376 results about "Effective energy" patented technology

The invention discloses a tunnel construction progress digital twinborn prediction and resource scheduling system and method, relates to the technical field of tunnel construction, and provides the following scheme that the method comprises the steps that real-time monitoring data of a tunnel construction area are collected, the real-time monitoring data comprise equipment position information and process progress quantitative data, and a BIM model of the tunnel construction area is constructed; dividing the equipment position information into a plurality of continuous time windows according to time nodes of the BIM model, and obtaining equipment operation parameters and corresponding energy consumption values in each time window; when the effective energy consumption is calculated, the geological condition grade weight and the construction process reference value are introduced to dynamically correct the initial efficiency coefficient, and meanwhile, the geological condition fluctuation, the equipment performance attenuation and the process connection change in the construction conditions are reflected through the time attenuation coefficient, so that the nonlinear influence of the geological difference and the process adjustment on the energy consumption efficiency is effectively eliminated; the strong relevance between the energy consumption and the progress is established, and a reliable data association basis is provided for progress prediction.

The invention relates to a distributed light storage energy control method, and the method comprises the steps: firstly collecting effective illumination data of all photovoltaic modules, constructing an illumination data set through combining historical data, collecting environment data, and associating the environment data with the illumination data, thereby forming an environment influence data set; through a machine self-learning algorithm, an environment influence data set is analyzed, an environment influence factor is generated, the conversion efficiency of a photovoltaic module is predicted, energy conversion data of an inverter and historical input data of an energy storage device are collected, a light energy conversion data set is constructed, a conversion efficiency factor is generated, and the photovoltaic module is analyzed by utilizing the predicted environment data and the environment influence factor. According to the method, effective illumination data is predicted, expected energy storage data is calculated, whether the expected energy storage data meets the power demand or not is judged according to the power demand data, and a power supply distribution strategy is generated, so that the distributed light storage energy system is regulated and controlled, and the energy effective utilization rate of the distributed light storage energy is improved.

The invention is suitable for the technical field of energy consumption analysis, and particularly relates to a smart energy consumption analysis method and system, and the method comprises the steps: drawing a technological process PID diagram, marking energy consumption equipment, positioning a control node of the energy consumption equipment, defining a standard working condition, reading a valve position of the control node through a preset DCS central control system, and carrying out the control of the energy consumption equipment. The fluctuation range of the valve position under the standard working condition is configured; and traversing the technological process PID diagram, determining the energy type of each control node, and clustering the fluctuation range based on the energy types. By generating the monitoring tree, the energy analysis result can be quickly output, the abnormal node can be found out, the energy consumption abnormal position can be accurately positioned, the more effective energy consumption management strategy can be formulated, and by drawing the change trend chart, the energy consumption condition can be visually displayed, the energy consumption state can be comprehensively known, and the energy consumption abnormity can be timely found and processed. And stable operation of a production system is ensured.

The invention provides an ad hoc network communication power control system and method based on a centerless node, and relates to the technical field of wireless communication, and the system comprises a link quality evaluation module which is used for evaluating the link quality between a node and an adjacent node; the power adjusting module is used for calculating and adjusting the transmitting power of the node according to the link quality, the service requirement and the energy state; the channel power coordination module is used for monitoring the channel interference condition in real time and dynamically selecting a channel and coordinating power when the interference is relatively large; the energy sensing and limiting module is used for monitoring node energy and limiting a power adjustment range according to an energy state; and the information interaction and synchronization module is used for ensuring accurate exchange and synchronization of information among the nodes. According to the invention, by improving link quality evaluation, optimizing a power adjustment strategy, enhancing interference processing capability and realizing more effective energy management, efficient power control in a dynamically changing network environment is realized, and the overall performance and stability of the network are improved.

