443 results about "Petrol station" patented technology

The invention relates to the technical field of gas station equipment monitoring, in particular to a gas station equipment monitoring system and method based on the Internet of Things. The method specifically comprises the steps of collecting multi-dimensional operation parameters of equipment and business process node dynamics in real time, constructing a bidirectional coupling graph model of the equipment and business, and extracting high-order features of physical association and business logic interaction between the equipment by using a graph convolutional network; predicting equipment fault risks by adopting a dynamic health scoring mechanism, backtracking a risk propagation chain in combination with an attention mechanism, and mapping multi-dimensional data into interpretable fault diagnosis information through an abnormal semantic generation network; a double-layer reinforcement learning game mechanism is introduced, an inner layer coordinates equipment maintenance and a risk suppression strategy, an outer layer overall plans service efficiency and a safety target, optimization actions such as resource scheduling and oil product allocation are generated, and a perception-diagnosis-decision closed loop is formed. According to the method, full-time perception of the equipment state, active fault early warning and cross-domain collaborative optimization are realized, and the operation and maintenance efficiency and safety of the gas station are remarkably improved.

The embodiment of the invention provides a local life service integration method and device and terminal equipment. The method comprises the following steps: integrating a plurality of heterogeneous local life service providers into a gas station service platform to obtain a local life service platform, and collecting real-time service data in real time; non-oil sales fluctuation of the gas station is predicted based on the real-time service data, and the order quantity and the delivery cycle of upstream and downstream suppliers are dynamically adjusted according to a prediction result; constructing a multi-dimensional data analysis model, predicting user traffic and various service demands in different time periods every day, and configuring a corresponding local life service time window based on a prediction result; dynamically updating callable local life service resources and dynamically deploying gas station human resources based on the order quantity, the delivery cycle and the local life service resource configuration; and generating a personalized service list of the user by using a collaborative filtering algorithm and a reinforcement learning algorithm, interacting with the user in an interaction interface, and providing corresponding local life service resources for the user.

The invention relates to the field of intelligent fault diagnosis, in particular to a system and method for integrating intelligent fault diagnosis of an oiling machine, and the method comprises the following steps: S1, integrating operation data obtained by sensors of an oil way, a circuit and associated equipment of the oiling machine in real time, and constructing a distributed framework based on a Spark core component and a Hadoop distributed file system; data storage is carried out through an HDFS; s2, continuously collected operation data of the oiling machine are input into the fault diagnosis model, and real-time anomaly detection is carried out; s3, analyzing the operation data through the fault prediction model, and predicting the fault probability of the oiling machine in the long-term change trend or the short-term change trend of the operation data; and S4, performing graded early warning according to the detected or predicted fault condition. According to the invention, the fault detection accuracy can be improved, real-time monitoring and early warning are realized, diagnosis and maintenance are facilitated, and the operation management level of the gas station is improved.

The invention discloses an operation state monitoring method and system based on gas station equipment, and relates to the technical field of equipment health monitoring, and the method comprises the steps: collecting and preprocessing load and behavior data, and calculating a load fluctuation value according to the preprocessed load and behavior data; calculating a health index according to the load fluctuation value, and calculating the remaining life and the maintenance priority according to the health index; and constructing a target function according to the maintenance priority, solving the target function, generating a distribution result, and storing, collecting and analyzing generated load and behavior data. According to the method, the weighting function is constructed through the high-coupling frequency point set, the load fluctuation value is calculated, the load fluctuation prediction precision is improved, the health indexes of gas station equipment are calculated by using a nonlinear weighted synthesis method, the problem that the relationship between consumer behavior data and equipment load data cannot be fully utilized is solved, and the load fluctuation prediction accuracy is improved. The maintenance priority of the gas station equipment is calculated, and the operation efficiency and maintenance precision of the gas station equipment are improved.

Methods and systems are provided for estimating a carbon footprint of a vehicle in real-time. In one example, the carbon footprint is estimated based on blockchain data. The blockchain data may record carbon emissions generated along one or more energy supply chains of the vehicle, and the estimated carbon footprint may be displayed at a user interface at a list of estimated carbon footprints corresponding to recharging or refueling sites.

