4198results about How to "Meet needs" patented technology

The invention belongs to the technical field of power grid regulation and control, and particularly relates to a park-level adjustable load-oriented resource regulation and control method and system, and the method comprises the steps: formulating an initial energy scheduling scheme according to the predicted energy demand in combination with the output characteristics of distributed energy in a park and the load condition of a power grid; and training a load regulation and control strategy model by adopting a reinforcement learning algorithm based on the initial energy scheduling scheme, and generating a personalized load regulation and control instruction for each energy consumption unit. According to the scheme, the real-time energy consumption data of the plurality of energy consumption units in the park, the output characteristics of the distributed energy and the power grid load condition can be comprehensively considered, a scientific and reasonable energy scheduling and load regulation and control strategy is formulated, and efficient utilization and green low-carbon development of park energy are realized. Meanwhile, the method also needs to have the characteristics of data sharing, accurate prediction, intelligent scheduling, rapid response and the like so as to adapt to complex and changeable energy requirements and environmental protection requirements of the park.

The invention discloses a control method and a control system of a data center liquid cooling heat dissipation system, and relates to the technical field of liquid cooling heat dissipation, the system realizes real-time state monitoring of server operation through a data acquisition and monitoring module, integrates multiple data such as temperature, flow velocity and pressure difference, forms a detailed comprehensive heat dissipation data set, and improves the heat dissipation efficiency. And a database is constructed for storage. And meanwhile, a cooling liquid flow velocity analysis control module of the system generates a server heat dissipation coefficient CN through the server operation environment parameter C1 and the server operation parameter C2, the server heat dissipation coefficient CN is compared with a preset heat dissipation threshold C for evaluation, and the cooling liquid flow velocity is adjusted in real time. Therefore, when the load of the server is increased, the cooling intensity can be automatically increased, the chip temperature is reduced, and stable operation of the server is kept; and when the load is reduced, the cooling intensity is reduced, the energy consumption is reduced, and the cooling efficiency and the energy utilization rate of the system are remarkably improved.

The invention discloses a charging pile operation safety management and control system based on artificial intelligence, and belongs to the technical field of charging pile operation safety management and control. A charging pile operation safety management and control system based on artificial intelligence comprises a data acquisition module, a physical environment monitoring module, a central processing unit, a safety evaluation model, a fault detection module, a risk warning and execution module, a multi-charging pile collaborative management module and a user interface. The problems that existing charging pile data collection and environment monitoring are not comprehensive, an intelligent safety evaluation mechanism is lacked, the fault detection and response efficiency is low, and resource allocation is unreasonable are solved. Precise monitoring and safety trend prediction of the operation state of the charging pile are achieved through comprehensive data collection and the safety evaluation model, an intelligent fault detection and grading early warning mechanism can rapidly recognize and respond to potential and existing faults, resource allocation is optimized through the multi-charging-pile collaborative management module, the overall performance is improved, and the system is suitable for large-scale popularization and application. The operation safety is ensured.

The invention discloses a short video advertisement putting optimization evaluation method based on deep learning, and relates to the technical field of advertisement putting, and the method collects user behavior data in real time, constructs a dynamic user portrait, enables an advertisement system to adjust the advertisement content and putting strategy in time according to the interest change of a user, improves the correlation of advertisements, and improves the advertisement putting efficiency. Meanwhile, user behavior mode data and advertisement content labels are subjected to multi-dimensional matching, and the matching degree of the advertisements and user interests is calculated by combining cosine similarity with a weighting algorithm, so that advertisement recommendation is more personalized and accurate, the advertisement click rate and conversion rate are greatly improved, and the advertisement recommendation efficiency is improved. Meanwhile, the optimal opportunity of advertisement display is defined by analyzing the exit tendency of the user and the advertisement clicking tendency, it is guaranteed that the advertisement can be displayed at the moment when the user is most likely to interact and click, and the problem of low conversion rate caused by poor opportunity in a traditional method is solved.

The invention discloses an intelligent financial statement automatic generation platform, and relates to the technical field of financial statement generation, and the platform comprises a data integration module which is used for connecting and synchronizing a data source, the data source comprises a bank transaction record, an enterprise resource planning system and an electronic invoice system, and data is grabbed through connection configuration of a data interface. According to the intelligent financial statement automatic generation platform, classification rules of financial subjects are customized by a user, so that the platform can adapt to specific financial statement requirements and business characteristics of different enterprises, the flexibility and applicability of the system are improved, statement customization is supported through the platform, financial statements of different versions are provided, and the user experience is improved. According to the method, different requirements of different users on financial information are met, the flexibility and applicability of the system are improved, a temporary version exclusive to the current requirement is formulated based on a customizable mechanism of a classification rule, and more targeted financial support is provided for decision and management of enterprises.

