476results about How to "Increase randomness" patented technology

The invention discloses an SM4 encryption method based on an FPGA, and relates to the technical field of data encryption, and the method comprises the steps: obtaining to-be-encrypted plaintext data; a plurality of SM4 encryption cores are configured on the FPGA chip to perform parallel encryption operation on plaintext data to be encrypted; wherein each SM4 encryption core adopts a pipeline architecture, and the pipeline architecture comprises an access device, a round function arithmetic unit and a key adder; an extraction circuit based on physical noise and integrated on the FPGA chip is utilized to generate N-bit random numbers as encryption keys of each SM4 encryption core; handshake signals are collected to calculate the operation efficiency of each SM4 encryption core; adjusting FPGA resource allocation among the SM4 encryption cores by adopting a priority scheduling algorithm according to the operation efficiency; in the encryption operation process, power consumption equalization is carried out by adopting polynomial and logical operation hybrid calculation, and time sequence randomization is carried out by adopting a random waiting period. Aiming at the problem of weak anti-difference sensitivity in the prior art, the side channel attack resistance is improved.

The invention discloses a key generation and distribution system based on quantum random numbers, and relates to the technical field of quantum key distribution. The system comprises a quantum random number generation module, a light source control module, a quantum key distribution module, a detector module, a data processing module, a communication control module, a network anomaly monitoring module and an identity authentication module. According to the secret key generation and distribution system based on the quantum random number, the quantum random number generator generates a real unpredictable random number sequence by using the randomness principle in quantum mechanics, and the random number sequence is taken as the basis of the secret key, so that the unpredictability and the safety of the secret key are fundamentally improved; compared with a traditional secret key generation method based on a pseudo-random number, the quantum random number has higher randomness and lower predictable risk, various cryptographic analysis attacks can be effectively resisted, the uncrackability of the secret key is ensured, and an unbreakable safety guarantee is provided for information communication.

The invention provides an electromagnetic photoacoustic synchronous integrated brain function imaging method and device, and relates to the field of multi-mode brain function imaging research. According to the invention, electroencephalogram, magnetoencephalogram, functional near infrared spectrum and functional ultrasonic imaging technologies are fused, important advantage complementation is formed in signal specificity and temporal-spatial resolution, and neural activity can be described from the angle of human cranial nerve electrophysiology and neural metabolism can be observed from hemodynamic information at the same time. And electrophysiology and hemodynamic activities of the brain can be synchronously recorded.

The invention discloses a federal learning data processing method based on privacy protection, and the method comprises the following steps: S1, a client uses local data to train a generator of a generative adversarial network, and generates virtual data similar to the local data in distribution; s2, setting three privacy protection levels according to the privacy sensitivity of the local data; s3, performing model updating operation by using a homomorphic encryption technology; s4, utilizing a dynamic weight optimization mechanism based on a multi-arm bandit algorithm to obtain a priority processing data set; s5, preliminarily updating the global model, analyzing generated data through a reverse inference detection mechanism, and judging whether a privacy disclosure risk exists or not; s6, the server feeds back the updated global model to the client, and the client continues personalized model training in combination with local data; and S7, generating new virtual data, and carrying out the next round of global model training. According to the method, the generative adversarial network, differential privacy and homomorphic encryption are combined, so that efficient federated learning under privacy protection is realized.

The invention provides a privacy data analysis method and system based on collaborative learning and dynamic encryption, and relates to the technical field of privacy, and the method comprises the steps: receiving original data of a plurality of participants, the original data of each participant being in an initial encryption state; performing secondary encryption on the original data of each participant by using the dynamic encryption key to obtain secondary encryption data; inputting the secondary encrypted data into a preset collaborative learning model, and decrypting the collaborative learning model by using a security computing protocol under homomorphic encryption in combination with a dynamic encryption key of each participant to obtain a privacy protection analysis model which can be used by each participant; when data analysis is carried out, the privacy protection analysis model is used for processing input data to be analyzed, and correctness of the analysis process is ensured through a verifiable computing technology; and based on a predefined access control strategy, only returning an analysis result that the participant has access to the participant to the corresponding participant.

