206 results about "Correction algorithm" patented technology

The invention discloses an AI-based regulation and control abnormal data identification and correction method, system and device and a medium, and belongs to the technical field of power system regulation and control, and the method comprises the steps: obtaining multi-source data of a main distribution network, carrying out the preprocessing, and constructing a power grid topology knowledge graph; the multi-source data comprises full voltage class model data, real-time measurement data and equipment state data. According to the method, a three-layer detection system of a statistics-density mixed detection layer, a graph neural network association detection layer and a time sequence Transform detection layer based on an LOF algorithm and a 3 sigma principle is constructed, deep association analysis of multi-source data is realized in combination with a power grid topology knowledge graph, and an intelligent correction module is used for matching a differentiation correction algorithm for different types of anomalies; the correction weight is dynamically adjusted based on reinforcement learning, and the problems that a traditional method depends on artificial experience to set a threshold value, the recognition capacity of a single algorithm is limited, a correction strategy lacks adaptability, and multi-source data association analysis cannot be achieved are solved.

The invention relates to the technical field of industrial control, and discloses a soda water production line intelligent control method and system based on the Internet of Things, and the method comprises the steps: obtaining a backpressure valve reference pressure value according to the obtained real-time dynamic data through employing a pre-constructed carbonation digital twin model, and calculating the backpressure valve reference pressure value according to the backpressure valve reference pressure value; the carbonation digital twinning model is set to obtain a theoretical pressure value by adopting the Henry law according to the target gas content and the real-time data of the mixed liquid temperature, and obtain a predicted pressure value by adopting the pre-constructed pressure prediction model according to the target gas content, the real-time data of the raw material liquid injection flow and the real-time data of the carbon dioxide injection flow; further obtaining a reference pressure value of the back pressure valve; according to a first difference value between the target gas content and the real-time gas content of the mixed liquid, a first feedback correction algorithm is adopted to correct the reference pressure value of the back pressure valve, and a dynamic pressure control instruction of the back pressure valve is obtained; and controlling the back pressure valve to execute the back pressure valve dynamic pressure control instruction. According to the method, the taste stability of the soda water is effectively improved.

The invention discloses a method for detecting tea saponin in a tea extract, and relates to the technical field of chemical analysis and computer science, and the method comprises the following steps: eliminating high-frequency noise of tea extract data by using a Gaussian filtering algorithm, eliminating baseline drift by using a baseline correction algorithm, and generating a tea extract sample data stream; the method comprises the following steps: performing dynamic gradient separation through a chromatographic signal simulation algorithm on the basis of a tea extract sample data stream to generate a virtual chromatographic peak sequence, calculating a peak area through a sliding window integration algorithm on the basis of the virtual chromatographic peak sequence, and generating chromatographic signal data by using a wavelet transform threshold denoising algorithm, the chromatographic signal data are input into the deep convolutional neural model, the feature pyramid network is obtained through the multi-scale feature fusion algorithm, the feature information of the chromatographic peaks is extracted from different scales by constructing the deep convolutional neural model and combining the multi-scale feature fusion algorithm, and therefore the recognition precision of the feature peaks is improved.

The invention relates to a hyperspectral signal prediction method based on a hyperspectral remote sensing image and pseudo label guidance, and belongs to the technical field of hyperspectral signal prediction. The method comprises the following steps: collecting remote sensing spectral data and soil spectral data, and carrying out primary preprocessing on the remote sensing spectral data; based on a designed series correction algorithm, correcting the remote sensing spectral data after the primary preprocessing by using the soil spectral data, and performing secondary preprocessing; performing imaging on the remote sensing spectrum data after the secondary preprocessing; constructing a double-branch fusion model comprising a spectrum branch and an image branch; constructing a classification pseudo label, and introducing supervised contrast loss to train the double-branch fusion model; and inputting remote sensing spectral data to be predicted into the trained double-branch fusion model to obtain a hyperspectral signal prediction result so as to realize soil content prediction. The objective of the invention is to solve the technical problems of complex noise, low quality and difficulty in guaranteeing prediction accuracy when remote sensing spectral data is acquired in the prior art.

