matrix and sparse transforming matrix based on signal sparse representing theory to get the continuous through casing resistivity logging curve with equal space of depth interval. Experimental result is that abnormal values are eliminated effectively and formed logging curves by this method has good correspondence of thin beds with open-hole micronormal curves on logging data of five wells in SL oilfield. Results show that compared with traditional pre-processing methods, the method has good usability, stronger thin beds dividing ability and more greater application value. The implemented software provides powerful technical support for development and sustained and stable production in the oilfield during the application of dynamic supervising of SL oilfield.

Abstract:Aiming at the problems of low signal-to-noise ratio and blurred imaging, a method of terahertz concealed object detection based on multi-feature fusion is proposed. First, the terahertz image preprocessing is designed to realize the noise filtering and image enhancement. After that, by extracting the oriented gradient distribution feature, the grayscale distribution feature, and the pixel spatial distribution feature, then fusing them into a multi-feature vector, the comprehensive representation of the concealed object is accomplished. Finally, the support-vector machine is employed to achieve the classification task, and the location task is completed by calculating the bounding box of the largest contour. The experiment is conducted on the 0.2 THz data set. The results show that the proposed detection method based on multi-feature fusion outperforms better than other methods employing a single feature or pairwise combination of these features. This method has good performance for detecting passive terahertz concealed objects.

Abstract:Due to the limitation of network structure and training mode for shallow neural network, network learning ability and generalization ability are weaker than deep learning network under large sample conditions. Therefore, a data fusion algorithm of water quality sensor based on stacked hybrid encoder is proposed. The algorithm forms a deep learning network model by stacking automatic encoder and sparse automatic encoder, which realizes the feature mining and sparse representation of sample data. The network model can fit the complex nonlinear function after large-scale sample training, and has generalization ability for low quality sample data. It can improve the accuracy of prediction classification. Simulation results show that the proposed algorithm achieves higher classification accuracy.

Abstract:The dimension detection of hole parts is carried out by machine vision technology, which is the on-line detection that is implemented simultaneously with processing and measurement. Therefore, it can shorten the production cycle and improve the production efficiency. The CMOS camera and telecentric lens with high precision are selected by analyzing the process features of parts. For features of parts with chamfering, ring light is used for illumination, while coaxial light is used for illumination in the case of features without chamfering. Using those hardwares can increase flexibility of platform. For the pepper and salt noise and Gaussian noise in the process of image acquisition and transmission, median filtering is firstly used to remove the pepper and salt noise in the collected grayscale image, then the minimum error method is used to select the threshold to complete image segmentation, and then the Canny operator is used to detect edges and remove the Gaussian noise. Finally, the camera is calibrated with the calibration target to obtain the calibration coefficient and the pre-processed images are measured by Open eVision that is an image processing tool. Furthermore, the system test data is compared and analyzed with the gage measurement data. The experimental results show that the accuracy of the system can reach 0.02mm.

Abstract:pupil localization is a key step in pupil recognition. In order to solve the problems of low accuracy, missing detection and false detection in the current pupil location algorithm, this paper proposes an algorithm to accurately locate the pupil center by creating a sliding window. Firstly, CLM model is used to extract the eye region of human face, and the extracted image is preprocessed. Then, by creating a circular sliding window to scan the image and calculate the sum of the gray values of pixels in each window. Taking advantage of the fact that the gray value of the pupil is very low, the window with the lowest gray value is selected as the pupil region, and the coordinates of its center point are calculated as the coordinates of the pupil center. The experimental results show that the algorithm can accurately locate the pupil center for different test objects, and can enhance the robustness of the system.

Abstract:The steel industry is the supporting industry of social development. In order to improve the level of industrial automation and effectively detect the surface defects of steel plates, an improved YOLOv3(You Only Look Once) detection algorithm was proposed. Firstly, wavelet - median filter is used to improve the image contrast. Then, a scale output is added on the darknet-53 network to enhance the algorithm's ability to recognize small target defects. Finally, in order to enhance the accuracy of the algorithm model, the original loss function of the algorithm is optimized and the improved YOLOv3 algorithm model is obtained. The mAP value of the improved network on the test set is 7.9 higher than that of the original YOLOv3 network, which has a better application prospect in plate surface defect detection.

Abstract:In view of the current situation that sedentary people lack of exercise for a long time, resulting in sub-health state and the lack of supervision of existing training methods, this paper proposes a method of human motion recognition and counting to realize the accurate recognition and counting of four kinds of training without equipment. Taking the video information of the trainer captured by the mobile camera as the input, the human skeleton point data processed by the BlazePose network model is processed by data filtering and feature extraction, and three common machine learning algorithms are used for action classification. The classification results are combined with the bone information, and the peak and trough counting algorithm is used to count the number of training actions completed. The experimental results show that: using GBDT classification algorithm, the action recognition rate is 96.5%, and the accuracy of counting algorithm is 98.9%, which has good practical application value.