The invention discloses a knowledge graph-based nursing corpus automatic creation method, and relates to the field of artificial intelligence technology and medical information processing, and the method comprises a multi-dimensional data acquisition stage, a knowledge graph construction stage, a corpus automatic generation and updating stage, and a corpus quality control and evaluation stage. According to the automatic corpus generation method driven by the knowledge graph, dynamic generation and real-time updating of corpora are achieved by constructing an ontology structure, a corpus generation template and an updating algorithm in the nursing field; through a deep learning model and a transfer learning technology, new nursing knowledge and a diversified information structure are continuously introduced into the corpus, and the diversity of corpus content is increased.

The invention relates to a light control method and system based on a holographic interactive projection technology, and the method comprises the steps: projection region recognition, user interaction detection, light parameter calculation and light real-time regulation and control, the projection region recognition, scanning of a target region through a holographic projection device and a depth induction sensor, and generation of a three-dimensional space model of an environment; a motion capture device and a deep learning algorithm are used for carrying out real-time recognition on gestures or motions of a user, interaction intentions and priority ranking are generated, a holographic projection device is used for generating a three-dimensional environment model, the motion capture device recognizes the intentions of the user, and an illumination optimization model is used for calculating regulation and control parameters; and the output of the light equipment is dynamically adjusted, so that high-precision and intelligent light control is realized, and the problems that a traditional light control method is insufficient in environment perception capability, lacks a user interaction mode, is limited in flexibility and adaptability of light regulation and control, and lacks a multi-module cooperative working mechanism are solved.

The invention relates to the technical field of power grid planning, in particular to a charging pile planning method based on dynamic analysis. The method comprises the following steps: obtaining electric vehicle use data in a target area, and carrying out charging demand prediction analysis according to the electric vehicle use data to obtain a charging demand prediction model; based on the charging demand prediction model, performing multi-scene simulation to obtain charging demand distribution map data, multiple scenes including different traffic flows, different driving modes and different charging demand scenes; obtaining geographic information data of the target area; and constructing a spatial analysis model according to the geographic information data, and evaluating the candidate position of the charging pile according to the charging demand distribution map data, thereby obtaining position suitability score data. According to the method, different scenes are simulated, so that the adaptability and robustness of planning are enhanced.

The invention belongs to the technical field of computers, and particularly relates to a zero-code agent construction platform. The system comprises a module database, a semantic analysis and intention decomposition unit, a task flow tree generation unit and an agent construction unit, the semantic analysis and intention decomposition unit is used for performing image language analysis on a natural language instruction input by a user, decomposing the natural language instruction into a plurality of intention units with a sequence, and constructing an intention vector; the task flow tree generation unit is used for generating a plurality of corresponding task flow trees according to the intention vector; and the agent construction unit is used for analyzing all the task flow trees, finding out an optimal task flow tree, calling all target function modules in the task flow tree and completing the construction of the agent. According to the method, the precision of semantic analysis, the flexibility of task logic generation and the automation degree of agent construction are remarkably improved.

The invention discloses a course learning planning system based on a computer, and relates to the technical field of course learning planning, and the course learning planning system comprises a learning data acquisition module, a knowledge graph construction module, a learning index scoring module, a multi-index comprehensive evaluation module, a learning plan making module and a real-time progress feedback module. Wherein the modules are connected through electric signals; the learning data acquisition module is used for collecting learning data of students and determining evaluation indexes of the learning data. According to the course learning planning system based on the computer, by monitoring the learning progress and achievement of students, instant learning feedback is provided for the students, so that the students can quickly know the learning state of themselves, related learning resources and exercises are intelligently recommended according to the learning conditions of the students, the students are helped to consolidate knowledge and make up for deficiencies, and the learning efficiency is improved. Students can achieve a higher learning effect in a shorter time, and the learning efficiency is improved.

