1472 results about "Combustible gas" patented technology

The invention discloses a self-adaptive calibration system and method for a combustible gas sensor. The self-adaptive calibration system and method are suitable for a catalytic combustion type combustible gas sensor. The system comprises a basic calibration unit, a real-time monitoring unit, a drift detection and compensation unit and an output adjustment unit. The basic calibration unit is used for carrying out basic calibration on the sensor and determining an initial sensitivity coefficient, zero offset and response time of the sensor; the real-time monitoring unit is used for monitoring real-time parameters of the sensor under different environmental conditions; the drift detection and compensation unit is used for establishing a sensor performance parameter drift model and calculating a calibration compensation coefficient; the output adjusting unit is used for adjusting the voltage output value of the sensor in real time according to the calibration compensation coefficient; the method can adapt to environment change for real-time calibration, effectively compensates sensor drift, improves measurement precision and reliability, prolongs the service life of the sensor, reduces maintenance cost, and improves system safety.

The invention provides a factory energy safety dynamic monitoring method based on the Internet of Things and multi-mode perception, and belongs to the technical field of industrial Internet of Things. Comprising the following steps: acquiring electrical parameters, temperature data, combustible gas leakage concentration and vibration signals of equipment in real time; carrying out aggregation and protocol conversion on the electrical parameters, the temperature data, the combustible gas leakage concentration and the vibration signals through a multi-protocol intelligent gateway, and uploading the electrical parameters, the temperature data, the combustible gas leakage concentration and the vibration signals to a locally deployed edge computing node in a preset period; preprocessing the received data at the edge computing node, and generating a quantitative risk index based on a dynamic risk assessment model fusing the real-time state of the equipment, the historical aging trend and the environmental parameters; and carrying out risk grade judgment according to the quantitative risk index, and executing a corresponding grading response. Through fusion of multi-modal sensing data and edge intelligence, comprehensive sensing, real-time quantitative evaluation and hierarchical intelligent response of factory energy safety risks are realized.

The invention discloses a coal seam group occurrence three-area linkage gas extraction method. Firstly, a coal seam is divided into an underground coal gasification area, a pressure relief permeability increasing area and an original extraction area; in the initial stage of underground coal gasification, in the process that high-temperature combustible gas generated by underground coal gasification is injected into a ground drilling well, the high-temperature combustible gas and a coal body are subjected to heat transfer, so that the temperature of the coal body is increased, and gas desorption is enhanced; under the continuous coupling action of high temperature and high pressure of the high-temperature combustible gas, the permeability of the coal body is improved; in the process that high-temperature combustible gas is injected into the ground drilling well, gas extraction is continuously conducted on other adjacent drilling holes; under the condition that gas injection and gas extraction are sequentially and circularly performed in ground drilling, the coal body is circularly impacted by positive pressure-negative pressure alternating aerodynamic force, and further fracturing of the coal body is facilitated; under the triple effects of high-temperature coal body gas desorption strengthening, coal body permeability increasing and gas displacement, large-flow and high-quality extraction of deep coal seam gas is finally achieved.

The invention provides a portable fire blast risk dynamic identification and danger tracing method and terminal, and the method comprises the steps: collecting positioning data in real time through a GNSS positioning module; a high-speed analog-to-digital conversion chip ADC is used for carrying out high-frequency and synchronous processing on the gas concentration collected in real time; collecting field environment parameters in real time; performing dynamic threshold intelligent judgment to obtain a leakage judgment result, and executing a grading early warning mechanism; recording an inspection track in real time, and carrying out space gas concentration gradient analysis to obtain a gas concentration gradient; calculating a built-in space distance; judging the leakage direction according to the gas concentration gradient data, and intelligently tracing the leakage source according to the leakage judgment result; and uploading the security data to the cloud. According to the invention, the limitation of static and single-threshold alarm of an instrument is solved, and the technical problems of difficulty in spatial continuous sensing and automatic tracing positioning of gas leakage abnormity in a complex inspection environment with dynamic changes of multi-component combustible gas and environmental parameters are solved.