The invention relates to a DAS signal positioning method based on adaptive tensor decomposition and dynamic correction. The method comprises the steps of converting phase difference data into strain rate data, constructing a three-dimensional tensor based on a time domain signal of a space point, solving an optimization problem after constraint modeling, and extracting a de-noised DAS signal. Calculating an initial fault position, and calculating an actual optical path and an apparent position after temperature change based on a thermal expansion effect and a thermo-optic effect; and a dynamic correction algorithm is set, a system coordinate reference is adaptively calibrated, and a final positioning result is calculated. According to the method, original signals are separated into a low-rank background field, a sparse event field and a structured noise field through unsupervised tensor decomposition, and the defects of dependence on labeled data and insufficient complex noise separation are overcome; by establishing a temperature-optical path coupling physical model and a dynamic correction algorithm for real-time cross-correlation calibration, positioning drift caused by environmental factors is accurately compensated, and high-fidelity denoising and accurate positioning of cable line events in a complex environment are realized.

The invention discloses a power transmission line icing analysis method and system influenced by microtopography and micrometeorology, and relates to the technical field of power transmission line risk prediction.The method comprises the steps that original meteorological data of an area where a power transmission line is located is collected and fused, and micrometeorological field variables are generated based on topographic parameters extracted by a DEM; on the basis of the fusion data and the micrometeorological field variables, three-dimensional micrometeorological field data are obtained through a fluid mechanics model, the three-dimensional micrometeorological field data are corrected through terrain parameters obtained through a DEM model, an exponential weighted moving average method is used for adjustment, and accurate three-dimensional micrometeorological field data are obtained; based on the accurate micrometeorological field data, the icing thickness is obtained by adopting a physical-empirical hybrid icing growth model, the output icing thickness is adjusted in real time through a dynamic correction algorithm, and a final icing simulation result is obtained. The accuracy of power transmission line icing disaster prediction and the flexibility of emergency response are improved.

The invention discloses a shaft scaling prediction method and system based on a transfer function and machine learning. The method comprises the steps that scaling prediction basic parameters such as fluid pressure, temperature, flow velocity and ion concentration in an oil and gas shaft are obtained and imported into an oil and gas shaft scaling dynamic analysis platform; calling a seepage coupling transfer function scaling prediction model to process seepage related parameters, and establishing a correlation between a fluid seepage state and a scaling initial trend; starting a dynamic transfer function out-of-bag scaling algorithm to dynamically iterate different depth parameters, and outputting a preliminary scaling amount; correcting a preliminary result through a chemical thermodynamic transfer function correction algorithm in combination with parameters such as temperature; and a machine learning model is adopted to train a corrected result and a shaft position parameter, a mapping model is established, a dynamic scaling prediction curve is output, and the platform carries out visualization processing on the curve. The system is matched with the method to realize parameter acquisition, processing, calculation, correction, modeling and display, and the scaling prediction accuracy and the dynamic adaptability are improved.

The invention relates to the technical field of environment control, and discloses a time-sharing optimization control method for a cold storage central air conditioner based on a large model, which comprises the following steps of: firstly, acquiring a system cold demand quantity and an environment working condition predicted value at a future moment through a pre-trained deep learning model, and estimating a current cold storage charging and discharging state in combination with a thermal front degradation correction algorithm; then, a non-linear flow resistance model associated with the porosity and the cold storage state is established, and a hydraulic high-energy-consumption interval in which fluid resistance is highly sensitive to flow change is recognized; and on the basis, deducing the energy efficiency trend of the water chilling unit by utilizing the environment temperature to determine load distribution, actively inhibiting cold storage output in a high flow resistance interval through energy efficiency gating logic, and finally generating a time sequence control strategy containing flow and load instructions to realize optimal scheduling of system-level energy efficiency.

The invention belongs to the technical field of medical information processing, and discloses a wound repair analysis method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining three-dimensional point cloud data, spectral data and patient physiological signals obtained through multiple times of scanning of a to-be-repaired wound; performing dynamic correction on the three-dimensional point cloud data based on the physiological signal of the patient and the spectral data to generate a standardized wound three-dimensional model; performing space-time dimension wound assessment based on the model and the dynamic data of the wound to obtain a quantitative assessment report; and finally, generating an individualized repair scheme through double-path driving of historical data and operator experience. According to the method, the scanning precision is improved through a dynamic correction algorithm fused with physiological signals, advanced prediction of postoperative risks is achieved through a space-time dimension evaluation model, the individual suitability of the scheme is improved through a double-path scheme generation mechanism, and the precision and success rate of plastic wound repair are remarkably improved.