The invention discloses an unmanned aerial vehicle path planning method based on global search and meta-heuristic optimization, and the method comprises the steps: firstly building an unmanned aerial vehicle path planning model under complex constraints, determining a fitness function and a constraint condition thereof, setting algorithm initialization parameters, carrying out the chaotic mapping of an initialization population position, and carrying out the optimization of the algorithm; and performing loop iteration solution by using a meta-heuristic optimization algorithm, outputting a global optimal path, finally realizing the global optimal path on the unmanned aerial vehicle, and calculating a flight distance corresponding to the optimal path to complete unmanned aerial vehicle path planning. According to the method, a meta-heuristic algorithm, namely a crown porcupine algorithm, is combined with tabu search, the global search capability is enhanced, and meanwhile, population initialization is optimized in combination with chaotic mapping, so that the randomness and unpredictability are increased, the algorithm can converge more quickly, and the robustness of the algorithm is improved. The method has obvious advantages in solving the problem of path planning with complex environment and complex constraint, and solves the problem of path planning of the unmanned aerial vehicle in the three-dimensional complex mountain environment.

The invention relates to the field of PID control, and provides a tread calender rotating speed PID control method and system, a storage medium and equipment. The tread calender rotating speed PID control method comprises the following steps: processing an initial solution space of a plurality of to-be-optimized parameters based on Logistic-Tent chaotic mapping and dynamic reverse learning to obtain an initial population matrix of a Sabot swarm algorithm; according to the evaluation function, calculating the initial fitness of the soloat group individuals, and updating the global optimal position of the soloat individual with the optimal fitness to the current optimal position; executing a salmons swarm algorithm, and searching the to-be-optimized parameters by simulating a search behavior or an attack behavior of a salmons; in the process of executing the sodat swarm algorithm, if it is judged that the algorithm enters a development stagnation state, executing a transverse crossing strategy and a longitudinal crossing strategy to enable the algorithm to get rid of the development stagnation state; and when a set termination condition is satisfied, outputting a solution corresponding to the current optimal position, and controlling the direct current brushless motor. The method can improve the response speed.

The invention discloses a robot optimal path planning method based on an improved angle skid optimization algorithm, and the method comprises the steps: designing a single-target optimization problem under a constraint condition based on the angle skid optimization algorithm, setting a target function as the shortest distance between a starting point and an end point, and determining the constraint condition; a good point set strategy is adopted to replace random node initialization distribution, and an adaptive dynamic weight, a dynamic weight, an adaptive coefficient, a Brownian motion random disturbance parameter and a random walk and adaptive t distribution disturbance strategy of step length adjustment are introduced. A hiding behavior, a blood jetting behavior, an escape behavior, a skin blackening and brightening behavior and a melanocyte stimulating hormone (MSH) rate formula of the algorithm are optimized respectively, and a planned path is optimized through the improved HLOA algorithm. Compared with the prior art, the method has the advantages that the convergence speed, the optimization precision and the global search capability of the angle exid optimization algorithm in robot path planning are improved, and the method is suitable for optimal path planning in a complex environment.

The invention discloses a multi-agent unmanned aerial vehicle search task energy optimization method based on an entropy maximization strategy, and belongs to the field of unmanned aerial vehicle search task energy optimization. The implementation method comprises the following steps: modeling a multi-region search task of the multi-agent unmanned aerial vehicle, constructing an energy consumption model of the unmanned aerial vehicle, taking the minimum energy consumption of a multi-agent system as a priority target, adopting a reinforcement learning algorithm with maximized multi-agent entropy, making a decision on the action of each unmanned aerial vehicle, and obtaining a multi-region search task of the multi-agent unmanned aerial vehicle. According to the method, the randomness of strategy implementation of each agent is enhanced, premature falling into a suboptimal solution is avoided, real-time adjustment is performed on the next action decision of each unmanned aerial vehicle according to the environment and energy consumption observed by other unmanned aerial vehicles based on a method of centralized training in distributed execution, and when the unmanned aerial vehicle arrives at a target area, the unmanned aerial vehicle is subjected to real-time control. And carrying out full-path search on the target area to ensure the optimality of solving sub-problems, namely, realizing energy optimization of a multi-unmanned aerial vehicle search task based on an entropy maximization strategy.

