6133 results about "Water temperature" patented technology

The invention discloses a vehicle idling start and stop control system and method. The control system judges whether a vehicle has idling start and stop conditions by monitoring the water temperatureof an engine, the capacity of a storage battery, a safety belt and other information, judges whether the vehicle has conditions of stopping the engine by monitoring the rotating speed of the engine, the speed of the vehicle, the brake air pressure and other conditions, and judges whether the vehicle has conditions of starting the engine by monitoring the gear of a gearbox, the speed of the vehicle, a hand brake and other information. When the relevant conditions are met, start and stop work signals are sent to the engine though a CAN bus. In order to guarantee the reliability of frequent startand stop of the engine, the system strengthens flywheel gear rings of a starter and the engine. In order to ensure that the battery does not lose power, a storage battery capacity sensor is added tothe system on the basis of increasing the capacity of the storage battery, and the idling start and stop are allowed when the state of charge (SOC) of the storage battery satisfies a safe starting threshold. The idling start and stop control system has advantages of low cost and high reliability, and is especially suitable for commercial vehicles.

The invention relates to the technical field of air conditioner chilled water control, in particular to an air conditioner chilled water control method and system based on deep learning, and the method comprises the following steps: collecting states of an air conditioner water chilling unit, including water pump frequency and valve opening feedback, and pipe network water supply temperature, return water temperature, flow and differential pressure operation readings; according to the method, the state parameters of the water chilling unit are dynamically collected, the system operation state feature set is constructed, real-time fusion and standardization processing of multi-source heterogeneous data are achieved, the problem of time sequence dislocation caused by sensor sampling frequency differences is solved, the heat load change key input quantity is recognized based on the feature set, and the system operation state feature set is established. And the performance attenuation trend of the water pump is accurately pre-judged in combination with prediction calculation, and extra energy consumption caused by lagging adjustment is reduced. A layered optimization framework with total energy consumption minimization as a target is introduced, water supply temperature, pressure difference setting and unit operation combination are decoupled into independent optimization sub-problems, and invalid work of a water pump is reduced on the premise that the tail end heat requirement is met.

The invention discloses an intelligent fishery comprehensive evaluation system based on multi-dimensional indexes, and belongs to the field of intelligent fishery. The intelligent fishery comprehensive evaluation system based on the multi-dimensional indexes comprises a water quality monitoring unit, a prediction and early warning unit, a breeding regulation and control unit, an ecological evaluation unit and a decision output unit. The method solves the problem of hysteresis of the detection result in the prior art, can advance the water quality change trend and the red tide occurrence probability in the future by monitoring the water temperature, the dissolved oxygen, the pH value and other key water quality parameters in real time and by means of the prediction model, provides a key basis for breeding decision making, and improves the breeding quality. Execution equipment is flexibly adjusted according to real-time data and early warning information to improve the breeding environment and improve breeding benefits, meanwhile, multi-source data is integrated to comprehensively evaluate the influence of breeding activities on the ecological environment, ecological balance maintenance is assisted, comprehensive evaluation results are integrated to generate ecological improvement suggestions, resource allocation is optimized, and the economic benefit is improved. And the intelligent and ecological level of fishery is integrally improved.

Disclosed is a reservoir ecological operation method integrating ecological flow process and water temperature process requirements of fish species, including: establishing a habitat model for a target fish species and deducing an ecological flow process of a lift history of the target fish species; calculating a critical spawning water temperature threshold and a critical gonadal development accumulated temperature threshold; establishing a multi-objective reservoir operation model to obtain flow process and water level after optimized reservoir operation; establishing a multi-objective reservoir ecological operation model integrating both the ecological flow process and the water temperature process, and calculating reservoir outflow water temperatures before and after the optimized reservoir operation; and calculating an improvement difference between the critical water temperature threshold and the accumulated temperature threshold of the target fish species on arrival dates after the reservoir ecological operation and those before the optimized reservoir operation.

