181results about How to "Verify accuracy" patented technology

The invention relates to a gradient aggregation federated learning method based on combination of zero knowledge proof and a block chain technology, and belongs to the field of distributed machine learning. Through combination of zero knowledge proof (zk-SNARK) and an extensible block chain technology, limitations of a traditional method in aspects of data privacy protection and model verification are broken through. According to the method, the correctness of a global model is verified by using zero-knowledge proof, the transparency and data privacy of an aggregation process are ensured, the Chinese remainder theorem is introduced to compress the proof, and the storage burden of block chain nodes is reduced. And the hash value updated by the encryption model is recorded through the block chain, verification is carried out based on a block chain consensus node, and the data integrity and the system transparency are further improved. Besides, a dynamic client selection mechanism is introduced in the method, participants are optimized based on training performance scores, and the training efficiency and the model quality are improved. As a whole, the invention provides a safe, efficient and transparent distributed learning solution.

A CFD (computational fluid dynamics)-based wind turbine generator load simulation method under a high slope comprises the following steps: step 1, acquiring topographic data and position information of the high slope: acquiring the topographic data and position information of the high slope through a multi-source data acquisition means; step 2, constructing a high slope simplified physical model according to the high slope topographic data and the machine position information; 3, a CFD tool is used for flow field numerical simulation calculation, and according to the constructed high slope simplified physical model, the CFD tool is used for obtaining the wind speed distribution and turbulence intensity distribution conditions of the whole wind wheel face of the wind turbine generator; step 4, generating a target wind seed file by using a TurbSim tool; 5, establishing a high slope wind file library; step 6, calculating the dynamic response of the whole machine; and obtaining an accurate load result of the wind turbine generator under the high slope terrain. The accuracy of the simulation result is improved, and the safety, the power generation efficiency and the service life of the wind turbine generator are improved.

The invention provides a mine monitoring and early warning system and method based on microseismic data acquisition, and particularly relates to the technical field of mine early warning, and the mine monitoring and early warning system based on microseismic data acquisition mainly comprises an earth surface monitoring assembly, an internal monitoring assembly and a control assembly, surface data information, environment data information, positioning data information, strain information and micro-seismic information can be collected in real time, three-dimensional visualization of real-time changes of a mine is achieved, mine safety comprehensive evaluation indexes are obtained in real time according to the strain information and the micro-seismic information, comprehensive judgment is conducted by combining the strain information and the micro-seismic information, and the safety of the mine is improved. According to the invention, all-around monitoring coverage from the ground to the underground is realized, the monitoring capability of the whole condition of a mine is improved, the real-time combination of mine surface monitoring and rock stratum monitoring is effectively realized, the comprehensive evaluation index of mine safety is comprehensively judged, and the monitoring efficiency, timeliness and accuracy of coal mine safety are improved.

The invention belongs to the field of safety and stability analysis of tailing dams, and discloses a tailing dam stability analysis method based on a GCN-AGRU fusion model and a related device, and the method comprises the steps: obtaining the monitoring data of a multi-source heterogeneous sensor of a tailing dam; preprocessing the monitoring data to obtain multi-source heterogeneous time series data; performing feature analysis on the multi-source heterogeneous time series data to obtain key factors of the stable state of the tailing dam; constructing a heterogeneous hierarchical causal graph by using the key factors; determining a key factor stable state index system according to the heterogeneous hierarchy causal diagram; a multi-source GCN-AGRU fusion space-time prediction model is utilized to obtain space information of the state of the tailing dam; performing time correlation modeling on the multi-source heterogeneous time sequence data to obtain a time sequence of the state of the tailing dam; calculating a predicted value of the multi-source heterogeneous sensor according to the spatial information and the time sequence; and determining the stability state trend of the tailing dam according to the predicted value in combination with a key factor stability state index system. The intelligent sensing of the situation of the tailing dam can be realized.

The invention discloses a biological material mechanical testing method and system based on finite element analysis, and is used for the technical field of data processing method.The biological material mechanical testing method comprises the following steps that a three-dimensional geometric model of a biological material is constructed, the three-dimensional geometric model of the biological material is imported into finite element analysis software, and the finite element analysis software is used for analyzing the three-dimensional geometric model of the biological material; grid division is executed, and material attributes and boundary conditions are set; finite element simulation is operated according to the set material attributes and boundary conditions, stress and strain distribution is analyzed, and grid division and the material attributes are adjusted based on the analysis result; and the adjusted grid division and material attributes are simulated again, a simulation result is verified through experimental data, and meanwhile material composition is adjusted based on the simulation result and a verification result. According to the method, each step can be completed according to preset time and quality standards, and deep understanding of the simulation process and prevention of potential problems are enhanced.