The invention discloses an environmental monitoring system based on an optical sensor, and relates to the technical field of environmental monitoring, and the system comprises the following components: a quantum entanglement module, an optical sensor integration module, a quantum measurement and data processing module, and a data transmission and sharing module. By integrating the quantum entanglement module, the optical sensor integration module and the quantum measurement and data processing module, high-precision and real-time monitoring of environmental parameters is realized, the quantum entanglement technology provides measurement precision and anti-interference capability superior to those of a traditional optical sensor for the system, the accuracy and reliability of data are ensured, and meanwhile, the quantum entanglement technology can be used for monitoring the environmental parameters in real time. Due to the design of high sensitivity and wide dynamic range of the optical sensor, the system can stably work under various complex environment conditions, and the efficiency and accuracy of environment monitoring are effectively improved.

The invention discloses a water turbine wear fault diagnosis method based on a deep learning model, and belongs to the technical field of water turbine fault signal processing. Comprising the following steps: acquiring a water turbine wear fault sound signal; a Tent chaotic mapping function is adopted to optimize an initial population of a white shark optimization algorithm WSO; introducing a long and short term memory (LSTM) network model to solve the limitation of a convolutional neural network (CNN) in processing a long sequence problem, and constructing a CNN-LSTM water turbine wear fault diagnosis model; an improved white shark optimization algorithm IWSO is introduced into the CNN-LSTM model, and hyper-parameters of the model are optimized, so that the diagnosis precision is improved, and the calculation amount is reduced; and importing the collected fault signal as an input into the model for training and testing to obtain a final diagnosis result. Diagnosis and identification of the water turbine wear fault signal are completed through the steps, the deep learning model has good robust performance, the diagnosis precision of the water turbine wear fault can be improved, and the deep learning model serves as a beneficial supplement of an existing water turbine state monitoring and fault diagnosis system.

The invention discloses a file transmission protection method, system and device based on multiple encryption algorithms, and relates to the technical field of information, and the method comprises the steps: selecting a target file needing to be transmitted, carrying out the preprocessing, and generating file fragments; analyzing the sensitivity of each file fragment, and performing hierarchical encryption processing to obtain an encrypted fragment set; selecting a steganography carrier file, and embedding the encrypted fragments into the carrier file to generate a steganography index table; generating a dynamic session key based on the confusion key pool, encrypting the steganographic file transmission layer and embedding a dynamic key generation parameter; the receiving end generates a session key according to the transmission message header, decrypts the transmission layer data, extracts the steganographic file and decrypts the steganographic file; recombining the decrypted and recovered fragmented data into a complete file according to an identifier sequence; by dynamically matching the steganography carrier file, the efficient embedding of the fragmented data and the generation of the steganography index table are realized, and the concealment and the adaptability in the transmission process are ensured.

The invention relates to a data calibration method suitable for an atmospheric pollutant sensor deployed in an embedded terminal. The method comprises the following steps: acquiring original response data of different sensors with different concentrations in different atmospheric environments after temperature compensation, and corresponding temperature, humidity, air pressure data and sampling time; collecting real concentration values of detection objects corresponding to different sensors at corresponding moments given by a national control station or a provincial control station; preprocessing the obtained data to obtain a final data set; a random forest algorithm is used as a teacher model, a gradient elevator algorithm is used as a student model, and hyper-parameters of the gradient elevator algorithm and the random forest algorithm are optimized by using a hedera helix algorithm; substituting a hyper-parameter optimal solution found by optimization into a corresponding algorithm, and retraining the teacher model and the student model by using hyper-parameter combinations; and deploying, updating and displaying the model in the embedded equipment. And the model size is reduced to realize the deployment of the embedded end on the premise of ensuring the accuracy.