The invention discloses an intelligent heat supply two-network balance control method and system based on fuzzy reinforcement learning, and the method comprises the steps: obtaining real-time operation parameters which comprise the return water temperature, the heat load and the environment temperature; based on the real-time operation parameters, preliminarily generating a preliminary adjusting quantity of the opening degree of the valve; operation data are analyzed in real time, fuzzy rule parameters are adjusted according to feedback of the reinforcement learning module, and the fuzzy rule parameters comprise priority weights and membership functions of return water temperature deviation; and according to the preliminary adjustment effect, a deep learning algorithm is utilized to construct a state-action space equation, an energy consumption design reward function is considered, the priority weight is further optimized and fed back to a dynamic optimization module of a fuzzy rule, and secondary adjustment of the valve opening degree is output to an execution mechanism. The problems that a traditional fuzzy control method cannot adapt to complex working condition changes in the operation of the heat supply two-network, the adjusting strategy lags behind, the adjusting effect is not accurate enough, and the adjusting efficiency and energy consumption are affected are solved.

The invention discloses a deep and large reservoir ecological scheduling method, system and equipment based on a data-driven model of a coupling physical mechanism, and belongs to the technical field of water resource management and environmental protection. Firstly, a physical water temperature model is constructed based on measured data, diversified water temperature change scenes are generated, and a deep learning model constrained by a physical mechanism is constructed. Secondly, carrying out sensitivity analysis to identify key influence factors for driving water temperature change, constructing a reservoir optimization scheduling model, coupling a deep learning model constrained by a physical mechanism, and deducing a scheduling rule set on the premise of meeting a water temperature target; and finally, carrying out multi-index optimization analysis. The invention further provides a deep and large reservoir ecological scheduling system and electronic equipment, and the deep and large reservoir ecological scheduling method is realized. According to the method, the power generation scheduling rule set of the deep and large reservoir can be scientifically deduced, the optimal scheduling scheme with both ecological benefits and economic benefits is screened out by introducing the multi-index optimization method, and overall balance of ecological requirements and power generation benefits is achieved.

The invention relates to the technical field of temperature control, in particular to a mass concrete water cooling water temperature control method and system. The method comprises the following steps: collecting concrete key parameters through a multi-source sensor, constructing a microenvironment model based on information geometry, and generating a thermosensitive characteristic spectrum; forming a distributed thermodynamic model by utilizing a mutual information routing algorithm and heat-fluid-solid coupling analysis, and calculating an optimal cooling strategy; water flow path and flow optimization is realized in combination with fractional order particle swarm optimization; a pump set and a valve are adjusted through fuzzy self-adaptive control; and a potential instability region is identified through the spectrum energy gradient, and risk early warning is triggered. The precision and reliability of mass concrete cooling temperature control are remarkably improved, and intelligent, efficient and safe temperature control adjustment in the whole process is achieved.

The invention provides a high-efficiency control method and system for a central air conditioner refrigeration machine room, and relates to the technical field of automatic control, and the method comprises the steps: 1, obtaining chilled water supply and return water temperature difference and flow data, and calculating the dynamic cold load demand of a building in combination with the personnel distribution thermal imaging data of each floor; and 2, on the basis of the dynamic cooling load requirement, a dynamic adjustment model for the number of running water chilling units is built, matching degree calculation is conducted on the actual cooling load value and the single refrigerating capacity of the water chilling units through a fuzzy PID control algorithm, and a final unit running combination scheme is generated. By calculating the cooling load requirement, dynamically adjusting the operation parameters of the water chilling unit, the chilled water pump and the cooling tower and balancing the equipment operation time, the system energy efficiency is effectively improved, the energy consumption and the operation and maintenance cost are reduced, and stable operation of the refrigerating system is guaranteed.