The invention relates to a low-concentration combustible gas concentration system and an operation method thereof, and the low-concentration combustible gas concentration system comprises a flame arrester, a mixing cavity, a non-combustible gas supplementing tank, a gas compressor, a primary separator, a light component secondary separator, a heavy component secondary separator and a concentration regulating valve, the premixed gas sequentially passes through a primary separator, a light component secondary separator and a heavy component secondary separator under the action of a gas compressor to carry out concentration operation on light component combustible gas, non-combustible gas is returned to a mixing cavity, and heavy component gas is discharged into the atmosphere; the invention aims to solve the technical problems of large occupied area and volume, low operation efficiency and poor separation effect of the existing combustible gas separation equipment.

The invention belongs to the technical field of gas pipeline fault prediction, and discloses a pipe gallery gas pipeline defect identification method and system and an inspection robot. The method comprises the following steps: synchronously sensing multi-dimensional time sequence data of a pipe gallery gas pipeline, wherein the multi-dimensional time sequence data comprises gas pipeline time sequence data, combustible gas concentration time sequence data and environment time sequence data; performing structured processing and feature extraction on the multi-dimensional time series data, and outputting a multi-modal feature data set for defect identification and risk assessment; performing joint modeling based on the multi-modal feature data set to obtain a fusion interaction embedding vector, and identifying a coupling abnormal state with causal correlation or collaborative performance between the structural defect and the trace gas leakage based on the fusion interaction embedding vector; based on the fusion interaction embedding vector and the coupling abnormal state, the early defect type of the pipe gallery gas pipeline is recognized; the early-stage defect identification accuracy and response speed of the pipe gallery gas pipeline are remarkably improved.

The invention relates to the technical field of fire-fighting management, and discloses an intelligent fire-fighting management method and system based on a multi-modal large model, and the method comprises the steps: 1, collecting multi-modal perception data in a field environment, and transmitting the multi-modal perception data as input data to a multi-modal semantic recognition module; and 2, performing modal analysis and semantic fusion on the input data by using the multi-modal semantic recognition module, and generating a unified semantic description containing fire state elements. According to the invention, a multi-modal perception data semantic fusion mechanism and a multi-modal large model-driven fire behavior recognition framework are adopted, and data of different modals from a camera, a temperature and humidity sensor, a smoke detector and combustible gas monitoring equipment are input into a unified semantic recognition module, so that unified fire behavior state semantic description is constructed; and the technical effects of multi-source data complementation and semantic-level collaborative recognition of the fire state are achieved.

The utility model relates to a raw gas source upgrading system for an internal heating type vertical furnace. The raw gas source upgrading system comprises a dry distillation furnace, a carbon dioxide removal device and a pure oxygen preparation device, the device further comprises a first multi-stage mixer, a second multi-stage mixer, a gas sampling analysis tube and a gas component detector. Pure oxygen is adopted as a combustion improver, so that the content of nitrogen in the raw gas is greatly reduced, and the application scene of coal gasification production and deep processing of the internal heating type vertical furnace is expanded; the components of combustion-supporting gas, combustible gas and inert gas in mixed gas in a lattice wall of the dry distillation furnace are controlled by adopting double-circulation control of carbon dioxide and recirculated gas, the combustion intensity and the uniformity degree are strictly controlled under the condition that dry distillation heat supply is met, and scabbing and burning loss of a dry distillation furnace body are avoided.

The invention is applicable to the technical field of gas isotope detection, and provides a wide-range gas isotope detection system and method based on TDLAS (tunable diode laser absorption spectroscopy), the detection system comprises a primary gas dilution system, a secondary gas dilution system, a control unit and a combustible gas isotope detection system; the primary gas dilution system comprises a first regulating valve and a first detection module, the first regulating valve is connected with a one-way valve, the one-way valve and the first detection module are both connected with an anti-explosion sensor, and the anti-explosion sensor is connected with a discharge valve; the secondary gas dilution system comprises a second regulating valve and a flow-limiting valve, the flow-limiting valve is connected with a second detection module, the second regulating valve is also connected with the second detection module, and the second detection module is connected with the combustible gas isotope detection system; the control unit comprises a data processing and tracing module and an anti-memory effect module. According to the system, through cooperation of two stages of dilution systems, wide-range, high-precision and high-robustness carbon isotope detection from percentage content to ppb level is realized.