The invention relates to the technical field of signal encryption, in particular to an aviation data bus signal encryption method and system based on a field programmable gate array (FPGA), which comprises the following steps of: based on input three-dimensional tensor signal data, extracting slices from a time index of an aviation data bus according to a fixed interval, progressively sequencing amplitudes of signal channels, and then segmenting; according to the method, through processing logic of matrix decomposition and feature curve generation, the feature extraction and dimension reduction process is optimized, the distinction degree and the expression capacity of feature information are improved, the randomness and the anti-cracking capacity of a key are enhanced through a key generation mode combining a dynamic disturbance factor and an encryption parameter, and the safety of signal transmission is guaranteed; through combination of amplitude superposition and frame-by-frame storage, dynamism and high efficiency of a signal encryption process are realized, signal tampering and eavesdropping risks are reduced, and through feature reconstruction and point-by-point matching processing in a decryption stage, accurate restoration of signal amplitude is ensured, and data integrity and anti-interference capability are guaranteed.

The invention relates to the technical field of electric power data acquisition with an encryption function, and discloses an electric power data acquisition terminal with an encryption function and a method. By combining the environment data and the equipment state, the encryption process enhances the security and adaptability of data encryption. Environment and equipment data input ensures that encryption results are different, and potential safety hazards caused by static data sources are avoided. The data are reasonably combined through a seed generation formula, it is ensured that the seeds have enough randomness, and the brute force cracking risk is reduced. The key generation strategy generates a unique key through a seed, so that the attack resistance of the system is improved. The key matrix and random number generation strategy improves the unpredictability of the encryption algorithm. And dynamically updating the encryption matrix to prevent the encryption matrix from being cracked in long-term use. In the whole process, comprehensive protection of the data in acquisition, encryption and transmission is ensured, and the data is effectively prevented from being tampered or stolen.

The invention relates to the technical field of crowd sensing, in particular to a cooperation mode excitation method and system based on a Stackelberg game. The method comprises the steps of obtaining a task set of crowdsourcing tasks and user historical data; calculating a quality score of the crowdsourcing task according to the urgency degree and the energy consumption of the crowdsourcing task; performing task division on the crowdsourcing task based on the quality score of the crowdsourcing task, and generating a cooperative task based on the task division; performing capability value evaluation on the user according to the historical data of the user; and task allocation is carried out based on a capability value evaluation result and the generated cooperative task, a Nash equilibrium solution is solved in the task completion process by using a Stackelberg game, and an optimal allocation strategy is obtained. By introducing concepts of capability values, shelving levels and quality scores, tasks which exist in a system for a long time and are high in difficulty are combined, the tasks are completed through cooperation of users, and the receiving completion rate of the tasks is guaranteed.

The invention discloses a spectrum map construction-oriented sensing time resource allocation method, which belongs to the field of electromagnetic spectrum, and comprises the following steps of: establishing a time resource allocation model of a sensor; based on the timeliness index, setting an information age, and establishing a relationship between the information age and a service rate, a data arrival rate and a packet loss rate in a data transmission stage as a constraint condition of a time resource allocation model; converting a resource optimization problem in the time resource allocation model after setting the information age constraint into a convex optimization problem; solving a convex optimization problem by using a multi-strategy improved dung beetle optimization algorithm MSDBO to obtain an optimal time resource allocation scheme of three time periods of data acquisition Tc, channel detection Ts and data transmission time Tt; wherein the MSDBO improves the dung beetle optimization algorithm DBO by setting chaos pseudo-random, tangential flight search and crisscross strategies. Aiming at incoordination of communication and perception in the prior art, efficient allocation of communication time resources in a spectrum map construction process is realized.

