334 results about "Underground cavern" patented technology

The invention provides an underground cavern surrounding rock parameter collaborative sensing method and system based on multi-source data fusion, and the method comprises the steps: firstly deploying a sensor group comprising an optical fiber strain sensor, a micro-seismic monitoring array, a three-dimensional laser scanner and an acoustic emission sensor, the optical fiber strain sensor is arranged along the axis of a cavern, the micro-seismic monitoring array is deployed according to a triangular network, and the three-dimensional laser scanner is arranged along the axis of the cavern; performing time synchronization on the sensor group through a synchronization pulse signal, establishing a local coordinate system at a central point of a cavern entrance, uniformly collecting data, generating a time-aligned data stream and a space-unified data set, and triggering associated sensors to enter a hierarchical response collection mode according to a strain rate and a vibration signal; and generating a multi-modal monitoring data set, finally carrying out dynamic weight distribution and conflict resolution processing on the multi-modal monitoring data set, extracting surrounding rock deformation characteristics and fracture event density, and outputting a surrounding rock stability evaluation result, thereby realizing underground cavern surrounding rock parameter collaborative perception and stability evaluation.

The invention relates to the technical field of rock mechanics, and discloses a rock three-dimensional reconstruction method and system based on multi-source information fusion, and the method comprises the steps: obtaining and preprocessing data, carrying out the spatial feature learning of a fusion feature vector through a 3D-CNN network, and constructing a three-dimensional voxel model of rock microscopic damage; converting the fused image data into a point cloud model of the underground cavern surrounding rock structure by adopting a three-dimensional reconstruction algorithm based on point cloud, and constructing a digital twin framework of the underground cavern surrounding rock structure based on an implicit surface reconstruction algorithm; feature parameters output by the three-dimensional voxel model and the digital twinning framework are used as input, and the optimal supporting opportunity and supporting parameters are output through an LSTM-CNN fusion model; in the underground engineering construction process, surrounding rock deformation data are collected in real time, and a supporting scheme is adjusted in real time through a depth deterministic strategy gradient algorithm; according to the method, the scientificity and timeliness of support design under complex geological conditions can be improved.

The invention provides an underground cavern construction method generation method and system based on multi-source data fusion, and the method comprises the steps: collecting geological exploration, construction machinery operation and environment monitoring data, carrying out the time-space alignment processing, generating a standardized monitoring data set, carrying out the multi-source feature extraction of the standardized monitoring data set, and carrying out the multi-source feature extraction of the standardized monitoring data set; obtaining a construction state feature set and a geological risk feature set, inputting a reinforcement learning model for multi-target parameter optimization to obtain a preliminary construction method parameter set, inputting the preliminary construction method parameter set into a digital twin simulation system for simulating mechanical response, and iteratively optimizing parameters when a preset safety threshold is exceeded to obtain a preliminary construction method parameter set; the optimized construction method parameter set is matched and verified with a preset construction specification knowledge base, manual correction is carried out when illegal items exist, finally, full-period risk prediction is carried out on the corrected construction method parameter set, dynamic regulation and control are carried out according to a construction risk distribution map, a final construction method instruction set is generated, and scientific and intelligent construction method generation is achieved.

The invention relates to the technical field of route planning, in particular to an underground cavern inspection method and system. The method comprises the following steps: acquiring geological survey data, micro-seismic monitoring data and historical deformation monitoring data; according to the geological survey data and the micro-seismic monitoring data, rock mass viscoelasticity local modeling is carried out, and a rock mass viscoelasticity model is obtained; performing deformation trend prediction according to the rock mass viscoelastic model and the historical deformation monitoring data to obtain deformation trend data; performing deformation disturbance resonance analysis according to the deformation trend data and the micro-seismic monitoring data to obtain deformation disturbance resonance data; performing risk area grading on the deformation disturbance resonance data to obtain risk area grading data; and generating a routing inspection graph according to the risk area grading data to obtain routing inspection graph data so as to carry out underground cavern routing inspection auxiliary operation. The method accurately identifies the potential risk area, dynamically plans the inspection task, and improves the inspection efficiency and decision timeliness.