The invention discloses a flow measurement and analysis system in a multiphase flow environment, and relates to the technical field of flow measurement, the system comprises a flow pattern identification module, a parameter acquisition module, a coupling mapping model module, an incremental learning module, a residual error correction module and a flow calculation output module; through cooperation of the flow pattern recognition module and the coupling mapping model module, compensation logic is dynamically switched, precise compensation of flow pattern and working condition adaptation is achieved, complex scenes such as medium component fluctuation and temperature and pressure sudden change are automatically adapted through the incremental learning module, the defect that in the prior art, adaptability to complex working conditions is poor is overcome, and the working condition accuracy is improved. According to the method, the working condition adaptation capacity of the system is improved, flow pattern conversion lag errors and sensor signal noise interference are corrected at the same time through a multi-scale residual error correction algorithm, the consistency and reliability of flow measurement results are guaranteed, finally, the precision and stability of multi-phase flow measurement are remarkably improved, and the actual requirements of industrial production are met.

To provide an ultra-precise optical measurement method. [Solution] The system comprises a mounting base 100, a laser system provided on the mounting base 100, a probe system, and a measurement table system. The probe system includes a probe 300 and a Z-direction movement mechanism for moving the probe 300 up and down. The measurement table system includes a stage and an XY movement mechanism for moving the stage along the X and Y directions. The laser system includes a laser transmitter, a set of reflective mirrors, multiple laser interferometers, and a deflection mirror. Inside the probe 300 is a floating rod that can levitate and a stylus sphere attached to the bottom end of the floating rod, and the stylus sphere contacts the workpiece to be measured during measurement. The steps of the roundness error correction algorithm are to place a reference sphere on the stage and measure it, remove the error parameter, solve the shape error of the reference sphere using an aspherical equation, and then correct the measurement data by the shape error in the subsequent measurement process.

A computer system comprising processing circuitry is provided. The computer system is configured to obtain a chassis voltage between a first traction voltage pole and a chassis of a vehicle; obtain a scheduled switching time to switch from the first traction voltage pole to the second traction voltage pole in order to measure the chassis voltage between the second traction voltage pole and the chassis of the vehicle; determine a disturbance on the first or second voltage pole; adjust the scheduled switching time and / or a corrective algorithm; and obtain a chassis voltage between the second traction voltage pole and the chassis of the vehicle based on the adjusted scheduled switching time and / or the corrective algorithm.

The application discloses a charged water body equivalent impedance model construction and parameter acquisition method and related devices, and innovatively establishes a calculation system containing resistance and inductance correction factors, and realizes high-precision characterization of water body impedance characteristics by introducing an electrode spacing function. Specifically, a scalable grid technology is used to construct an adaptive calculation framework, and the calculation accuracy of resistance and inductance parameters is significantly improved through a power function correction algorithm. A reliable numerical calculation is provided for water body impedance network model analysis in complex hydrological environments. The application solves the problems of the prior art, such as complex modeling process, difficulty in accurately describing nonlinear behavior, insufficient precision, and inability to accurately capture the real behavior of water body.

This invention belongs to the field of positioning algorithm technology and discloses a method for motion bistation time-frequency difference (SDP) positioning. The algorithm of this invention provides a complete process for motion bistation positioning without requiring manual selection of an initial solution. The SDP algorithm used can handle the problem of motion bistation SDP positioning. When noise is high, SDP gradually deviates from the CRLB bound. The accuracy of the corrected result can be guaranteed by using the Refine algorithm or maximum likelihood estimation based on Gauss-Newton. With low measurement error, the direct correction algorithm slightly deviates from the CRLB bound, mainly due to errors introduced by linearization.

This invention discloses a method and system for dynamically determining the impact of construction projects on hydrological monitoring, relating to the field of hydrological monitoring technology. The specific steps are as follows: constructing an evaluation index system that couples static and dynamic indicators; assigning static weights to static indicators using the analytic hierarchy process (AHP) and dynamic weights to dynamic indicators using the entropy weight method; calculating the total weight based on the static and dynamic weights; constructing and training a machine learning model; inputting the static, dynamic, and total weight data into the trained machine learning model; and outputting the impact level; automatically matching response measures based on the impact level and trend prediction results. This invention proposes a dynamic weight correction algorithm based on project stage and hydrological conditions, applying machine learning algorithms to determine the impact level of construction projects on hydrological monitoring, achieving a closed-loop linkage from level determination to measure matching, and solving the problems of singular and disconnected evaluation in existing technologies.

