1106 results about "Distribution system" patented technology

The invention relates to the technical field of intelligent power distribution system state monitoring, in particular to a cable connection state online monitoring method for a low-voltage cable branch box, which comprises the following steps of: applying a disturbance excitation signal to a connection node of the cable branch box, and acquiring transient voltage, current and phase response parameters of the node in different excitation periods; establishing a mapping relation between the node electrical characteristics and the connection state; performing dynamic reference calibration on the acquired signals based on a multi-node space-time coupling matrix to form an adaptive judgment reference of electrical coupling between nodes; a connection degradation sensitive index is extracted through feature sequence differential calculation, a connection state quantitative evaluation result is generated, and real-time updating and anomaly recognition are carried out according to the state change trend; according to the method, the problems of misjudgment and delay caused by a monitoring mode depending on indirect parameters such as temperature and current are solved, high environmental adaptability and degradation identification precision are achieved, and the operation safety and monitoring reliability of the low-voltage power distribution system are greatly improved.

The invention discloses a dynamic task distribution system based on multi-source data fusion, belongs to the technical field of intelligent task scheduling, and aims to solve the problems of response delay and execution failure caused by undifferentiated rule verification, fuzzy resource matching logic and inaccurate real-time state evaluation in a traditional task distribution system. According to the system, a task request is obtained through a task receiving module, multiple indexes are converted through a data standardization processing module, a rule matching engine carries out multi-rule verification and outputs a matching degree score, a real-time capability evaluation module calculates a current capability value of an executor, and a dynamic decision module dynamically adjusts double weights according to a task emergency degree and generates a comprehensive score. And time, resource and skill conflicts are eliminated through the conflict detection unit, and finally the optimal executor is selected by the task allocation unit to issue the task. The system is suitable for various fields requiring efficient and accurate task allocation, such as grid command center order distribution, emergency response, logistics distribution, maintenance service and the like.

A gas-liquid contactor includes at least one packing section, a liquid distribution system, one or more liquid collection devices, and a fan. The at least one packing section includes a plurality of packing supports. Each packing support is removably attached to at least one other packing support and includes a structure defining a bottom surface and a packing perimeter and a plurality of structured packings positioned on the bottom surface within the packing perimeter. The structure includes at least one first attachment and at least one second attachment. The liquid distribution system is configured to flow a carbon dioxide (CO2) capture solution through at least one packing section. The one or more liquid collection devices include a bottom basin positioned beneath the at least one packing section. The fan is operable to form a CO2 lean stream and flow the CO2 lean stream from the at least one packing section.

The invention discloses a task load balanced distribution system and method based on a node resource state, and relates to the technical field of distributed computing, and the method comprises the steps: collecting and associating multi-dimensional node resource data and dependency relationship data between tasks; establishing a virtual synaptic connection for each pair of tasks with data interaction, and constructing a task-dependent neural network model; the node resource state is monitored in real time, and the synaptic connection strength is adjusted; dynamically generating an optimal task allocation strategy; when the node resource saturation is continuously too high or the task execution efficiency is obviously reduced, starting a task migration process; and in the migration process, a synaptic cache region is created in the intermediate node, interaction data is cached, a dependency task node mapping relation is updated, data is synchronized, and the collaboration efficiency is verified. According to the method, CPU and GPU resource states and task dependency are considered at the same time, accurate matching and cooperative scheduling are achieved, overload or idling of a single resource is avoided, and the resource utilization rate is increased.

A solid distribution system of an agricultural spreader includes a product hopper configured to contain solid particulate material, a blower, a manifold coupled to the blower and having a plurality of outlets, at least one boom arm comprising a plurality of parallel rigid tubes configured to carry the solid particulate material and air from the blower, and a plurality of hoses. The manifold is configured to split air flow from the blower into flows through each of the plurality of outlets. Each valve is in fluid communication with one of the outlets and one of the rigid tubes, and each valve individually controls flow through a respective one of the rigid tubes. Vehicles having such solid distribution systems are also disclosed.