The utility model discloses a buried oil tank of a double-layer gas station, and relates to the technical field of double-layer oil tanks. The device comprises a base, a first connecting assembly is arranged on the outer surface of the base, and an adjusting assembly is fixedly connected to the outer surface of the first connecting assembly. Through the connection of the adjusting assembly and the second connecting assembly, after the positions of the first connecting assembly and the adjusting assembly are fixed, the second connecting assembly can be driven to move up and down by changing the length of the adjusting assembly, so that the second connecting assembly can move to the same height as a fixed steel belt; when the fixing steel belt is located on the double-layer oil tank with the large size, even if the position of the fixing steel belt is close to the upper portion, the fixing steel belt can be connected with the fixing steel belt through movement of the second connecting assembly, and therefore the fixing steel belt can be conveniently connected. Different second connecting assemblies and fixing steel belts do not need to be selected according to the size of the double-layer oil tank, certain universality is achieved, and use is convenient.

The invention particularly relates to a gas station oil gas recovery online monitoring system, method and device and a medium, the monitoring system comprises a sensor network, an edge controller and a cloud computing monitoring platform, and the sensor network is used for collecting working parameters at key nodes in the oil gas recovery process. And the edge controller is used for performing preliminary data processing based on the working parameters to obtain oil gas recovery performance parameters and refueling equipment early warning information. And furthermore, the cloud computing monitoring platform is used for acquiring the oil gas recovery performance parameter sent by each edge controller in the gas station, and performing multi-dimensional data analysis based on each oil gas recovery performance parameter to obtain an oil gas recovery multi-dimensional monitoring result. By executing multi-dimensional data analysis, abnormal conditions in the oil and gas recovery process can be found and fed back in time, efficient oil and gas recovery work is ensured, meanwhile, potential fault points can be recognized in advance, the downtime and maintenance cost caused by faults are reduced, and the stability and reliability of the oil and gas recovery process are improved.

The invention belongs to the technical field of oil product transaction supervision, and discloses an intelligent supervision platform and a monitoring method for oil product circulation. The method comprises the following steps: deploying an edge node at a gas station and calibrating through a satellite signal; synchronizing a device signal based on an improved PTP protocol; the method comprises the following steps: collecting product oil circulation data through product oil circulation equipment, adding a PTP calibration timestamp to the product oil circulation data, and storing the product oil circulation data through a Hyperledger Fabric alliance chain to generate a block containing a time anchor point; the SSL / TLS protocol is adopted to encrypt and transmit data to the provincial cloud platform, and cross-database operation of product oil circulation data is carried out through a two-stage submission transaction processing mechanism; product oil circulation data are integrated based on an SOA architecture, a standardized tax control model is generated through ETL, and intelligent analysis and early warning are performed through a dynamic double-track early warning mechanism; according to the method, the problem of unreliable time synchronization in a complex network environment is solved, data such as transaction and inventory are ensured to carry credible timestamps, and second-level anomaly traceability is supported.

The invention discloses a gas station optical storage, charging and switching level supervision system, and belongs to the field of gas station optical storage, charging and switching level supervision. The problems that in an existing optical storage, charging and switching station, all devices are mutually independent, data are not shared, integrated management or data analysis cannot be carried out, and energy-saving benefits cannot be visually inquired are solved. The gas station light storage, charging and switching station comprises photovoltaic equipment, energy storage equipment, photovoltaic residual electricity networking equipment, electric equipment and operational equipment. And the operating equipment comprises charging equipment and battery replacement equipment. The system is suitable for managing the light storage, charging and station switching of the gas station.

The invention discloses an intelligent analysis method and system for gas station operation data, and relates to the technical field of operation data analysis, and the method comprises the steps: collecting gas station data for preprocessing, generating symbolized sequence data for the preprocessed data through employing a symbolized approximate aggregation SAX algorithm, and calculating the similarity of the symbolized sequence data by using a dynamic time warping (DTW) algorithm, constructing an accumulative error matrix, and backtracking an optimal alignment path to obtain high-similarity sequence data. According to the method, a continuous time sequence is converted into a discrete symbol sequence through the application of a symbolic approximate aggregation algorithm, the data complexity is remarkably reduced, the trend characteristics of original data are reserved, a symbol quantile interval is generated through a cumulative distribution function of Gaussian distribution and an inverse cumulative distribution function of standard normal distribution, and the probability that the symbol quantile interval is larger than the discrete symbol sequence is reduced. The symbolization process has a strict statistical basis, and the frequent pattern is extracted by using an Apriori algorithm through a high-similarity sequence data set.

