24 results about "Specific energy consumption" patented technology

The invention relates to the technical field of cable production and manufacturing and automation control, in particular to an energy-saving cable extrusion production process control system, which comprises a data acquisition module for acquiring real-time working condition parameters of an extrusion production line; the rheological thermal coupling analysis module is used for resolving the shear heat contribution rate under the current working condition; the heat engine response decoupling module is used for determining a heat engine response lag time difference between mechanical shear heat and machine barrel heat conduction; the energy efficiency optimization calculation module is configured to generate a dynamic heat balance control strategy aiming at an unsteady state working condition according to the heat engine response lag time difference and a preset unit output ratio energy consumption target; the self-adaptive execution module is configured to output a cooperative control instruction for a heating and cooling system and a screw driving system based on the dynamic heat balance control strategy so as to realize minimization of system energy consumption; according to the method, the common energy confrontation phenomenon of alternate operation of heating and cooling in traditional control is solved, and the energy consumption in the transition process is greatly reduced.

The application discloses a driving behavior influence on energy consumption evaluation method, system, vehicle and equipment. Wherein, the driving behavior influence on energy consumption evaluation method comprises: obtaining driving data of a vehicle; obtaining driving behavior characteristic data according to the driving data; taking unit energy consumption of the vehicle as a target variable and taking the driving behavior characteristic data as an input variable, a regression analysis model between the driving behavior and the unit energy consumption is constructed, wherein the regression analysis model represents the influence relationship of different driving behaviors on the energy consumption of the vehicle; according to the parameters of the regression analysis model, the energy consumption influence weight corresponding to each type of driving behavior characteristic data is calculated, and the influence of the driving behavior on the energy consumption is evaluated according to the energy consumption influence weight. By analyzing the influence of the driving behavior on the energy consumption of the vehicle, the driving habit, the loading configuration and the driving route can be optimized, and the energy consumption and the carbon emission can be significantly reduced.

The invention relates to a cutting rock-breaking mechanism and a cutting method, and the cutting rock-breaking mechanism comprises a cutter assembly which comprises a sun gear rotating around a first axis; the planet gears are arranged at intervals in the circumferential direction, and eccentric structures are arranged on the planet gears; the planet wheel mandrel is sleeved with the planet wheel and rotationally connected with the planet wheel so as to bear inertia moment and / or radial inertia force which alternately rotates around the first axis; the planet carrier is coaxial with the first axis and is fixedly connected with the planet wheel mandrel; the cutterhead frame is connected with the planet carrier; when the planet carrier alternately rotates around the first axis, the cutter head frame reciprocates along the first axis and / or alternately rotates around the first axis; when the planet carrier swings in the radial direction, the cutterhead frame swings in the radial direction in a rotating mode. And the cutter is fixedly connected with the cutter head frame and has an eccentric distance. Rock is cut and broken under the multiple actions of extrusion feeding force of the cutter, vibration impact of the cutter and radial eccentric impact rock breaking, so that the rock breaking capacity (productivity) and the rock breaking efficiency are improved, the specific energy consumption of rock breaking is reduced, and the cutter is suitable for breaking hard rock.

The utility model relates to the technical field of nitryl mother liquor recovery and energy conservation, in particular to a high-concentration nitryl mother liquor recovery and energy conservation device. Comprising a supporting cylinder, a supporting beam is arranged on the top face of a supporting cylinder body, a motor is arranged on the supporting beam, an output shaft of a motor body is connected with a shaft rod, the shaft rod is located in an inner cavity of the reaction kettle, and the inner cavity of the supporting cylinder body is sleeved with a reaction kettle body; a scraping plate is fixedly arranged on the shaft rod body, a plurality of teeth are arranged on the outer side surface of the scraping plate body, and the teeth are used for scraping mixed scale on the inner wall of the reaction kettle; the cleaning efficiency of the teeth on inner wall polymer scaling is improved, the temperature difference stability is improved, the recycling value of the teeth as a low-grade heat source is increased, the evaporation time is shortened, unit energy consumption is reduced, and the energy utilization rate and economic benefits of multi-effect evaporation are improved.