The invention relates to the technical field of sewage treatment, in particular to an aerobic aeration treatment system for plateau domestic sewage treatment, which comprises a pretreatment unit, a biological treatment unit, an advanced treatment unit and a recycling unit which are connected in sequence, the system further comprises a data acquisition module, an aerobic aeration intelligent regulation and control module, a biochemical environment constant-temperature maintenance module, a carbon-nitrogen proportion and backflow dynamic regulation and control module, a digital twinning and sludge characteristic simulation module and an energy collaborative scheduling module. Compared with the prior art which adopts a standard aeration strategy and cannot adapt to the special environment of low air pressure and low oxygen partial pressure of the plateau, the system can accurately adapt to the plateau environment by integrating real-time atmospheric pressure and water temperature monitoring, dynamically calculating the oxygen saturation solubility and correcting the aeration control target according to the oxygen saturation solubility, so that the aeration control target is optimized. Stable supply of dissolved oxygen required by biochemical reaction is ensured, and the technical bottleneck of low efficiency of traditional sewage treatment in plateau regions is fundamentally overcome.

The invention relates to a water plant intelligent chemical adding amount prediction method based on data preprocessing, and belongs to the technical field of deep learning and intelligent chemical adding. Calculating a theoretical dosage based on historical flow, pH, water temperature and turbidity; dividing a plurality of clusters and splicing to query historical dosage data; weighting and fusing the theoretical dosing amount and the inquired historical dosing amount as a pre-treatment dosing amount; learning the relationship among the flow, the pH, the water temperature, the turbidity and the pretreatment dosage to perform forward feedback optimization; building an alumen ustum image recognition model, classifying alumen ustum, and associating the alumen ustum with corresponding dosage to form a dosage feedback algorithm model; building a dosage feedback model based on the sedimentation tank outlet water quality monitoring data; and correcting the weight in the preprocessed dosage based on the adjusted data of alumen ustum identification and water quality feedback on the dosage. The method can effectively reduce the influence of the dosage data error on the effectiveness of the model, can reduce the complexity of the algorithm model, and improves the robustness of the model.

The invention discloses a water-cooling energy consumption adaptive regulation and control method suitable for a data center, and the method comprises the following steps: obtaining a multi-dimensional operation parameter set of the data center in real time, and generating a real-time thermal load density distribution diagram reflecting the heat distribution condition in a machine room; calculating the overall thermal deviation degree and the local hot spot intensity, and solving through a dynamic energy efficiency optimization function to obtain a target system supply and return water temperature difference and a target cooling liquid flow; inputting into a hydraulic and thermodynamic simulation model, and generating an optimal multi-device coordinated regulation instruction set; and executing the multi-device coordinated regulation instruction set, and then performing parameter calibration on the hydraulic and thermodynamic simulation model. The method has the following advantages and effects that the thermal environment of the machine room can be sensed in real time, the energy consumption and heat dissipation requirements can be intelligently balanced, and multiple devices in the cooling system can be cooperatively regulated and controlled, so that the overall energy consumption of the cooling system is optimized while the local overheating risk of the machine room is thoroughly eliminated.

The invention relates to the technical field of non-electrical variable control, and discloses an industrial water chiller temperature intelligent adjusting system, which comprises a refrigeration circulation loop and a control unit, the control unit calculates a steady state control component based on the water outlet temperature deviation, performs differential processing on the refrigerant pressure to extract the gradient, and outputs the gradient. Generating a transient compensation component when the gradient exceeds a dynamic noise threshold; according to the method, the problem of thermal lag is solved by utilizing the pressure wave transmission speed advantage, aggressive response is prevented from triggering low-pressure shutdown through a safety margin constraint mechanism, the pressure safety margin is calculated in real time, a gain coefficient is determined according to a nonlinear model, and a final driving instruction is generated. And the dynamic balance of the control response speed and the system physical security boundary is realized.

The invention relates to the field of factory intelligent cooling, and discloses an MPC-based large factory intelligent cooling system and a cooling control method, the system comprises a data acquisition module, an AI control module, a cooling tower control module, a cooling water pump control module and a cooling-water machine control module; the data acquisition module acquires outdoor environment temperature and humidity, cooling tower outlet water temperature, cooling water pump inlet and outlet water temperature difference and flow and water chiller operation state data in real time. The AI control module constructs a system model through real-time data, predicts and optimizes by using an MPC algorithm, and calculates optimal values of the running frequency of a cooling tower fan, the running frequency of a cooling water pump and the power of a cooling-water machine compressor by adopting sequential quadratic programming, so as to realize cooperative dynamic control of equipment in the system; the overall operation efficiency of the cooling system under the outdoor temperature and humidity change condition is effectively improved, and the overall energy consumption of the system is minimized in real time.