The present invention belongs to the field of virtual character generation and relates to interactive testing technology, which is used to solve the problem that the existing technology cannot generate virtual characters for simulation training. Specifically, it is a virtual character interaction design generation method based on multimodal perception, including a character generation sub-method and a test optimization sub-method; the character generation sub-method includes the following steps: "Virtual image setting conception": setting basic parameters of the virtual character, the basic parameters include image style, category, positioning and basic information, the basic information includes gender, age, appearance characteristics and personality characteristics, realizing first-person perspective roaming and device interactive operation, allowing users to operate virtual devices; the present invention can simulate gas stations, oil depots and other depot scenes, and can also develop emergency accident scenes for simulation training. At the same time, it combines key technologies such as 3D modeling and emergency simulation to ensure training effects.

The embodiment of the invention provides a gas station user information and local service linkage method and device and terminal equipment, and belongs to the technical field of data processing. The method comprises the steps of obtaining first consumption information corresponding to a historical user in a target gas station in a target area and second consumption information corresponding to the historical user in a target shop in the target area, and obtaining initial evaluation information corresponding to the target shop; performing false detection on the initial evaluation information to obtain target evaluation information corresponding to the target shop; determining a target consumption model corresponding to a historical user in the target area according to the first consumption information, the second consumption information and the target evaluation information; obtaining third consumption information corresponding to the target user in the target gas station and fourth consumption information corresponding to the related shop in the target area; and determining a target consumption route corresponding to the target user by using a target consumption model according to the third consumption information and the fourth consumption information.

The invention relates to the technical field of oil gas recovery, and discloses a gas station oil gas recovery intelligent operation and maintenance system based on high-performance flow measurement, and the system comprises a collection module which is used for collecting the oil gun refueling amount, the oil gas recovery amount and the recovered oil gas pipeline pressure in real time through a sensor in the refueling process, and collecting the control degree used for controlling the oil gas flow; the correction module is used for correcting the control degree value by using an extended Kalman filtering algorithm to dynamically correct the oil and gas recovery amount, recursively estimating the flow state through the extended Kalman filtering algorithm and outputting the corrected gas-liquid ratio; the judgment module is used for judging whether the corrected gas-liquid ratio is in a preset normal interval or not, judging that the system equipment is normal if the corrected gas-liquid ratio is in the preset normal interval, and performing equipment state diagnosis based on a Bi-LSTM network and a VMD algorithm if the corrected gas-liquid ratio is not in the preset normal interval; the generation module is used for generating an optimal operation and maintenance scheme by adopting a DQN network based on the diagnosis result and generating a corresponding operation and maintenance instruction; intelligent operation and maintenance of gas station oil gas recovery are promoted.

The invention belongs to the technical field of intelligent detection and operation and maintenance, and provides a gas station and oil depot inspection and maintenance and inspection system based on AR glasses, and the system comprises the steps that an AR module detects a storage tank to obtain comprehensive multi-source data; the data visualization module superposes and displays the comprehensive multi-source data at the physical position of the storage tank in real time to obtain real-time picture data of the AR glasses; the path optimization module plans a shortest inspection path and guides an inspector through a ground projection arrow; the collaborative maintenance module receives the real-time picture data of the AR glasses through the collaborative platform, marks the real-time picture data and sends a maintenance instruction; the training drilling module simulates the oil unloading process of the oil tank truck, sends out an operation instruction and records the operation duration; the simulation evaluation module compares actual operation with the operation instruction, sends out virtual leakage early warning information and generates a capability evaluation report; the real-time storage tank state is obtained through the AR technology, and the shortest inspection path is obtained, so that the inspection time and energy consumption are reduced, and meanwhile, the maintenance time is shortened.

The invention relates to the technical field of product oil management, and discloses a product oil purchase-sale-stock multi-modal data analysis method and system. The method comprises the following steps: acquiring real-time inventory data, transportation state data and sales terminal data in a product oil supply chain to form a multi-modal data set; performing data cleaning on the data, and extracting key inventory characteristics to generate a cleaned data subset; obtaining associated historical purchase data, regional demand prediction data and market price fluctuation data based on the gas station identification information to form a multi-dimensional auxiliary data set; inputting the features into an inventory feature extraction model, generating a multi-feature vector set, and fusing the multi-feature vector set; inputting the fused feature vectors into an inventory state evaluation model set, and outputting inventory early warning level and abnormal type information; and finally, a dynamic allocation scheme is generated by combining real-time inventory data and the like. According to the method, multi-modal data are integrated, so that the comprehensiveness and accuracy of data analysis are improved, and the purchase-sales-stock management of the product oil is assisted to be more suitable for market dynamics.