The application discloses a kind of electric vehicle charging pile order exception clearing settlement method and device, comprising: obtaining the real-time order of vehicle networking platform;Based on the inference engine of preset detection real-time order whether it is abnormal order;Response to real-time order is normal order, then directly upload real-time order to vehicle networking platform;Response to real-time order is abnormal order, then based on correction algorithm or preset prediction model carries out numerical correction or data prediction to real-time order, obtains revised abnormal order and uploads to vehicle networking platform.One aspect, according to the mass historical abnormal data obtained by vehicle networking platform, mining clearing screening rule, combined with the experience rule of power grid expert custom clearing screening rule, the inference engine obtained can accurately detect abnormal order, on the other hand, it can be to electric vehicle charging pile abnormal order numerical correction or data prediction, reduce the economic loss caused by order exception.

The application discloses a temperature compensation method and a compensation system of a pressure sensor, and the compensation method adopts a constant current source temperature compensation circuit or a constant voltage source temperature compensation circuit to realize temperature compensation, wherein a temperature compensation resistor value in the temperature compensation circuit is searched through a multi-target particle swarm optimization algorithm, and after an output result of the compensation circuit is output, the output result is corrected through an output correction algorithm based on two-dimensional interpolation calculation. The application can reduce the difficulty of product miniaturization, reduce the production cost of the sensor, and improve the temperature compensation precision.

The invention relates to the technical field of intelligent data terminal remote control, in particular to a bar code data transmission method allowing missing codes, which comprises a code generation step of data file conversion and a decoding step of scanning equipment. When data transmission is carried out, a to-be-transmitted data file is coded to generate a series of bar codes, continuous scanning is carried out through a code scanning device, the data is completely transmitted into the device, a fault-tolerant mechanism is constructed by using an RS error correction algorithm principle, RS error correction code words are added to realize redundancy, and part of the bar codes cannot be successfully scanned or have recognition errors. And the system can still utilize the redundant information reserved in the error correction group in the subsequent decoding stage to recover missing or wrong code words, so as to reconstruct a complete data file. Compared with the prior art, the code scanning equipment does not need to interact with equipment for displaying bar codes, has higher stability, is particularly suitable for a data transmission scene in a dynamic or interference environment, and has higher feasibility and adaptability.

This application discloses a 3D imaging method and system based on structured light phase measurement, relating to the field of 3D imaging technology. The method includes: calibrating a structured light measurement system to obtain intrinsic and extrinsic parameters, and determining the effective measurement depth range and the corresponding effective absolute phase interval; controlling a projector to project a preset sinusoidal fringe pattern onto the measured scene, acquiring a deformed fringe image modulated by the surface of the measured object, and obtaining a wrapping phase map; calculating the initial fringe order of each pixel based on the effective measurement depth range using a frequency domain order-based fringe order no-neighborhood solution algorithm; performing no-neighborhood verification and error correction on the initial fringe order based on the effective absolute phase interval using an order self-verification and error correction algorithm to obtain the final fringe order; and calculating the absolute phase map of the entire field of view based on the wrapping phase map and the final fringe order, and converting the point cloud data. This application aims to solve the technical problem of existing spatial phase unfolding techniques relying on the continuity of adjacent pixels.

The invention discloses a data self-adaptive correction and acquisition method and device for dynamic environment monitoring. The method comprises the following steps: configuring key data item test points, classifying the priorities of the test points, setting update levels and weights, allocating polling resources to each level of test point, and acquiring dynamic environment monitoring data of each data item; creating a task in the power and environment monitoring system, performing field measurement, calculating the difference between power and environment monitoring data and actually acquired data, and analyzing a difference mode; dynamically adjusting the parameters of the dynamic environment monitoring system through an adaptive correction algorithm according to the difference mode to obtain corrected data; a selective polling strategy is adopted, polling priority weight and polling frequency are dynamically adjusted, and polling resources are updated and distributed; constructing a difference data prediction model to predict future differences, and judging whether the future differences exceed a preset safety threshold value or not to perform error correction; according to the invention, difference modes can be identified in real time, environment and equipment state changes can be handled, and monitoring data accuracy and system response timeliness can be improved.

The application belongs to the technical field of biomedical and computer vision, and discloses a real-time measurement method of cardiac outflow tract wall shear force based on a neural network. An image is collected by using an SD-OCT imaging system to obtain a structure image and a flow velocity image. A Doppler angle is recorded by changing the incident angle of the probe beam through a protractor head rotation. An ALSegNet network is used to extract the flow area of the cardiac outflow tract in the structure image; the flow velocity image is combined with the extracted flow area to calculate the cardiac outflow tract wall shear force through a laminar flow model flow velocity gradient and a three-dimensional rotation correction algorithm. The ALSegNet network designed in the method has small complexity, can be migrated to a mobile device, and has fast inference speed, wherein the parallel sub-network and the PDAM can ensure that the target of the OFT blood flow area is not lost to a certain extent, that is, the inference accuracy is relatively high. The method can obtain the cardiac outflow tract wall shear force in real time at a relatively fast speed.

