6376 results about "Power unit" patented technology

The invention provides a data management method, device and equipment and a readable storage medium, and the method comprises the steps: obtaining key value cache data generated by a first type of computing power unit in a pre-filling stage, transmitting the key value cache data to a memory pool, and caching the key value cache data in the memory pool; and in response to a data acquisition demand of the second type of computing power unit in a decoding stage, transmitting the specified key value cache data cached in the memory pool to the second type of computing power unit according to the data acquisition demand. According to the technical scheme of the invention, the memory pool is arranged and the aggregated transmission channel is utilized, so that the transmission efficiency of the key value cache data between the computing power devices is effectively improved, the data transmission delay is reduced, and the network transmission protocol overhead is reduced, thereby improving the data interaction efficiency of the computing power devices in a pre-filling stage and a decoding stage, and improving the user experience. The utilization of computing power resources is optimized, and the throughput and performance of large model reasoning are improved.

The invention discloses a thermal power generating unit deep peak regulation control system, and relates to the technical field of thermal power generating unit deep peak regulation, the thermal power generating unit deep peak regulation control system comprises a deep peak regulation control center, and the deep peak regulation control center is in communication connection with a data acquisition module, a load prediction module, a working condition monitoring module, a distributed control module and a safety monitoring early warning module. By introducing a distributed control architecture and bat algorithm optimization, each subsystem of the thermal power generating unit is divided into a plurality of local control units, independent and cooperative control is realized, the flexibility and the response speed of the thermal power generating unit in the deep peak regulation process are remarkably improved, and the reliability of the thermal power generating unit is improved. Distributed control ensures that each subsystem can quickly adjust operation parameters according to actual load requirements, and the global optimization capability of the bat algorithm further improves the self-adaptability and decision-making efficiency of the system in a complex working condition, so that the problem of response lag in a traditional centralized control mode is effectively solved.

The invention discloses a hierarchical optimization scheduling method for deep peak regulation of thermal power generating units, and the method comprises the following steps: system layering: dividing a power system into a plurality of subsystems, each subsystem comprising a thermal power generating unit cluster and differentiated load demands; subsystem-level prediction: generating a basic scheduling plan; dynamic preference-driven multi-target collaborative optimization: receiving multi-target data from each subsystem, carrying out multi-target collaborative optimization, modeling three targets of a power grid company, an environmental protection department and a terminal user as game participants, quantifying the priority of each party by adopting a fuzzy membership function, generating a dynamic game solution through a Nash equilibrium solver, and carrying out multi-target collaborative optimization; screening out a Pareto optimal solution giving consideration to interests of multiple parties; performing online verification on the dynamic security domain; virtual synchronous machine cooperative support: simulating operation characteristics of a synchronous generator; and global coordination and iterative optimization: uploading the optimal scheduling scheme of each subsystem to a scheduling center through a message queue telemetry transmission protocol, and performing global constraint verification.

The invention relates to the technical field of resource allocation, in particular to a unified resource pooling management method for multiple computing power sources of an unmanned aerial vehicle platform, which comprises the following steps of: analyzing an unmanned aerial vehicle service flow to obtain subtask nodes and dependency relationship edges, and measuring and calculating the execution time of each subtask on different heterogeneous computing power units. According to the method, subtask nodes and dependency edges are obtained by analyzing the unmanned aerial vehicle service flow, the refined execution time of each subtask on a heterogeneous computing power unit is measured and calculated on the basis of task execution priority ranking, the actual consumed time of data transmission between tasks is clearly calculated, a complete heterogeneous computing power pool scheduling basic view is formed, and the scheduling efficiency of the heterogeneous computing power pool is improved. Therefore, the task execution efficiency and the resource scheduling accuracy are improved; meanwhile, in the resource allocation process, the real-time operation temperature and the calculation error rate of each computing power unit are continuously monitored, the dynamic health state is intelligently analyzed and calculated, the potential fault risk is recognized in time, and a pre-degradation control signal is actively triggered.

The invention discloses a collaborative optimization scheduling method and system considering energy storage frequency modulation reserve. The method comprises the following steps: acquiring basic data of a power system; based on the basic data, a collaborative optimization scheduling model considering energy storage frequency modulation reserve is established, and the collaborative optimization scheduling model takes the minimum sum of the coal consumption cost, the unit start-stop cost and the wind curtailment cost of the thermal power generating unit as a scheduling target under multiple constraint conditions; the multiple constraint conditions comprise a lithium battery power constraint, a charging and discharging state constraint, an SOC constraint, a frequency modulation response constraint, a frequency safety constraint, a frequency modulation standby constraint, a flywheel energy recovery constraint, a thermal power generating unit operation constraint and a power balance constraint; solving the collaborative optimization scheduling model to obtain an optimal scheduling scheme of the power system; by comprehensively utilizing the advantages of a traditional unit, flywheel energy storage and lithium battery energy storage, the safety and operation economy of the system during frequency disturbance are improved.