The invention relates to the technical field of intelligent manufacturing, in particular to an electrical manufacturing execution management system based on cloud computing, which comprises a scheduling optimization module, an energy management module, an equipment health and state monitoring module and a production efficiency improvement module. According to the method, accurate scheduling of production resources is realized by capturing electrical production task progress, equipment use conditions, process parameters and energy consumption data, then the operation mode, time and speed of equipment are regulated and controlled, resource allocation is more flexible, the energy consumption data are analyzed by relying on cloud computing, the energy use mode and equipment load are optimized, and the energy utilization efficiency is improved. Effective energy distribution is realized, energy efficiency is improved, equipment faults can be predicted in advance in combination with an equipment health assessment model, a maintenance period is adjusted according to an equipment state, production interruption caused by equipment shutdown is avoided, deep analysis is performed on production scheduling, then a production sequence and resource distribution are adjusted, production efficiency is improved, and production efficiency is improved. And the stability and the flexibility of the production line reach a higher level.

The invention discloses a photovoltaic power generation system energy storage management method based on dynamic regulation and control and computer equipment. The method comprises the following steps: S1, obtaining and preliminarily analyzing power grid load data; s2, constructing a power grid cost dynamic scheduling model; s3, calculating and optimizing the number of the energy storage units; s4, constructing an optimal dynamic scheduling model; and S5, historical data matching and strategy optimization are carried out. In order to solve the problem that power output is unstable due to the fact that photovoltaic power generation is influenced by weather and day and night changes in the prior art, power grid load data, photovoltaic power generation historical data, the number of energy storage units and other information are obtained, decision making is conducted through the historical data and a load prediction model, it is ensured that an energy storage management strategy is more scientific and reasonable, and the energy storage efficiency is improved. The method aims at optimizing energy storage management, improving the utilization rate and the economic benefit of photovoltaic power generation, and remarkably improving the economical efficiency and the stability of a photovoltaic power generation system through an effective energy storage management method.

The invention relates to a refrigeration air conditioner control method and system based on a dynamic adjusting algorithm, a low-pressure area and a high-pressure area in a cold-chain logistics transportation cabinet are judged through real-time reference air pressure data of a barometer, and the real-time reference air pressure data of the barometer can be received and analyzed. A sliding window is established, based on the sliding window, a parameter diagram of real-time reference air pressure data is segmented, real-time pressure data in the sliding window is obtained, when the conveying amount of cold air is too large, a low-pressure area can be formed in the cold-chain logistics transportation cabinet, and then more wet hot air is absorbed, so that the interior of the cold-chain logistics transportation cabinet is frosted and frozen; and more effective energy can be consumed. When the conveying amount of the cold air is too small, a high-pressure area can be formed in the cold-chain logistics transportation cabinet, and the preset temperature cannot be reached. Through the air pressure data, the temperature in the cold-chain logistics transportation cabinet can be accurately obtained.

The invention discloses a variable-working-condition IES optimal scheduling method considering a GCT-LTC joint mechanism and a PDR mechanism. The method comprises the steps that S1, a comprehensive energy system comprising power, heat and gas multi-energy complementation is constructed; s2, constructing a variable working condition equipment operation model in the integrated energy system; s3, on the basis of the equipment operation model, constructing a variable working condition IES optimization scheduling model considering a GCT-LTC joint mechanism and a PDR mechanism; and S4, solving the variable working condition IES optimal scheduling model by using a particle swarm algorithm to obtain an operation optimization parameter taking the lowest total operation cost as a target, and performing optimal scheduling of the integrated energy system according to the operation optimization parameter. According to the method, based on a green certificate-stepped carbon transaction joint mechanism, the corresponding optimal scheduling model considering the variable working condition characteristics and requirements of the IES is established with the lowest economic cost as the target, so that the effects of more effective energy conversion and reduced energy waste are achieved, economic operation of the IES is facilitated, and analysis on the overall operation scheduling condition of the IES is more accurate.