The invention discloses a fishery pond water temperature control optimization method based on a swarm intelligence algorithm, and belongs to the technical field of control optimization, and the method comprises the following steps: S1, constructing a fishery pond water temperature PID control system introducing an improved single-corner whale optimization algorithm module; s2, introducing an improved single-corner whale optimization algorithm, and constructing an improved single-corner whale optimization algorithm module; s3, setting and optimizing the pond water temperature PID control parameters by using an improved single-corner whale optimization algorithm to obtain optimal control parameters; and S4, setting an optimal control parameter obtained through optimization by using the improved single-corner whale optimization algorithm as a parameter of a pool water temperature PID controller, and optimizing a pool water temperature regulation control effect. According to the method, a swarm intelligent optimization algorithm, namely an improved unicorn whale optimization algorithm, is introduced, high-performance control over the pond water temperature is achieved, and reliable control technical support is provided for efficient, stable and safe operation of aquaculture.

The invention discloses an intelligent water quality monitoring and evaluating system based on image recognition, which relates to the technical field of environment monitoring, and comprises a fusion module for controlling a polarizer array to rotate based on an environment parameter set, capturing water surface optical images in different polarization directions, and performing image reconstruction through a polarization characteristic tensor decomposition method, generating a high-definition water surface image after reflection suppression; the three-dimensional diagram generation module is used for acquiring a morphology stripe image of the water surface through a DLP projection method, and generating a three-dimensional depth diagram in combination with the high-definition water surface image; the pollution identification module is used for correcting the three-dimensional depth map based on the real-time water temperature data, identifying spatial distribution of pollutants through a dynamic structure element opening and closing algorithm and generating a three-dimensional pollution distribution map; according to the method, mirror reflection noise is suppressed through multi-angle polarization image fusion, and the distinguishability of pollutant characteristics is remarkably enhanced while the image resolution is kept.

The invention relates to the technical field of intelligent control, in particular to an inspection system and method for a heating and ventilation system based on a knowledge graph, and the system comprises a feature extraction module, a graph construction module, an anomaly tracing module, a causal analysis module and a priority module. According to the method, the inlet and outlet water temperature and flow data of the water chilling unit are collected, deviation characteristics are extracted in combination with principal component analysis, the operation state is quantified, an embedded map participates in state judgment, the anomaly detection capacity is improved, initial anomaly and upstream nodes are focused, the analysis range is narrowed, and causal tracing is carried out based on the state influence between devices; by means of a Bayesian network, a state evolution chain is constructed, a time sequence and an inter-structure fault are bridged, task priority is evaluated according to a link starting point and length, equipment dynamic sorting and state updating are carried out, inspection scheduling accuracy and efficiency are improved, and a closed-loop process which is high in recognition accuracy, small in analysis boundary, clear in path and excellent in resource allocation is formed.

The invention provides a bioreactor aeration self-adaptive control method and system based on machine learning, and the method comprises the steps: collecting the water inlet flow, ammonia nitrogen concentration, dissolved oxygen concentration, water temperature and chemical oxygen demand data of a bioreactor in real time through a sensor, and carrying out the water balance verification and the Kalman filtering pretreatment containing a water temperature compensation item; generating an aeration instruction by adopting multi-model collaboration; outputting a reference aeration rate by a deep reinforcement learning DRL model; the self-adaptive PID controller dynamically adjusts the proportionality coefficient according to the dissolved oxygen deviation and calculates the correction amount; and the LSTM network generates a fusion weight, and combines the seasonal compensation factor and the safety coefficient to synthesize the final aeration rate. The system passes mutation rate constraint and nitrification efficiency verification, an ASM1 model is triggered to recheck when the deviation exceeds the standard, and after passing, an air blower with the precision of + / -2% executes an instruction and performs closed-loop feedback in a period smaller than or equal to 10 seconds. After the method is implemented, the aeration energy consumption is reduced to 0.38 kWh / m, the effluent ammonia nitrogen standard reaching rate is improved to 98.5%, the dissolved oxygen fluctuation range is reduced to + / -0.3 mg / L, and the impact load response time is shortened to be within 15 minutes.