The invention provides an intelligent gas station optimization scheduling method and system, is applied to the technical field of vehicle scheduling, and aims to guide a vehicle to enter a proper initial parking position by obtaining the identity and service demand of the vehicle when the vehicle enters the station and generating a service voucher and combining real-time resource information in an energy station. And when the service resources in the station are available, selecting the most suitable target vehicle for resource allocation according to the type of the available service resources and the demand information recorded in the waiting vehicle service voucher. In the service process, if service demand update information exists, the service voucher of the vehicle is dynamically adjusted according to the update information, and according to the adjusted service voucher, the system can provide an accurate second guide signal for the vehicle completing the current service to guide the vehicle to go to the next stop, so that the service quality of the vehicle is improved. The whole process of the vehicle in the station is ensured to be smooth and efficient, and path conflict or congestion caused by demand change is avoided, so that optimal scheduling of the vehicle in the whole life cycle in the energy station is realized.

The invention provides a multi-mode perception gas station environment safety early warning method and system, which are applied to the technical field of safety early warning, and are used for obtaining video and audio data, extracting vehicle and environment sound information, carrying out preliminary judgment, and carrying out event confirmation, priority ranking and linkage instruction generation through a rule inference engine. Therefore, deep fusion and comprehensive analysis of the multi-modal information are achieved, the accuracy and robustness of event judgment are improved, concurrent events can be effectively processed, refined linkage control is achieved, the accuracy and robustness of event judgment are improved through multi-modal information fusion, priority ranking and linkage can be carried out according to the events, and the efficiency of event judgment is improved. The method has the advantages that the problems that single-modal information is limited, simple fusion is insufficient, and concurrent event processing is not fine are solved.

A hydrogen refueling station including a first and a second dispensing module having first and second dispensing pressure detection means, where supply lines are fluidly connecting a storage module to an inlet compressor line and a compressor outlet line is fluidly connecting an outlet of the compressor to a dispensing line and thereby to the first and / or second dispensing module via output compressor valves, cascade lines are fluidly connecting the hydrogen storage module and the dispenser modules thereby configured for bypassing the compressor, where a controller is configured for controlling valves and thereby a fluid path from the hydrogen storage module to the dispensing modules, the controller is configured for controlling a bypass valve based on feedback from pressure detection means, from a first dispensing pressure detection means or from a second dispensing pressure detection means to establish a required pressure in the compressor outlet line.

The invention relates to the technical field of gas station operation optimization, in particular to an intelligent gas station operation optimization system and method based on big data and artificial intelligence. The data acquisition module acquires and uploads multi-source data in real time, the data processing module cleans and standardizes the multi-source data to generate auditable tagged data, the AI analysis module performs demand prediction based on a demand prediction model, and performs grouping through a K-means algorithm to generate user portraits. The intelligent scheduling module carries out intelligent dynamic scheduling according to a demand prediction result, optimizes service efficiency and reduces client waiting time, the operation optimization module carries out precise marketing according to a client portrait and formulates a personalized preferential strategy, and the feedback suggestion collection module monitors operation data and client feedback in real time. And the result is returned to the AI analysis module to optimize the prediction model and the marketing strategy. According to the invention, the scheduling and prediction precision is improved, an operation decision basis is provided for managers, and the gas station operation efficiency and customer satisfaction are improved.

The invention discloses a gas station anomaly detection method based on a multi-modal large model, and the method comprises the following steps: collecting a video image of a gas station; acquiring environment sensor data of the gas station; fusing the video image and the sensor data to construct multi-modal data; and inputting the fused multi-modal data into the trained multi-modal large model for reasoning, and judging whether an abnormal event occurs in the gas station.