The invention discloses a dynamic S-box generation method and test system based on a spatiotemporal chaotic system, and the method comprises the steps: constructing an iteration matrix through employing a preset m sequence, and determining a coupling object index and a disturbance symbol of each grid in an iteration process; wherein each element of the iteration matrix represents a grid; performing dynamic disturbance on the initial chaotic sequence according to the coupling object index, the disturbance symbol, the index offset and the grid coordinate to obtain a dynamic chaotic sequence; initializing the two-dimensional coupling image lattice by using a dynamic chaos sequence, and carrying out iteration to obtain an iterated coupling image lattice; removing the previous N iteration results of the coupled image lattice after iteration; and performing numerical conversion on the chaotic sequence value obtained by the (N + 1) th iteration to construct an S box. According to the S box design and test method, the safety and the attack resistance of the S box are improved, and an efficient and reliable research tool can be provided for cryptography researchers.

The embodiment of the invention discloses an anti-quantum secure communication method, device and equipment applied to a public network channel. A specific embodiment of the method comprises the following steps: sending user authentication information to a communication receiving end; generating public and private key information of a sending end; based on public and private key information of a sending end, the following steps are executed: generating a sending end random number pair; sending the sending end public key information and a receiving end public key information request to a communication receiving end; performing public key scheme encryption on the random number pair of the sending end to obtain encrypted information of the sending end; generating master secret information; in response to determining that the current time meets the period time bar, based on the master secret information, executing a second loop step: determining a temporary session key and a temporary session effective duration; and in response to determining that the current communication duration is less than or equal to the valid duration of the temporary session key, performing encryption processing on the communication information. According to the embodiment, on the basis of resisting quantum attacks, the storage resource overhead of both communication parties can be reduced, and the communication encryption security can be improved.

The invention discloses an AGV obstacle avoidance path planning method in an unmanned warehousing system, and the method comprises the steps: employing nested Logistic mapping and Skew Tent mapping to generate a chaotic initialization population to replace a population generation mode of a conventional differential evolution algorithm, carrying out the Levy flight operation after the selection operation, and carrying out the global path search on an environment map, thereby achieving the optimal path planning. And obtaining an AGV global feasible path avoiding obstacles in the environment map, and when the AGV has an unknown obstacle on the feasible path, re-planning the local path by adopting a dynamic window method so as to enable the AGV to realize an obstacle avoidance process in an interval where the unknown obstacle is located. The improved differential evolution algorithm enhances the global search capability through chaos initialization and a Levy flight strategy, and the AGV can quickly respond to an unknown obstacle through a dynamic window rule. The adaptability and the accuracy of path planning are improved, and the obstacle avoidance capability and the safety of the AGV in a complex environment are enhanced at the same time.

The invention relates to a multi-unmanned aerial vehicle cooperative confrontation decision-making method and system. The method comprises the following steps: constructing a multi-unmanned aerial vehicle cooperative air combat confrontation decision-making environment by establishing a multi-unmanned aerial vehicle air combat confrontation motion model and an air combat situation evaluation model; establishing a distributed partially observable Markov decision process model of the multi-unmanned aerial vehicle cooperative confrontation decision problem according to the action space and the local observation and state of each unmanned aerial vehicle in the confrontation decision environment; designing a multi-machine collaborative adversarial reward function and an HASAC algorithm network space; and training and generating a multi-unmanned-aerial-vehicle cooperative confrontation strategy model based on interaction between a network space and a multi-unmanned-aerial-vehicle cooperative confrontation decision-making environment of an HASAC algorithm. According to the method, for the multi-aircraft cooperative air combat confrontation problem, the specific global state is designed for the multi-aircraft cooperative confrontation decision-making unmanned aerial vehicle, and compared with direct splicing of observation vectors of all unmanned aerial vehicles, the global state dimension is reduced, and the training efficiency is improved.