The invention relates to the technical field of temperature control, in particular to a heating and ventilation heating power constant-temperature variable-flow control method, and provides the following scheme that circulating pump frequency instructions and water temperature response data of multiple historical regulation and control periods are collected, and a dynamic track of the current water temperature in a temperature inertia field is constructed; calculating an attraction potential energy state between the current water temperature and a target constant temperature value in combination with the disturbance residual matrix; and outputting the frequency bandwidth interval of the circulating pump based on the state to realize dynamic adjustment. An adjacency matrix and a Laplacian matrix are constructed by introducing a hydraulic communication relation, spatial convolution and weighted updating are performed on disturbance residues in combination with a topological diffusion core, and accurate propagation and suppression of disturbance are realized. The method can effectively solve the problems of nonlinear response, delay effect and disturbance coupling of the water temperature to the pump frequency, and the temperature stability and the energy utilization efficiency of a heating system are improved.

The invention relates to the technical field of boiler control, and discloses a gas-fired boiler starting control method and system. The method comprises the following steps: acquiring initial operation parameters such as hearth pressure, water inlet temperature, flue gas oxygen content and fuel valve opening of the gas-fired boiler, establishing a thermodynamic state model in a starting stage according to the initial operation parameters, and dividing dynamic response thresholds of different load intervals; and calculating a theoretical fuel supply rate of the combustor based on the model, generating and dynamically updating a fuel supply correction coefficient in combination with a threshold value, synchronously marking key nodes according to abnormal distribution of hearth temperature, and adjusting a spatial air distribution strategy of the combustor. And after the correction coefficient is subjected to multi-stage buffer smoothing, a fuel control instruction is output to an executing mechanism. And switching to steady state control after the boiler reaches the preset load. The method adapts to the characteristics of a power plant unit, so that the starting process is more stable, the damage to a heated surface and pollutant emission are reduced, and rapid grid connection is assisted.

Provided is a temperature therapy chamber comprising a housing with an interior for accommodating a user. The interior of the chamber has a heating system configured to increase the temperature within the housing to create a heated area. The housing also has a plunge pool system having a pool with an opening accessible from within the interior and configured to hold water and accommodate the user. A chiller is configured to decrease the temperature of the water in the pool. The user can move between the heated area and the pool without leaving the interior of the housing. The housing can also include a vertical rail system with a mounting plate slidably coupled to at least one rail on a wall of the housing and configured to removably support the heating element. The user can move the heating system between a top and bottom position of the vertical rail system.

The invention discloses a water pollution monitoring method and device based on an intelligent sensor, and the method comprises the steps: collecting the real-time water temperature, pollutant concentration and environmental parameter data of a water body through a sensor network, and storing the data into a distributed database to form a multi-dimensional time series data set; a feature extraction and dimension reduction module is used for obtaining key feature vectors, a potential pollution event marking module is used for screening out a preliminary event candidate set, and an event detection model is trained by means of a random forest algorithm. And when the model judges that a pollution event occurs and the confidence reaches the standard, generating an early warning signal. The water temperature abnormal trend is predicted through a long and short term memory network, Kalman filtering smoothing processing is carried out, finally, a pollution event early warning report is generated according to abnormal points in a stable water temperature change trend sequence, and efficient and accurate monitoring and early warning of water pollution are achieved.

The invention belongs to the technical field of water supply network adjustment, and particularly relates to a water supply network pressure and flow adjusting method. The method comprises the following steps: firstly, collecting pressure, flow and water temperature data of a monitoring node at present and in a preset time period, wherein the preset time period is set according to a water consumption period; preprocessing flow data through a sliding window method and fitting a curve, and marking an instantaneous disturbance time period; the dynamic response coefficient of each disturbance time period is calculated, and water temperature correction is needed; combining the flow standard score, the dynamic response coefficient and the real-time deviation coefficient to obtain a flow dynamic regulation index; a pressure stability index is obtained through pressure and water temperature trend feature vector matching; the two are subjected to weighted fusion to form a pipe network comprehensive regulation factor, and the valve opening and the water pump power are regulated accordingly. The method can accurately identify instantaneous disturbance, improve the adjustment precision and response speed, and guarantee stable water supply.

