5837results about "Measurement apparatus components" patented technology

The invention relates to the technical field of abnormal monitoring of water-turbine generator sets, in particular to an abnormal monitoring system and method for a water-turbine generator set, and the system comprises a sensor module, an edge computing node, a cloud analysis platform and a scheduling decision center. The edge computing node performs data preprocessing, the cloud analysis platform realizes accurate early warning by applying technologies such as multi-source data fusion, a dynamic early warning model library and adaptive threshold adjustment, the scheduling decision center optimizes scheduling decisions through a resource matching engine and an emergency plan generation module, and the industrial communication network guarantees reliable transmission of data. In addition, the system is also provided with a visual interaction interface and a state evaluation report generation module. According to the invention, comprehensive and accurate monitoring and intelligent early warning of the water-turbine generator set are realized, the fault processing efficiency is effectively improved, the probability of false alarm and missing alarm is reduced, resource allocation is optimized, the operation safety is enhanced, and a powerful guarantee is provided for stable operation of the water-turbine generator set.

The invention discloses a bridge health prediction device based on a Beidou system and a monitoring analysis method, and relates to the field of bridge health monitoring. The method comprises the following steps: S1, deploying monitoring points at key structure nodes of a bridge, and collecting three-dimensional position information and multi-source data by using a Beidou system and a multi-type sensor; s2, constructing a time-varying displacement field and a continuous deformation tensor, fusing stress and strain to construct a structural fatigue factor, and introducing environmental disturbance to realize dynamic correction of the fatigue factor; s3, a health state function is constructed based on the stress response, the displacement gradient and the deformation tensor, a damage mapping function is constructed in combination with accumulated deformation and a historical threshold value, and a damage thermodynamic diagram is generated; and S4, finally fusing fatigue, health and damage indexes to evaluate bridge risks, and performing dynamic early warning. Through fusion of mechanical tensor features and environmental disturbance modeling, a multi-index linkage fatigue and damage assessment mechanism is constructed, and the precision, robustness and global perception ability of bridge health monitoring are improved.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The invention provides a non-contact optical fiber sensing system and method, the system comprises a passive optical fiber grating sensor and an active demodulation analyzer, the passive optical fiber grating sensor comprises an optical fiber and an optical fiber grating sensor serially connected to the optical fiber, and the active demodulation analyzer comprises a laser light source, an optical circulator and a demodulation analyzer; one end of the passive fiber grating sensor is connected with a first fiber collimator; the active demodulation analyzer further comprises a second optical fiber collimator and an alignment mechanism; the laser light source is connected with the first end of the optical circulator and used for outputting optical signals. An optical fiber is led out from the second end of the optical circulator and is connected with a second optical fiber collimator; the second optical fiber collimator is used for being aligned with the first optical fiber collimator in a non-contact manner under the adjustment of the alignment mechanism so as to transmit optical signals bidirectionally; and the demodulation analyzer is connected with the third end of the optical circulator. The application scene of the optical fiber sensing system can be expanded, and the cost is saved.

The invention relates to a high-precision data acquisition method and system for an MEMS sensor, and the method comprises the following steps: carrying out the multi-channel parallel sampling of an initial electric signal outputted by the MEMS sensor, and obtaining an original data flow matrix; performing adaptive denoising processing on the original data stream matrix to obtain a denoised data set; performing signal phase reconstruction on the noise reduction data set through a phase unwrapping technology to obtain a continuous phase feature sequence; performing dynamic drift compensation on the continuous phase feature sequence to obtain a calibration signal vector; performing transient characteristic extraction on the calibration signal vector to obtain a sensor response characteristic curve; and performing high-precision data resampling on the sensor response characteristic curve based on an adaptive quantization coding technology to obtain a high-precision data acquisition result, thereby solving the technical problem of how to effectively remove noise interference generated in a multi-channel parallel sampling process.