The utility model discloses a kind of unit energy consumption uses online monitoring device, including monitoring box, the lower end in monitoring box is equipped with monitoring equipment protection shell, the monitoring equipment protection shell is boat type structure, recess is equipped between the monitoring equipment protection shell and monitoring box, the upper end of monitoring equipment protection shell extends device recess, fixed mechanism is equipped in the recess, the lower end of monitoring box is equipped with article slot, servo motor is fixedly connected in the article slot, the output shaft end of servo motor is fixedly connected with rotating rod, the end of rotating rod away from servo motor is rotatably connected with article slot inner side wall. The unit energy consumption uses online monitoring device when online monitoring can be adjusted in multiple angles multidirection, realizes unit energy consumption comprehensive monitoring, improves the accuracy of unit energy consumption monitoring result.

The invention relates to the technical field of intelligent control of grease processing equipment, in particular to a temperature self-adaptive control method of rapeseed oil squeezing equipment. Comprising the following steps: a data acquisition step: calculating a first-order derivative of real-time temperature with respect to time to obtain a temperature change rate; an observer construction step: constructing a dynamic friction heat flow observation model, and calculating the rheological impedance coefficient of the material at the current moment; a space mapping step: mapping the rheological impedance coefficient to a preset two-dimensional energy efficiency phase plane, and calculating a normal deviation between the current working condition point and a preset optimal energy efficiency manifold trajectory; a closed-loop control step: driving the current working condition point to evolve along the optimal energy efficiency manifold trajectory based on the normal deviation; according to the method, the limitation that traditional control only depends on single temperature feedback is broken through, blind work of a motor in a low-efficiency interval is avoided by constructing an extrusion efficiency-heat dissipation rate two-dimensional energy efficiency phase plane, and the physical extrusion effect is maximized while unit energy consumption is reduced.

The invention relates to a wheel-rail traction large web plate whole machine flying load separation electricity and water cooling cogeneration flying path system, in particular to a train rail path system provided with a groove splicing whole path wheel-rail traction large web plate air lubrication and magnetic suspension roller shaft, which comprises a large web plate dragged by a wheel rail on an air bearing suspension roller shaft road surface, and the web plate is connected into an odd-length train in a hanging mode. The flight path is provided with four to a plurality of layers on the viaduct, the upper path and the lower path are oppositely opened in a one-way reciprocation manner, and the total energy-saving unit energy consumption ratio is less than 0.6; the flight path system is safe, green, service, order, fairness, sharing, rapidness, high efficiency, energy saving and the like, and is provided with electric power self-sufficient, green hydrogen, green alcohol and green ammonia new energy co-production and canal canal huge wheel river-through and sea-through output full-ecological enclave-sharing flight path system.

The invention relates to the technical field of equipment energy-saving management, and discloses a multi-machine linkage equipment integrated energy-saving management and intelligent decision-making method and system, and the method comprises the steps: 1, obtaining equipment operation parameters, calculating unit energy consumption, determining an operable load interval, and splitting a task into standard task units; step 2, determining group-level residual available energy consumption and establishing output and energy consumption constraints; step 3, according to the unit energy consumption and in combination with the equipment energy consumption coefficient, performing iteration to obtain a final throughput target of each equipment; step 4, calculating marginal energy consumption cost and allocating standard task units to obtain a final task allocation amount; 5, generating a strategy parameter set based on the final task distribution amount and the throughput target, monitoring an out-of-limit state, updating the strategy when the out-of-limit state is reached, and giving an alarm; and step 6, generating energy consumption settlement and management output based on the actual energy consumption and the energy consumption budget. According to the invention, intelligent management of controllable energy consumption budget, accounting of resource allocation and evaluation of energy-saving performance in a multi-machine cooperation scene is realized.

This invention relates to the field of artificial intelligence technology, specifically providing a method, system, device, and medium for energy consumption grading monitoring that combines flow direction prediction. The method includes: collecting and standardizing multi-source data from an energy system to form a standardized dataset containing flow direction data and grade data. Next, basic features and correlation features between flow direction and grade are mined from the dataset to form a feature set. This feature set is then input into a trained dual-objective prediction model, simultaneously outputting predicted energy flow rates and energy consumption grade predictions for future periods. Finally, based on the prediction results, when the probability of a target area reaching a specific energy consumption grade in the future exceeds a preset threshold, the monitoring strategy is automatically and dynamically adjusted. This invention achieves intelligent linkage between prediction and monitoring, effectively improving the timeliness of early warning and the accuracy of response.