The invention discloses a bare concrete appearance quality evaluation method, which belongs to the field of concrete quality evaluation, and adopts the technical scheme that process data are synchronously acquired in a bare concrete pouring process; obtaining concrete surface appearance index data after demolding; performing time synchronization and spatial inverse registration on the acquired data, and performing gridding association on the appearance indexes and the process data in the corresponding time windows; for each grid unit, extracting vibration effective energy, pumping pressure fluctuation characteristics, template deformation characteristics and environment correction factors from the process data in the corresponding time window and space range, and combining the vibration effective energy, the pumping pressure fluctuation characteristics, the template deformation characteristics and the environment correction factors into a joint characteristic vector; constructing a structural causal model, calculating the cause posterior probability of the appearance defect for each grid, and outputting cause probability distribution of under-vibration, over-vibration, unstable pumping, insufficient template rigidity and environmental sensitization; and generating an appearance quality score according to the cause probability distribution. The method has the beneficial effect that the method for evaluating the appearance quality of the fair-faced concrete is provided.

The invention relates to a plant factory illumination adjustment system and method based on growth period intelligent identification. The system comprises a background management module, a growth detection module, a data storage module and an intelligent regulation and control module which are connected in sequence. The background management module receives the real-time image and environment data of leaf vegetable growth and inputs the real-time image and environment data to the growth detection module; the growth detection module performs image preprocessing on the real-time image, intelligently identifies the growth period of the current leaf vegetable, predicts the growth information of the current leaf vegetable, and sends the growth information to the data storage module for storage and recording; the data storage module automatically matches an optimal light supplementing strategy suitable for the current growth information of the leaf vegetables according to a pre-configured staged light supplementing formula; and the intelligent regulation and control module dynamically regulates parameters of the execution mechanism based on the optimal light supplement strategy, and maintains the optimal illumination environment of the leaf vegetables in real time. Compared with the prior art, the method has the advantages of rapid and accurate regulation, effective energy conservation and the like.

The invention discloses an energy consumption analysis method for an ultra-low energy consumption building, and belongs to the technical field of ultra-low energy consumption buildings, and the method comprises the following steps: S1, collecting and processing the historical data of the ultra-low energy consumption building, and determining the feature data of the ultra-low energy consumption building; s2, performing test optimization on the energy consumption prediction model of the ultra-low energy consumption building, and determining an optimal energy consumption prediction model of the ultra-low energy consumption building; s3, performing energy consumption prediction on the ultra-low energy consumption building, and determining an energy consumption prediction value of the ultra-low energy consumption building; and S4, analyzing the energy consumption predicted value of the ultra-low energy consumption building, and determining an energy consumption analysis result of the ultra-low energy consumption building. The problem that the use effect of the ultra-low energy consumption building is poor due to the fact that effective energy consumption analysis and timely energy consumption management cannot be carried out on the ultra-low energy consumption building in the prior art is solved. According to the invention, effective energy consumption analysis can be carried out on the ultra-low energy consumption building, timely energy consumption management can be carried out on the ultra-low energy consumption building, and the use effect of the ultra-low energy consumption building can be improved.

The invention relates to an intelligent charging station resource scheduling method and system based on data processing, and relates to the field of the vehicle charging technology, and the method comprises the steps: obtaining the remaining energy storage electric quantity; determining required supplementary electric quantity according to the full-load energy storage electric quantity and the residual energy storage electric quantity; determining energy storage demand duration according to the energy storage efficiency and the demand supplementary electric quantity; constructing a permissible energy storage time period and delimiting a unit interval; constructing a historical interval, determining a similar interval in the historical interval according to each unit interval, and determining a historical energy storage electricity price in the similar interval; combining each unit interval according to the energy storage demand duration to construct a simulated energy storage scheme, and determining the overall electricity price of the scheme according to each historical energy storage electricity price in each simulated energy storage scheme; and defining the simulation energy storage scheme corresponding to the scheme overall electricity price with the minimum numerical value as an effective energy storage scheme, and controlling the charging station to perform energy storage scheduling in a unit interval in the effective energy storage scheme. The charging station has the effect of reducing the power utilization cost of the charging station.