The invention provides a multi-sensor adaptive anti-interference working well environment detection system and method, and the system comprises a single-chip microcomputer control panel, a temperature and humidity monitoring sensor, a four-in-one combustible gas detector, a dust particle detector, a differential pressure transmitter, and a cloud server. The temperature and humidity monitoring sensor, the four-in-one combustible gas detector, the dust particle detector and the differential pressure transmitter are in circuit connection with the single-chip microcomputer control panel, the single-chip microcomputer control panel is in wireless communication with the cloud server, the detection method dynamically adjusts the weight distribution of the sensor through the feature level attention module, a lightweight neural network and a hard redundancy check rule are combined, and the detection accuracy is improved. Compared with the prior art, the method has the advantages that the low false alarm rate is kept, the model size is low, and the method is suitable for industrial field deployment.

According to the infrared combustible gas sensor and the method thereof, firstly, original voltage signals of a measurement channel and a reference channel and original signals of a temperature sensor are subjected to digital filtering, basic concentration is calculated based on the voltage of the measurement channel and the voltage of the reference channel after filtering, and dynamic impact detection is carried out; obtaining a reference channel signal change rate; furthermore, a self-adaptive dynamic compensation gain is introduced, the gain is dynamically adjusted according to the reference channel signal change rate and the filtered reference channel voltage, and the basic concentration is comprehensively compensated by combining the filtered temperature, so that unbalance caused by thermal shock in the photoelectric system is reflected more directly and more quickly. Therefore, the measurement precision and the data reliability of the infrared combustible gas sensor in a complex and changeable environment can be remarkably improved, and more accurate and more robust effects of compensation can be realized under different working conditions.

The invention provides a positive electrode active material and a preparation method thereof, a positive plate and a battery. An inner slow-release layer in the positive electrode active material coats at least part of the surface of a positive electrode active material main body, and an outer inhibition layer coats at least part of the surface of the inner slow-release layer; the inner slow-release layer comprises lithium carbonate and M metal oxide, and the outer inhibition layer comprises at least one of nitride, fluoride and oxide of inhibition elements; the inhibiting elements comprise at least two elements in VA, IVA family, IIIA family, IIA family and IVB family. The lithium carbonate in the inner slow-release layer can release non-flammable gas mainly containing CO2, the metal oxide can inhibit release of lattice oxygen in the positive electrode active material main body at high temperature, and the proportion of combustible gas is reduced. The lithium carbonate is provided with a temperature decomposition window, so that the release time of carbon dioxide pressure relief for the first time can be accurately controlled. And the outer inhibition layer can avoid the contact between the positive electrode active material main body and the electrolyte, so that the proportion of the combustible gas is further reduced.

The invention relates to the technical field of safety supervision and intelligent early warning, in particular to a multi-mode alarm safety supervision system and a control method thereof.The control method comprises the following steps that 1, environment smoke concentration, combustible gas concentration, CO concentration, door and window opening and closing states, human body motion information, voiceprint signals, environment temperature and humidity, H and user posture information are obtained, respectively representing three-axis acceleration and angular velocity vectors, and adding a timestamp t to the obtained data; step 2, filtering the collected original data at the edge gateway based on a preset threshold value of an ith sensor, and identifying a single sensor abnormal event corresponding to the obtained data; and step 3, integrating the lightweight neural network model at the edge gateway, and carrying out glass breaking and call-for-help feature recognition on the collected voiceprint signals, in the invention, differentiated and local and cloud seamless linkage responses can be implemented for events with different severity, so that the reliability, the real-time performance and the availability of the system are remarkably improved.