The invention provides a PDF drawing key information extraction method and system, and belongs to the technical field of information. The method comprises the steps of obtaining an execution process of a current task and detailed text description of a current construction process, and extracting keywords by utilizing a TextRank algorithm; searching in a metadata tag of a drawing library by utilizing the keyword, and quickly screening out a drawing file highly related to the current construction process; for the screened PDF drawing file, converting image characters in the PDF into editable text information by adopting an OCR (Optical Character Recognition) technology, and preprocessing the text information; key parameters are extracted from the preprocessed text according to predefined parameter extraction rules, and reasonability analysis is carried out. Through the automatic information extraction process, the key parameters matched with the current project execution process are rapidly and accurately extracted from a large number of PDF drawings, and the information processing efficiency is greatly improved. And strict rationality analysis is carried out on key parameter information, so that the accuracy and reliability of information extraction are further ensured.

The invention discloses a breakable crop stalk discrete element simulation model construction method, which comprises the following steps: firstly, measuring the actual feature size of a crop stalk, and layering the internal structure of the crop stalk based on a microstructure; then performing an experiment to obtain intrinsic parameters and contact parameters of the stalks, constructing a multi-layer geometry three-dimensional model according to measurement characteristics, filling each layer of the geometry three-dimensional model with different types of particles, establishing an initial discrete element simulation model, introducing a contact model, and constructing an initial breakable discrete element simulation model; and finally, adjusting the mesoscopic parameters of the simulation model according to the actually measured data until the mesoscopic parameters are kept consistent. According to the method, the contact model is introduced, different structural layers are filled with particles with different material attributes, the biological characteristics and mechanical characteristics of multiple layers of real stalks from outside to inside are restored, and errors are smaller when mechanical behaviors are simulated.

The invention relates to the technical field of data processing evaluation, in particular to a water ecological health evaluation method based on fish environment DNA experiment big data. The method comprises the following steps: acquiring a water sample in a target area; filtering the water sample in the target area to generate water sample filtering data; performing water centrifugation on the target area water sample to generate water centrifugation data; performing fish environment DNA extraction on the target area water sample based on the water sample filtering data and the water body centrifugation data to obtain area fish environment DNA data; performing target DNA fragment determination on the regional fish environment DNA data to obtain target DNA fragment information; through a data processing technology, a high-throughput sequencing technology and a machine learning algorithm, flow parameter water level correlation analysis is carried out on a specific water body area, and index determination is carried out in combination with a fish community structure, so that the accuracy of water ecological health assessment is improved.

The invention discloses a remote sensing image change detection method based on fine tuning CLIP, and the method comprises the steps: obtaining an original dual-time remote sensing image, and carrying out the preprocessing of the remote sensing image; constructing an initial remote sensing image change detection model, and training the initial remote sensing image change detection model by using the training set to obtain a target remote sensing image change detection model; and performing change detection on the remote sensing image by using the target remote sensing image change detection model. According to the method, a large model CLIP pre-trained in a large-scale data set is introduced into a change detection task, and the method aims at guiding the model to pay attention to universal features of changing ground features, so that the generalization ability of the model is improved; according to the method, the CLIP is finely adjusted by adopting a visual prompt method, so that the CLIP can be well migrated in a remote sensing downstream task; in addition, when a loss function is constructed, Dice coefficient loss is introduced to enhance the sensitivity of the model to a positive example.

The invention provides a transformer magnetic core loss calculation method and system considering a variable loss coefficient, and the method comprises the steps: considering the influence of a high-frequency skin effect and a dynamic hysteresis loop on the iron core loss, and building a variable coefficient loss calculation formula; substituting the normalization constant into an integral form of an average value of the magnetic induction intensity in a period to obtain an equivalent frequency expression; and obtaining a generalized Steinmetz waveform coefficient formula under non-sine excitation based on the equivalent frequency expression and the variable coefficient loss calculation formula, and calculating the magnetic core loss of the nanocrystalline high-frequency transformer based on the formula.