The invention discloses a distributed outer node detection method based on energy evaluation and propagation, and belongs to the field of deep learning. The technical problem to be solved by the invention is that graph data in a real scene is generally continuously expanded along with continuous acquisition of external knowledge, and the distribution difference between new nodes and original nodes may cause reduction of the effect of an existing graph neural network method. Meanwhile, an existing out-of-distribution detection method based on softmax confidence score may cause the problem of excessive self-confident posterior distribution of out-of-distribution data. Therefore, the invention provides the distributed external node detection method based on energy evaluation and propagation, and the graph neural network is endowed with the capability of identifying the distributed external nodes. The system comprises an energy-based distribution external evaluation module used for distributing corresponding energy values for different nodes, a structure sensing energy propagation module used for realizing effective energy aggregation, and a joint alignment regularization module used for further guiding a learning process.

The invention relates to the technical field of photovoltaic cooling hydrogen production, and particularly provides a multi-source synergistic spray cooling concentrating frequency division photovoltaic hydrogen production system and a regulation and control method. Accurate separation of solar spectrums is achieved through jacketed pipe frequency division and a reaction pipe, visible light wave bands are converted into electric energy through a photovoltaic module, infrared wave bands are subjected to photo-thermal conversion through a catalytic reaction pipe, surplus heat energy is directly used for the activation process of hydrogen production through water electrolysis, and gradient utilization of solar energy is achieved. And precise temperature control is realized, and the temperature of the photovoltaic panel is stabilized in an optimal interval in combination with a closed-loop temperature control strategy. The wind-solar complementary power supply and the waste heat cascade recovery device synergistically improve the energy utilization rate, and the multifunctional integrated electric control system realizes hydrogen-electricity-heat multi-target scheduling through a dynamic game optimization algorithm and a digital twin simulation platform. The working temperature of a solar cell is stabilized in the optimal efficiency interval, meanwhile, heat energy loss of a traditional system is converted into hydrogen production effective energy, and an efficient and stable solar energy-hydrogen energy conversion system is constructed.

The invention provides a flexible mobile micro-grid energy management strategy generation method based on an intelligent optimization algorithm, and the method comprises the steps: initializing the parameters of all basic elements in a flexible mobile micro-grid energy management strategy according to the basic elements in the flexible mobile micro-grid energy management strategy; determining constraint conditions according to technical requirements of parameters, and constructing a target function based on a management target of flexible mobile micro-grid energy; according to the objective function, searching parameters of each basic element in the optimal flexible mobile micro-grid energy management strategy by using an improved Wuyu-gull optimization algorithm; and generating a flexible mobile micro-grid energy management strategy based on an intelligent optimization algorithm according to the parameters of the optimal basic elements. According to the method, an effective energy management strategy can be formed, and the working efficiency of the flexible mobile microgrid is further improved.

A hydraulic fracturing system and method uses an effective energy model to reflect energy loss in pressurized fracturing fluid passing into and through a wellbore to a reservoir formation during hydraulic fracturing. The model determines effective energy delivered to the reservoir formation as a function of surface energy added to the fracturing fluid to raise the fracturing fluid to a high-pressure state, gravitational potential energy gains in the pressurized fracturing fluid as the fluid travels down to the reservoir formation, and energy losses in the pressurized fracturing fluid as the fluid travels down to the reservoir formation. The effective energy model is applied to a selected reservoir formation and an operational cost for hydraulic fracturing of the selected reservoir formation is selected based on the effective energy model.