The invention provides an intelligent safety and stability assessment method, system and device for an underground cavern and a medium, and the method comprises the following steps: S1, building a three-dimensional geological model of the underground cavern according to initial geological exploration data; s2, multiple monitoring instruments are pre-buried in key parts of the underground cavern, and monitoring data are collected in real time; s3, constructing an underground cavern safety and stability evaluation model based on a deep learning algorithm; s4, inputting real-time monitoring data into an evaluation model, combining historical monitoring data and geological model information, analyzing and comparing with a three-dimensional numerical calculation result, adjusting geological parameters, performing reconstruction evaluation, and outputting a safety and stability level; and S5, according to an evaluation result, automatically generating early warning information and processing suggestions. According to the method, the problems of poor real-time performance and low data utilization rate of traditional evaluation under complex geological conditions are solved, and the intelligent level of construction safety monitoring of underground cavern groups such as hydropower stations and pumped storage projects can be effectively improved.

The invention provides a blast suppression method and system for an underground cavity of a pumped storage power station. The method comprises the following steps: configuring and deploying a multispectral gas sensor array; carrying out gas explosion limit calculation and risk assessment; calculating the risk level of explosion by using the prediction model; performing graded explosion suppression operation by using a graded explosion suppression execution module; combustible gas is guided to enter an inerting area by utilizing a space flow guide optimization module; and the ignition source blocking module is used for cooperative control to block an ignition source. The technical problems of low mixed gas explosion risk prediction and monitoring precision, low explosion suppression efficiency, slow response speed and relatively high operation and maintenance cost are solved.

The invention relates to the technical field of underground cavern construction, and discloses a layered rock mass cavern excavation parameter dynamic optimization decision system and method, and the system comprises a rock stratum database building module, an excavation simulation module and an excavation model optimization module. The method comprises the following steps: collecting basic data such as engineering geological conditions, rock mechanical properties and ground stress distribution; establishing an initial rock stratum parameter database through a three-dimensional ground stress test and rock mass permeability characteristic analysis; establishing a stratified rock mass excavation simulation model, simulating a failure mode of a stratified rock stratum under excavation disturbance, and analyzing stress redistribution and a potential failure area; determining a cavern axis direction, an excavation sequence and support parameters according to a simulation result; acquiring surrounding rock deformation, loosening circle expansion and seepage characteristic change; and utilizing a damage proximity index to predict the distribution of the loose circles, and optimizing the stratified rock mass excavation simulation model. The method can adapt to various complex working conditions from a sand shale interbed to an ultra-deep fractured stratum and the like.

The invention relates to the technical field of underground cavern surrounding rock displacement prediction, in particular to a high-stress large underground cavern group surrounding rock displacement prediction method. According to the technical scheme, the method comprises the following steps that data collection and arrangement are carried out, and various types of sensors are arranged at different parts of a high-stress large underground cavern group to collect data; the method comprises the following steps: performing preliminary screening, cleaning and normalization processing on collected data, performing feature engineering and data enhancement work, including time-frequency domain feature extraction, wavelet transform-based data decomposition and reconstruction and a data enhancement strategy, and constructing a hybrid neural network model fusing a convolutional neural network and a gating circulation unit. Through multi-source accurate data acquisition and processing, depth feature engineering, hybrid neural network construction training and scientific evaluation and early warning, the accuracy, reliability and timeliness of high-stress large underground cavern group surrounding rock displacement prediction are remarkably improved, powerful support is provided for engineering safety guarantee, and risks and losses are effectively reduced.