The invention discloses a cold storage temperature optimization control system and method for a chilled water storage air conditioning system, and relates to the technical field of chilled water storage air conditioning management.The method comprises the steps that 1, a plurality of operation parameters in the system operation process are collected; performing time synchronization and abnormal value elimination on the operation parameters to form a dynamic operation data set; and 2, judging the current hydraulic circulation state based on the dynamic operation data set, and outputting a circulation deviation signal when any index of the total flow of the system, the flow distribution of each branch or the temperature difference change rate of the supplied water and the returned water exceeds a set corresponding threshold value. By constructing the dynamic operation data set and monitoring key parameters such as the system temperature, the flow and the water pump operation state in real time, a unified multi-dimensional data basis is established, support is provided for follow-up operation state recognition and control strategy execution, and the real-time performance and accuracy of control are remarkably improved.

The invention discloses a self-adaptive metering method of an ultrasonic water meter, which relates to the field of water meter metering, and comprises the following steps: acquiring real-time water temperature data and real-time flow velocity data of a measured fluid, compensating the sound velocity of ultrasonic waves based on the real-time water temperature data to obtain a first compensated sound velocity, based on the first compensation sound velocity, an excitation voltage self-adaptive adjustment strategy with ultrasonic wave head-wave ratio regulation and control and a measurement frequency dynamic regulation and control strategy are executed, secondary compensation is conducted through a built error curved surface compensation model with the water temperature and the flow velocity as indexes, and the initial flow value is corrected through an error compensation value; by means of multi-parameter collaborative real-time optimization, high-precision measurement and low-power-consumption operation under all working conditions are achieved, the measurement precision in the full-scale and full-temperature range is remarkably improved, and by intelligently adjusting the measurement frequency, cooperating with the flow rate change rate and error model feedback and dynamically balancing the dynamic response speed and static power consumption, the measurement precision is improved. And finally, double optimization of precision and energy efficiency is achieved.

The invention belongs to the technical field of wastewater treatment, and provides a wastewater treatment equipment remote control system based on the Internet of Things, which aims at solving the problems that the traditional fixed DO concentration control cannot adapt to water inlet load fluctuation, the effluent is easy to be substandard or the aeration energy consumption is high, the monitoring data noise is large, and the time sequence is misplaced. According to the scheme, a multi-dimensional real-time sensing network is constructed, flow, COD, BOD, ammonia nitrogen, water temperature, distributed DO and sludge activity sensors are deployed, discrete wavelet transform is adopted for noise reduction, and a data time sequence is aligned; a three-layer load-DO-energy consumption dynamic correlation model is designed, a basic layer predicts a load trend through LSTM, a middle layer quantifies a DO demand through a microbial metabolism model, and an optimization layer outputs an optimal DO set value through a PPO algorithm; and developing a dynamic decision-making system, adaptively generating a DO interval according to a load state, and adjusting fan parameters and number in a linkage manner. According to the invention, load dynamic adaptation is realized, effluent ammonia nitrogen is guaranteed to reach the standard, aeration energy consumption is reduced, and remote control precision and equipment operation efficiency are improved.

The invention provides an arrangement method of a steel fishway structure capable of automatically pulling and stretching along with water level changes. The arrangement method comprises the steps that the water level difference of an inlet and an outlet of a fishway is monitored in real time; the buoyancy driving assembly is triggered according to the water level difference to drive the steel fishway subsections to move along the rails; calculating the telescopic length based on the water level difference and the fishway base length to ensure that the gradient is within the design range; the track motor is controlled to adjust the cable-stayed angles and gaps of the fishway sections; the gradient error is corrected in real time through the tilt angle sensor; the distribution density and the opening-closing angle of the guide plates are dynamically adjusted according to the flow speed and the water depth, and vortex is inhibited; the water temperature change is monitored, the thermal deformation compensation amount is calculated, and deformation is absorbed through the elastic sealing assembly. The fish passing rate can be increased, the adaptability and stability of the structure are enhanced, and the device is suitable for complex hydrological environments.