The invention discloses a new energy charging pile charging control method and system, and relates to the technical field of new energy, and the method comprises the steps: collecting user historical charging data, power grid load data, fixed electricity price information and weather forecast data in real time, and recognizing user charging habits and demands; generating a personalized charging scheduling strategy according to the charging habit of the user and the real-time power grid state; the availability of various energy sources is monitored in real time, the generating capacity and the cost of each energy source are evaluated, the priority of energy source selection is adjusted by using a personalized charging scheduling strategy, and an optimal charging mode is automatically selected; executing charging operation based on the charging mode selected by the user, and performing adjustment according to the power grid load and the energy consumption condition; the availability of various energy sources is monitored in real time, the generating capacity and the cost are evaluated, and the priority of the energy sources is dynamically adjusted, so that the response capability of the charging pile to environment change is improved, the charging cost of a user can be reduced, and renewable energy sources are fully utilized.

The invention belongs to the technical field of AI interaction, and discloses an AI interaction method and system based on emotion recognition. The method comprises the following steps that in a cloud data center, an emotion relieving database is built, and an emotion AI interaction engine is built; according to the real-time multi-mode monitoring data, using an emotion AI interaction engine to generate a real-time emotion recognition result and real-time AI interaction data; according to the real-time emotion recognition result, a real-time AI response strategy is generated, and real-time emotion relieving data is extracted; generating real-time AI response data according to the real-time AI response strategy, the real-time AI interaction data and the real-time emotion relieving data; and optimizing the emotion AI interaction engine according to the real-time feedback data to obtain an optimized emotion AI interaction engine. According to the method, the problems of low emotion recognition accuracy, low AI intelligence degree and lack of an evolution function in the prior art are solved.

The invention provides a distributed energy storage output scheduling optimization method, medium and system, and belongs to the technical field of distributed energy storage output scheduling, and the method comprises the steps: firstly, collecting the electrical parameters, load parameters, renewable energy power generation parameters and energy storage equipment parameters of a transformer area, and building an energy storage grid-connected equation set which comprehensively considers the factors; and predicting a load, renewable energy output and energy storage demand curve in a period of time in the future according to historical data. Then, a multi-time-period energy storage scheduling optimization model is constructed, and objectives comprise operation cost minimization, renewable energy consumption maximization and power grid fluctuation minimization; and solving the multi-objective optimization problem by adopting an improved particle swarm optimization algorithm to obtain a plurality of candidate schemes. And finally, comprehensively evaluating the candidate schemes by using a multi-objective decision-making method, and selecting an optimal energy storage scheduling scheme. The technical problem that in the prior art, only parameters of an energy storage system are considered, and influences of power grid input electrical parameters and load parameters are ignored is solved.

The invention discloses a charging pile output power control method, and particularly relates to the technical field of charging pile management, and the method comprises the following steps: collecting the real-time operation information of a charging station, analyzing the overall load fluctuation condition, and judging whether an early sign that the operation fluctuation intensity is too high exists or not; and if abnormity is identified, further collecting operation information of each charging pile, extracting feature data, and performing stability and adaptability evaluation. And an evaluation result is imported into a fuzzy reasoning model, and the charging pile is divided into a high-quality operation state and a low-quality operation state. In a single abnormal scene, the charging piles in a high-quality operation state maintain a constant-current and constant-voltage strategy, and the charging piles in a low-quality operation state are switched to an adaptive power adjustment strategy; in an overall abnormal scene, all the charging piles are switched to an adaptive power adjustment strategy, so that the operation efficiency and stability are improved; the strategy can be dynamically adjusted according to different operation scenes, and the requirements under different operation conditions are met.

The invention relates to the field of data asset management, and discloses a DCMM-based data asset active management method and system, and the method comprises the following steps: collecting data assets from all business systems, extracting multi-dimensional features, and generating a data attribute matrix; constructing a data value quantification model, and calculating the value of each data asset; based on a multi-objective optimization model, data assets are subjected to classification management, and optimization balance of data value, security, access efficiency and storage cost is realized; dynamically adjusting the weight of an optimization target according to different levels of the DCMM to enable a data management strategy to adapt to the data management maturity requirement of an enterprise; and performing resource allocation and priority control on the data assets according to an optimization result to realize active management. According to the method and the system, the accuracy, the flexibility and the resource utilization rate of data asset management are improved, and optimal configuration and efficient management of data assets in different development stages of enterprises are facilitated.