The invention provides an underground cavern three-dimensional modeling method and system based on dynamic parameterization node regulation, and the method comprises the steps: firstly obtaining a multi-source sensing data set which covers section contour point cloud, geological environment and real-time monitoring data, generating an initial section contour curve based on the section contour point cloud data, obtaining a dynamically adjusted curve and node regulation and control parameters through dynamic parameterization node regulation and control, and generating a stretching path reference line according to the cavern axis coordinate parameters; the adjusted section profile curve is axially stretched to generate a three-dimensional cavern curved surface containing a local three-dimensional curved surface set, finally, section stitching is conducted on the local three-dimensional curved surface set, a connection area topological structure is generated according to joint direction parameters and optimized, and therefore an optimized three-dimensional cavern model is generated. Therefore, more accurate and flexible underground cavern three-dimensional modeling is realized.

The invention discloses a preparation method of a green high-performance industrial solid waste-based grouting material, and belongs to the field of industrial solid waste treatment and grouting reinforcement, and the preparation method comprises the following steps: performing dry mixing on red mud, slag, fly ash and cement which are dried and ground to specified fineness according to a preset proportion to obtain a uniform dry material; preparing a composite alkali activator from water glass and sodium hydroxide according to a molar ratio of 3: 1, premixing the composite alkali activator with water, and adding the dry material in batches to form wet slurry; and carrying out high-speed shearing and stirring on the wet slurry, and standing and curing to obtain the solid waste-based slurry which can be directly used for grouting. The method obviously improves the solid waste utilization rate, relieves the environmental pressure, and is suitable for related projects such as stratum settlement control, gushing water blocking, mine roadway broken rock mass supporting and underground cavity concrete lining crack repairing in tunnel and subway projects.

A rock mass cavern seismic dynamic stability analysis method considering layer vibration degradation comprises the following steps: determining transverse isotropic elastic mechanical behaviors, strength criteria and plastic potential functions of a layered rock mass, and constructing an elastic-plastic degradation constitutive model of the layered rock mass; determining a stratified rock mass layer surface strength parameter calculation formula under the earthquake action, determining a stratified rock mass rock mass strength parameter calculation formula, and establishing a stratified rock mass strength parameter evolution rule considering the layer surface vibration degradation effect; defining a layer damage degree index, and constructing a layered rock mass damage degree evaluation index under the earthquake action; and calculating the earthquake stability safety degree coefficient of the rock mass underground cavern, and determining the earthquake stability safety degree interval of the rock mass underground cavern. According to the method, the layer vibration degradation effect is considered, the safety evaluation result is more accurate, the application range is wide, the principle is simple, the physical significance is clear, the earthquake stability of the rock mass underground cavity is effectively analyzed, and the method has good practical engineering application prospects.

The invention provides a potential safety hazard analysis method and system based on underground cavern three-dimensional geological intelligent modeling, and the method comprises the steps: firstly, based on underground cavern three-dimensional model data, cutting the underground cavern three-dimensional model data into a plurality of sub-models according to a geological condition segmentation rule, and enabling the geological condition segmentation rule to dynamically adjust the cutting spacing according to the gradient change characteristics of a rock stratum; performing gradient analysis on the longitudinal and axial rock stratum attributes of each sub-model to generate rock stratum transition characteristic data containing the adjacent rock stratum attribute change rate and the transition area space distribution, and dynamically identifying the surrounding rock type of the sub-model according to the rock stratum transition characteristic data; and mapping and matching the surrounding rock identification result with a preset protected object space coordinate, collecting a sub-model geological parameter set in real time, finally triggering a safety early warning signal according to a geological parameter set numerical value interval, and generating an emergency disposal scheme set associated with the safety early warning signal, so that the potential safety hazard of the underground cavern can be effectively analyzed.

The invention relates to the field of pumped storage power station engineering, in particular to an efficient ventilation, waste dissipation and cooling system and method for an underground cavern group, and the system comprises a distributed environment sensing network, a partitioned ventilation execution unit, a partitioned cooling execution unit and a control unit. The prediction model is adopted to predict the future environment or load change trend, and the system coordination control model evaluates the influence of a control instruction on the overall state of the system; by comprehensively considering a real-time measured value, a future predicted value and an evaluation result of a system coordination control model and considering multiple targets of an environment index and operation energy efficiency, an optimization control instruction capable of cooperatively regulating and controlling each partition execution unit is determined and executed.