The invention relates to a toughened modified epoxy resin material and a preparation method thereof, and belongs to the technical field of high polymer materials. The toughened modified epoxy resin material comprises the following components in parts by weight: 90-120 parts of epoxy resin, 8-25 parts of a curing agent, 1-3 parts of a diluent, 0.5-5 parts of a curing accelerator, 4-18 parts of graphite, 5-15 parts of a modified toughening agent and 1-5 parts of a modified flame retardant, in the modified flexibilizer, a benzene ring and carbonyl of a polyimide structure endow the material with excellent heat resistance, intertwining between chains is avoided, embrittlement is avoided, the material and polyurethane are synergistically toughened, and a flexible-Si-O-Si-chain segment relieves thermal stress generated in the resin and improves the tensile strength; benzoxazine in the modified flame retardant contains a nitrogen element, releases non-combustible gas during combustion, forms a carbon layer at high temperature and covers the surface of the material, so that the flame retardance is improved; the toughened and modified epoxy resin material prepared by the invention not only has good toughening and heat-resisting effects, but also has an excellent flame-retardant effect.

The invention provides a fire identification method based on LSTM model and multi-sensor data fusion, and the method comprises the steps: collecting smoke concentration data, temperature data and combustible gas concentration data in a scene, and forming multivariable time series data; sequentially executing data cleaning, data normalization and data relevance enhancement operations to obtain preprocessed data; calculating eigenvalues and eigenvectors based on a Gaussian radial basis function, and screening the eigenvectors of which the variance contribution rates meet a preset condition to obtain fusion features; executing MK test on a time sequence in the preprocessed data, and calculating a standard normal statistical variable as a trend factor; and inputting the fusion feature and the trend factor into an LSTM model combined with an attention mechanism, processing long sequence information through a gate structure, endowing key information with a high weight in combination with the attention mechanism, and outputting a fire identification result. According to the invention, the sensitivity of fire monitoring can be effectively improved, and the false alarm rate can be reduced.

The invention relates to the field of electrical digital data processing, in particular to a boiler atmosphere field state monitoring method, which comprises the following steps: collecting concentration data of combustible gases in a boiler water wall area through measuring equipment, carrying out space-time calibration on the concentration data of multiple measuring points, constructing a data processing model based on a graph convolutional network, and training the data processing model. Obtaining a trained data processing model; the method comprises the following steps: collecting concentration data of each combustible gas in a boiler water-cooled wall area through measuring equipment to obtain new multi-measuring-point concentration data; and after the steps are executed, inputting the data into a trained data processing model to obtain a combustible gas predicted concentration matrix of each measuring point at a future moment, continuously monitoring the combustible gas predicted concentration matrix of each measuring point at the future moment, and when the predicted concentration of any measuring point exceeds a safety threshold value, triggering an early warning signal and positioning a high-risk area. An existing boiler atmosphere field state monitoring method has the problem of low prediction credibility, and the method provided by the invention is high in prediction credibility.

The present application belongs to the field of smelting coal gas recovery, and particularly relates to an optimized control method and system for combustible gas recovery. The method divides the smelting process into N measurement time periods, and calculates the average secondary combustion coefficient of each time period in real time. Meanwhile, M target smelting time zones and their weights are set, and a dynamic target value sequence is established. Based on the initial fan speed, the measured coefficient is adjusted through multiple iterations of the furnace, and when the measured coefficient is greater than the target value, the speed is reduced in steps, and a thermal imager and a differential pressure instrument are introduced to monitor the smoke emission. A smoke emission rate statistics and tolerance threshold judgment mechanism is established to trigger speed backtracking adjustment, and finally the average secondary combustion coefficient of each time period is minimized to generate an optimal fan speed model. The present application maximizes the improvement of the calorific value of coal gas and the recovery of carbon monoxide under the premise of preventing smoke from the furnace mouth.