The invention belongs to the field of miRNA detection, and particularly relates to a non-diagnostic-purpose miRNA detection method based on dual cascade amplification of a Pt nanoprobe and a kit. Comprising the following steps: 1) obtaining a Pt NPs (at) Ab nanoprobe; (2) carrying out an ISAR-CRISPR / Cas12a reaction; and (3) dripping on a nucleic acid test strip for capillary action, adding a quenching substrate into the T line for catalysis after the chromatographic reaction is finished, and judging the concentration of miRNA by observing the T line. According to the invention, a Pt nanoprobe is introduced as a fluorescence quenching probe, and after TMB is dropwise added, double-amplification cascade fluorescence quenching is generated. Due to the adoption of a double-amplification cascade fluorescence quenching strategy, the fluorescence quenching efficiency can be greatly improved, so that an ultra-low background fluorescence signal is ensured. The method has a good application prospect, can be used as a general detection method for detecting a specific nucleic acid target, and is widely applied to the fields of nucleic acid detection and the like.

The invention discloses a method for simulating sediment erosion around an offshore wind turbine foundation by combining ISPH with a modified k-epsilon turbulence model. The method comprises the following steps: establishing an ISPH discrete algorithm for solving an average mass conservation equation and a momentum conservation equation of a fluid dynamic ensemble; correcting the standard k-epsilon turbulence model, and calculating the turbulence vortex viscosity vt in the Reynolds stress tensor expression; a critical starting theory on a slope is introduced, a traditional two-dimensional sediment starting model is corrected and expanded, and a three-dimensional sediment starting model is established; establishing a local scouring experiment water tank model of the offshore wind turbine single pile foundation; establishing a corresponding ISPH numerical water tank model; the experimental water tank model and the numerical water tank model respectively simulate the characteristics of the scouring process of sediment around the cylinder, and a numerical simulation result and an experimental result are compared, verified and analyzed. By means of the method, the sediment erosion process around the offshore wind turbine single-pile foundation can be well simulated, the calculation time is short, and the requirements of actual engineering can be met.

The invention relates to the technical field of data processing and prediction, in particular to a large hydrological model construction method integrating multi-source fusion and dynamic optimization. The method comprises the following steps: acquiring hydrological monitoring data; performing data preprocessing on the hydrological monitoring data to obtain standard hydrological monitoring data; performing multi-dimensional feature recognition on the standard hydrological monitoring data to obtain multi-dimensional hydrological feature data; and carrying out runoff feature extraction on the multi-dimensional hydrological feature data to obtain hydrological runoff feature data. According to the invention, through a data processing technology, a mode identification technology, a geographic information system technology and a deep learning technology, seasonal change influence evaluation is carried out on hydrological monitoring data; and the hydrological monitoring model is dynamically optimized according to the hydrological geographic position information and the hydrological change evaluation data, so that the response speed of the hydrological monitoring model is higher, and the precision of a prediction result is higher.

The invention relates to the technical field of tire simulation design, in particular to a tire pattern longitudinal groove edge optimization design method and system and a computer program product. The method comprises the following steps: extracting actual grounding pressure data of a tire; establishing a pattern block geometric plane model, and applying proper boundary conditions; according to the condition of non-uniform grounding pressure distribution, the shape of the contact surface of the pattern block is adjusted to realize uniform distribution; the grounding pressure distribution of the edge of the pattern block is optimized by minimizing a grounding pressure skewness value; and finally, calculating and adjusting the outer contour curve of the tire to realize final optimization design. According to the method, the road holding force, the controllability and the driving stability of the tire can be remarkably improved, the service life is prolonged, the modeling and calculation time is relatively low, and the design and development cost is remarkably reduced.

The embodiment of the invention provides a verification method and device of a chip encryption module, electronic equipment and a storage medium. The method comprises the steps of obtaining random input data; determining a first calculation result according to the random input data and the DUT to be detected, and determining a random detection result corresponding to the random input data according to the random input data and a preset detection model; according to the random detection result and the first calculation result, determining a first verification result corresponding to the DUT to be detected, generating random input data to ensure that the verification process has wide coverage under various inputs and multiple modes, and respectively inputting the random input data into the DUT to be detected and a preset detection model to ensure that the verification process has wide coverage under various input and multiple modes. The first calculation result and the random detection result are obtained and compared, then the verification result is obtained, and the reliability and comprehensiveness of function verification are improved by using a large amount of random excitation and randomly setting register configuration of the AES.