A firework shell launching device comprises a gas generator and a launching tube; the upper end of the launching tube is open, and the gas generator is pressed into the launching tube from the lower end and is flush with the bottom end of the launching tube; the gas generator comprises a wire, an electric ignition head, a plugging screw, propellant, a powder cup, a pressure control chamber and a shell; the powder cup is sealed inside the pressure control chamber by the plugging screw, and the powder cup and the side wall of the pressure control chamber are interference fit; the propellant is arranged in the powder cup; the electric ignition head is arranged on the plugging screw, one end of the electric ignition head is connected to the propellant, and the other end is connected to the wire extending outside the launching tube; the utility model has the following beneficial effects: the double-layer structure of the utility model has an effective energy utilization rate, and can be moisture-proof and anti-deterioration; at the same time, it also ensures a stable exit speed, a high control accuracy of the firing height, a high launching success rate, and can be reused and can also be suitable for launching the same or different types of firework shells, effectively reducing the production cost.

The invention discloses a metabolite detection method for diagnosing lithangiuria, and relates to the technical field of metabolite detection. The method comprises the following steps: collecting and preprocessing a urine sample, and generating a composite fluorescence signal based on the preprocessed urine sample so as to obtain a composite function; constructing an orbital function system, and performing projection processing on a composite function to obtain initial orbital energy; based on the initial orbital energy, a mutual exclusion function between metabolites is introduced, an effective energy contribution value is calculated, and a decoupled energy response amount is obtained; converting the decoupled energy response quantity into a concentration estimation value, and generating a rotation response value based on the concentration estimation value; generating a coupling threshold based on the concentration estimation value and the rotation response value; and carrying out risk scoring based on the coupling threshold value to obtain an individual risk score value of the urinary calculi. The invention solves the problems of inaccurate concentration estimation of the metabolite and low metabolite detection precision caused by inaccurate analysis of the metabolite under complex interference conditions in the existing metabolite detection method.

Described are various embodiments of a smart attic ventilation system, and sensor module therefor. Also described are various embodiments of an effective energy storage and delivery mechanism for such systems, for example, when predominantly powered from an integrated solar energy capturing component such as a solar panel, for continuous operation in dark environmental conditions such as at night and / or on cloudy days.

The invention provides a method for adjusting the solid fuel ratio of a hydrogen-rich carbon cycle oxygen blast furnace. The method comprises the following steps: step 1, calculating the variation of energy input of the hydrogen-rich carbon cycle oxygen blast furnace caused by cycle gas change; 2, effective energy input of the solid fuel per unit mass in the hydrogen-rich carbon circulation oxygen blast furnace is calculated; and 3, calculating the adjustment amount of the hydrogen-carbon-rich circulating oxygen blast furnace solid fuel ratio according to the results of the previous two steps.

The invention discloses an intelligent multi-source energy collaborative optimization system. According to the method, the efficiency and the economical efficiency of energy management are remarkably improved through the dynamic decision-making capability of the multi-objective optimization engine. The engine is based on real-time energy data and environment variables, deep prediction and reinforcement learning technologies are combined, accurate distribution and dynamic balance of multi-source energy are achieved, for example, when the electricity price fluctuates or the equipment load suddenly changes, the system can rapidly adjust the proportion of electric energy, heat energy and waste heat recovery, energy waste is reduced, and the operation cost is optimized. And meanwhile, the energy recovery module converts traditional waste energy into available resources, the dependence on external energy is further reduced in cooperation with global scheduling of the cloud service platform, and the comprehensive energy efficiency of the enterprise can be improved by more than 20%. The system supports a multi-scene adaptive strategy, takes into account short-term cost control and long-term equipment health management on the premise of ensuring production continuity, and provides an energy solution with high cost performance for industrial and commercial users.