The invention provides a surrounding rock stability dynamic analysis method and system in the excavation process of an underground cavern group. The method comprises the steps that original surrounding rock monitoring data of the underground cavern group are collected at the self-adaptive sampling frequency through a distributed optical fiber sensor; performing real-time filtering, abnormal value primary screening and data compression processing on the original surrounding rock monitoring data to obtain target surrounding rock monitoring data; performing feature extraction on the target surrounding rock monitoring data to obtain a feature vector corresponding to the target surrounding rock monitoring data; and inputting the feature vector into a pre-constructed surrounding rock stability evaluation model for evaluation to obtain the stability level of the surrounding rock. Therefore, data redundancy can be prevented, key information omission is avoided, and the reliability of a surrounding rock stability evaluation result is improved.

The invention discloses an underground cavern harmful gas diffusion prediction simulation method based on a generative adversarial network, relates to the technical field of underground engineering safety monitoring, and provides the following scheme: acquiring three-dimensional point cloud spatial data, geological exploration data and real-time gas concentration monitoring values of an underground cavern, and unifying the three-dimensional point cloud spatial data, the geological exploration data and the real-time gas concentration monitoring values to an initial coordinate system; and extracting permeability parameters of the geological exploration data for discrete grading, associating a grading result to the space coordinates, and outputting permeability grading codes. According to the method, three-dimensional point cloud space data is converted into an obstacle distribution density function field, isovolumetric grid units are divided through a volume compensation algorithm in a dynamic deformation coordinate system, permeability grading code difference values, obstacle distribution density difference values and node concentration gradient differences of adjacent units are fused to construct a weighted edge, and the weighted edge is calculated. And a high-precision diffusion resistance topological structure diagram is generated, and the local resistance quantitative modeling problem caused by micro-scale concave-convex obstacles and permeability abrupt change is solved.

The invention discloses an underground cave depot slurry diffusion and solidification state space-time identification method and system, and belongs to the technical field of underground cave depot grouting, and the method comprises the steps: taking an on-site grouting influence region as a monitoring region, and detecting the apparent resistivity of the monitoring region at different grouting stages in real time in a cave depot grouting process; drawing visual cloud charts of the apparent resistivity of the monitoring areas at different grouting stages; and based on the visual nephograms of the apparent resistivity of the monitoring areas at different grouting stages and in combination with a preset grout solidification degree judgment criterion, judging the grout diffusion range, the grout solidification degree, the grout solidification time and the grouting water plugging effect. According to the scheme, the slurry diffusion range, the solidification degree, the solidification time and the grouting water plugging effect in the cave depot grouting process can be intelligently and accurately judged, so that monitoring of the grouting process and improvement of the grouting effect are achieved, the grouting precision and efficiency are improved, and the grouting cost is reduced.

The application provides a kind of stability discrimination method of underground gas storage cavern initial support of compressed air energy storage power station, the method comprises: considering the expansion force and softening of hydrophilic surrounding rock of underground gas storage cavern, draw the response curve of surrounding rock in humidification process;Obtain the supporting parameters of underground gas storage cavern, calculate and draw the characteristic curve of supporting structure;The intersection point of the response curve of surrounding rock and the characteristic curve of supporting structure is determined, and the coordinate of the intersection point is obtained according to the coordinate of the intersection point, and the equilibrium supporting force of hydrophilic surrounding rock and supporting balance is obtained according to the coordinate of the intersection point;According to the safety factor of underground gas storage cavern, the stability of the cavern is judged according to the safety factor.The application fully considers the expansion force, softening and supporting force effect of surrounding rock in the relationship between surrounding rock and support, and uses safety factor as the stability index of underground gas storage cavern, which is suitable for the stability evaluation of underground cavern with complex surrounding rock characteristics, and the discrimination method is accurate and efficient.