The invention discloses a natural disaster risk relieving method and device for a power system, and the method comprises the steps: constructing an hour-level composite cascade event set generation module which is used for generating hour-level data sets in various natural disaster scenes, capturing the cascade effects of different disasters, and generating a data set; data support is provided for power system risk influence quantification and risk mitigation module strategy generation; a distributed resource evaluation module is constructed and used for evaluating the availability and power generation potential of distributed resources in the third-level region, and the power generation potential of the distributed resources in various natural disaster periods is analyzed in combination with weather and disaster factors; a natural disaster influence module is constructed, the influence of various natural disasters on the power system is simulated based on the hour-level composite cascade event set, the damage degree of the disasters on loads, power generation facilities, power transmission and distribution lines and the like is analyzed, and the risk influence on the power system is quantified; and constructing a risk relief module, for an area with risk influence, formulating a disaster emergency scheme based on a three-level cooperation mechanism, and based on the power generation potential of the distributed resource assessment module, by scheduling various distributed resources, repairing the power grid, adjusting the load and reducing the disaster influence, ensuring rapid recovery and stable operation of the power grid.

The invention relates to the technical field of computational fluid mechanics, in particular to a method for calculating the blocking effect of an underwater vehicle towing tank, and the method comprises the steps: building an underwater vehicle physical model; defining each boundary condition of the CFD numerical calculation domain, and solving the total resistance and each resistance component of the underwater vehicle based on the calculation domain grid and the configured numerical calculation condition; and post-processing the total resistance and each resistance component to obtain a calculation numerical result of the underwater vehicle under different blocking ratio working conditions. According to the method, by verifying the independence of the grids, the appropriate number of the grids is determined, and the calculation precision and efficiency are guaranteed.

The invention discloses a path optimization method based on a memristor bidirectional coupling fractional order network model. The method comprises the following steps: step 1, determining a fractional order derivative expression by adopting a Caputo definition; 2, constructing a fractional order Hopfield neural network model, and determining a hyperbolic tangent memristor in the fractional order Hopfield neural network model; step 3, determining a coupled hyperbolic tangent memristor; and step 4, based on a specific TSP problem, obtaining an optimal solution through a fractional order Hopfield neural network model, and completing path planning. The invention belongs to the technical field of neural network application, and solves the problem that an integer order Hopfield neural network (HNN) model in the prior art is insufficient in precision when solving complex problems. Two hyperbolic tangent memristors are used for coupling two neurons to simulate a synaptic crosstalk phenomenon, and the coupling strategy is expanded to a fractional order system, so that dynamic behaviors of the model are greatly enriched, and more complex and diversified dynamic characteristics are shown.

The invention belongs to the technical field of automobile transverse stabilizer bars, and relates to a static and fatigue performance research method of a transverse stabilizer bar, a finite element model of the transverse stabilizer bar is established, and the accuracy of stress and roll stiffness calculation of a numerical model under a vertical load working condition is verified through mechanical theoretical calculation and a stiffness bench test. Static strength analysis is carried out on the transverse stabilizer bar assembly under the combined load working condition; on the basis, a road load spectrum is combined with a part rack fatigue test and a virtual simulation technology, and the fatigue life of the transverse stabilizer bar is researched.

The invention discloses a method and system for verifying a broadband impedance characteristic model of a wind turbine generator, and belongs to the technical field of new energy power generation. The method comprises the steps that a simulation working condition is set, under the set simulation working condition, a to-be-verified wind turbine generator broadband impedance characteristic model is used for model simulation operation, and disturbance is injected in the model simulation operation process; collecting model simulation data in a model simulation operation process, extracting a disturbance component from the model simulation data, and calculating an impedance value based on the disturbance component; and based on the impedance value, verifying the accuracy of the broadband impedance characteristic model of the wind turbine generator to be verified. According to the method, the accuracy of the wind turbine generator model can be effectively verified through model simulation, so that the accuracy of new energy grid-connected stability analysis is improved, and the technical progress and safe and rapid development of the industry are promoted.

The invention relates to the technical field of video anomaly detection, and comprises a detection method based on multi-target tracking, and the method comprises the steps: employing a target detection and target tracking algorithm to carry out the precise detection and tracking of a vehicle in video data; according to the detection method based on the weak supervision video, vehicle abnormal behavior detection based on a video abnormal detection algorithm is adopted; according to the track classification-based detection method, a motion track-based detection algorithm is adopted to realize detection of vehicles with abnormal tracks in a monitoring video, and dichotomy of motion tracks of all vehicles in the monitoring video is realized through the track anomaly-based detection algorithm. Through combination of multiple detection modes, target detection tracking and lane line detection are combined to realize detection of vehicle positions and motion states, a two-stage network is provided, and accurate detection of abnormal events of highway vehicles is realized.