Abstract:Abstract: Quantifying sports energy consumption is the foundation of scientific sports. At present, there are many limitations in the detection equipment of daily exercise energy consumption. To address this problem, this paper adopts the image recognition technology that has been developing rapidly in recent years, and designs a set of human movement energy consumption monitoring system based on the mobile phone terminal, the system contains four kinds of movement and fitness actions, through the mobile phone front camera to shoot the video of the human body completing the corresponding action under the voice and video guidance, using the image analysis technology to calculate the human movement energy consumption value in real time, to realize the human movement energy consumption monitoring. The correlation coefficients between the experimental results and the measured value of indirect calorimetry, which is called the "gold standard", reached more than 0.6 (P<0.01), and the energy consumption prediction equations for four actions were proposed. The methods are more consistent and can be used as an alternative to traditional methods.

Abstract:The eye tracker was used to extract the design factors in the bronze mirror with arc pattern and inscription in order to design and develop creative products in the new cultural and creative era. An eye movement experiment was conducted to analyze the visual hot spots of 20 subjects watching the mirror. Subjects’ interest areas in the mirror were then divided according to experimental data. The main interest areas were determined by analytic hierarchy process, and the dominant and invisible design factors were extracted by induction and deduction methods . The extracted factors were applied to the design of a cultural and creative product, and it was compared with other cultural and creative products. The possibility of extracting design factors from cultural relics by eye trackers was verified by experimental data.

Abstract:To solve the problem of underwater and long-distance transmission of ocean sensor data,a PLC long-line transmission circuit system is proposed. The system adopts power line communication (PLC) technology, CR600 as the control core, CR150 as the analog front end with chip control data receiving and sending. The data is transmitted back to the ground through the umbilical cord, and then the data is received by the ground control system and the upper computer,realize the ocean sensor data transmission. In order to ensure the normal operation of the circuit system in 1000 meters underwater, the pressure chamber is designed. According to the theoretical calculation and COMSOL simulation, the specific parameters of the pressure chamber are determined. It has been verified that the system works stably, the long-term data transmission is complete, and it can realize the long-term transmission of marine sensor data.

Abstract:As one of the core components of the traction system of rail vehicles, the failure of the supporting capacitor will seriously affect the safe and stable operation of the train. Therefore, it is of great significance to study the fault prognostics and health management (PHM) technology of the support capacitor and realize the online health state prediction of the support capacitor. In this paper, firstly, the structure design, working characteristics and aging mechanism of the supporting capacitor are deeply studied, and the degradation rate of capacitance value and ESR value is taken as the failure criterion of the support capacitor. Then, a soft sensing model of capacitance value and ESR value is constructed based on mathematical statistics and polynomial regression algorithm. A large number of test data are used to train and optimize the model, Finally, the accuracy of the soft sensing results is evaluated from two aspects of the soft sensing error and the consistency of mathematical statistics distribution. The experimental results show that the mathematical statistics + polynomial regression soft sensing model can effectively soft sensing the support capacitance and ESR values in different sample sets and different working conditions, which verifies the feasibility and accuracy of the model.

Abstract:Aiming at the problems of difficulty in obtaining vibration signals and failure of measured signals in the harsh environment of high temperature, high pressure, high overload, etc. of missile tail during launch, we design a three-axis based on ADXL345 using dynamic storage test technology and three-axis digital accelerometer in this paper. Specifically, by selecting a suitable empennage vibration test acceleration sensor and constructing a multi-buffer outer structure with strong shock resistance, the real acquisition of the vibration signal of the missile empennage was successfully realized. And the effective acceleration curve and the vibration spectrogram were obtained by analyzing and collecting the vibration data of the empennage, which provide an important basis for the improvement of the tail structure, and are of great significance to collect the tail vibration signal in the future.

Abstract:Airborne phased array radar is greatly affected by ground clutter when it is working downwards. Although the space-time adaptive processing (STAP) technology has good performance of suppressing clutter, its performance depends on a large number of training samples and high computational complexity, It is difficult to apply in practice. In order to make up for the shortcomings of the STAP algorithm, an optimization algorithm for local joint processing (JDL) is proposed. When constructing the dimensionality reduction matrix, the method adjusts the selection strategy of the local processing region, four independent auxiliary channels are selected at the clutter ridge corresponding to the main channel to improve the directivity of the beam and cancel the clutter in the main beam. The results show that the optimized method has better clutter suppression performance than the traditional JDL method, further reduces the amount of system calculation, and maintains better stability in the case of amplitude-phase error.