The invention relates to the technical field of electric energy metering of a low-voltage power distribution system, and provides an EM algorithm-based district metering device misalignment identification method and system. The method comprises the following steps: establishing a theoretical misalignment value model of each outgoing line in different metering misalignment states, and determining a mapping relation between the different misalignment states and actual electric quantity data; the method comprises the following steps: constructing theoretical deviation values of each outgoing line metering device in different misalignment states on the basis of a transformer area incoming and outgoing line electric energy data and energy conservation relationship, estimating an initial attribution probability of a line state in combination with an index normalization mapping method, and obtaining a posterior attribution probability of each outgoing line line through Gaussian mixture distribution modeling under dynamic prior guidance; and based on the posterior affiliation probability of each outgoing line, constructing an objective function of joint observation value fitting quality, time continuity and misalignment amplitude balance, solving the objective function, and quantifying the electric quantity misalignment proportion of each outgoing line at each moment so as to judge classification and identification of misalignment behaviors.

The invention discloses an electrical integrated energy system toughness planning method considering an extreme event tail risk, and relates to the technical field of integrated energy system optimization, and the method comprises the steps: firstly, considering the massive load shedding risk caused by a small-probability extreme event, and constructing a pre-disaster defense-post-disaster emergency response electrical integrated energy system toughness planning frame; secondly, comprehensively considering toughness planning cost, emergency scheduling cost and tail risk loss in a small-probability extreme scene, and establishing an objective function of a planning model; then, for a disaster stage, establishing disaster prevention resource deployment related constraints of the toughness planning model; then, considering operation constraints of the post-disaster power distribution system and the natural gas system, and establishing post-disaster emergency response related constraints; and finally, performing linearization processing on the established planning model, and calling a commercial solver for solving.

The invention discloses an Internet of Things real-time task distribution system based on AI scheduling, and the system comprises a data collection module which is used for generating a task input vector, and constructing a node resource vector set; the semantic modeling module is used for inputting the task input vector into an improved StructBERT model to construct a task semantic vector; the intention analysis module is used for constructing a historical task intention vector library and a semantic conflict graph; the comparison judgment module is used for executing task conflict judgment and scheduling priority adjustment operation according to the task aggregation degree and the semantic difference vector; and the scheduling execution module is used for executing a scheduling calculation operation, generating a task allocation result and updating the historical task intention vector library and the semantic conflict graph. The method has the advantages of high task semantic understanding precision, high conflict judgment efficiency and high scheduling decision intelligent degree, and is suitable for a real-time task allocation scene in a multi-node heterogeneous Internet of Things environment.

The invention discloses a data element income automatic distribution system based on an intelligent contract. The system is constructed based on an alliance chain, the contribution degree of each party is quantified through an intelligent contract, the distribution proportion is dynamically calculated, and finally income settlement and on-chain evidence storage are automatically completed. According to the invention, high efficiency, transparency and fairness of data transaction income distribution are realized, rights and interests of all parties are effectively guaranteed, and credible circulation of a data element market is promoted.

The invention provides a logistics resource sharing and dynamic optimization configuration method based on the industrial internet in order to solve the technical problems that an existing distribution task distribution mode is mostly based on static data and is not flexible and efficient enough, and most distribution systems do not fully utilize real-time state information of vehicles, so that dynamic adjustment and optimization cannot be achieved in the distribution process. On the basis of perception of logistics resource real-time state information and customer demand dynamic information, a vehicle path model suitable for mixed taking and delivering is constructed, and the model is a multi-target model considering vehicle cost, time window deviation punishment cost and the like. In combination with the state information of the current logistics resources and the dynamic change of the customer demand, the hybrid delivery vehicle path model is solved through an improved adaptive large-scale neighborhood search algorithm to obtain an optimized delivery path scheme, so that the logistics vehicles can dynamically respond to the customer demand in the delivery process, and the delivery efficiency is improved. The method is more flexibly suitable for dynamically changing distribution requirements and complex urban traffic environments, and efficient logistics services are realized.

The invention belongs to the technical field of energy consumption management, and particularly relates to an energy consumption optimization control method and system for heating and ventilation equipment, and the method comprises the steps: constructing a distributed pump set architecture, and converting a transmission and distribution system from a centralized regulation and control mode into a distributed regulation and control mode; developing adaptation technology and equipment; establishing a dynamic hydraulic balance regulation and control model by combining a digital twinning technology and an intelligent algorithm; the dynamic regulation and control model is used for optimizing the pump set operation state and the valve opening degree in real time; by constructing a distributed pump set framework, the system can independently adjust the rotating speed of the pump units according to the actual requirements of different sub-areas, the adaptability of the system to different working conditions and load changes is greatly improved, and the heating and ventilation requirements of all the areas can be more accurately met; the problem of excessive energy supply or insufficient energy supply of partial areas caused by overall adjustment in a centralized regulation and control mode is avoided, so that the overall operation efficiency and comfort of the system are effectively improved.