The invention provides a limited space operation safety protection method and device, and belongs to the technical field of safety production, and the device comprises an illumination module which employs a head-mounted outdoor lamp induction miner's lamp and is used for providing illumination for an operator in an operation process and providing a light source for a camera; the gas detection module adopts an oxygen, carbon monoxide, hydrogen sulfide and combustible gas four-in-one sensor module and is carried by an operator; the camera monitoring module adopts a portable monitoring camera, videos can be stored and forwarded, and a limited space operation management and control process is migrated to an intelligent management and control platform for real-time online management; a 5G communication technology and a virtual reality (VR) technology are introduced into limited space operation safety management and control; defects of existing equipment are improved, for example, vital sign monitoring content of operating personnel is added, a UWB personnel positioning function is achieved, and video and sound of an operating site and various monitoring data are forwarded and stored in real time for future reference.

The invention discloses a fire-fighting detection early warning system, and relates to the technical field of fire-fighting early warning, and the system comprises a multi-source data obtaining module which comprises a gas monitoring unit, a smoke monitoring unit and a temperature obtaining unit, obtains the concentration of combustible gas, the granularity of smoke and the temperature data, carries out the preprocessing of the data, and integrates the data into a data set; the analysis and early warning module analyzes the data based on the data set, introduces a gradient compensation algorithm into the temperature acquisition unit, synchronously records the ambient temperatures of three different distances around, calculates a temperature gradient value, judges whether the temperature data exceeds the standard or not based on the gradient value, preliminarily obtains a judgment result from the temperature direction, and sends the judgment result to the early warning unit; and performing trend prediction on the multi-source data based on a time sequence analysis method. According to the method, the gradient compensation algorithm is introduced, the gradient value is calculated by using the three temperature monitoring points at different distances, local temperature anomaly can be accurately captured, the danger diffusion trend can be recognized earlier, local fluctuation and system risks can be distinguished, and time is won for early intervention.

The invention discloses a combustible gas remote monitoring management system and method based on Internet of Things and AI, and relates to the technical field of combustible gas monitoring. The system comprises a source heterogeneous sensing module, an edge AI reasoning module, a networking communication transmission module, an AI collaborative decision-making module and a judgment collaborative response module which run in sequence, and is technically characterized in that the AI collaborative decision-making module driven by a user behavior portrait is adopted in the scheme, and multi-dimensional characteristic factors are introduced, so that the dynamic sensing of abnormal gas consumption behaviors is realized, and the dynamic sensing of the abnormal gas consumption behaviors is realized; in addition, the understanding is completed by configuring an overrun protection item, it is ensured that sudden leakage and other situations are not missed to a certain extent, the defect that a traditional pure data driving model lacks interpretability and real-time performance is overcome, historical behavior contexts and real-time physical states are fused and bound, and collaborative optimization processing on safety and experience effects is completed.

The invention relates to the technical field of composite materials, in particular to a silicone rubber composition and a preparation method thereof. The silicone rubber composition is prepared from the following raw materials in parts by weight: 100 parts of methyl vinyl silicone rubber, 25-35 parts of white carbon black, 2.8-3.0 parts of hydroxyl silicone oil, 1.1-1.2 parts of hydrogen-containing silicone oil, 0.8-1 part of a cross-linking agent, 20-30 parts of an additive A, 6-8 parts of an additive B and 1.5 parts of a silane coupling agent KH-550. The additive in the additive A is carbonized and forms an intumescent flame-retardant system in the reaction under the combined action of mannitol and bamboo fiber, and generates a flame-retardant gas during decomposition, so that the fire resistance and flame retardance of the silicone rubber composition can be effectively improved, and meanwhile, the additive B is capable of effectively improving the flame retardance of the silicone rubber composition based on the loading of blumea oil and chitosan quaternary ammonium salt. The blumea oil endows the material with an anti-aging function through the good anti-oxidation characteristic, so that the thermal stability and durability of the silicone rubber composition are effectively improved under the combined action of the additives.