The invention provides a thermoelectric unit intelligent early warning method and system based on an artificial intelligence model. The method comprises the steps that firstly, multi-source operation monitoring information of different operation dimensions of core components such as a turbine, a boiler and a generator of a thermoelectric unit is obtained; performing time sequence correlation analysis on each modal monitoring data, constructing a dynamic correlation matrix, generating a modal conflict correction coefficient, and obtaining a time sequence dependence feature set; inputting the model into a hierarchical evolutionary early warning model, and obtaining an evolutionary fusion early warning feature vector through modal conflict correction and dynamic feature evolution modeling; generating a working condition self-adaptive dynamic early warning threshold value based on the current operation working condition; through comparison and abnormal traceability of the traceability verification module, an abnormal root component and a propagation path are determined, and a targeted traceability early warning instruction is output, so that the early warning accuracy and adaptability of the thermoelectric unit are improved, and safe and stable operation of the unit is guaranteed.

The invention discloses a thermal power generating unit coal conveying belt intelligent inspection system and method based on artificial intelligence, and relates to the field of artificial intelligence and machine learning, and the method comprises the steps: collecting multi-source data, dividing a coal conveying belt into a grid coordinate system, distributing an initial risk score for each grid through an artificial intelligence model, and obtaining a preliminary inspection path; analyzing the time change trend of the coal flow speed through an artificial intelligence attention mechanism, processing the preliminary inspection path, marking a high-risk area, generating an optimized inspection path, and fusing multi-source data to obtain a comprehensive feature set; according to the method, the time change trend of the coal flow speed is analyzed through the attention mechanism, the routing inspection path is optimized according to the real-time coal flow trend and space correlation, blindness of artificial experience and hysteresis of static design are avoided, and efficient distribution of routing inspection resources is ensured.

The invention relates to the technical field of underwater vehicle drainage, and discloses an air and carbon dioxide linkage drainage device and an underwater vehicle, the air and carbon dioxide linkage drainage device comprises a power unit, an air unit, a pressure reduction unit and a flow guide assembly, and the power unit is provided with a first storage cavity; the first storage chamber is used for storing liquid carbon dioxide, the air unit is provided with a second storage chamber, the second storage chamber is used for storing high-pressure air, the pressure reduction unit is provided with a pressure reduction chamber, the first air inlet is communicated with the pressure reduction chamber, the first air outlet is communicated with the water ballast space, and a first heating source is arranged in the second storage chamber; the heating source is suitable for generating heat after receiving the signal so as to heat the air stored in the second storage chamber. The technical problems that in the air release process and when the air is in contact with water, the temperature is reduced, so that the volume of the air is reduced, and the drainage capacity of the air and carbon dioxide linkage drainage device is reduced are solved.

The invention relates to the technical field of aircrafts, in particular to a built-in compressed air and carbon dioxide linkage drainage system and an aircraft. The drainage system comprises a drainage device, a water ballast tank, a first connecting pipeline and a control unit, a first storage cavity for storing liquid carbon dioxide is formed in the first power unit, a second storage cavity for storing high-pressure air is formed in the second power unit, and a pressure reduction cavity is formed in the pressure reduction unit; the first storage chamber and the second storage chamber are both selectively communicated with the pressure reduction chamber; the water ballast tank is provided with a third storage chamber selectively communicated with the pressure reduction chamber; the first connecting pipeline is connected with the second power unit and the pressure reduction unit, and a first on-off valve is arranged on the first connecting pipeline; the first power unit is suitable for converting liquid carbon dioxide into high-pressure supercritical carbon dioxide under the control of the control unit, and the high-pressure supercritical carbon dioxide enters the third storage chamber after being decompressed by the decompression chamber, so that the first connecting pipeline selectively communicates with the second storage chamber and the decompression chamber.