The embodiment of the application provides a gravity self-balancing uniform water distribution system, which comprises first, second and third stage gravity self-balancing water distribution pipelines. Each second stage gravity self-balancing water distribution pipeline is connected to the first stage gravity self-balancing water distribution pipeline, and each third stage gravity self-balancing water distribution pipeline is connected to the second stage gravity self-balancing water distribution pipeline. The circulating water of the cooling tower is automatically depressurized after entering the first stage gravity self-balancing water distribution pipeline, and flows into each second stage gravity self-balancing water distribution pipeline on the basis of the self-weight of the water to realize double uniform water distribution. The water level height of each second stage gravity self-balancing water distribution pipeline is consistent, and the water inlet flows to the third stage gravity self-balancing water distribution pipeline again. The pressure at each water nozzle directly or indirectly connected to the third stage gravity self-balancing water distribution pipeline is consistent, and the water outlet of each water nozzle and the spraying area are substantially the same, so that uniform water distribution is realized, the water inlet is not affected by the water pressure, and the cooling efficiency of the cooling tower is significantly improved.

The invention discloses an agent scheduling and distribution system based on a user interaction scene, provides a page-level agent scheduling system for the first time, and breaks through the technical bottleneck that a traditional general AI model cannot adapt to a fine-grained scene. The method comprises the following steps: a function identification module, which is used for identifying a website or an application function module where a user is currently located; the page analysis module is used for analyzing the content structure of the current page and the user interaction context in the function identification module to obtain page features; the agent scheduling module is used for selecting and binding a corresponding agent from an agent resource pool according to the page features; and the life cycle management module is used for controlling the state storage, freezing or releasing of the intelligent agent when the page is loaded, switched or exited. The technical problems that although multi-agent cooperation is involved in the prior art, but most of the multi-agent cooperation is limited to back-end task scheduling, and dynamic mapping based on page granularity is not achieved are solved.

The invention relates to the technical field of intelligent power distribution systems, and particularly discloses a voltage fault diagnosis method based on an intelligent voltage protector, and the method comprises the following steps: extracting influence characteristics based on power grid data when a voltage fault occurs, and building a voltage fault first recognition model according to the influence characteristics; determining similar faults of each voltage fault according to an output result after the experimental characteristics are input into the other types of voltage faults; establishing a second voltage fault identification model, wherein all the first voltage fault identification models and all the second voltage fault identification models are deployed at the local and the cloud respectively; extracting real-time influence characteristics and inputting the real-time influence characteristics into all the voltage fault first identification models to determine a target fault; and inputting the real-time influence characteristics into a voltage fault second identification model corresponding to the target fault, and judging the type of the current voltage fault. According to the invention, the accuracy of voltage fault type identification is improved.

The invention belongs to the technical field of artificial intelligence, and discloses a smart energy production and distribution system based on artificial intelligence. The system comprises a sensing layer used for collecting energy production parameters, storage capacity, transmission loss and user requirements in real time; the data processing layer is used for performing exception elimination, format standardization and integrated storage according to production, storage, transmission and demand dimensions; according to the AI intelligent decision-making layer, a prediction unit outputs energy production potential and demand peak values in the future 1-24 hours, and an optimization unit generates a production adjustment, storage allocation and transmission path optimization scheme; and the execution layer receives and executes the scheduling operation. According to the system, supply and demand pre-judgment and dynamic regulation and control are realized through AI intelligent decision, the problem of traditional response lag is solved, and the energy utilization rate is increased by more than 15%; accurate input is provided for decision-making through full-chain data acquisition and standardized processing, so that the scheduling scheme is more practical, and the transmission loss is reduced by more than 10%.