The invention discloses an explosion-proof coating as well as a preparation method and application thereof. The raw materials of the coating comprise a component A and a component B, and the mass ratio of the component A to the component B is (100: 100)-(100: 50); wherein the component A is prepared from the following components in parts by weight: 70 to 90 parts of epoxy resin, 3 to 8 parts of reactive diluent, 2 to 6 parts of silane coupling agent and 0.5 to 3 parts of fumed silica; and the component B comprises the following components in parts by weight: 30-60 parts of a nano reinforced curing agent, 5-30 parts of aluminum hydroxide, 8-15 parts of ammonium polyphosphate, 3-10 parts of expanded graphite, 3-8 parts of zinc phosphate, 3-12 parts of hollow glass beads, 3-15 parts of hexagonal boron nitride, 3-10 parts of silicon carbide whiskers, 2-5 parts of graphene dispersion liquid, 5-10 parts of a solvent, 0.2-1.5 parts of a dispersing agent and 0.1-1 part of a defoaming agent. The coating disclosed by the invention has the functions of toughening, flame retardance, heat conduction and non-combustible gas release, and can be applied to flame-retardant and explosion-proof products.

The invention discloses a control system of a device for drying metal powder containing combustible volatile substances, and belongs to the technical field of automatic control. In the system, a first subtracter generates a sequence first error signal according to the weight of two pieces of metal powder provided by a weighing sensor at an interval of a time step length; the second subtracter generates a sequence second error signal according to the actually measured temperature and the set temperature in the drying cavity provided by the temperature sensor; the reinforcement learning module respectively generates a first state and a second state according to the sequence first error signal and the sequence second error signal, and generates a control strategy of a PID controller for controlling the working state of the heater according to the first state and the second state; and the fire detection model estimates the probability value of the fire in the drying cavity according to the oxygen concentration in the drying cavity, the concentration of the volatile matter and the actually measured temperature, and if the probability value exceeds a threshold value, the stored inert gas is injected into the drying cavity to reduce the probability of the fire. The explosion risk caused by combustible gas accumulation is avoided.

The invention belongs to the field of hydrogen energy, and discloses a hydrogen recovery system and method for a hydrogenation mother station. The system comprises a hydrogen purification device, a product gas and recovery gas compressor, and an integrated pipeline network connecting feed gas, product gas, desorbed gas and a long pipe vehicle. According to the system, through a plurality of recovery paths, hydrogen which is not qualified in purification, desorbed gas and hydrogen replaced in the long pipe vehicle can be recovered to a fuel gas pipe network, a raw material gas inlet or a desorbed gas system respectively, and high-purity hydrogen can be used for carrying out online regeneration on a penetrating adsorbent. According to the invention, comprehensive recovery of the vented combustible gas in the hydrogenation mother station is realized, the hydrogen recovery rate is obviously improved, and the product gas quality and supply stability are ensured.

The invention discloses a flame-retardant PA66 material and a preparation method thereof.The flame-retardant PA66 material is prepared from, by weight, 80-100 parts of a modified PA66 material, 3-5 parts of modified graphene, 15-30 parts of a flame-retardant additive and 0.1-0.5 part of tetraphenylphosphorus bromide, a molecular chain of the flame-retardant additive contains an organic silicon chain segment and an organic phosphorus structure and is doped with nitrogen and boron elements, and when the material is burnt, the flame-retardant PA66 material has a flame-retardant effect, and the flame-retardant PA66 material has a flame-retardant effect. The organic phosphorus can be dehydrated to form a phosphoric acid carbon layer, the nitrogen element can release inert gas, dilute combustible gas and generate an expansive phosphorus-nitrogen carbon layer with the organic phosphorus, the boron element can improve the compactness and high-temperature stability of the carbon layer, and the organic silicon can form a cross-linked network shape, so that the continuity of the carbon layer is improved; a fluorine-containing polysiloxane chain segment of a side chain of the flame-retardant additive is embedded among molecules of the modified PA66 material, and is decomposed to generate fluorine free radicals during combustion, and active free radicals in a combustion chain reaction are quenched, so that a rapid flame-retardant effect is achieved.