The invention provides a thermal power generating unit intelligent start-stop process multi-level linkage cooperative control optimization method, which relates to the field of thermal power generating unit control, and comprises the steps of collecting equipment group operation parameters, establishing a multi-level dynamic control reference, constructing a cascade response mechanism to determine a target operation interval, subintervals are divided according to the parameter coupling degree, compensation adjustment coefficients are set for hierarchical adjustment, and a linkage control link is constructed to coordinate the adjustment process of each level of equipment group. According to the method, accurate cooperation among equipment in the starting and stopping process of the thermal power generating unit is achieved, the safety and efficiency of the starting and stopping process are improved, and energy consumption is reduced.

The invention discloses a multi-energy-storage thermal power generating unit optimal scheduling method, which belongs to the technical field of power system scheduling, and specifically comprises the following steps: acquiring operation data and power grid load data of a multi-energy-storage thermal power generating unit; constructing a load prediction model based on the collected data to obtain a load prediction result; taking the minimum comprehensive cost as a target, and combining a thermal power generating unit output constraint, an energy storage equipment charging and discharging constraint and a power grid security constraint to construct an optimal scheduling model; solving the optimal scheduling model by adopting an improved intelligent optimization algorithm to obtain an optimal scheduling scheme; performing real-time scheduling on the multi-energy-storage thermal power generating unit according to the optimal scheduling scheme; the method can improve the scheduling flexibility of the multi-energy-storage thermal power generating unit, effectively deals with the load fluctuation of the power grid, and is suitable for the optimal scheduling task of the multi-energy-storage thermal power generating unit in a complex power grid environment.

The invention relates to the technical field of underwater vehicles, in particular to a modular supercritical carbon dioxide phase change drainage device and an underwater vehicle. The modular supercritical carbon dioxide phase change drainage device comprises a plurality of power unit sets, a plurality of pressure reduction units and a flow guide assembly, each power unit set comprises a plurality of power units, each power unit is provided with a first storage cavity, and the first storage cavity is used for storing liquid carbon dioxide; the plurality of pressure reduction units are in one-to-one correspondence with the plurality of power unit groups, each pressure reduction unit is provided with a pressure reduction chamber, the pressure reduction chambers selectively communicate with the corresponding first storage chambers, and the pressure reduction chambers of the plurality of pressure reduction units communicate with one another; the flow guide assembly is provided with a first air inlet and a first air outlet, the first air inlet communicates with at least one of the multiple pressure reduction cavities, and the first air outlet communicates with the water ballast space. The modular supercritical carbon dioxide phase change drainage device is small in occupied space, safe, efficient and high in drainage capacity.

The invention discloses a system climbing demand evaluation and calling method for high-proportion new energy consumption. The method comprises the following steps: step 1, determining a thermal power generating unit start-stop model based on a fan, photovoltaic and load prediction curve of a time period scale; 2, evaluating the output condition of the fire motor start-stop model in the sub-period based on the short-time scale prediction fan and photovoltaic data; 3, evaluating the climbing power vacancy of the system by calculating the climbing capacity and the climbing capacity based on the output data of the thermal power generating unit; 4, constructing an energy storage sequential constraint model based on the system climbing power vacancy; and step 5, evaluating the system power supply shortage, the wind and light discarding result and the calling cost based on the system climbing power vacancy. The multi-source cooperative climbing capacity evaluation model including thermal power, hydroelectric power and energy storage is constructed, and the deep peak regulation capability of the thermal power generating unit and the cooperative optimization mechanism of the energy storage rapid response characteristic are combined; and the extreme climbing event coping capability is obviously improved.

A pneumatic conveying system and a control method therefor. The system comprises a power unit (1), a fan unit (2), a valve unit (3), a sensor unit (4), a pneumatic conveying unit (5), a pipeline arrangement net (6) and a control system (7), wherein the he fan unit (2), the valve unit (3), the sensor unit (4) and the pneumatic conveying unit (5) are connected together in an ordered manner by means of the pipeline arrangement net (6) to form a whole.

The invention relates to the technical field of power supply, and particularly discloses a peak and frequency regulation heat supply method for a multi-element energy storage coupling coal power unit, which is used for solving the problems that only active frequency is optimized, electric heating coordination and charge state constraint are lacked and time delay compensation is insufficient in the prior art. The method provided by the invention comprises the steps of system modeling, controller design, coupling constraint, adaptive parameter adjustment, delay compensation and distributed consensus. According to the method, a dual-domain electric power-thermal interconnection model is constructed, a cooperative controller based on delay compensation distributed model prediction control is designed, electric-thermal cooperative penalty and charge state constraint are introduced into a target function, a prediction window and weight parameters are adaptively adjusted, and network delay is identified and compensated online. And a consensus algorithm is adopted to realize multi-region power-heat collaborative optimization.