The invention discloses an equipment health state dynamic prediction method fusing digital twinning and multi-scale evaluation, and relates to the technical field of equipment health prediction of an active launching platform, and the method comprises the steps: laying multiple types of sensors on a mechanical structure layer, a hydraulic execution layer, an electric control layer and an environmental action layer of the active launching platform; multi-source operation data such as stress strain, pressure torque, temperature power and environment load are collected in real time, and a standardized input parameter set is formed; and constructing a multi-layer digital twinborn model, forming a multi-scale twinborn mapping matrix, calculating a healthy coupling evolution coefficient, and evaluating the stability of the multi-layer collaborative structure of the platform. Calculating a multi-scale stability coefficient, and updating the multi-scale twin mapping matrix; and calculating a dynamic prediction driving index to realize prediction reliability judgment and digital twin model self-learning updating. And a health prediction closed loop of digital twinning and physical equipment is realized.

The invention relates to a shear-based acceleration and pressure composite sensor and an assembly method thereof, and belongs to the field of composite sensors. According to the technical scheme of the acceleration and pressure composite sensor based on the shear type structure, an acceleration detection module comprises a mass block of a regular polygon prism structure, and each side face of the mass block is provided with an acceleration sensitive ceramic piece; the pressure detection module comprises a force transmission column of a regular polygon prism structure, and each side face of the force transmission column is provided with a pressure sensitive ceramic piece, an electrode piece and an insulation block. According to the scheme, the sensitive elements of the acceleration sensor and the pressure sensor core are arranged in a polygonal mode to form a spatial three-dimensional structure, the effective area of the sensitive elements in unit volume is increased, the multiple sensitive elements act together to form superposition of pressure signals, the detection precision and sensitivity of the two are guaranteed, and the detection precision is improved. Therefore, the overall size of the composite sensor is greatly reduced on the premise that the original precision is maintained, and the composite sensor is miniaturized.

The present invention relates to the technical field of bridge structure monitoring, and specifically to a bridge disease monitoring method based on an inspection robot, comprising: obtaining a BIM model of a bridge, collecting GIS data of a location of the bridge and establishing associations with elements in the BIM model, and integrating the BIM model and the GIS data into a BIM+GIS fusion model; configuring a sensor and a communication module in the inspection robot, building a Web platform and establishing a communication connection with the inspection robot; when the inspection robot inspects the bridge, real-time data is collected through sensors, and the collected bridge structure data and position data of the inspection robot are sent to the Web platform; the Web platform receives and parses the position data, searches for a component corresponding to the position data in the BIM+GIS fusion model according to the position data, and maps the real-time position of the inspection robot to the corresponding component, thereby realizing accurate positioning and dynamic visualization of the position of the inspection robot.

The invention provides an adjustment method of detection equipment, and the detection equipment sequentially comprises an objective lens, a spectroscope, a barrel lens and a detector from an object space to an image space, and also comprises a Kohler illumination module. The illumination light beam is emitted from the Kohler illumination module and is transmitted to the objective lens through the spectroscope, when the object to be detected is arranged on one side, far away from the spectroscope, of the objective lens, the illumination light beam emitted from the objective lens is reflected to obtain a reflected light beam, and the reflected light beam sequentially passes through the objective lens, the spectroscope and the barrel lens to reach the detector. After an aperture diaphragm is inserted into the Kohler illumination module and an auxiliary lens is arranged between the barrel lens and the detector, obtaining a first light spot position of a light spot formed by the aperture diaphragm at an entrance pupil of the objective lens through the detector; and under the condition that the Kohler illumination module does not provide the illumination light beam and the light source is used as an object to be detected, acquiring a second light spot position of the light spot of the entrance pupil of the objective lens through the detector, adjusting the position of the aperture diaphragm according to the first light spot position and the second light spot position, and aligning the illumination optical axis and the imaging optical axis.

The invention discloses a double-rocker-arm derrick monitoring system based on multi-sensor data fusion, and particularly relates to the field of monitoring, which comprises a sensor module, a data preprocessing module, a data fusion analysis module, a state evaluation module and a visual terminal module, parameters of the double-rocker-arm derrick are monitored in real time through the sensor array, multi-source data synchronization and feature extraction are achieved in combination with the data preprocessing module, multi-modal data fusion is conducted through the improved D-S evidence theory, and the structure health index, the risk level and the fault probability are output; the state evaluation module generates three-level early warning signals based on a dynamic threshold model, historical data is compressed and stored and supports cloud synchronization, and the visual terminal renders a three-dimensional digital twinborn model through Unity 3D, dynamically displays postures, deformation fields and environmental factors, provides an interactive evaluation report and AR early warning annotation, and realizes whole-process real-time monitoring and intelligent decision support.