A method of predicting energy consumption, performed by a computing device, includes: obtaining historical manufacturing data, wherein each piece of historical manufacturing data includes total energy consumption and historical performance values corresponding to manufacturing conditions, respectively, each of manufacturing conditions includes at least one of an equipment type and a product type, and each of historical performance value indicates at least one of an equipment operation duration and a product quantity; training and generating unit energy consumption prediction model using the historical manufacturing data; obtaining at least one piece of unit energy consumption of at least one manufacturing conditions using default performance values corresponding to manufacturing conditions and unit energy consumption prediction model; and outputting at least one piece of unit energy consumption. The present disclosure further provides a system of predicting energy consumption and recommending method of installing energy consumption measuring device.

The invention discloses a fully mechanized coal mining face coal rock identification method and device, and the method comprises the steps: extracting the current coal cutting number based on the coal cutting rule of a coal cutter; according to roller cutting information collected in real time, the cutting specific energy consumption of the roller passing through each support under the current coal cutter number is calculated, and a cutting specific energy consumption sequence of the current coal cutter number is formed; and obtaining a coal rock identification result according to a comparison result between the cutting specific energy consumption of the roller passing through each bracket in the cutting specific energy consumption sequence and preset coal cutting specific energy consumption. According to the embodiment of the invention, videos do not need to be collected, and the phenomenon of poor coal rock recognition effect caused by incapability of guaranteeing video clearness due to the reasons of relatively large coal dust on the working face, mist spray and the like can be avoided.

The invention discloses a performance test and evaluation method for a wet dust collector, which comprises the following steps of: selecting dust collection efficiency eta, specific energy consumption phi and dust wettability xi as evaluation parameters, and defining comprehensive quality factors of the wet dust collector; the comprehensive quality factor of the wet dust collector is calculated by comprehensively considering the mutual relation among the dust collection efficiency eta, the specific energy consumption phi and the dust wettability xi and is used for evaluating the comprehensive performance of the wet dust collector; then different wet dust collectors are selected for performance testing under the same environment condition and the same wet dust collector is selected for performance testing under different environment conditions, so that not only can the performance sequence of the different wet dust collectors under the same condition be obtained, but also the performance sequence of the same wet dust collector under the different environment conditions can be obtained; and the corresponding wet dust collector can be conveniently selected under the subsequent specific environment condition, and the wet dust collector can be specifically optimized according to the evaluation result.

The invention relates to the technical field of reinforcement learning, and particularly discloses a refrigeration dryer energy-saving control method and system based on reinforcement learning, and the method comprises the following steps: S1, obtaining the temperature and volume of to-be-treated air, pressurizing the to-be-treated air, and constructing an equation corresponding to the change of the pressure intensity of the to-be-treated air along with the volume; s2, the temperature and volume of to-be-treated air in the pressurization process are obtained, compression power consumption is calculated based on the volume sum equation, and the temperature difference and cooling power consumption are calculated; s3, a coordinate system is established with the moment in the pressurization process as the x axis and the total energy consumption as the y axis, a plurality of energy efficiency points are constructed, a fitting curve is generated, a fitting equation is obtained, and the target moment is marked; and S4, pressurizing to a target moment at rated power, obtaining the volume and temperature at the moment, measuring a standard dew point temperature and cooling. Adjustment is carried out according to the target volume and the target pressure intensity, the unit energy consumption ratio is increased, and energy efficiency loss and equipment abrasion are reduced.

The invention discloses an AI-optimized charging pile charging curve dynamic adjustment energy efficiency improvement system, and relates to the fields of artificial intelligence, intelligent charging, energy management and new energy automobiles. Aiming at the problems that a fixed charging curve of a traditional charging pile is difficult to adapt to dynamic factors, the energy efficiency is low and the service life of a battery is influenced, the system collects multi-source data such as a vehicle battery state, environmental parameters and power grid loads in real time, dynamically optimizes the charging curve through an AI algorithm, accurately adjusts output parameters of the charging pile, and is matched with energy efficiency analysis feedback and user interaction functions. Experiments show that the average charging energy efficiency is improved by 12%, the unit energy consumption is reduced by 11%, the charging time is shortened by 8%, and the health degree of the battery is improved. The system has been popularized and applied in charging operation enterprises, smart parks and the like, the charging efficiency is improved, the battery life is prolonged, and the user experience is optimized.