The invention discloses an intelligent thermal power plant hierarchical optimization control method based on multiple agents, and the method comprises the steps: obtaining the observation data of each thermal power generating unit agent, each wind and light storage agent and each deduction agent through an upper-layer plant-level scheduling decision agent, and calling a preset multi-agent reinforcement learning module, modeling the electric heating load optimal distribution problem of the thermal power plant, and solving to obtain an optimal load distribution result of each thermal power generating unit intelligent body and each wind and light storage intelligent body; the lower-layer equipment level control agent defines a steam turbine, a boiler body, boiler auxiliary equipment and a heat supply steam extraction device in each thermal power generating unit as corresponding equipment agents according to the optimal load distribution result of each thermal power generating unit agent, and integrates interaction information, equipment operation data and equipment parameter control mechanisms among the equipment agents; and carrying out equipment-level multi-agent optimization control modeling by taking a load distribution result and the minimum operation cost as targets, and solving to obtain an optimal control instruction of each equipment agent.

The invention discloses a secondary frequency modulation optimization control method under a low-load working condition, relates to the technical field of power grid resource optimization, and is used for solving the problem that a control strategy under the low-load working condition is not fully considered in the prior art. The current load interval is recognized, and control parameter correction is conducted on the unit located in the low load interval; calculating a total output power reference value; carrying out calculation by adopting a self-adaptive optimization algorithm, and carrying out power fine distribution to obtain an optimal charging and discharging instruction of each energy storage unit; and the output power is adjusted in real time through double-closed-loop control. The invention further discloses a secondary frequency modulation optimization control device under the low-load working condition, electronic equipment and a computer storage medium. By dynamically correcting the control parameters of the low-load thermal power generating unit and cooperatively distributing the hybrid energy storage power in combination with the adaptive optimization algorithm, the safety and economical efficiency of the energy storage system are guaranteed.

The invention relates to the technical field of power system automation, in particular to a climbing-frequency modulation coordinated optimization method and system considering energy storage capacity uncertainty, and the method comprises the steps: building an opportunity constraint model of an energy storage system based on the capacity uncertainty, and enabling the opportunity constraint model to be used for describing a reliable feasible region under the deviation of energy storage electric quantity; establishing an energy storage system linearization model considering a climbing-frequency modulation power unified constraint, and realizing power coupling and sharing constraint description of two types of adjustment services; aiming at the nonlinear characteristic of the gradeability of the thermal power generating unit, establishing a piecewise linearization model of the gradeability by adopting a piecewise linearization method; and establishing a thermal power-energy storage combined climbing-frequency modulation coordinated optimization model, and solving the optimization model by adopting a quadratic programming method to obtain the climbing power and frequency modulation reserve capacity of the thermal power generating unit and energy storage. According to the method, the actual available range of the energy storage system capacity can be dynamically reflected, the electric quantity out-of-limit risk caused by the uncertainty of the energy storage capacity is avoided, and the reliability of the scheduling result is improved.

The invention relates to the field of an energy storage frequency modulation system, in particular to a thermal power frequency modulation power optimization method for an energy storage cluster cooperating with a Saggowski new energy base, and aims to solve the problem that the frequency modulation enthusiasm of an energy storage cluster power station in a high-proportion new energy power system is reduced due to limited frequency modulation capability caused by power-capacity constraint. Thermal power generating unit compensation output is designed to reserve frequency modulation capacity for an energy storage cluster power station, meanwhile, sufficient coefficients related to the residual frequency modulation capacity of the thermal power generating unit are introduced, a thermal power generating unit frequency modulation power distribution model is designed, and the equipment loss condition of the unit is reduced while the operation cost of the thermal power generating unit is reduced. The SOC overall balance target, the cycle life and the economical efficiency target of each energy storage power station are considered, preference decision making is carried out on the SOC balance target of the energy storage power station to ensure that the frequency modulation capacity of the energy storage power station is sufficient, and the frequency modulation capacity of each energy storage power station is fully utilized while the frequency modulation cost of the energy storage cluster is reduced.