A sensor assembly includes a carrier plate, a mounting plate, and a sensor on or over the mounting plate. The assembly can additionally include two ball studs attaching the mounting plate to the carrier plate, the ball studs defining a first axis passing through center points of the ball studs. A first adjustable screw can be positioned to tilt the mounting plate about the first axis, and a second adjustable screw can be positioned to rotate the mounting plate about a vertically oriented second axis, in which the second axis is spaced from the ball studs.

The invention relates to the technical field of air permeability testing devices, in particular to a non-woven fabric air permeability detecting device which comprises a bottom plate, a lower barrel fixedly connected to the bottom plate in a suspended mode and an upper barrel arranged above the lower barrel, an opening of the upper barrel and an opening of the lower barrel are oppositely arranged, a liftable bearing disc is arranged in the lower barrel, a vertical plate is fixedly connected to one side of the bottom plate, and the vertical plate is fixedly connected to the other side of the bottom plate. A C-shaped lifting frame is slidably connected to the vertical plate, a first linear module used for driving the lifting frame to ascend and descend is installed on the vertical plate, the upper portion of the lifting frame is fixedly connected with the upper barrel, and the lower portion of the lifting frame slidably penetrates through the side wall of the lower barrel and is fixedly connected with the bearing disc. Through cooperation of the rotating ring, the curved guide rail and the linkage mechanism, the multiple clamps synchronously move in the radial direction, multidirectional uniform drawing force can be applied when the cloth is clamped, the tension is monitored in real time in combination with the tension sensor, the stretching amount is accurately adjusted, and air permeability detection of the cloth under different stretching degrees is achieved.

The invention discloses a visual sand storage tank reserve accurate monitoring method and system based on multi-dimensional sensing fusion, and the method comprises the following steps: installing a sensor at a key position of a sand storage tank, collecting the multi-dimensional data of the sand storage tank in real time, and carrying out the preprocessing of the collected multi-dimensional data; according to the method, pressure, height, form and humidity data of a sand body are acquired through cooperation of multiple sensors such as pressure, ultrasonic, laser radar and humidity sensors, a dynamic data fusion algorithm and partition mechanical modeling are combined, and reserves trend prediction is realized by using LSTM (Long Short Term Memory); a three-dimensional digital twinborn model is constructed, sand body distribution and flow states are dynamically displayed by color / transparency, a multi-level early warning mechanism is established in combination with multi-dimensional parameters, and meanwhile, a block chain evidence storage technology is introduced to perform uplink evidence storage on key data to ensure that the data cannot be tampered and operation is traceable.

The invention provides a decoupling and Kalman filtering temperature strain demodulation method and system for double fiber gratings, and relates to the technical field of optical fiber sensing. The method comprises the following steps: firstly, designing an FBG sensing module for measuring environment temperature change and strain information; the FBG sensing module comprises a two-channel sensing system composed of an FBG1 sensor and an FBG2 sensor, and is used for measuring environment temperature change and strain information at the same time. Then, aiming at optical signals which are acquired by the two FBG sensors and contain physical quantity information, a wavelength demodulation module is used for acquiring the central wavelength drift distance of reflection spectrums of the two FBG sensors; temperature sensitivity coefficients and strain sensitivity coefficients of the two FBG sensors are obtained, and a linear equation set is constructed for independent variation of temperature and strain to perform matrix decoupling so as to distinguish the influence of the temperature and the strain on the change of the central wavelength; and performing optimization estimation on the decoupled temperature and strain by using the prior information of the temperature and the strain and combining a real-time measurement value by adopting a Kalman filtering method.