This invention provides a silicon carbide porous combustion medium plate and a silicon carbide porous medium burner, relating to the field of porous medium combustion technology. The silicon carbide porous combustion medium plate has three-dimensional continuous pores, formed by a single or multiple triple-period minimal surface structures. The average curvature at each point on the triple-period minimal surface structure is zero, which can effectively reduce the concentration of thermal stress. The combustion medium plate prepared from silicon carbide slurry based on this structure has high compressive strength, which is beneficial to improving the service life of the silicon carbide porous combustion medium plate. The porous medium burner using this silicon carbide porous combustion medium plate utilizes its interconnected pores to promote uniform mixing of combustible gas and air. The combination of multiple triple-period minimal surface structures can specifically regulate the internal flow behavior of the mixed gas, thereby improving the thermal performance of the porous medium burner.

The embodiment of the invention provides a battery fire treatment method, device and equipment based on multi-modal data fusion, and relates to the technical field related to batteries. The method comprises the following steps: acquiring real-time multi-modal data acquired by a multi-modal sensor; the real-time multi-modal data at least comprises temperature, voltage, current, combustible gas concentration and sound wave data; according to the historical multi-modal database and the real-time multi-modal data, determining a comprehensive fault index through a dynamic weight model; the historical multi-modal database stores multi-modal data samples of each stage of thermal runaway development of the battery in the battery cell module in different fault modes, and the comprehensive fault index is used for indicating the fire risk degree; and outputting positioning information of the target area according to the comprehensive fault index and a preset spatial position mapping table, the preset spatial position mapping table is used for indicating a corresponding relation between the deployment position of the multi-modal sensor and the position of the target area. The method is used for achieving the effects of improving fire detection real-time performance and positioning precision and the like.

The invention belongs to the technical field of combustion science and chemical kinetics simulation, and provides a method for predicting the lower combustible limit of mixed combustible gas. The method comprises the following steps: firstly, constructing and verifying a laminar flame velocity mechanism covering a single component and multiple components and the applicability to multi-component fuel; secondly, on the basis that flame stretching and radiation effects are considered in a traditional model, a dynamic instability factor is further introduced, so that the prediction precision of the lower combustible limit of the low-Lewis-number combustible gas is improved; finally, a single-component data set is generated in a unified mode, multiple regression algorithms are adopted for training and comparison, a prediction model is determined in a preferential mode, the Lunchaterow principle is combined, generalization prediction of the multi-component combustible lower limit is achieved, and finally comparison verification is conducted with existing experimental data. According to the system and the method, the dependence on a large-scale training data set is remarkably reduced, the calculation efficiency is improved on the premise of ensuring the prediction precision, and the system and the method have obvious engineering application value and are particularly suitable for the safety-critical field.

The invention discloses a data analysis method, device and equipment of a combustible gas sensor and a readable storage medium, and relates to the technical field of data analysis. Comprising the following steps: analyzing the gas condition in a target building according to the data of a combustible gas sensor by establishing a space-time heterogeneous causal diagram skeleton in the target building, and further adjusting the gas condition in the building according to the real-time condition, thereby ensuring the gas use safety.

The utility model discloses a biomass fluidized bed gasification furnace heat supply coupling internal combustion engine power generation system. A biomass gasification furnace utilizes biomass raw materials to produce combustible gas; the internal combustion generator set generates power by taking combustible gas as a gas source, the working time of the internal combustion generator set is concentrated on the peak-flat section of the power grid electricity price, and the electric energy generated by the internal combustion generator set is supplied to the power grid; the biomass gas steam boiler receives combustible gas and burns the combustible gas to generate heat, steam heat energy generated by the biomass gas steam boiler is supplied to the user side, and the working time period of the biomass gas steam boiler is concentrated in the valley period of the power grid electricity price. Both the biomass gas steam boiler and the internal combustion generator set receive combustible gas produced by the biomass gasification furnace through gas pipelines, and the gas pipelines are provided with electric control valves for controlling the gas supply states of the internal combustion generator set and the biomass gas steam boiler. The comprehensive energy consumption cost can be reduced, the energy utilization efficiency is improved, and meanwhile, remarkable environmental benefits are achieved.