The invention relates to the technical field of tunnel engineering construction, and discloses an intelligent control system and method for tunnel blasting smoke exhaust, and the system comprises a spraying subsystem, a multi-sensor detection module, and a remote control terminal with a display. The spraying subsystem comprises a plurality of nozzles and a booster water pump; the remote control terminal with a display receives information of the multi-sensor detection module and controls the booster water pump; a remote control terminal with a display displays data detected by the multi-sensor detection module; the multi-sensor detection module comprises a smoke sensor, a sound sensor, a vibration sensor and an air quality detector; the device is applied to tunnels or underground cavern groups, especially environments with poor ventilation and need of continuous blasting construction, dust in air can be effectively reduced, dust generated by blasting cannot affect operation construction after being subjected to multi-channel atomization spraying, meanwhile, spraying water resources can be effectively saved, good economic benefits and social benefits are achieved, and the device is worthy of popularization and application. And popularization and use are facilitated.

The application discloses the technical field of image data processing, and provides a method, device and equipment for risk assessment of an underground cavern and a medium, which comprises the following steps: adopting a geometric segmentation algorithm to process point cloud data of a target cavern acquired in advance, combining a plane fitting technology, identifying a structural surface and extracting structural surface parameters; constructing a geological topology model according to the structural surface parameters, identifying key blocks of the geological topology model based on a preset block identification standard, and randomly disturbing the structural surface parameters to obtain multiple groups of sample parameters; determining the instability probability of each key block based on the sample parameters, performing risk assessment on the key blocks based on the instability probability, and obtaining a risk assessment result of the underground cavern. The application significantly improves the timeliness and efficiency of risk identification of underground engineering, and effectively solves the problems of accurate identification of a structural surface and risk quantization under complex geological conditions.

The invention relates to a large underground cavern group crustal stress field inversion method under a complex geological condition, and provides a method for inversing a crustal stress field of a large underground cavern group by taking a river valley center line or a ridge line as an inversion numerical model boundary to solve the problems that underground cavern group crustal stress measured data is discrete and difficult to accurately predict under the background of deep river valley terrain and multi-fault development. And selecting actual measurement points which are far away from the fault and are in three-dimensional distribution. The method comprises the following steps: acquiring a displacement boundary and a gravitational acceleration magnitude of a three-dimensional numerical model through limited measured data by adopting stepwise multiple linear regression and evolutionary neural network joint inversion, positively loading the displacement boundary and the gravitational acceleration magnitude to a model boundary to obtain a regional crustal stress field, and extracting measured point data for preliminary verification; and simulating caving excavation, and analyzing whether the stress concentration area is consistent with the observed stress type damage position or not. The method integrates the advantages of the two methods, more optimal solutions can be selected, the problem that precision and calculated amount are difficult to consider in stress field prediction of the complex structure motion area is solved, and the method is suitable for crustal stress field prediction of the complex structure area.

The invention discloses a compressed air energy storage cavern fatigue life prediction method and system and storage equipment, and belongs to the technical field of compressed air energy storage. The method comprises the following steps: preprocessing compressed air storage hole data to be analyzed to obtain a sample data set; and inputting the sample data set into a pre-trained prediction model of the key parameters of the gas storage cavern structure, performing analysis to obtain an analysis result, and predicting the fatigue life of the cavern structure of the compressed air storage cavern according to the analysis result. The method can accurately predict the fatigue life of the compressed air energy storage cavern, discover potential safety and efficiency problems in advance, effectively reduce the fatigue damage risk of long-term operation of the underground cavern, and guarantee the stability of a power grid.

The invention provides an underground cavern intelligent construction sequencing optimization method and system, and the method comprises the steps: firstly integrating geological parameters, construction machinery parameters and historical construction cases to construct a construction method database, and then determining a layering height parameter set through a dynamic matching algorithm according to the spatial topological relation between geomechanical indexes and a three-dimensional geological model in the database, according to construction machinery and layering height parameters, a transverse partition and axial partition parameter set is generated by using an octree space subdivision algorithm, then composite coding is performed based on multiple attributes of the three-dimensional geologic model and the parameters, and a unique construction block coding set is generated; and finally, performing construction sequence optimization on the code set by using a multi-objective optimization algorithm to generate a Pareto optimal solution set containing construction period, cost and stability optimization paths, and dynamically adjusting construction sequence parameters in the solution set according to surrounding rock deformation data to realize intelligent construction sequencing optimization of the underground cavern.