The invention relates to the technical field of high-low voltage electrical equipment, and discloses a high-low voltage switchgear assembly with adaptive protection parameters and an online fault diagnosis method. The equipment comprises a parameter acquisition module, a core control module, an execution module and a wireless communication module, wherein a self-adaptive protection parameter adjustment and fault diagnosis unit is arranged in the core control module; the method comprises the steps of parameter preprocessing, feature extraction, hierarchical diagnosis and fault positioning. The protection parameters are dynamically adapted by innovatively adopting a multi-dimensional parameter weighted iterative correction algorithm, and the weight is optimized in combination with parameter self-learning; a whole-process online hierarchical diagnosis system is constructed, and 5G-LoRa dual-mode communication and dual-parameter backup are matched. The method solves the problems of fixed protection parameters of existing equipment, misjudgment and missing judgment of fault diagnosis, unstable communication and the like, improves protection adaptation precision and diagnosis reliability, guarantees continuous power supply, and is suitable for complex power grid scenes such as new energy grid connection.

The application discloses a wavefront correction method for a wavefront detection-free adaptive optical system based on deep learning, comprising the following steps: S110, constructing a neural network to train a mapping relationship from far-field focal plane light intensity to corresponding complex conjugate wavefront data; S120, constructing a data set, taking the far-field focal plane light intensity as the input of the neural network, and taking a pair of complex conjugate wavefront data corresponding to the far-field focal plane light intensity as the standard output of the neural network; S130, using a loss function to process the loss of back propagation, and making the network learn a certain mapping relationship by taking a smaller loss; and S140, designing a wavefront correction algorithm for the neural network of the wavefront detection-free adaptive optical system to realize closed-loop correction of the wavefront detection-free adaptive optical system. According to the technical scheme, the wavefront correction speed and precision are greatly improved, and fast and high-precision wavefront correction of the wavefront detection-free adaptive optical system is realized.

The invention relates to the technical field of false eyelash image recognition, in particular to a gluing line defect detection method and system based on multispectral image recognition, and the method comprises the steps that false eyelash bases are attached to a heating aluminum ring, the false eyelash bases are connected in series through a silk thread, a gluing mechanism is used for gluing along the silk thread to form a gluing line, and the gluing line is connected with the heating aluminum ring; the gluing line is deformed by heating the aluminum ring, and eyelash is promoted to fill gaps of the gluing line; the platform deck rotates the glued false eyelashes to a detection area, the multispectral imaging mechanism obtains multispectral images of the top face and the single side face of a gluing line, the images are preprocessed, and the preprocessing on the images comprises the steps of eliminating ambient light interference through a spectrum correction algorithm and highlighting a defect area through a gluing line characteristic wave band operation enhancement algorithm; and integrating spectral image features by using a multi-source image fusion algorithm, generating a fusion feature map according to the preprocessed image, and inputting the fusion feature map into a convolutional neural network model to realize the detection of the defects of the gluing line with the radian.

The application discloses a multi-cavity anti-blocking breaking hammer control system with self-adaptive buffer, and relates to the technical field of engineering machinery control. The breaking hammer is provided with three groups of independently driven eccentric shafts on the outer periphery of a main shaft, and is matched with a planetary or harmonic speed reduction mechanism to realize high-precision dynamic adjustment of a hammer head eccentric angle (±0.5°) and an eccentric distance (±0.2mm). In combination with an independently electrically-controlled hydraulic buffer cavity of each hammer head, self-adaptive absorption of striking energy is realized. The system is provided with an industrial camera and an infrared light supplementing vision module, non-contact real-time monitoring of a hammer head wear profile is realized, and three core algorithms, namely, a foreign matter overload buffer algorithm, a rotor static unbalance correction algorithm and a wear compensation algorithm, are scheduled through an RTOS hard real-time operating system, so that the highest risk event is preferentially responded to under the concurrent working conditions of impact, vibration and wear, and the technical difficulties of uneven hammer head wear, rotor imbalance, foreign matter overload fracture and material blockage and the like are solved from the root, the service life of the equipment is increased by more than 25%, the failure rate is reduced by 80%, and the breaking efficiency is increased by 15%.