The invention discloses an internal medicine laboratory data sharing and querying system, and relates to the technical field of laboratory data security sharing. A special management and control terminal is arranged to match internal medicine laboratory data of a corresponding patient according to identity information of a pre-queried patient; according to the method, the preset security conversion rule is used for converting the internal medicine laboratory data to obtain the corresponding shared query data, so that the dependence on a key is eliminated, the management cost of the key is saved, and the management difficulty is reduced; in the process of converting the internal medicine laboratory data, the internal medicine laboratory data is intercepted through the preset intercepted character quantity, whether each character in the intercepted data is 8 or 9 or not is judged, a plurality of grouped word strings are intercepted and selected based on judgment, and then the corresponding shared conversion sequence is obtained, so that the security of the data is improved, and the conversion efficiency of the internal medicine laboratory data is improved. And a safer and more reliable guarantee is provided for sharing and querying of internal medicine laboratory data, and the privacy of patients and the safety of medical data are ensured.

The invention belongs to the technical field of photovoltaic panel detection equipment, and particularly relates to photovoltaic panel impact resistance detection equipment which comprises a plurality of detection frames, and turnover mechanisms and displacement mechanisms are arranged in the detection frames; a top cover is arranged at the top of the detection frame, an operation box is installed between the outer walls of the detection frame, an ice hockey storage box is arranged on the outer wall of the top cover, and a limiting piece is arranged on the inner wall of the detection frame. The effect of changing the motion trail of the ice hockey transmitter is achieved by changing the rotating speed of the longitudinal gear, teeth of the second speed change gear are meshed with teeth of the first speed change gear, the circumference of the second speed change gear and the circumference of the first speed change gear differ greatly, and therefore the rotating speed of the first speed change gear is different from that of the second speed change gear. When the first change gear rotates for one circle, the second change gear already rotates for many circles, and the ice hockey transmitter is controlled to move, the transverse moving speed and the longitudinal moving speed are different, and the movement track of the ice hockey transmitter changes accordingly, so that the randomness of the ice hockey transmitting position is improved.

The invention discloses a speed control optimization method for an electric vehicle, and belongs to the technical field of PID control, and the method comprises the steps: S1, constructing an electric vehicle speed control system; s2, improving an information acquisition optimization algorithm, wherein an improved strategy is as follows: D1, introducing a hyperbolic cosine adaptive weight factor omega, and D2, using a growth helix updating strategy fused with reverse learning; s3, parameter setting is conducted on a PID controller module of the electric vehicle speed control system through an improved information acquisition optimization algorithm, and optimal three parameters Kp, Ki and Kd are obtained through algorithm optimization; and S4, applying the three optimal parameters of the PID controller obtained through optimization of the improved information acquisition optimization algorithm to the PID controller of the electric vehicle speed control system so as to optimize the control performance of the whole control system.

The invention discloses a network edge calculation method and a communication device, and relates to the technical field of network communication, and the method comprises the following calculation steps: inputting original data into a calculation processing module, and outputting processed data, encrypted data, a hash value of the encrypted data, an authentication code of a message and a verification result. And transmitting the encrypted data, the hash value of the encrypted data, the authentication code of the message and the verification result to a cloud server. The method has the advantages that the received data is changed firstly, so that the encryption efficiency and security of the data are improved, the data are encrypted in an encryption mode, the confidentiality of the data is guaranteed, the integrity verification of the data is carried out through the hash function and the message authentication code, and the security of the data is improved. According to the data transmission method and device, the data are ensured not to be tampered in the transmission process, all-directional protection of the data is achieved, meanwhile, the received data are verified in a verification mode so as to ensure the authenticity of the data, and dual guarantee of data transmission and verification is achieved.

The invention provides a true random number generator based on a magnetic tunnel junction device and a random number generation method. The true random number generator provided by the invention comprises a control circuit, a magnetic tunnel junction device and a random number generator, the control circuit is used for providing a plurality of continuous voltage pulse signals for the magnetic tunnel junction device, so that the resistance of the magnetic tunnel junction device oscillates; the plurality of continuous voltage pulse signals correspond to different flip probabilities of the magnetic tunnel junction device, and after the plurality of continuous voltage pulse signals cooperatively act on the magnetic tunnel junction device, the magnetic tunnel junction device accumulates the flip probabilities based on in-memory calculation, so that the final flip probability after accumulation tends to be a half-and-half probability; and the random number generator is used for generating a random number according to the resistance state of the magnetic tunnel junction device after the plurality of continuous voltage pulse signals are applied. According to the true random number generator based on the magnetic tunnel junction device and the random number generation method provided by the invention, random numbers with high randomness and uniform distribution can be generated.