The invention discloses a camera module and a motor thereof, the motor comprises a base, a frame, a carrier, a driving assembly and an anti-shake circuit board, the frame is movably arranged on the base, the carrier is movably arranged in the frame, the driving assembly comprises a focusing driving assembly and an anti-shake driving assembly, and the anti-shake driving assembly comprises a focusing driving assembly and an anti-shake driving assembly. The focusing driving assembly is arranged on the carrier and the frame and used for driving the carrier to move in the longitudinal direction relative to the frame, and the anti-shake driving assembly is arranged on the frame and the base and used for driving the frame to move in the transverse direction relative to the base. The motor is arranged on the base, the anti-shake driving assembly and the focusing driving assembly are arranged on different sides of the motor, the anti-shake circuit board is arranged on the top surface of the base, the anti-shake driving assembly is located above the anti-shake circuit board, and the focusing driving assembly and the anti-shake circuit board are not overlapped in the longitudinal direction.

The invention relates to the technical field of television image communication, in particular to a user information input method and system in an intelligent television all-in-one machine. The method comprises the following steps: collecting a user image, carrying out white balance correction and focusing processing, generating a moving object focusing image, carrying out identification and attention tendency analysis on a character in the focusing image, obtaining character tendency data, analyzing a historical interaction image, identifying an interaction mode and constructing a user intention prediction model, and obtaining a user intention prediction result. And when the tendency data shows that the user preferences the television content, intention drilling and auxiliary adjustment are performed on the current image based on the prediction model, predicted user input information is generated, logic conflicts in the predicted information are detected, feedback optimization is performed, and final user input information is output. According to the invention, a more accurate and more flexible user information input method is realized.

The invention discloses a personalized digital human image creation and generation system based on deep learning, which relates to the technical field of digital human generation and comprises a multivariate data acquisition module, an image creation module, a model storage module, a matching module and a rendering interaction module. The multivariate data acquisition module collects facial images and whole body photos through a camera, and records voice samples through a microphone. According to the invention, by constructing the multivariate data acquisition module, the image creation module, the model storage module, the matching module and the rendering interaction module, full-process automatic processing from data acquisition to digital human image generation is realized; the multivariate data acquisition module can comprehensively capture the appearance and voice features of a user, and the image creation module extracts feature vectors by using a deep learning technology and generates a personalized digital human image by using a generative adversarial network technology.

The invention relates to a data verification method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining to-be-verified data, and determining a verification priority corresponding to the to-be-verified data based on a data type of the to-be-verified data; dividing the to-be-verified data into a plurality of to-be-verified data sets according to the verification priority; determining a target verification mechanism corresponding to each to-be-verified data set based on the verification priority corresponding to each to-be-verified data set, and determining a target verification strategy corresponding to each to-be-verified data set based on a corresponding relationship between the verification mechanism and a preset verification strategy; and according to the target verification mechanism and the target verification strategy corresponding to each to-be-verified data set, performing data consistency verification on each to-be-verified data to obtain a data verification result. By adopting the method, the efficiency of data verification can be improved.

The utility model discloses a kneading and beating massage machine core which comprises a machine core shell, a driving motor, a kneading transmission mechanism, a beating transmission mechanism, a deflection mechanism, a massage mechanism and a beating mechanism. The driving motor is connected with the kneading transmission mechanism and the hammering transmission mechanism, the deflection mechanism is provided with two deflection wheels and two kneading and hammering swing arms, the massage mechanism comprises deflection massage heads and ejector rods, the kneading and hammering swing arms and the ejector rods are installed at the two ends of each deflection wheel respectively, the deflection massage heads are installed at the top ends of the kneading and hammering swing arms, and deflection ball heads are arranged at the bottom ends of the kneading and hammering swing arms. A movable limiting seat at the bottom end of the ejector rod is arranged in a limiting groove of the movement shell; the beating mechanism is provided with a shaft sleeve, a spring, two beating eccentric wheels, two connecting rods and two swing rods, the shaft sleeve is arranged on the beating shaft, one end of the spring is connected with the shaft sleeve, the other end of the spring is connected with the beating transmission mechanism, the beating eccentric wheels are arranged at the two ends of the beating shaft and connected with the two connecting rods, the connecting rods are rotatably connected with the swing rods, and the swing rods are connected with the deflection ball head. The massage device can be used for kneading and beating massage at the same time.