The invention discloses a battery SOC prediction method fusing online identification and an adaptive algorithm, relates to the technical field of power battery monitoring, and aims to solve the problem of insufficient SOC prediction precision of an electric vehicle power battery under a dynamic working condition. The prediction method comprises the steps of obtaining lithium battery charging and discharging experiment data, establishing a dual-polarization equivalent circuit model to simulate a strong nonlinear behavior in the battery, and fitting an OCV-SOC curve based on the experiment data; performing online parameter identification on the equivalent circuit model by using a forgetting factor recursive least square method based on grid search-real-time voltage difference improvement; sOC prediction is carried out by combining online parameter identification with a self-adaptive expansion Kalman filtering algorithm; and the proposed prediction algorithm is verified under a mixed pulse power characteristic test working condition. According to the method, the accuracy and the real-time performance of SOC prediction are remarkably improved, and the method has a wide application prospect.

A ceramic matrix composite micro-hole drilling quality and material removal mechanism analysis method comprises the following steps: determining a damage model and performance parameters of carbon fibers, a damage model and performance parameters of a SiC matrix, and a damage model and material attributes of an interface layer according to ceramic matrix composite micro-holes with the diameter phi of 0.5-2mm; a drill bit model and a ceramic matrix composite macroscopic model are established in simulation software, macroscopic finite element simulation is carried out, and a macroscopic finite element simulation result is obtained; a drill bit model and a ceramic matrix composite microscopic model are established in simulation software, microscopic finite element simulation is carried out, and a microscopic finite element simulation result is obtained. Carrying out a drilling test to obtain a test result; and comparing the test result, the macroscopic finite element simulation result and the microscopic finite element simulation result, and verifying the effectiveness of the macroscopic finite element simulation result and the microscopic finite element simulation result.

The invention relates to the field of medical instruments, in particular to a detection system for assisting accurate positioning of chest lesions, which comprises a data acquisition module for acquiring preoperative CT image data; the three-dimensional reconstruction module is used for converting into a three-dimensional model; the coordinate construction module is used for establishing a unified virtual coordinate system and determining key positioning points; the virtual cutting module is used for simulating different paths and angles to perform pathological section on the three-dimensional model; the image tracking module is used for capturing image data in the body of the patient in real time during an operation and fusing the image data with the three-dimensional model based on the key positioning points; the image processing module is used for carrying out image acquisition and processing on the pathological section; and the space verification module is used for carrying out space position matching on the image data and the three-dimensional model and calculating the similarity between the image and the corresponding region and the overlap ratio index of the lesion position. The objective of the invention is to realize accurate spatial position correspondence between the lesion area in the preoperative CT image and the actual resection pathological section in the operation.

The invention belongs to the technical field of cable harness manufacturing, and discloses a visual auxiliary manufacturing platform and method for cable assembly, and the platform comprises a station operation platform, a small RFID tool cabinet, a large RFID tool cabinet, a station terminal, a secondary central control terminal, and a code scanner. The station operation platforms are provided with workbenches for cable assembly, the secondary central control terminal is connected with the station terminals of the plurality of station operation platforms, each station terminal comprises a display and a host, and the displays provide input, management and display of tools, tasks and parts for operators; the secondary central control terminal provides a dispatch task for the station terminal, and monitors the use of tools, the progress of the task and the consumption of parts through the station terminal; the ID is used for acquiring information of tools and parts; the large RFID tool cabinet is commonly used by a plurality of station operation platforms. A digital technical means and an intensive production mode are adopted, automatic and informationized technological equipment is fused, the technological content of aviation cable manufacturing is improved, and human influence factors are reduced.

The invention discloses a transformer winding strength detection method based on a short circuit test, and the method comprises the following steps: S1, determining winding wire cake parameters according to a transformer parameter table, and obtaining the size of a transformer single cake, the size of a supporting strip, and the size of a cushion block; and S2, according to the size of the single cake obtained in the step S1, ignoring a supporting strip and a cushion block, uniformly distributing the compression height of the winding to each oil duct, constructing a two-dimensional cake-by-cake model, applying single short-circuit impact current excitation to the two-dimensional cake-by-cake model, and carrying out coupled electromagnetic-structure field calculation to obtain displacement deformation distribution of each wire cake. The boundary constraint effect of the supporting strips and the cushion blocks is considered in the three-dimensional single-line cake model, and the stress condition of the winding under short-circuit impact can be simulated more accurately. The simulation analysis considering the boundary constraint can more truly reflect the deformation and stress distribution of the winding under the short-circuit impact, and provides more reliable data support for evaluating the winding strength.