The invention discloses a motor-clutch time division multiplexing driving system for a rope-driven dexterous hand. The motor-clutch time division multiplexing driving system comprises a driving box, a plurality of rope-driven mechanisms and a plurality of dexterous fingers, wherein the rope-driven mechanisms and the dexterous fingers are arranged on the driving box; the rope driving mechanism comprises a power unit, a worm and gear unit and a guide unit. The power unit uses a sun gear to drive a plurality of planetary gears, and an electromagnetic clutch outputs power to the worm and gear unit; the plurality of worm and gear units are respectively used for controlling the winding and unwinding of the plurality of driving ropes; the plurality of guide units respectively guide the plurality of driving ropes to the same rope-driven rotating joints of the plurality of dexterous fingers; different rope-driven rotating joints of the dexterous fingers are controlled by different rope-driven mechanisms, and the same rope-driven rotating joint of the multiple dexterous fingers is controlled by the same rope-driven mechanism. According to the scheme, the fast switching characteristic of the electromagnetic clutch is ingeniously utilized, and driving control over multiple degrees of freedom by a single motor is achieved.

The invention relates to the technical field of electric power system regulation and control, and particularly discloses an electric power active balance control method for coupling multi-element energy storage of a coal power unit, which is used for solving the problem that the existing static active safety margin evaluation method cannot evaluate the safety of the coal power unit under the complex working conditions of high wind power penetration, large disturbance, system inertia decline and the like. The method solves the problems that multi-stage frequency response cannot be accurately described, online self-adaptive power distribution and continuous smooth scheduling are lacked, and consequently frequency drop is large, recovery is slow and output suddenly changes, and comprises the steps of building a collaborative characteristic model, calculating dominant characteristics on line, optimizing scheduling in a segmented mode and updating parameters in a closed loop. According to the method, by constructing a hierarchical inertia and multi-stage frequency modulation collaborative model, and adopting multi-scale online feature extraction and adaptive power distribution, segmented gradient optimization scheduling and closed-loop online parameter updating, quick response, smooth connection and accurate optimization of frequency support and economic scheduling in a wind power high-permeability scene are realized.

A modular satellite system is provided comprising a main body member, one or more controllers, a communication system, a datastore, a power unit, and one or more orbital cameras. The controller(s) may be operable to perform a mission instruction. The communication system may be in communication with the controller(s) and with a client terminal. The datastore may store data accessible by the controller(s). The orbital camera(s) may be operable to capture one or more image(s) associated with the mission instruction, which may be defined as captured image(s). The controller(s) may be operable to detect and identify one or more predetermined object(s) in the one or more captured image(s). The controller(s) may generate a mission analytics packet, and the controller(s) may be operable to transmit the mission analytics packet to the client terminal.

The embodiment of the invention discloses a power grid configuration operation cooperation method and device, electronic equipment and a storage medium. The method comprises the steps that an upper layer planning model with the purpose of minimizing the comprehensive planning cost of a power grid and with the installed capacity of a new energy unit and the installed capacity of an energy storage unit as optimization variables is constructed; a lower-layer operation simulation model with the aim of minimizing the comprehensive operation cost of the power grid and with the operation state of the thermal power generating unit, the operation state of the energy storage unit, the new energy abandoned power and the load shedding power as optimization variables is constructed; constructing a double-layer decision model based on the upper-layer planning model and the lower-layer operation simulation model, and enabling the output of the upper-layer planning model and the output of the lower-layer operation simulation model to be mutually influenced; and performing multi-round iterative optimization on the double-layer decision model based on a multi-time-sequence typical source load matching scene. The embodiment of the invention can improve the power supply reliability of the power grid on the premise of ensuring the safety of the power grid and the lowest comprehensive cost.

The invention discloses a thermal power generating unit operation state detection method and system, and relates to the technical field of operation state detection, and the method comprises the steps: S100, building a working condition variable label; s200, carrying out statistics on correlation coefficients of sensors and faults under various working conditions in historical operation data of the thermal power generating unit, dynamically updating weights, and storing the weights in a working condition database; s300, based on the energy transfer chain of the thermal power generating unit, establishing a parameter incidence matrix between devices; according to the method, the data weights of different sensors are adaptively adjusted according to the real-time operation state of the equipment, the defect that the traditional multi-sensor fusion adopts fixed weight or simple weighted average and is difficult to adapt to the working condition change is overcome, a physical relationship network between the equipment is constructed, key associated parameters are identified in an energy transfer form, and the fault identification accuracy is improved. The robustness of anomaly monitoring under complex working conditions is improved, and the false alarm rate is reduced.