Abstract:Traffic radar uses MIMO technology to achieve the goal of obtaining high angular resolution with a small degree of freedom. However, due to factors such as highly integrated hardware processing technology and device aging, there are amplitude and phase errors between the channels of millimeter wave MIMO radar. Considering the calibration accuracy and traffic application scenarios, this paper proposes an error self-calibration method based on the minimum entropy of power (MPE). The error vector is randomly generated as the initial value of optimization, and the error vector corresponding to the minimum entropy is searched through an adaptive optimization algorithm, and each is calibrated in real time. Errors caused by influencing factors. The paper gives the derivation of the algorithm, the analysis results of the darkroom measured data and the actual scene simulation data, which proves the effectiveness and superiority of the proposed algorithm.

Abstract:Aiming at the problem that the electric detonating device will generate induced current through electromagnetic coupling in a complex electromagnetic radiation environment, which will cause the electric detonating device to misfire, a non-contact induced current detection method based on phase lock technology is proposed. The current probe based on the tunnel magnetoresistance effect is used, and the output signal of the tunnel magnetoresistance probe is analyzed according to the principle of electromagnetic induction and phase-locking technology, so as to monitor the induced current in real time to avoid fire; and the non-contact based on phase-locking technology is obtained. Compared with the traditional infrared colorimetric temperature measurement method, the inductive current detection method has a faster response speed and higher measurement accuracy. A strong electromagnetic environment is built to simulate the working environment of the electric detonation device, and a non-contact current probe is used for experimental detection to realize the monitoring and detection of induced current and achieve the early warning effect. The experimental results show that the current detection accuracy of the method is ±0.1 Fluctuations in the mA range meet the detection requirements of the ignition current of the electric detonation device, and provide an effective solution for the induction current monitoring of the electric detonation device in a complex electromagnetic environment.

Abstract:Aiming at the disadvantages of large volume and high cost of traditional spectrum acquisition equipment, a driving and acquisition circuit of infrared spectrum sensor controlled by FPGA is designed based on MEMS-FPI spectrum sensor C14272 developed by Hamamatsu. The circuit includes voltage driving module of the tunable filter, spectrum and temperature signal acquisition module, USB transmission module and so on. The test results show that the spectrum of the C + L band ASE light source obtained by the circuit is similar to the simulation spectrum, which realizes the driving of the spectrum sensor and the collection of spectrum data. The wavelength detection range of the circuit is 1350-1650nm and the full band spectral resolution is less than 18nm. The design is compact in structure and low in cost, which is helpful in specific fields such as qualitative detection of material composition.

Abstract:To solve the issue of poor air quality in high-density classrooms, which leads to low learning efficiency and hurts the physical health, we design an integrated perception system. First of all, this paper elaborates the overall design of the integrated classroom air perception system. Secondly, the hardware circuits of indoor and outdoor data acquisition module, main control module, power supply module and liquid crystal display module are designed by modular design approach. Meanwhile, software programs are designed for the corresponding modules. After the software and hardware joint debugging of the system, it can not only display the perceived concentration of PM2.5, PM10, carbon dioxide, formaldehyde, volatile organic compounds, but also has good stability. The system can be applied to the classrooms of school, and has certain application value for making air better.

Abstract:Ultraviolet laser with a wavelength, high speed, high precision, small heat affected zone and nondestructive processing advantages, such as for ultraviolet laser machining process, the influence of different parameters on the etching results, by controlling the single variable method, designed the scanning speed, scanning frequency, energy density, repetition frequency, the coke deposition on the result of etching.The experimental results show that the etching width increases with the increase of energy density, but the increase rate decreases continuously.By reducing the scanning speed, the microchannel with deep depth and neat edge can be etched.With the increase of scanning times, the depth of laser etching is increasing, but the increase rate is decreasing, and the etching depth is too deep, so the laser will not etching the channel again.By optimizing the laser etching parameters, an L-shaped silicon-based micro-channel with an etching width of 146μm, an etching depth of 25.665μm, a neat edge and a roughness of 7μm, and a channel with a verticality of nearly 90° were obtained.

Abstract:The design of intelligent drug storage box conforms to the trend of social aging. Taking the protection of vulnerable groups and special drug storage as the research object, the intelligent requirements of target monitoring, alarm clock reminder and drug storage are deeply studied. In this paper, an intelligent drug storage box is designed, aiming at the physiological ability degradation of special groups and the demand of special drug storage. Users can stably mobilize the resources of the whole intelligent drug storage box through the human-computer interaction page, including timely medication reminder, opening detection of the drug storage box, temperature control, emergency alarm and other functions. The combination of infrared detection and multi-level signal operational amplifier is adopted in the design process, which can accurately measure the user's heart rate within 5 seconds. The functions set in the intelligent drug storage box can run stably, and the success rate is close to 100%. The results of many experiments show that the design can solve the problem of medication on time for patients and other special groups, at the same time, it is convenient for family members to observe the patient information, and can effectively facilitate the daily life of patients.