The invention belongs to but not limited to the technical field of electrode materials, and particularly relates to a high-tap-density lithium nickel manganese oxide positive electrode material, a preparation method and a lithium ion battery, the chemical general formula of the high-tap-density lithium nickel manganese oxide positive electrode material is LiNi < 0.5-x > Mn < 1.5-y > M < x > N < y > O < 4 >, 0.1, 0 < = y < lt >; 0.1, M and N are doping elements and comprise one or more of Mg, Co, Al, Zr, W, Sb, Ta and Ti; the material is micron-sized spherical secondary particles formed by stacking and aggregating nano-sized octahedral primary particles, and is uniformly dispersed without agglomeration; the spherical secondary particles are formed by mixing spherical secondary particles with large and small particle size distribution, and the average particle size range of the large particles is 3lt; d < 50lt >; the average particle size range of the small particles is 1lt; d < 50lt >; 2 [mu] m.

The invention discloses an electric power monitoring device for an energy storage power station, the electric power monitoring device is installed on an electric power support rod, the electric power monitoring device comprises a rack, the right side of the rack is welded with a fixing plate, the fixing plate is in a semicircle shape capable of surrounding the electric power support rod, the rack is provided with a clamping mechanism, and the clamping mechanism clamps the fixing plate on the electric power support rod; the top end of the rack is fixedly connected with a top plate through a second connecting rod, a rotating mechanism is arranged on the top plate, the rotating mechanism is connected with a rotating rod to drive the rotating rod to rotate, the top end of the rotating rod is fixedly connected with a mounting plate, and a freely telescopic cylinder is mounted on the mounting plate; a lifting mechanism is mounted at the tail end of the barrel and connected with the camera to drive the camera to move up and down; the rack is also provided with a solar cell panel, and the solar cell panel is used for storing energy and providing power for the electric power monitoring device. The power monitoring device is convenient to install and can comprehensively monitor the high-voltage lines installed on the two sides of the power support rod.

The invention relates to a personalized medical decision-making method based on artificial intelligence, and relates to the field of medical health and artificial intelligence, and the personalized medical decision-making method comprises the following steps: S1, inputting medical data of a patient in a patient information input module, including historical cases, examination reports, genomic sequences and real-time health monitoring data; and S2, based on the patient information, the patient health comprehensive evaluation module evaluates the health state of the patient, and the medical decision module outputs a preliminary treatment scheme according to the evaluation result. By collecting comprehensive medical data of a patient and comprehensively evaluating the health state of the patient based on the data, the illness state of the patient is more accurately grasped, a more accurate treatment scheme is made, individual differences, including age, physiological indexes, psychological conditions and disease duration, of the patient are fully considered, and by calculating the comprehensive evaluation score of the patient, the patient health state is comprehensively evaluated. The timeliness and effectiveness of a treatment scheme are ensured, and the rehabilitation speed of a patient is increased.

The invention discloses a network resource optimization method for network slices, which comprises the following steps of: acquiring historical flow data, user behavior data and network topology information of each network slice from each network node in real time by utilizing a distributed data acquisition system, and performing data preprocessing on the historical flow data, the user behavior data and the network topology information to form a feature data set; inputting the feature data set into a prediction model constructed based on an attention mechanism and a mixed density network algorithm, optimizing the network weight through a gradient descent algorithm, and training the prediction model; inputting feature data of the current moment into the trained prediction model, and outputting prediction values of probability distribution of different network slices for future traffic demands; and formulating a resource pre-allocation strategy according to the predicted probability distribution of different network slices for future traffic demands, and dynamically optimizing and adjusting network resources. According to the invention, through accurate resource pre-allocation, network resources are utilized to the maximum extent, the operation cost is reduced, and the resource utilization efficiency is improved.

The invention relates to the technical field of medicine cold-chain logistics, and discloses a medicine cold-chain logistics dynamic data cloud platform and a route analysis method.The cloud platform comprises a data acquisition unit, a preprocessing unit, a data transmission unit, a storage management unit and a route analysis unit. Key data such as temperature, humidity and position are collected in real time through multiple sensors and are subjected to standardized preprocessing, so that the data are comprehensive, real-time and reliable, and a foundation is laid for subsequent analysis. In the aspect of storage management, partition storage is carried out based on time and space dimensions, and the data retrieval and management efficiency is greatly improved; in the aspect of route planning, factors such as time, temperature and humidity, congestion and the like are comprehensively considered, a scientific route cost evaluation function is constructed, costs such as transportation duration, temperature and humidity stability, road conditions and the like are covered, and in combination with a greedy algorithm, the medicine transportation quality can be guaranteed, the cost can be effectively reduced, and the logistics efficiency can be improved.