The invention relates to the technical field of automatic control, and discloses a thermal power generating unit cooperative control method based on digital twinning, which comprises the following steps: firstly, off-line executing benchmark construction, and obtaining a benchmark digital twinning model and a benchmark cooperative control parameter set which represent the ideal state of a unit; a twinborn deviation vector is obtained by comparing real-time output of a physical unit with theoretical output of a model, a deviation characteristic vector of quantitative characteristic deviation is obtained through processing of a deconstruction algorithm, then historical deviation characteristics are analyzed by adopting a time sequence prediction model, a prediction output vector representing a future evolution trend is calculated, and then a prediction result is obtained. And calculating a prospective control parameter correction vector based on the prediction vector, and combining the prospective control parameter correction vector with a reference parameter set to generate a dynamic cooperative control parameter set. According to the method, the slow time-varying drift of the dynamic characteristics of the unit can be actively compensated, the continuous optimization of a control strategy is realized, and the stability and the operation economy of a control system are improved.

The invention provides a snakelike metal pipeline internal detection robot and an application method, and belongs to the technical field of pipeline detection and maintenance. The robot mainly comprises two tank probe vehicles of the same structure and a snakelike joint body connected between the two tank probe vehicles. The tank probe vehicle integrates a crawler-type walking mechanism, a detection unit, an operation unit, a magnetic adsorption unit, a control unit and a power unit, can provide main driving force, is adsorbed on the wall of a metal pipe and executes detection operation. The snakelike joint body is composed of a plurality of joint sections connected through movable joints, the unique conical helical tooth meshing design of the snakelike joint body enables the joint sections to generate multi-degree-of-freedom deflection, and therefore the whole robot can flexibly adapt to bending changes of vertical, horizontal and various bent pipes, and stable snakelike winding movement is achieved. The problems that an existing pipeline robot is poor in adaptability to complex pipelines and single in function are solved, and long-distance and all-directional detection and multifunctional operation under the complex pipeline environment are achieved.

An energy storage control system includes a plurality of energy storage modules and a plurality of control apparatuses in one-to-one correspondence with the plurality of energy storage modules, where each control apparatus is connected to the corresponding energy storage module, and the energy storage module includes a battery unit and a power unit, the battery unit including at least one battery group. The control apparatus includes a sub-module controller and at least one battery management system in one-to-one correspondence with the at least one battery group, where each battery management system is connected to the corresponding battery group and the sub-module controller, and the sub-module controller is connected to the power unit.

The invention discloses a unit operation state monitoring method based on multi-dimensional model prediction. Relates to the field of thermal power generating unit multi-dimensional model early warning. The key equipment of the unit is acquired, the monitoring parameters of the key equipment are acquired, the monitoring points corresponding to the monitoring parameters are set, and then the equipment operation network of the unit is acquired; setting a parameter association group and a training period of the equipment operation network, and obtaining parameter data corresponding to the parameter association group according to the training period; obtaining a correlation function of the parameter correlation group according to the parameter data, and further obtaining a multi-dimensional model of the unit; monitoring the running state of the unit based on a multi-dimensional model to obtain an abnormal running state; generating an abnormal early warning signal according to the abnormal operation state; the monitoring comprehensiveness of the operation state of the thermal power generating unit is effectively improved.

A fastener driving tool includes: an energy accumulation assembly, a striker, and a drive assembly which includes a power unit, a drive wheel, and a transmission construction, the power unit provided with an output shaft, the drive wheel fitted with the striker, the drive assembly provided with the transmission construction, the transmission construction having an engaged state and a disengaged state, the power shaft driving, via the transmission construction in the engaged state, the drive wheel to rotate forwardly so that the forwardly rotating drive wheel drives the striker and the piston to move upward to return in place; the transmission construction is in the disengaged state during a process of the piston driving the striker to move from a ready position to a striking position so that the drive wheel fitted with the striker may be driven by the downwardly moving striker to rotate reversely.

The invention relates to a fault detection method and device for an energy storage converter and computer equipment. The method comprises the following steps: determining resistance information and inductance information of the energy storage converter, converter three-phase voltage information output by the energy storage converter and power grid three-phase voltage information of a power grid accessed by the energy storage converter; detecting the output voltage of each power unit to obtain the voltage information of the power unit; according to the resistance information, the inductance information, the three-phase voltage information of the converter, the three-phase voltage information of the power grid and the voltage information of the power units, theoretical inductive current information output by each power unit is predicted; according to the difference between the theoretical inductive current information and the actual inductive current information of all the power units, fault detection is carried out on the multiple power units in the energy storage converter, and fault detection results are obtained. By adopting the method, the fault detection of the energy storage converter can be efficiently carried out.