The invention relates to the technical field of photovoltaic power station installation monitoring, in particular to a photovoltaic power station installation process real-time measurement and calibration system which comprises an installation data acquisition module, a positioning calibration module, an environment compensation module, an installation error analysis module and a dynamic adjustment module. Wherein the data acquisition module is used for acquiring three-dimensional coordinate data, inclination angle data and environmental parameters of the photovoltaic module; the positioning calibration module is used for constructing a component space topology network; the environment compensation module is used for outputting an environment compensation coefficient to correct the initial calibration parameter; and the installation error analysis module is used for calculating the three-dimensional coordinate deviation value and the inclination angle deviation value of each component. According to the invention, the three-dimensional coordinates and inclination angle data of the photovoltaic module are measured in real time, the installation error is corrected in combination with environmental compensation, and an automatic adjustment mechanism is utilized to drive the adjustment mechanism to accurately calibrate the position and angle of the module, so that the installation precision of the photovoltaic power station is improved, and the adaptability of the system to environmental change is enhanced.

The invention provides an oil and gas pipeline monitoring system based on a distributed optical fiber technology. The oil and gas pipeline monitoring system can monitor the strain and the internal pressure of a pipeline at the same time. The distributed monitoring of the axial strain of the pipeline and the quasi-distributed monitoring of the internal pressure are realized by laying the accompanying strain optical fiber beside the pipeline and winding and fixing the optical fiber in the circumferential direction of the pipeline at intervals. The system utilizes the BOTDA or BOTDR host to demodulate the data measured by the optical fiber and transmits the data to the local or cloud computer for processing, so that the pipeline axial strain and the area with large pressure change in the pipeline can be effectively monitored, and the system is used for providing corresponding early warning information. According to the method, the optical fiber originally used for strain monitoring can also be used for pressure monitoring, and the effect that one fiber has multiple purposes is achieved. The system is simple in design, easy to implement and suitable for real-time monitoring and maintenance management of large-scale oil and gas pipelines.

The invention relates to the technical field of inspection robots, and particularly discloses an underground pipe gallery environment detection system and method based on an inspection robot, and the system comprises a robot inspection system, a data transmission system, a monitoring system, an alarm system, and an artificial auxiliary inspection system. The robot inspection system comprises a pipeline, a charging storage bin, a controller, a carrying mechanism, a ground moving mechanism and an external detection mechanism. The carrying mechanism is arranged outside the charging storage bin; the ground moving mechanism is arranged outside the carrying mechanism; and the external detection mechanism is detachably placed outside the pipeline. Mobile inspection can be quickly and automatically carried out in the pipe gallery, inspection personnel are prevented from directly entering a dangerous environment, data are remotely analyzed in real time, early warning is carried out in time when fault hidden dangers are found, detection operation can be carried out along an external area of a pipeline and a ground area, and comprehensive state information of the pipe gallery is obtained at a time; and the time cost of multiple times of detection is reduced.

The invention relates to an intelligent soft rock tunnel surrounding rock deformation automatic monitoring and early warning system, and belongs to the field of tunnel construction safety monitoring. According to the system, multi-source data of surrounding rocks are synchronously acquired through a micron-sized laser displacement sensor, a fiber grating strain sensor, a pore water pressure sensor and a three-dimensional micro-seismic sensor array which are distributed; the edge calculation node fuses the data in real time and calculates the displacement rate, the strain gradient and the osmotic pressure coupling coefficient, and local early warning is triggered in combination with a dynamic threshold value; the cloud early warning platform predicts a deformation trend based on an LSTM-Transform fusion model, generates a multi-stage early warning signal through a risk grading engine, and is linked with the supporting equipment to regulate and control pressure; and meanwhile, a self-calibration device, an explosion-proof shell and a piezoelectric-thermal energy self-powered system are integrated. According to the method, closed-loop control from millimeter-level deformation sensing to active supporting can be achieved, and tunnel construction safety is remarkably improved.

The invention relates to the technical field of stainless steel welded pipe solid solution, in particular to stainless steel welded pipe online bright solid solution equipment which comprises a base, a motor A is fixedly connected to one end of the base, a reciprocating lead screw is connected to the output end of the motor A, a first support is arranged on the outer side of the reciprocating lead screw, and a movable ring is connected to the interior of the first support. And a bevel gear is arranged on one side of the movable ring, and a gear A is arranged on one side of the bevel gear. After the stainless steel pipe is polished, the stainless steel pipe can gradually move along with movement of the first support, meanwhile, air can be released upwards after entering the interior of the spray head, and therefore the outer wall of the polished stainless steel pipe is cleaned; and meanwhile, after welding is completed, the spray head can cool the welded position at the same time, and the grinding roller can grind the welded position, so that the welded position is smoother, and the stress generated by welding is also reduced.