The invention relates to the technical field of refrigeration, in particular to an anti-icing refrigeration method and system.The anti-icing refrigeration method comprises the steps that water temperature data in a water tank are collected in real time, and temperature dynamic parameters reflecting the temperature change trend and stability are calculated; dynamically adjusting the opening degree of the electronic expansion valve based on the temperature dynamic parameter; when the temperature dynamic parameter meets a preset icing triggering condition, deicing circulation is executed; a compressor and an electronic expansion valve are closed, and a circulating pump is started; monitoring the temperature dynamic parameter in real time in the deicing cycle, dynamically adjusting the duration of the deicing cycle based on the temperature dynamic parameter, judging whether a preset deicing completion condition is met or not based on the temperature dynamic parameter, if not, continuing the deicing cycle, and if yes, terminating the deicing cycle. And the compressor and the electronic expansion valve are restarted to recover the refrigeration cycle. The technical problems that in the prior art, due to freezing, energy consumption of a refrigerating system is too high, and the automation degree is insufficient are solved.

The invention relates to the technical field of flood discharge gate equipment, in particular to a flood discharge gate equipment operation fault diagnosis method, which comprises the steps of extracting and fusing first target data; analyzing and calculating the extracted and fused first target data, and generating second target data; and inputting the second target data into a historical database for calculation, and verifying the operation state of the gate equipment. The method has the beneficial effects that a multi-source heterogeneous data fusion technology is utilized, various internal parameters such as structural stress, deformation and vibration characteristics as well as hydraulic hoist system pressure, radial gate online vibration monitoring signals and water temperature signals are comprehensively considered, so that the actual operation state of equipment is more comprehensively reflected, the fault diagnosis accuracy is remarkably improved, and the fault diagnosis efficiency is improved. Key parameters during flood discharge of the arc-shaped service gate are monitored in real time, the state change of equipment is quickly responded, and the real-time performance of fault detection is enhanced.

The invention relates to the technical field of aquaculture equipment, and discloses a rainbow trout fry rearing special constant-temperature hatching device which comprises a heat preservation box, a constant-temperature mechanism, a tray mechanism, a top cover assembly and a control panel. The constant-temperature mechanism comprises an S-shaped heat conduction water pipe, a bidirectional water pump, an upper-end heating module and a lower-end refrigerating module, the heat conduction water pipe preheats or precools buffer water flow, the bidirectional water pump rotates forwards and backwards to control the water flow to flow up and down, and natural convection of water in the box is promoted by combining'heat flow rising and cold flow falling ', so that water temperature fluctuation is greatly reduced, and compared with an existing device, the temperature difference is remarkably reduced; the rainbow trout embryo development stable temperature environment is ensured. The folding push handle is turned over to the upper end, the linkage splash-proof grid automatically blocks the top cover vent hole, and water is prevented from being splashed when the device moves; a temperature and dissolved oxygen amount sensor is arranged on the side wall of the heat preservation box, a bubble generator at the bottom accurately adjusts dissolved oxygen, air holes are opened for ventilation when the splash-proof grids are fixed, and it is ensured that the internal environment is moderate.

The invention discloses an intelligent feeding method, device and equipment, a medium and a product, and relates to the field of aquaculture, the method comprises the following steps: collecting water quality information of an aquaculture water area and a fish depth image; the water quality information comprises water temperature, dissolved oxygen, pH value and flow velocity; based on the fish depth image, utilizing a computer vision model to estimate the number of fish schools and the weight of a single fish, and determining the total amount of fish biomass; the fish biomass amount and the water quality information are fused, and the primary bait feeding amount is determined; according to the residual bait image after primary feeding, whether secondary feeding is needed or not is judged, the secondary bait feeding amount is determined according to the fish feeding behavior image and the fish feeding audio in the primary feeding process, and real-time, automatic and accurate feeding can be achieved.