The invention discloses a material flow collaborative distribution system for a double-color injection mold of an automobile connector, relates to the technical field of intelligent manufacturing equipment, and can solve the technical problems of inaccurate regulation and control in the injection molding process and easy generation of a bonding line defect, and the material flow collaborative distribution system comprises the following steps: obtaining production monitoring data in the production process of the double-color injection mold; according to time sequence monitoring parameters in the production monitoring data, abnormal data generated by temporary interference are identified and eliminated, and abnormal state parameters are obtained; wherein the abnormal state parameter is used for representing a real process abnormal state after the temporary interference is eliminated; according to the abnormal state parameter, screening out a historical similar state similar to the current production process from the historical production monitoring data, and determining the interference degree on the defect of the bonding line in the current production process according to the historical similar state; determining a current regulation and control demand according to the interference degree; and a regulation and control instruction is generated according to the current regulation and control requirement, and an execution mechanism is driven according to the regulation and control instruction to adjust the melt propelling speed.

The invention relates to the technical field of unmanned aerial vehicle operation of low-altitude economic intelligent logistics, in particular to a multi-distribution-center vehicle-unmanned aerial vehicle cooperative distribution route planning method, which comprises the steps of constructing a multi-target and multi-constraint mathematical model adaptive to cooperative distribution decision of multiple distribution centers and heterogeneous vehicle-unmanned aerial vehicle carriers; and solving the mathematical model by using the improved NSGA-II to obtain a route scheme meeting actual distribution requirements. According to the method, a multi-objective optimization model containing total transportation cost, distance and time is constructed, multiple constraints such as vehicle paths and unmanned aerial vehicle cooperation are introduced, a multi-level coded improved NSGA-II algorithm is adopted for solving, feasibility and diversity of solutions are initialized and guaranteed through a multi-strategy population, a multi-objective optimization tradeoff scheme is provided, and the method has the advantages of being high in robustness and high in robustness. The adaptability to a multi-distribution-center scene is improved, the economical efficiency, the space efficiency and the time efficiency of a distribution system are optimized, and the multi-dimensional requirements of intelligent logistics are met.

A video distribution system of an embodiment is a video distribution system that includes: a plurality of movable body devices mounted on a movable body on which an occupant boards; a user device that is used by a user at a location which is different from that of the movable body; and a communication network that communicably connects the plurality of movable body devices to the user device, and distributes a video from the plurality of movable body devices to the user device, wherein each of the plurality of movable body devices distributes a plurality of videos to the user device by an individual line, and the user device performs a combination process of the plurality of videos distributed from the plurality of movable body devices and generates a composition video.

The invention discloses an emotion response analysis and distribution system and method based on campus propagation, and relates to the technical field of information processing and emotion calculation. Comprising the following steps: acquiring a comment text, user feature information, user interaction information and a content topic label; performing emotion recognition on the comment text based on the user feature information, and performing correction in combination with a preset group weight coefficient to obtain a group characterization emotion value; constructing time sequence emotion data based on the emotion value and performing trend prediction to obtain a propagation popularity prediction result; constructing a propagation topological graph by using the user interaction information, and determining an opinion leader node and a key propagation path; calculating an emotion sensitivity coefficient of the topic, and generating a distribution priority matrix; and dynamically adjusting the rhythm and range of content distribution according to the priority matrix. According to the invention, the accuracy of campus public opinion perception and the timeliness of the distribution strategy can be improved.

The invention discloses a multi-micro-grid power distribution system two-stage robust collaborative optimization method and device, and belongs to the technical field of multi-micro-grid power distribution system optimization scheduling, and the method comprises the steps: inputting the obtained basic operation data and uncertainty characterization parameters of a multi-micro-grid power distribution system into a pre-constructed multi-micro-grid economic scheduling model, solving the model by adopting a column and constraint generation algorithm to obtain a day-ahead scheduling plan of the multi-microgrid power distribution system in the worst scene considering the space-time correlation; inputting the day-ahead scheduling plan, the obtained basic operation data of the multi-microgrid power distribution system and the tie line power coupling constraint between the power distribution network and the multiple microgrids into a pre-constructed double-layer collaborative optimization model, and solving the model in a distributed manner by adopting an alternating direction multiplier method, an intra-day optimization scheduling scheme meeting the requirement of good cooperative operation of the power distribution network and the multi-micro network friends is obtained; according to the method, the optimization result in the worst scene meets the robustness requirement, and meanwhile, the economical efficiency of the system is guaranteed.