The present application relates to cable production and automation control technical field, concretely is a kind of control system of energy-saving cable extrusion production process, comprising: data acquisition module, obtains the real-time working condition parameter of extrusion production line;Rheological thermal coupling analysis module, solve the shear heat contribution rate under current working condition;Thermal-mechanical response decoupling module, determine the thermal-mechanical response lag time difference between mechanical shear heat and cylinder heat conduction;Energy efficiency optimization calculation module, configured to generate dynamic thermal balance control strategy for non-steady state condition according to the thermal-mechanical response lag time difference and the preset unit output specific energy consumption target;Adaptive execution module, configured to output the coordinated control instruction of heating and cooling system and screw drive system based on the dynamic thermal balance control strategy, to realize the minimization of system energy consumption;The present application solves the energy confrontation phenomenon of common heating and cooling alternate operation in traditional control, greatly reduces the energy consumption of transition process.

The application discloses a building big data-based intelligent building energy-saving scheme automatic generation system and relates to the technical field of building big data; two reasoning models are constructed, a first reasoning model is constructed based on environmental data, and a second reasoning model is constructed based on personnel distribution and time data; the first and second reasoning models are complementary in performance consumption prediction; different reasoning models are selected and enabled comprehensively, the system can dynamically adjust energy efficiency prediction according to actual data quality and integrity, and the accuracy of prediction is improved; through comparison with historical data, abnormal energy consumption can be found and corrected in time, and specific energy consumption control signals are generated according to an energy-saving scheme adjustment matrix. A control execution module further controls various energy-using equipment, such as air conditioners, lighting and ventilation equipment, according to the signals, energy use of the building is optimized, and intelligent energy-saving management is realized.

The invention relates to the technical field of secondary aluminum processing equipment, and discloses an ash frying machine with a high-strength slag frying pan, and the ash frying machine comprises the high-strength slag frying pan, a gas collection sealing plate, a smoke pipe, a stirring module and a stirring speed self-adaptive regulation and control system. The stirring speed self-adaptive regulation and control system is used for regulating the stirring speed of the stirring main shaft in real time based on the instantaneous power and the torque change rate of the stirring main shaft, the temperature gradient, the standard deviation and the temperature rise rate in the pot, the flue gas oxygen and dust concentration, the accumulated specific energy consumption, the molten aluminum outflow rate and the flue gas carbon monoxide concentration; respectively calculating to obtain a force-resistance interaction coefficient, a thermal dynamic coefficient, a comprehensive working condition quality factor and a progress coefficient, and calculating a target stirring speed according to the parameters for adjustment. According to the invention, intelligent self-adaptive adjustment of the stirring speed is realized, and the treatment efficiency and the operation stability are obviously improved.

The application discloses a kind of performance test and evaluation method of wet dust collector, selects dust removal efficiency η, specific energy consumption φ And dust wettability ξ As evaluation parameter, define wet dust collector comprehensive quality factor, and comprehensively consider the interrelation between dust removal efficiency η, specific energy consumption φ And dust wettability ξ Calculation obtains wet dust collector comprehensive quality factor, for evaluating the comprehensive performance of wet dust collector;Then select different wet dust collector under the same environmental conditions and the same wet dust collector under different environmental conditions are respectively carried out performance test, so not only can the performance ordering of different wet dust collector under the same conditions be obtained, but also the performance ordering of the same wet dust collector under different environmental conditions can be obtained, which is convenient for subsequent specific environmental conditions to select corresponding wet dust collector, and targeted optimization of wet dust collector according to the evaluation result.

The present application relates to the technical field of equipment energy-saving management, and discloses a multi-machine linkage equipment integrated energy-saving management and intelligent decision method and system, comprising: step 1, obtaining equipment operation parameters, calculating unit energy consumption, determining a runnable load interval, and splitting a task into standard task units; step 2, determining group-level remaining available energy consumption and establishing output and energy consumption constraints; step 3, according to unit energy consumption and in combination with equipment energy consumption coefficients, iteratively obtaining final throughput targets of each device; step 4, calculating marginal energy consumption cost and allocating standard task units to obtain final task allocation; step 5, generating a strategy parameter set based on the final task allocation and the throughput target and monitoring an out-of-limit state, updating the strategy and issuing an alarm when the out-of-limit state occurs; and step 6, generating energy consumption settlement and management output based on actual energy consumption and energy consumption budget. The present application realizes intelligent management of controllable energy consumption budget, accountable resource allocation and evaluatable energy-saving performance in a multi-machine collaborative scenario.