The invention discloses a mixed sampling network traffic sample balancing method, which comprises the following steps of: firstly, carrying out data preprocessing on network traffic in a CIC IDS-2017 data set, and dividing the network traffic into a training set and a test set; secondly, the training set is subjected to SMOTE oversampling and ENN undersampling processing, Gaussian noise processing is introduced after SMOTE oversampling, and a mixed sampling sample is obtained; and finally, carrying out CNN training on the mixed sampling sample and verifying a training result through a test set to obtain a classification result. According to the method, Gaussian noise is added after SMOTE processing, so that the complexity of data is increased, the generated sample can better reflect various characteristics in real network traffic, and the risk of overfitting is remarkably reduced. According to the method, most of important information is reserved in the ENN, and unnecessary redundant data is reduced, so that the problem of information loss is avoided, and the adaptability of the model to complex network traffic data is improved. And the function of balancing the network flow data is realized.

The utility model discloses a controllable flexible pressing device applied to microneedle patch skin surface drug delivery, and belongs to the technical field of drug delivery, the controllable flexible pressing device comprises a microneedle patch, an electrostatic adsorption membrane, a rigid support body, an air bag and a thin film pressure sensor, the microneedle patch is attached to the skin surface, and a needle head is downward; the electrostatic adsorption membrane is arranged above the microneedle patch; the rigid support body is arranged on the electrostatic adsorption membrane, and an air bag mounting cavity is formed in the middle of the rigid support body; the air bag is arranged in the air bag mounting cavity; and the thin film pressure sensor covers the air bag. The device is simple in structure and convenient to operate, the application direction, the change rate, the magnitude and the action time of force in the dosing process can be controlled, the penetration depth of the microneedle is influenced, and then the positive influence on the experimental result and the clinical effect is generated.

The invention discloses a multi-dimensional load spectrum acceleration compilation method for a vehicle frame based on a WLTC working condition, and the method comprises the following steps: setting rigid connection of the vehicle frame, and building a whole vehicle dynamics model; creating a WLTC event working condition, carrying out whole vehicle dynamics simulation, and extracting a load at a connection point; performing finite element analysis by using an inertial release method; carrying out fatigue life analysis on the frame, and extracting fatigue hot spot numbers; reconstructing an analysis process, and extracting stress time sequence data; carrying out pseudo damage analysis on the stress time spectrum to intercept an original load spectrum; carrying out smooth connection processing on the intercepted acceleration spectrum fragments; and performing power spectrum density analysis on the acceleration spectrum and the original spectrum, screening the acceleration spectrum according to a result, and finally obtaining the multi-dimensional load acceleration spectrum of the vehicle frame based on the WLTC working condition, thereby shortening the bench test time and reducing the development cost of the vehicle frame.

The invention discloses a drill jumbo working hour prediction method and device, electronic equipment and a storage medium, and belongs to the technical field of working hour prediction, and the method comprises the steps: updating an original particle swarm position formula of an SABO algorithm according to Cubic chaotic mapping, and generating a first SABO algorithm; updating an initial iteration formula of the first SABO algorithm according to Piecewise chaotic mapping, and generating a second SABO algorithm; updating a position iteration formula of the second SABO algorithm according to a golden sine algorithm, and generating an optimal GSABO algorithm; performing iterative training on an initial neural network model based on the optimal GSABO algorithm and the index data to obtain an operation man-hour prediction model; and performing drill jumbo working hour prediction on the target operation based on the working hour prediction model. According to the method, the model parameters are determined by optimizing the SABO algorithm through the two chaotic mapping and golden sine algorithms, and the accuracy and efficiency of predicting the working hours of the drill jumbo are improved.