The invention discloses a handheld integrated itinerant detector and an itinerant detection method thereof. The itinerant detector comprises a multi-source sensing unit and a magnetic attraction positioning module, the inspection method comprises the following steps: establishing a multi-dimensional calibration parameter of a target device, adsorbing on the surface of the target device based on a magnetic attraction positioning module, loading a spatial layout, and generating an environment calibration model; synchronously operating the far / close distance temperature measurement module and the vibration sensing module, and outputting multi-source fusion data; performing dynamic correlation analysis, analyzing vibration spectrum energy distribution by using a feature extraction algorithm, constructing a vibration-temperature coupling feature vector in combination with temperature gradient change, inputting a fault diagnosis result of a pre-trained fault diagnosis model, generating a visual early warning map, and feeding back the early warning map in real time through an interactive interface; according to the method, the limitation of single parameter monitoring is overcome, the detection precision is remarkably improved, and a real-time, rapid and accurate fault detection result is provided through self-adaptive switching of a temperature measurement mode and a multi-frequency-band vibration acquisition strategy.

To provide an information collection device and a battery pack which improve the sealing performance of a signal collection device.SOLUTION: The present disclosure relates to the field of battery technologies, and provides an information collection device and a battery pack. The information collection device includes a casing, an air pressure sensor, and a sealing member. The casing has a first installation hole. The air pressure sensor is installed inside the casing, and at least a part of the air pressure sensor is snap-fitted into the first installation hole to acquire an air pressure parameter outside the casing. The sealing member seals the first installation hole, and the sealing member is used to allow gas to pass through and prevent liquid from passing through. Thereby, the information collection device can be arranged in a battery cell, and can collect information in an environment of electrolyte, thus capable of mitigating the technical problems of complex structure and insufficient reliability of a cover plate of the battery cell caused by external arrangement of the information collection device.SELECTED DRAWING: Figure 1

The invention discloses a porcelain insulator defect detection system and a detection method thereof, and relates to the technical field of porcelain insulator defect detection. According to the porcelain insulator defect detection method, the mechanical strength, the electrical performance, the vibration response and the temperature response data of the porcelain insulator are obtained, all the data are comprehensively analyzed, all the defect evaluation indexes are obtained and compared with the preset defect evaluation interval, and defect marking processing is carried out. According to the invention, through comprehensive analysis of measurement data of mechanical strength, electrical performance, vibration response and temperature response, the health condition of the porcelain insulator can be evaluated more accurately, and compared with a traditional single detection method, the multi-dimensional evaluation can identify more types of defects, so that the detection accuracy is improved. According to the method, potential faults caused by tiny physical damage, electrical performance abnormity and temperature change are eliminated, and through comparative analysis of multiple indexes, the possibility of misjudgment and missed judgment is reduced, so that the detection process is more refined, and long-term stable operation of the porcelain insulator in a complex environment is guaranteed.

The invention provides a workpiece carrying table and semiconductor detection equipment. The workpiece carrying table comprises a lifting assembly, a jacking assembly, a reversing assembly and a driving mechanism. The lifting assembly comprises a lifting inclined face and a bearing face which are opposite in the height direction of the workpiece carrying table. A jacking inclined plane is arranged at the bottom of the jacking assembly, a supporting column is arranged at the top of the jacking assembly, and the inclined plane where the jacking inclined plane is located intersects with the inclined plane where the lifting inclined plane is located; the reversing assembly is in sliding fit with the lifting assembly and the jacking assembly. The driving mechanism comprises a transmission part and a linear driving part, the transmission part abuts against the lifting inclined face and the jacking inclined face, the linear driving part is connected with the transmission part, and the driving direction of the linear driving part intersects with the guiding direction of the reversing assembly. The lifting assembly and the jacking assembly share one driving mechanism, the structure is simple, transmission is smooth, and accurate cooperative operation of the lifting assembly and the jacking assembly can be achieved.