The invention provides a nonlinear finite element discrimination method for a critical stable section of an underground cavern, and the method comprises the steps: determining a rock mass strain softening parameter according to a rock mass mechanical test in actual engineering; performing secondary development on a rock mass constitutive model based on the rock mass strain softening parameters; based on the rock mass constitutive model after secondary development, a nonlinear finite element initial model for solving the critical stable section of the underground cavern is constructed; the nonlinear finite element model is solved, and the overall tangent rigidity of the model in the calculation time step is obtained; based on the overall tangent stiffness, calculating to obtain a minimum characteristic value of an overall tangent stiffness matrix; and based on the minimum characteristic value, distinguishing the critical stable section of the underground cavern. The method directly and quantitatively reflects the essential characteristics of rigidity loss and bearing capacity reduction of the whole cavern structure system after a complex nonlinear deformation path including strain softening is considered, so that the critical instability moment and the potential instability section are accurately captured.

The invention relates to the technical field of stratified rock mass numerical simulation, and discloses a stratified rock mass numerical simulation method based on a hybrid progressive failure model, and the method comprises the steps: obtaining an engineering rock mass structural plane of a research area, and grading geological structural planes such as faults, rock veins and fractures of surrounding rock of an underground cavity based on structural plane features; through three-dimensional laser scanning, obtaining the spatial three-dimensional coordinates of each sampling point on the surface of the footrill, obtaining the point cloud of a measured object, and connecting adjacent discrete points; carrying out secondary sampling on the spliced point cloud data, carrying out plane fitting to obtain a structural plane occurrence, and constructing a footrill simulation model; analyzing the occurrence of the structural surface by the footrill simulation model to obtain a stratified rock mass value, and dividing the structural surface in the rock mass into a rigid structural surface and a weak structural surface according to the character, weathering degree, tightness degree and filler condition; and outputting the data to a cloud platform. According to the invention, manual intervention is reduced, and the safety, accuracy and efficiency of measurement are improved.

The invention relates to the technical field of robot navigation, in particular to a precise inspection method for an underground cavity and an inspection robot. The method comprises the following steps: acquiring spatial point cloud data, robot pose data and scene magnetic field data, and constructing a magnetic field model according to the scene magnetic field data to obtain a scene magnetic field model; obtaining interference characteristic data according to the scene magnetic field model and the spatial point cloud data; obtaining magnetic disturbance weight data according to the disturbance characteristic data and the robot pose data; performing fusion filtering on the spatial point cloud data and the robot pose data according to the magnetic disturbance weight data to obtain navigation optimization data; performing residual analysis on the spatial point cloud data and the robot pose data according to the navigation optimization data to obtain residual trend data; and performing dynamic compensation according to the residual trend data to obtain space optimization point cloud data and robot optimization pose data. The anti-interference capability and the environmental adaptability of the inspection robot are improved.

The invention discloses a compressed air energy storage underground cavern temperature adjusting structure and a manufacturing method thereof, and belongs to the technical field of compressed air energy storage, the temperature adjusting structure is sequentially provided with a flexible sealing layer, a phase change temperature adjusting layer and an optical fiber sensing layer from inside to outside, the optical fiber sensing layer is connected with the inner wall of a concrete lining, and the phase change temperature adjusting layer is used for stabilizing temperature fluctuation in a cavern; the optical fiber sensing layer is used for monitoring temperature and a strain field in real time and is electrically connected with an external fiber grating sensor grid monitoring system through a sensor lead. According to the method, latent heat can be absorbed or released through the phase change process, temperature fluctuation in the cavern can be effectively stabilized, material fatigue and structural damage caused by thermal stress circulation are reduced, real-time monitoring of the temperature and strain of the sealing layer is achieved, and the sensing capacity and the early warning level of the operation state of the cavern are improved.