The invention discloses an oiling machine with a pipeline monitoring function, relates to the technical field of oiling machine monitoring, and solves the technical problems that intelligent analysis is difficult to carry out according to pipeline operation data and oil product characteristic changes, and an effective abnormal early warning and oil outlet amount compensation adjustment scheme cannot be automatically generated. Through the super-threshold analysis unit and the low-threshold analysis unit, whether the pipeline pressure is abnormal or not and whether the flow is in a normal range or not can be accurately judged, the problems of pipeline leakage, blockage and the like can be found in time, the operation safety of the gas station is greatly improved, and the super-threshold analysis unit can accurately judge whether the pipeline pressure is abnormal or not according to comparison between real-time pressure and set standard pressure. The pressure abnormal condition is rapidly judged, a detailed abnormal reason report is generated, based on accurate calculation of oil product temperature changes and expansion coefficients and deep analysis of the relation between oil product viscosity and flow, the oil outlet amount can be accurately compensated and adjusted according to the actual condition, and metering errors are reduced.

Charging device for charging a traction battery (120) of an electrically powered motor vehicle (100), with a device for making an electrical connection to the traction battery (120), with a first storage unit (30) for storing thermal energy, wherein the first storage unit (30) comprises a reservoir (32) filled with a first coolant, which is water and / or glycol and has a temperature between 30°C and 50°C, with a second storage unit (40) for storing thermal energy, wherein the second storage (40) is a fuel tank of a filling station is formed and comprises a reservoir (42) filled with a second coolant, which is a fossil fuel and has a temperature between 30°C and 50°C and is lower than the temperature of the first coolant, with an energy transmission device (50) having a coolant line (52), wherein the energy transfer device (50) for transferring thermal energy between the first storage unit (30) and the traction battery (120) is thermally coupled to the first storage unit (30) and thermally coupleable to the traction battery (120), and wherein the energy transfer device (50) is furthermore thermally coupled to the second storage device (40) and thermally coupleable to the traction battery (120) for the transfer of thermal energy between the second storage device (40) and the traction battery (120), wherein the coolant line (52) is designed for selective supply of either the first coolant or the second coolant to the energy transmission device (50) and comprises at least one valve (56) which is connected on the one hand by fluid communication to the reservoir (32) of the first storage unit (30) and the reservoir (42) of the second storage unit (40) and on the other hand by fluid communication to a heat exchanger (110) of the motor vehicle (100), with a temperature control device (60) for temperature control of the first storage unit (30) and for temperature control of the second storage unit (40), wherein the temperature control device (60) comprises a heating device (62) which is thermally coupled exclusively to the first storage unit (30) to heat the first coolant, wherein the temperature control device (60) further comprises a refrigeration machine (64) which is thermally coupled to the first storage unit (30) and to the second storage unit (40), which represent two different thermal inertias, and which is designed and arranged to extract thermal energy from the second storage unit (40) and supply it to the first storage unit (30).

The invention discloses an oil abnormal loss root cause positioning method for a gas station, and belongs to the field of intelligent monitoring. According to the method, a homologous time synchronization cross-modal event bus is established, and multi-source sensor data and an operation and maintenance text log are fused; performing event extraction by adopting a template constraint Transform-BiGRU double-layer coding framework, and correcting the confidence coefficient of the event in combination with physical verification; and constructing a dynamic cause and effect graph under the constraint of a hard physical rule, calculating an effect quantity sorting root cause through intervention simulation, and finally generating a diagnosis report and realizing online iteration of the model. According to the method, the problems of insufficient timeliness, limited event screening precision and lack of credible physical support of an interpretation chain in the prior art are solved, and the root cause of oil loss abnormity can be accurately and traceably judged in real time.

The invention discloses a gas station oil discharge standard behavior detection method based on a video stream. The method specifically comprises the following steps: setting an image acquisition module to carry out image acquisition on a detection area as required; constructing and training a deep learning detection model for identifying a target object in the detection area; judging the credibility of a detection result output by the detection model according to an experience confidence threshold; and carrying out logical judgment on the credible detection result to determine whether the oil unloading process is a standard behavior or not.