This invention provides a method for estimating the driving range of electric vehicles based on battery aging levels. The method includes: collecting operational data of the electric vehicle, including average driving speed and battery usage intervals; obtaining the battery aging level corresponding to each battery usage interval using incremental capacity analysis; grouping the battery usage intervals based on temperature conditions; constructing a nonlinear estimation model of the electric vehicle's speed versus unit energy consumption driving range based on the operational data; and constructing a driving range calculation model within the battery usage interval based on the nonlinear estimation model of speed versus unit energy consumption driving range, thereby calculating the driving range of the electric vehicle under different battery aging levels and temperature conditions. This invention achieves accurate estimation of the electric vehicle's driving range while effectively incorporating the characteristics of the actual operating environment, making it suitable for driving range detection and prediction systems for electric vehicles in complex urban traffic environments.

This invention discloses a method, system, and medium for energy consumption allocation and settlement of cross-space shared equipment. The method includes the following steps: collecting the total energy consumption of the main electricity meter at a site and determining the portion consumed by a set of shared equipment, wherein the set of shared equipment is equipment or circuits serving multiple spaces simultaneously; obtaining the load proxy amount of each space in each time slot within the allocation period, wherein the load proxy amount is constructed based on observable operating status data within the space and is used to reflect the demand intensity of the space for shared equipment; calculating the space allocation coefficient for each time slot based on the load proxy amount of each space in the same time slot; calculating the allocated energy consumption of each space in the corresponding time slot based on the space allocation coefficient and the energy consumption of the set of shared equipment; obtaining the specific energy consumption of each space, and verifying and correcting the total energy consumption of each space using the total energy consumption of the main electricity meter as an energy conservation constraint.

The application discloses a kind of multi-parameter desulfurization absorption tower energy consumption evaluation method and system, and evaluation method includes following process: the desulfurization efficiency and unit energy consumption of desulfurization absorption tower under each working condition are calculated;When the energy consumption of two kinds of working conditions of desulfurization absorption tower is evaluated, the unit energy consumption efficiency ratio of the two kinds of working conditions is calculated, for the working condition with lower unit energy consumption efficiency ratio value, the energy consumption economy of desulfurization absorption tower running under the working condition is evaluated better;When the energy consumption of more than three kinds of working conditions of desulfurization absorption tower is evaluated, the energy consumption efficiency difference ratio of each non-basic working condition and basic working condition is calculated respectively, for the non-basic working condition with minimum energy consumption efficiency difference ratio, the energy consumption economy of desulfurization absorption tower running under the non-basic working condition is evaluated better.The application can carry out the analysis benchmark of desulfurization absorption tower energy consumption comparison under different working conditions, and the running economy of desulfurization absorption tower can be more accurately evaluated.

The invention discloses a low-carbon comprehensive energy collaborative scheduling system for multi-time scale prediction, relates to the technical field of energy collaborative scheduling, and is used for solving the problem of insufficient response of an overall scheduling strategy to a low-carbon target. The condensation temperature is monitored, the carbon emission coefficient is analyzed in combination with the parameters, emission grades are divided according to the carbon emission coefficient and transmitted to the classification marking module, meanwhile, monitoring signals are sent to the data acquisition module, the start-stop frequency and the start delay time are acquired, the equipment efficiency is evaluated, the scheduling weight is calculated, and after the scheduling weight is transmitted to the classification marking module, the equipment efficiency is evaluated. And the scheduling level is analyzed by integrating the emission level and the scheduling weight, and finally the scheduling priority of each device is determined. According to the scheme, low-emission equipment can be scheduled preferentially, carbon emission and the total amount of carbon emission under unit energy consumption are reduced, and low-carbon development of the park is promoted.

The invention relates to the technical field of artificial intelligence, and particularly provides an energy consumption grading monitoring method, system and equipment combined with flow direction prediction and a medium, and the method comprises the steps: collecting and standardizing multi-source data of an energy system, and forming a standardized data set containing flow direction data and grade data; then, basic features and flow direction-level correlation features are mined from the data set, and a feature set is formed; and inputting the feature set into a trained double-target prediction model, and synchronously outputting an energy flow prediction value and an energy consumption grade prediction result in a future time period. And finally, according to a prediction result, when it is predicted that the probability that the target area reaches the specific energy consumption level in the future exceeds a preset threshold value, dynamic adjustment of the monitoring strategy is automatically executed. According to the invention, intelligent linkage of prediction and monitoring is realized, and early warning timeliness and response accuracy are effectively improved.