The invention relates to a federated learning contribution degree evaluation and income distribution system and method, and belongs to the fields of federated learning, cooperative game theory and privacy computing. Comprising the steps that in each round of training, a client side not only executes local model updating, but also calculates contribution of the client side in a gradient space and a data space in parallel, then double-dimension evaluation results are fused, and a fusion contribution value of the double-dimension client side is obtained; accumulating or smoothing and normalizing the calculated fusion contribution values of the double-dimension clients to form an approximate Shapley value of each client in the current round; calculating an approximate minimum kernel value, carrying out weighted integration on the approximate minimum kernel value and the approximate Shapley value to generate a final aggregation weight, and carrying out weighted aggregation on local update models uploaded by all clients by the server by utilizing the final aggregation weight to update a global model; according to the method, the convergence speed of the model can be increased, 'convenient vehicle building 'is prevented, and fairness and stability between federal participants can be ensured at the same time.

The invention discloses an intelligent load distribution system and method for a centrifugal compressor unit. The system comprises a data sensing module, an intelligent decision-making module, an instruction execution module and a model updating module. The method comprises the steps that operation parameters of multiple parallel centrifugal compressors are synchronously collected in a high-precision mode through an industrial real-time network supporting hardware timestamps, and time-aligned system state observation data are obtained; constructing a state vector based on the data and a load prediction result, inputting a deep reinforcement learning agent fused with compressor physical characteristic constraints, and generating a load distribution instruction and a unit start-stop suggestion; after safety boundary verification is conducted on the original action, the guide vane opening degree is adjusted through a feedforward speed planning and fuzzy self-adaption PID composite servo control algorithm, and starting and stopping operation is executed; meanwhile, empirical data are collected online, and model parameters are periodically and finely adjusted. According to the invention, efficient, safe, accurate and self-evolution compressor group control is realized.

The invention relates to the technical field, and discloses a product dehydration optimization method based on an inclined box dense grader and an HNS ultrafilter, which comprises the following steps: introducing slurry into a vibration inclined box dense grader through a feed distribution system, and dynamically adjusting the vibration frequency, amplitude and period by combining an intermittent vibration system and a slurry concentration detection control system, the concentration self-adaptive control is realized; overflowing slurry is conveyed into an HNS ultrafilter through a slurry conveying system, and efficient separation is achieved through a centrifugal force field and cross flow filtration; the filtrate is shunted by a clear water self-circulation system and is used for process recycling and equipment cleaning; and the concentrated discharged slurry of the HNS ultrafilter and the underflow of the thickener are mixed and output or return to the previous process. The general drawing arrangement is optimized, the slurry dehydration efficiency is improved, and valuable metal is recycled to the maximum extent.

A method for providing item access comprises an item being locked in a storage area of a storage apparatus via a lock; an unlocking code, to unlock the lock, being provided to a user, via an electronic device of the user; and the storage area being unlocked by the user via using the unlocking code. Disclosure is provided of the user paying for the item. Short-range communication / interaction technology, such as QR code, may be used to facilitate the unlocking code being provided to the user.

The invention discloses a vehicle and unmanned aerial vehicle cooperative distribution path planning method based on a temporary waiting mode, and the method comprises the steps: carrying out the preprocessing of a customer set, carrying out the clustering of the customer set served by a vehicle-mounted unmanned aerial vehicle based on the capacity of a truck, obtaining a clustering center and affiliated to-be-served customers, and obtaining an initial network; modifying the initial network, constructing a spatial expansion network, splitting each clustering center into an unmanned aerial vehicle virtual outflow node and a virtual inflow node, and introducing a corresponding virtual arc; establishing a mixed integer nonlinear programming model; performing objective function and soft time window constraint linearization processing on the mixed integer nonlinear programming model, and establishing an arc-based mixed integer linear programming model; and solving to obtain an optimal distribution scheme. According to the invention, complex constraints of multi-vehicle multi-unmanned aerial vehicle cooperative distribution can be systematically considered, distribution cost minimization and time window constraint satisfaction are realized, and a scientific and efficient scheduling planning scheme is provided for urban logistics and intelligent distribution.