The invention relates to the technical field of roadway supporting, in particular to a roadway hydraulic support resistance-increasing energy-absorbing and impact-stopping method which comprises an energy-absorbing component arranged in a support, a support base used for supporting a roadway bottom plate is arranged below the energy-absorbing component, and a stand column and a support top beam used for supporting a roadway top plate are arranged above the energy-absorbing component. Starting from the energy-absorbing abdicating displacement of the energy-absorbing component, the bearing reaction generated by the energy-absorbing component is increased along with the increase of the abdicating displacement, and the characteristic of resistance-increasing type energy absorption is presented; in the energy absorption abdicating process of the resistance-increasing type energy absorption component, the pressure of the emulsion in the stand column is in the rising trend, but is not higher than the peak pressure of the emulsion at the initial moment of energy absorption starting all the time; under the condition of the same energy absorption amount, the effective energy absorption stroke required by the resistance-increasing type energy absorption component is shorter; according to the stand column provided with the resistance-increasing type energy absorption component, at the end of energy absorption receding, the hard impact bearing reaction peak value generated by the stand column and a support base is smaller than the bearing reaction peak value of a stand column provided with a constant-resistance energy absorption component.

The invention provides an optimized energy scheduling method for centralized shared energy storage, and relates to the technical field of energy storage optimization, and the method comprises the steps: obtaining a power system monitoring data set, carrying out the energy scheduling target feature fitting, constructing a prediction shared energy storage scheduling scene, obtaining a plurality of energy storage unit monitoring data sets, and then carrying out the energy scheduling decision registration, and determining a shared energy storage scheduling decision, performing fitting correction optimization to output a shared energy storage scheduling scheme, and finally performing energy scheduling on the centralized shared energy storage system according to the shared energy storage scheduling scheme. According to the invention, the technical problem that the energy scheduling efficiency and the stable operation of the power system are further influenced due to inaccurate state monitoring of the power system caused by untimely data acquisition, insufficient data processing capability and insufficient advanced scheduling decision method in the prior art can be solved; effective energy scheduling is carried out on the centralized shared energy storage system according to the shared energy storage scheduling scheme, and the stability of a power system is improved.

The invention discloses a ship waste heat utilization system and an energy recovery method, and the method comprises the steps: monitoring and collecting waste heat parameters in real time through a multi-sensor array, processing data fluctuation through a self-adaptive filtering algorithm, and carrying out the quality evaluation in combination with an effective energy model; according to the real-time effective energy value, the fluctuation index and the host load, the waste heat resource allocation priority is dynamically adjusted, and a multi-mode waste heat resource allocation strategy is synchronously formulated based on the output predicted by the extended Kalman filtering algorithm; a full-state prediction model based on an ORC system is constructed, and a prediction-optimization-compensation adaptive control framework is established; a heat charging and discharging sequence is optimized based on model prediction control, and energy loss is minimized; according to the method, performance indexes of the whole waste heat utilization system are monitored, control parameters are optimized by using a reinforcement learning algorithm based on real-time data, the optimized parameters are applied to the system, and closed-loop control is performed. The problem of insufficient waste heat utilization is solved, energy loss is remarkably reduced, and the waste heat utilization efficiency of the system is improved.

The invention discloses an electric power system multi-element energy storage planning method and equipment considering extreme disasters, and belongs to the technical field of electric power system planning. Through uniformly describing the operation characteristics of battery energy storage and hydrogen energy storage, the short-time rapid adjustment capability and the long-time large-scale energy transfer capability are integrated into the same planning framework; compared with an existing method which only depends on a single energy storage mode or independently models different energy storage devices, the method can construct effective energy reserve before a disaster, provide continuous power supply support in the disaster and promote rapid recovery of a power grid after the disaster, so that the bearing capacity and the self-healing capacity of the system under the extreme disaster condition are remarkably enhanced; according to the invention, the energy storage construction cost, the maintenance cost and the operation cost in a disaster scene are integrated into a double-layer stochastic programming framework, so that the energy storage configuration can give consideration to both economy and system reliability, and the maximization of energy storage investment income and the synchronous improvement of power supply reliability in a disaster period are realized.