The invention relates to an ultralight and ultrahigh-storage-ratio flexible solar wing, and belongs to the technical field of solar wing devices. The device comprises two solar box blankets, two scissor rods, two single-fork hinges, a pressing device and a lifting rod. Wherein the lifting rod is axially and horizontally placed; the two solar box blankets are axially and symmetrically arranged on the two sides of the lifting rod in parallel. The middle positions of the opposite side walls of the two solar box blankets are each provided with a scissor rod. A single-fork hinge is mounted at the bottom of each scissor rod; the two single-fork hinges are in butt joint with the lifting rod from the two sides of the lifting rod respectively. A pressing device is arranged on the side wall of the solar box blanket; clamping of the solar box blanket structure is achieved through the pressing device; the flexible solar wing has the advantages of being light in weight, small in folding size, good in configuration expandability and the like.

The invention relates to a method and a system for realizing personalized recommendation based on multi-feature fusion face recognition, and aims to provide real-time, efficient and accurate recommendation service, the method comprises the following steps: collecting a face image of a target audience in real time through a camera device, and preprocessing the image to extract a face region; running a face recognition algorithm in the edge computing device, and extracting multi-modal features including age, gender, appearance and style features; a comprehensive feature vector is generated by using a Transform model through a feature fusion module, and style classification and appearance classification are realized; according to the method, user feature vectors and a content database are matched on the basis of cosine similarity, personalized recommendation content is generated, the weight of a classification model is dynamically optimized in combination with user feedback, and dynamic behaviors and appearance features of a user are accurately captured through a time sequence analysis module, a dynamic style analysis module and a deep appearance analysis module; and comprehensively generating user feature description by combining vision, voice and character multi-mode information.

The invention discloses an intelligent ventilation system and method for a cage for livestock breeding, and belongs to the technical field of livestock breeding, and the system comprises an acquisition processing module, an environment modeling module, a change prediction module, an optimization decision module, a strategy simulation module, a storage safety module, an equipment control module, a monitoring feedback module, a user interaction module and an emergency response module. According to the invention, environmental conditions can be managed more actively, environmental parameters are prevented from deviating from an ideal state due to a hysteresis effect, the stress influence on animals is reduced, specific requirements of different livestock animals are met, the air quality and animal health level in an animal house are improved, the decision precision of the system is improved, and the economic benefit is increased. It is ensured that the cage environment is always kept in the most ideal state, improvement of air quality in a short term and minimization of long-term energy consumption are balanced, and the overall efficiency of the system is effectively optimized.

The invention relates to the field of juicer communication, in particular to a background communication method and a background communication system for a juicer system. The method comprises the following steps: obtaining a fruit and vegetable image reserved in a juicer; performing self-adaptive juicing feature analysis on the reserved fruit and vegetable image, performing intelligent juicing parameter adjustment, and constructing a self-adaptive juicing strategy; identifying surrounding environment parameters of the juicer; according to the surrounding environment parameters of the juicer, a self-adaptive juicing strategy is carried out, environment trend influence intelligent adjustment is carried out, juicing control simulation is carried out, and juicing control simulation data are obtained; multi-period juicing effect evolution is carried out on the juicing control simulation data, abnormal state prediction is carried out, and juicer abnormal early warning signals and juicer abnormal fault prediction information are generated; acquiring the network access state of the current juicer; through efficient and rapid background communication, the juicer use experience and performance of a user are improved.

The invention discloses an intelligent vibrating rod, and relates to the technical field of concrete pouring equipment. The device comprises a gasoline engine, a vibrating rod head is arranged on one side of the gasoline engine, and an adjustable rod body is arranged between the gasoline engine and the vibrating rod head; a direction adjusting part and an angle adjusting part are arranged in the adjustable rod body, and the vibrating rod head is fixed after being adjusted in a circumferential rotation mode around the adjustable rod body through the direction adjusting part. And the vibrating rod head is fixed after being overturned and adjusted at the end part of the adjustable rod body through the angle adjusting piece. According to the device, the adjustability of the angle of the vibrating rod head is realized through the matching of the worm, the worm gear and the like, the vibrating coverage can be ensured without frequently moving the vibrating rod or adjusting the construction position in a narrow space, the vibrating surface can be greatly increased through the matching of the angle adjusting piece, the vibrating blind area does not exist, and the working efficiency is improved. The uniformity and compactness of the concrete are ensured, and the requirements of users are met.