The embodiment of the invention provides a data query method, system and device, and the method comprises the steps: analyzing a grouping operator, an aggregation operator, a sorting operator and a filtering operator in a first query statement, accurately recognizing key elements in a query operation, including a field of a grouping basis, a field and type of an aggregation operation, a field of a sorting basis and an arrangement sequence, according to the method, the key elements in the query operation and the fields and specific conditions related to the filtering conditions are obtained, and the interface containing the detailed key elements in the query operation and the query result is displayed after the query result is obtained based on the key elements in the query operation, so that a user can intuitively see the whole process of the query operation, including specific details of grouping, aggregation, sorting and filtering, and the user experience is improved. Therefore, whether the query result meets own requirements can be verified more easily. The visual query feedback mechanism not only enables the user to clearly see the query result, but also can deeply understand the query process, so that the accuracy of the query result is effectively verified, and the efficiency and accuracy of data query are improved.

A CPT magnetometer sensitivity improving method based on magnetic field modulation in geomagnetic prospecting comprises the following steps: performing half-wave modulation on laser generated by a laser by using an EOM to obtain multicolor laser, and weakening the light intensity and changing the polarization state of the laser through a light intensity adjusting device; meanwhile, sine wave modulation is applied to the magnetic field where the air chamber is located, a lock-in amplifier is used for demodulating optical signals through sine wave modulation signals to obtain corresponding dispersion signals, and the size of the magnetic field to be measured in geomagnetic prospecting is further obtained. The sensitivity of the magnetometer modulated by the magnetic field is close to the sensitivity obtained by the traditional laser light source modulation method, but the magnetic field modulation method gets rid of the difficulty of too high requirement on the laser light source, and the coil structure and principle are relatively simple and are more suitable for a complex working environment. In conclusion, the CPT atomic magnetometer based on the magnetic field modulation method can be widely applied to the fields of magnetic field drawing, mineral exploration and the like, has the characteristics of high precision, high resolution and the like, and also shows a wide market application prospect in the aspects of miniaturization, low power consumption and the like.

The invention relates to the technical field of hyperspectral remote sensing image classification, and discloses a hyperspectral small sample classification method, system and device and a medium, and the method comprises the steps: obtaining a hyperspectral source domain data set and a target domain data set; constructing a multi-level spatial spectrum feature fusion network (comprising a multi-level spatial spectrum feature coding module, a self-adaptive layered feature fusion module and a feature set matching module), extracting spatial spectrum local fusion features in the multi-level spatial spectrum feature coding module, obtaining global features in the self-adaptive layered feature fusion module, and matching the global features with the feature set; constructing a domain distribution feature loss function; utilizing a feature set matching module to calculate a feature distance, and constructing a multi-level feature matching loss function; combining the two types of loss functions to construct a total loss function so as to train a multi-level spatial spectral feature fusion network and obtain an initial classification model; and inputting a target domain data set into the model for adaptive adjustment so as to realize accurate prediction of hyperspectral small sample classification.

The invention relates to the technical field of optical fiber monitoring, and particularly discloses a distributed optical fiber sensing system and method for coal mine settlement monitoring, the distributed optical fiber sensing system comprises a measuring part and a data acquisition and processing part, the measuring part comprises an optical cable embedded in a coal mine soil body, an FBG-based osmometer and an FBG-based extensometer, and the data acquisition and processing part comprises a data acquisition and processing part. The data acquisition and processing part comprises an OFDR demodulator, an FBG demodulator and a computer, and the optical cable comprises a first optical fiber, a sheath steel pipe and a PUC outer sheath which are sequentially arranged from inside to outside. According to the distributed optical fiber sensing system and method for coal mine settlement monitoring, the optical fiber is used for measuring strain, then the strain is converted into three physical quantities including optical cable deformation, pore pressure and extensometer measurement displacement to represent the coal mine settlement condition, verification is carried out through coal mine field experiments, and the coal mine settlement monitoring accuracy is improved. The method can be used for monitoring the coal mine settlement condition.