The utility model discloses an air conditioner outdoor unit spray cooling device which comprises an air conditioner outdoor unit body, an auxiliary assembly is arranged at one end of the air conditioner outdoor unit body, one side of the auxiliary assembly makes contact with one side of the air conditioner outdoor unit body, a cooling assembly is arranged in the auxiliary assembly, and heat dissipation treatment can be conducted on multiple faces of an air conditioner outdoor unit. Meanwhile, heat dissipation treatment can be conducted repeatedly, the air conditioner outdoor unit is rapidly cooled, effective energy saving and consumption reduction are promoted, the outer wall of the air conditioner outdoor unit can be flushed in the heat dissipation process, and the phenomenon that aging of the air conditioner outdoor unit is accelerated due to the fact that impurities adhere to the air conditioner outdoor unit for a long time can be effectively avoided; the cooling device can be installed and fixed conveniently, the cooling device can be installed on air conditioner outdoor units of different specifications, meanwhile, the temperature and humidity of the air conditioner outdoor units can be intelligently monitored, and the equipment operation effect and efficiency can be more accurately and effectively improved in real time.

The invention relates to a wood structure damage detection method and system based on acoustic emission effective energy density, and belongs to the technical field of wood nondestructive testing. The method comprises the following five steps: mounting an acoustic emission sensor, acquiring an acoustic emission signal, processing an effective acoustic emission signal, calculating effective energy density, and evaluating the wood damage grade. According to the invention, the in-situ dynamic nondestructive testing of the wood structure is realized directly according to the effective energy density index of the original acoustic emission signal, so that a dynamic damage grade evaluation report is given, and a diagnosis basis is provided for safe and healthy use of the wood structure.

The invention discloses a carbon footprint accounting method for a remanufactured generator based on a remanufacturing life cycle, and relates to the technical field of generator remanufacturing, and the method comprises the steps: obtaining a corresponding remanufacturing life cycle when a generator which does not meet a use demand is remanufactured, and a remanufacturing reason which does not meet the use demand; creating a boundary model corresponding to the remanufacturing process; based on the boundary model and the remanufacturing reason, determining a carbon emission source of each stage in the remanufacturing process; and obtaining an emission factor corresponding to the carbon emission source of each stage, calculating the carbon emission of each stage based on the emission factor, and carrying out summation processing on the carbon emission of each stage to obtain the carbon footprint of the remanufacturing life cycle. The problem that in the prior art, after the generator loses original efficiency, resources are wasted when the generator is scrapped is solved, and remanufacturing of the generator losing the original efficiency is achieved so that energy can be saved.

A coincidence technique-based X-ray detection device and composition analysis method are provided, wherein the X-ray detection device includes: a sample holding device; an excitation unit for outputting X-rays with continuously adjustable energy; detectors comprising two SiC semiconductor detectors and two SiPIN semiconductor detectors; a signal processing unit for performing amplification, analog-to-digital conversion and classification on the detected signals to obtain energy information; a data processing device connected to the signal processing unit and used for analysis and calculation according to the energy information and determining element type and content of the sample to be tested, wherein the data processing device comprises a processor and a memory, the processor is used for executing following program modules stored in the memory: a storage module, a baseline recovery module, a calibration curve construction module, an extraction module, an effective energy information determination module, and a peak comparison module.

The invention discloses a substance identification method based on self-adaptive quantitative decomposition, which comprises the following steps of: establishing a polynomial relationship among coefficients, energy and effective atomic numbers participating in substance identification in the interaction of rays and substances, and scanning and reconstructing by using various known materials as calibration substances; based on the linear attenuation coefficients of different energy regions of the calibration object, the real effective atomic number and density of the calibration object and the polynomial relation obtained before, effective energy of the corresponding energy region is determined; in actual operation, after scanning reconstruction is carried out on a to-be-decomposed substance, due to the fact that effective energy is determined through calibration and linear attenuation coefficients reconstructed in different energy regions are only related to effective atomic numbers and densities, two ray and substance interaction formulas containing variable parameters are simultaneously established, and solving is carried out; and the effective atomic number and density of the scanned substance can be accurately obtained. According to the invention, correlation coefficients can be automatically adjusted according to different substances, so that the decomposition precision is improved.