The utility model provides a fabricated decoration structure of an underground cavity. The fabricated decoration structure comprises a metal decoration plate wall surface, a metal decoration plate suspended ceiling and a waterproof layer, waterproof layers are laid on the top and the side portion of the cavern rock wall; a metal decorative plate wall surface is mounted on the outer side of the waterproof layer on the side part in an assembled manner; a metal decorative plate suspended ceiling is installed below the waterproof layer on the top in an assembly mode; decorative plates of the metal decorative plate wall surface and the metal decorative plate suspended ceiling are curved decorative plates formed by splicing small blocks. The utility model has the following advantages: 1, the wall surface and the top arch adopt a plurality of spliced small curved surface decorative plates, so that the mounting efficiency of the curved surface decorative plates can be improved, and the curved surface decorative plates are prevented from deforming; in the construction process, the position of the curved-surface decorative plate can be flexibly adjusted, and the curved-surface decorative plate has the advantages of being convenient to construct and efficient to disassemble and assemble, so that the use requirement is met. 2, the fabricated decoration structure greatly improves the decoration work efficiency, ensures the decoration quality, is green and environment-friendly, and can be widely applied to decoration projects such as suspended ceilings and wall surfaces;

The invention belongs to the technical field of pumped storage power station intelligent data processing, and discloses a pumped storage power station data processing method and system based on a space-time knowledge graph. The 5G Internet of Things dynamic data, the BIM + GIS static data and the construction log semi-static data are deeply associated with a millisecond-level timestamp based on a national 2000 geodetic coordinate system; in an underground cavern excavation scene, real-time displacement monitoring data can be synchronously matched with BIM component deformation simulation, the problem of monitoring-simulation asynchronization is solved, obvious lag does not exist in progress deviation early warning any more, the management and control delay risk caused by data splitting is effectively avoided, and the dynamic safety of underground cavern group construction is guaranteed; in a data acquisition stage, a data standard is directly embedded into a source through a standard semantic pre-labeling module, and unified semantic tags such as unique component identifiers and process codes are preset for various types of data.

The invention discloses a rail installation method of underground cavern top arch hoisting equipment, which comprises the following steps of: S1, designing a rail layout scheme, and measuring and paying off on an underground cavern top arch; s2, fixing assemblies are installed, the multiple fixing assemblies are arranged along the center line of the track at intervals, each fixing assembly is composed of a pair of anchoring parts and a bearing part connected with the anchoring parts, the tops of the anchoring parts are anchored into the cavern top arch rock mass, and the bearing parts are fixedly connected with the exposed sections of the bottoms of the two anchoring parts; and S3, the rails are welded to the bearing pieces of all the fixing assemblies, and rail installation is completed. The rail installation method of the underground cavern top arch lifting equipment is convenient to construct, safe, reliable, low in investment cost and suitable for the situation that rail fixing embedded parts cannot be pre-embedded due to the fact that an underground cavern top arch is not provided with a reinforced concrete lining, and the operation requirement of the lifting equipment can be met.

The invention discloses a construction scheme multi-modal multi-objective optimization method considering carbon emission. The method comprises the following steps: establishing an underground cavern group construction simulation model shared by construction resources; based on the underground cavern group construction simulation model shared by the construction resources, establishing a target function by taking the minimum average value of the construction period, the cost and the carbon emission as a target, and establishing an underground cavern group construction scheme optimization mathematical model comprising a plurality of optimization targets of the construction period, the cost and the carbon emission; and adopting a star-graffiti optimization algorithm to improve a filial generation process of the hierarchical ordering evolutionary algorithm, and using the special crowding degree distance to select an optimal solution of the underground cavern group construction scheme optimization mathematical model. According to the optimization method of the multi-mode multi-target cooperation mode, the optimization method can be suitable for the underground cavern group construction scheme optimization problem with the high-dimensional characteristic, efficient search of the high-dimensional optimization problem is achieved, and overall and local optimal solutions of the problem are obtained comprehensively.