The invention discloses a logistics unmanned aerial vehicle material distribution energy consumption and communication collaborative optimization method. The method comprises the steps of collecting distribution task data of an unmanned aerial vehicle and communication deployment data in a flight environment; establishing an unmanned aerial vehicle distribution system model based on the distribution task data and the communication deployment data, and constructing an optimization target to optimize the total energy consumption and the total communication interruption time of the unmanned aerial vehicle for completing the distribution task; based on the unmanned aerial vehicle distribution system model, solving a global distribution sequence with the lowest energy consumption; taking the global distribution sequence as input, converting an unmanned aerial vehicle trajectory planning problem into a Markov decision process, and solving a local distribution trajectory in the unmanned aerial vehicle distribution process; on the basis of the local distribution track, a Bayesian optimization model and a deep reinforcement learning network are adopted to obtain an actual flight action of the unmanned aerial vehicle at the next moment and execute the actual flight action; and based on the real-time environment information, generating an optimal flight path satisfying energy consumption and communication collaboration, and completing a distribution task. According to the invention, an efficient and safe distribution system is realized.

The invention relates to the technical field of satellite-borne edge computing, and provides a satellite-borne distributed efficient data distribution system which comprises a computing processing module which is provided with a DDS and is used for processing satellite-borne computing tasks; the containerization module is used for packaging the application program and the DDS into a container; the dynamic unicast routing module is used for carrying out data routing among heterogeneous equipment and planning a data transmission path so as to deal with the situation that links are uncertainly connected and disconnected in a complex space environment; the ddrouter virtual multicast routing module is used for realizing forwarding of multicast routing by software and overcoming the dependence of a DDS service discovery stage on a hardware multicast routing function under a multi-hop network; the QoS configuration module is used for flexibly configuring QoS and multiple transmission modes to adapt to data stream transmission requirements under different task scenes; and the distributed consistency guarantee module is used for keeping the satellite data consistency through leader election and a log replication mechanism. The method aims to solve the problems of low data distribution efficiency, poor consistency, difficulty in heterogeneous adaptation and the like in a satellite-borne edge computing scene.

The utility model provides re-filtration equipment for iron-containing sludge wastewater produced by Fenton reaction, a water distribution system is used for uniformly distributing inlet water, the water is flocculated wastewater and enables the flocculated wastewater to automatically flow into a filtration system, and a transmission device in the filtration system comprises a driving wheel, a driven wheel and a belt, rotating shafts of the driving wheel and the driven wheel are parallel to the ground, the water distribution system is located above the transmission device, the movement direction of the top edge of the driving wheel in the transmission device during rotation is recorded as the conveying direction of the belt, and the conveying direction of the belt is opposite to the water incoming direction of the water distribution system during working; first HIW filter cloth is arranged on the belt, and the first HIW filter cloth is high-hydrophilic filter cloth and is made of a hydrophilic material. The re-filtration equipment solves the problem that iron-containing sludge wastewater is flocculent and is not separated, saves the medicament cost, improves the convenience of field operation, saves the manufacturing cost and occupied area of a sludge system, can operate automatically, and is low in investment cost, low in operation cost and simple and convenient in field operation management.

The invention relates to the technical field of data circulation and data security, and discloses a digital ecological data market circulation system, comprising: a data provider node deployed with a federated learning client and used for locally training a model by using original data, generating an encrypted intermediate result and managing a corresponding data asset voucher; the data demand side node is deployed with a federated learning coordination server and is used for defining a federated learning task, distributing an initial model and aggregating intermediate results from each data provider node to update a global model; the data element circulation method comprises the following steps of data capitalization and voucher generation, federal learning and process evidence storage, under-chain credible contribution degree evaluation and intelligent contract driven settlement. Compared with the prior art, the method has the advantages that the leakage risk is completely eradicated from the root of technology, a dynamic and accurate value evaluation and distribution system is achieved, a credible environment which is traceable in the whole process and transparent in rule is constructed, and the mobility and financial attributes of data assets are improved.

The present invention relates to a fire suppression arrangement for suppressing a fire on a vehicle in a fire containment zone. The fire suppression arrangement includes a base defining a platform onto which a vehicle can be driven. The base is transportable and mobile. The base includes wet compartments for storage of fire extinguishing agent. An erectable enclosure is dispersed around the platform. The erectable enclosure is capable of moving between a stowed condition in which a vehicle is movable onto the base and an enclosing condition in which the erectable enclosure contains fire extinguishing agent around the vehicle to put out a vehicle fire in use. A fire extinguishing agent distribution system is also provided for dispensing fire extinguishing agent from the wet compartments onto the vehicle in the event of a fire. The fire extinguishing agent can also be drained and recycled.