The embodiment of the invention discloses a gas station commodity automatic recommendation method and device and electronic equipment. The method comprises the following steps: acquiring historical consumption data of a target user, and generating date-associated historical refueling data and historical shopping data based on the data to obtain an associated data set; and then, constructing a user behavior portrait corresponding to the associated data set based on a feature recognition algorithm. Furthermore, after the current refueling data of the target user is obtained, the current refueling data and the user behavior portrait are processed based on a machine learning algorithm, and a commodity recommendation list is obtained. Different commodity recommendation lists are generated by analyzing the historical consumption data of each target user, personalized requirements of different customer users are met, the purpose of improving the commodity purchase rate is achieved, a commodity recommendation model can be automatically optimized after each recommendation is completed, and the commodity recommendation efficiency is improved. And the accuracy and the user satisfaction of the gas station commodity automatic recommendation method are further improved.

The invention belongs to the technical field of activated carbon preparation, and relates to a preparation method of modified activated carbon for oil gas recovery, which comprises the following steps: (1) pretreating activated carbon; (2) modifying activated carbon; (3) high-temperature curing treatment; and (4) post-treatment. By reasonably controlling the reaction ratio of the modifier solution and modifying the basic performance of the coconut shell activated carbon through the preparation process, the prepared activated carbon for oil and gas recovery has the advantages that the adsorption specific surface area is increased, the adsorption capacity is obviously improved, the strength is enhanced, and the butane working capacity value is increased; the working efficiency and the recovery effect of the oil gas recovery system are effectively improved, the oil gas emission concentration is reduced, and environmental protection and resource recycling are facilitated; meanwhile, a balance point is found between efficient oil gas recovery and economic cost control, so that the prepared activated carbon is suitable for oil gas recovery of the skid-mounted gas station, and a very valuable solution is provided for optimization of an oil gas recovery system of the skid-mounted gas station.

For powering a vehicle, a high energy density fuel is preferred. However, for example when the high energy fuel is highly concentrated hydrogen peroxide, this fuel may be dangerous to handle; especially when the person handling the fuel is a normal consumer filling a fuel reservoir of his vehicle at a gas station. The present invention therefore provides a vehicle arranged to receive a diluted—and thus safer—fuel, and to density this fuel to a concentrated fuel in low quantities on board for direct use. To this end a fuel densifier is provided in the vehicle arranged for receiving liquid diluted fuel and arranged to provide a concentrated fuel based on the diluted fuel, the concentrated fuel having a higher energy density than the diluted fuel. A power conversion module of the vehicle is arranged to convert the concentrated fuel to kinetic energy for powering the vehicle.

The utility model discloses gas-liquid ratio detection equipment suitable for an oil gas recovery system of a gas station, and relates to the technical field of gas-liquid ratio detection of oil gas recovery systems, and the gas-liquid ratio detection equipment comprises a first three-way pipe, a first detection valve and a movable gas flow detector. And the first three-way pipe is arranged on a recovery header pipe of the oil gas recovery system. A first port of the first detection valve is connected with the first three-way pipe, and a second port of the first detection valve is connected with the movable gas flow detector. The movable gas flow detector comprises a gas flow meter, a connector and two connecting pipes. And two ports of the gas flowmeter are respectively connected with the two connecting pipes through connectors. The ends, away from the gas flow meter, of the two connecting pipes are connected with the first detection valve and a detection valve of the oil gas recovery system respectively. Compared with a traditional method for judging the operation state of the oil gas recovery equipment by relying on representation, the equipment can provide a more accurate and more reliable monitoring result.

Systems and techniques may generally be used to integrate automated teller machine (ATM) functions into one or more fuel pumps at a gas station. An example system may include a media transfer slot and a display screen to present a fuel pump prompt and an automated teller machine (ATM) prompt. The example system may cause a fuel to be dispensed when the fuel pump prompt is selected. The example system may cause the media transfer slot to activate when the ATM prompt is selected.

The utility model discloses an oil gas recovery device for a gas station, and relates to the technical field of oil gas recovery devices, in particular to the oil gas recovery device for the gas station, which comprises an oil gun shell, a fixing device fixedly connected inside the oil gun shell, and an oil gun head fixedly connected inside the oil gun shell. And one side of the oil gun shell is fixedly connected with an air extractor. According to the oil gas recovery device for the gas station, through the arrangement of the supporting plate, the oil gas recovery device for the gas station has the effects that the structure is more stable, and meanwhile the service life of the device is prolonged; in the using process, oil gas in the oil tank can be extracted through the conical extraction opening in the oiling process, so that the effect of extracting and recycling the oil gas more conveniently and rapidly is achieved, and the purposes of being convenient and rapid to operate, simple in structure and high in practicability are achieved.