A sensor mounting assembly is configured for use with a vessel arrangement including at least four vessels. The assembly includes first and second elongated frame members, first and second rollers, and first and second sensors. The first sensor is attached to the first elongated frame member and is configured to contact the surface of the first vessel upon actuation in a first direction. The second sensor is attached to the second elongated frame member and is configured to contact the surface of the second vessel upon actuation in a second direction that is substantially orthogonal to the first direction. This disclosure also describes a method of mounting at least six sensors for use with a vessel arrangement including at least four vessels, the vessel arrangement disposed in a container in a two-by-two stacked configuration having a central space.

The invention relates to the technical field of channel environment monitoring, and discloses a channel environment safety monitoring and early warning method and system based on multi-sensor fusion, which align visible light video, infrared thermal imaging, gas and vibration sensor data through space-time reference to ensure isomerous data synchronism and space consistency. Modal exclusive time sequence feature extraction is carried out, and unique space-time mode information is mined. A context sensing mechanism is introduced, key information such as an operation and maintenance plan is intelligently extracted in combination with a current environment state, dynamic weighting and deep fusion are performed on multi-sensor time sequence features through an attention fusion mechanism, and the importance of different sensor features is adaptively adjusted. And finally, inputting the fused channel environment state into a feedforward neural network model, and outputting an event probability and a risk score. Therefore, safety monitoring accuracy and reliability are remarkably improved, false alarms are reduced, potential safety hazards are recognized in advance, quantitative decision basis is provided, and continuous and safe operation of a channel environment is guaranteed.

The invention discloses a real-time monitoring device based on intelligent agriculture in the technical field of agricultural Internet of Things, comprising a stand column, a connecting block is fixedly mounted below one side surface of the stand column, a sliding groove is formed in one side surface of the connecting block, and a screw rod is vertically and rotatably connected to the inner side of the sliding groove; the top end of the lead screw extends to the position above the outer end of the connecting block, the surface of the lead screw is in threaded connection with a connecting rod in a sleeving mode, the connecting rod is arranged in the sliding groove in a sliding mode, a soil parameter sensor module is fixedly installed at the end of the connecting rod, and the bottom of the soil parameter sensor module is sequentially connected with a humidity probe, a temperature probe and an EC value probe. A main control box is fixedly installed on one side of the stand column, an air temperature and humidity sensor is fixedly installed on the outer side surface of the main control box, the monitoring device can obtain three-dimensional data of soil, air environment and crop growth at the same time, and therefore precise agricultural decision can be better supported.

The invention discloses an intelligent safety monitoring method, system and device for an offshore wind plant and a medium, and relates to the technical field of safety monitoring, and the method comprises the steps: deploying a plurality of different monitoring modular units in the offshore wind plant, and building a safety monitoring model; monitoring data acquired by each monitoring modular unit is transmitted to a preset central control terminal to form an intelligent safety monitoring platform, and the monitoring modular units execute data acquisition based on a received remote configuration parameter instruction; the intelligent safety monitoring platform supports analysis and calculation processing of monitoring data and outputs a safety monitoring result; in the safety monitoring model, a plurality of key performance indexes are defined for the monitoring modular unit based on the project unit identifier and a preset monitoring standard demand, and if a certain key performance index exceeds a corresponding data change threshold, a safety early warning instruction is triggered; the offshore wind plant safety monitoring method is more intelligent and efficient, and the monitoring level of the offshore wind plant is improved.

The invention relates to the technical field of evaluation and real-time optimization systems, and discloses a deep fluidized mining dynamic disaster prevention and control effect intelligent evaluation and real-time optimization system which comprises a data acquisition module used for acquiring monitoring data in real time through a multi-source sensor network arranged in a stope, a fluidized medium and surrounding rock, and an intelligent analysis module used for analyzing the monitoring data in real time. And the construction module is used for constructing a comprehensive evaluation index system comprising a statics index, a dynamics index and a stability index based on the monitoring data. The intelligent evaluation and real-time optimization system for the dynamic disaster prevention and control effect of deep fluidized mining breaks through the limitation of traditional single index evaluation, constructs a comprehensive evaluation index system covering statics, dynamics and stability by integrating stress, microseismic, acoustic emission, displacement and other multi-source sensor networks, and improves the dynamic disaster prevention and control effect of deep fluidized mining. A deep learning model is used for carrying out fusion analysis on mass heterogeneous data, and multi-dimensional precursor information of disaster inoculation can be disclosed.