This invention proposes a method for multi-target recognition, tracking, and vibration extraction of bridge cable-stayed bridge videos based on unmanned aerial vehicles (UAVs). The method includes: Step 1: Constructing a refined tilted and slender target detection model for bridge cable-stayed bridges based on the YOLOv11 model; Step 2: Proposing a multi-target tracking algorithm that integrates the tilted and slender target detection model and the StrongSORT algorithm; Step 3: Improving the displacement extraction method by combining SIFT / ORB feature point matching and sub-pixel refinement techniques; Step 4: Designing a UAV motion correction algorithm based on variational mode decomposition and time-frequency domain joint screening; Step 5: Constructing a joint working mode analysis algorithm that combines natural excitation technology and random subspace recognition algorithm. This method achieves high-precision extraction of cable-stayed bridge vibration signals and identification of cable-stayed bridge modal parameters, providing technical support for health monitoring of long-span cable-stayed bridges.

The application discloses a kind of based on space sampling consistency determination pipe robot multi-source perception full true simulation test system, belong to pipe detection simulation test technical field, it includes mechanical execution system, space state perception gate and physical trigger system, multi-sensor sampling unit, true value reconstruction system.Mechanical execution system provides the motion reference along the axial direction of pipeline, and allow to introduce controlled nonlinear disturbance, space state perception gate and physical trigger system are used for the arbitration of sampling opportunity when FPGA motion control card, step modulation and physical trigger;Multi-sensor sampling unit is used to execute sampling instruction and generate original data with position label;True value reconstruction system is used to construct the standardized pipeline true value containing position, texture and geometric information;The application realizes high-fidelity three-dimensional digital reconstruction to the inner wall of pipeline by introducing IMU posture latch, micro time delay elastic capture, binocular vision forward variable frequency modulation and reverse geometry correction algorithm.

This invention provides a Pinyin error correction method that simplifies the noise channel model used in most current Pinyin error correction algorithms by employing a real-time frequency counting method, effectively improving the efficiency and lightweighting of the algorithm. Furthermore, this invention uses a direct character substitution method instead of the traditional edit distance calculation method, avoiding frequent edit distance calculations in the Pinyin error correction algorithm. The dictionary database itself is localized to the individual user, resulting in a highly personalized, targeted, and small-scale dictionary that provides accurate candidate words. Compared to existing algorithms, this invention offers significant improvements in error checking rate, candidate word accuracy, and execution efficiency.

The application discloses a kind of tool butt joint method and system, including end setting with laser range finder, positioning tool interface is provided with measured piece;When reaching the position to be corrected, the laser measurement height value is read by laser range finder;The correlation analysis of the installation offset of laser range finder and the projection point on measured piece is carried out, and the coordinate relationship equation is established;Offset is calculated according to coordinate relationship equation, whether offset meets the requirement is judged, if it meets the requirement, then butt joint is completed, if it does not meet the requirement, then translation adjustment is carried out.The application is tested in laboratory, can control robot end absolute positioning accuracy to be below ±0.25mm, satisfies the requirement that robot completes butt joint operation;Uniform processing standard and gauge standard batch processing measured target are used, and quick replacement can be realized;3-point correction algorithm is used, installation error is weakened, and calculation error caused by installation error is further reduced.

The invention relates to the technical field of rail shape monitoring, in particular to a rail deformation sensing method and device based on a flat-ribbon optical cable. The device is characterized by comprising a bandlet optical cable, a conduction optical fiber, a demodulator and a computer, a fiber bragg grating array which is weak in reflectivity, determined in grating distance and capable of being calibrated in position is accurately inscribed in two optical fibers in the flat-ribbon optical cable, interference of temperature fluctuation and axial strain is effectively eliminated through double-optical-fiber cooperative measurement and differential calculation, and when a rail is subjected to sedimentation or bending deformation under the action of train loads and environmental factors, the fiber bragg grating array is accurately inscribed in the flat-ribbon optical cable. Deformation is synchronously transmitted to the bandlet optical cable and causes the wavelength change of the reflection center of each fiber bragg grating, a wavelength change signal is transmitted to the demodulator through the conduction optical fiber to be demodulated in real time and output to the computer, and the computer is based on a wavelength-strain-curvature mapping relation and combines a Freen-Serret shape reconstruction and vertex error correction algorithm. The spatial shape reconstruction of the rail is realized, and the settlement height change is output, so that the real-time, continuous and visual monitoring of the settlement process of the rail is realized. The method is suitable for the technical field of rail deformation and settlement monitoring.