3664results about "Thermometers using physical/chemical changes" patented technology

The invention relates to the technical field of power equipment state monitoring, in particular to an oil-immersed transformer distributed temperature measurement method based on a fluorescent optical fiber sensor, and the method comprises the steps: arranging the fluorescent optical fiber sensor in a key temperature rise region in a transformer in a partitioned and layered three-dimensional topological structure, and forming a distributed temperature measurement network; exciting light is injected through a pulse laser to excite a fluorescence signal; a dual-channel phase-locked amplification technology is used to collect signals, and a dual-weight adaptive attenuation model and an oil flow coupling compensation function are combined to demodulate the temperature; reconstructing a dynamic temperature field based on a three-dimensional thermodynamic inversion algorithm, and marking high-gradient hot spots; and temperature, load current and oil flow velocity data are fused to realize graded alarm. According to the invention, the limitation of traditional single-point monitoring is broken through, the strong electromagnetic interference resistance is excellent, a global temperature field can be accurately reconstructed, dynamic early warning is realized, and the operation safety and the operation and maintenance efficiency of the transformer are remarkably improved.

The invention discloses an intelligent cable fault accurate positioning and early warning method and system, and the method comprises the steps: collecting the temperature gradient, strain distribution and partial discharge signals of the whole length of a cable in real time through a distributed optical fiber sensing network, and generating a multi-dimensional feature matrix of the operation state of the cable; based on the multi-dimensional feature matrix, outputting a preliminary fault positioning coordinate; generating corrected fault coordinates according to the topological structure data of the cable laying environment and the electromagnetic interference distribution diagram; historical fault data, real-time operation parameters and the corrected fault coordinates are fused, and a fault risk thermodynamic diagram in a future preset duration is output; and based on the fault risk thermodynamic diagram and real-time monitoring data, generating fault first-aid repair information by using a dynamic priority algorithm, synchronously triggering an early warning signal, and visually displaying a fault positioning result and a risk area in a three-dimensional geographic information system. According to the embodiment of the invention, rapid positioning, accurate early warning and intelligent disposal of the cable fault can be realized.

The invention discloses an electrical equipment operation state monitoring method, system and terminal, full life cycle health management of equipment is realized through multi-dimensional perception and intelligent analysis, a composite sensor network can be constructed from the level of the method, and high-frequency current, ultrahigh frequency, fiber grating temperature vibration, multi-parameter gas and acoustic sensors are integrated. Electromagnetic characteristics, mechanical states, environmental parameters and voiceprint characteristics are covered; the adaptive signal processing technology performs classification and noise reduction on multi-source data, and the three-dimensional digital twin model realizes time-space fusion of a temperature field, a vibration field, an electric field and a sound field; a lightweight space-time convolutional network is deployed to fuse a time domain waveform, a spectrogram and spatial distribution characteristics for diagnosis, and a hidden semi-Markov model and a particle filter algorithm are combined to dynamically predict the residual service life of equipment. The system architecture comprises a self-organizing sensor network with edge computing capability, a time-sensitive industrial communication network and a containerized analysis engine, and supports mixed reality visual interaction.

The invention provides a distributed optical fiber-based soil roadbed deformation monitoring method and monitoring system, and the method comprises the steps: obtaining a distributed optical fiber sensing data set of a target soil roadbed, dividing the target soil roadbed into a plurality of monitoring regions with different deformation characteristics according to the deformation intensity distribution of an optical fiber strain data sequence, and carrying out the monitoring of the deformation of the target soil roadbed. And performing coupling analysis processing on the optical fiber strain data sequence and the temperature compensation data sequence of each monitoring area to generate a multi-dimensional deformation feature set of the monitoring area, and generating deformation early warning information of the target soil roadbed according to a space-time matching result of the multi-dimensional deformation feature set and a preset deformation threshold condition. And generating a soil roadbed deformation optimization strategy based on the deformation early warning information, and feeding back the soil roadbed deformation optimization strategy to the roadbed maintenance system to trigger reinforcement response operation. The method can effectively improve the active control capability of the health state maintenance of the soil roadbed.

The invention discloses a high-temperature airflow two-dimensional temperature field and velocity field synchronous measurement system and method based on laser-induced phosphorescence, and the system comprises phosphorescence particles, a low-frequency double-pulse laser, an image collection device, a synchronous controller, and an image processing device. The image processing device analyzes the gray intensity ratio of different wave band images acquired by the two PIV cameras at the same time, and combines a temperature response function calibrated by an experiment to realize inversion of a temperature field; meanwhile, a double-frame time-resolved image acquired by any PIV camera is subjected to cross-correlation calculation, particle displacement is extracted, and then a velocity field is reconstructed. According to the invention, synchronous acquisition of temperature and speed based on the same data source is realized, and the system has the remarkable advantages of simple structure, high measurement precision and wide application environment.

The invention provides an LNG ship containment system monitoring system and method based on a fiber bragg grating sensor, and belongs to the crossing field of fiber sensing technology and ship safety engineering, the system comprises a fiber bragg grating sensor and a demodulation device, the fiber bragg grating sensor is used for collecting optical signals, and the demodulation device converts the optical signals into electric signals and processes the electric signals. The fiber bragg grating sensor adopts a double-grating structure and is respectively used for stress monitoring and temperature compensation so as to realize omnibearing real-time monitoring. The fiber grating sensor comprises a tail fiber, a protective tube, a base, and a strain grating, a spring and a temperature grating which are located in the protective tube. According to the invention, the monitoring precision and safety of the LNG ship containment system can be improved; through a double-grating temperature compensation technology, the influence of temperature change on stress measurement is eliminated, and the accuracy and reliability of data are ensured; in addition, stress information in different directions can be obtained in real time through the three-dimensional stress monitoring scheme, the stress condition of the structure is comprehensively reflected, and the flexibility and adaptability of monitoring are improved.

The invention relates to the technical field of industrial safety, and discloses an electrolytic aluminum short circuit port operation safety early warning system based on multi-parameter collaborative awareness and intelligent diagnosis, and the system comprises a parameter collaborative awareness module, a dynamic diagnosis module, an early warning decision module, and an execution feedback module. By constructing a multi-dimensional parameter collaborative sensing mechanism, fusing temperature field distribution, current balance degree and insulation state multi-source data in real time and dynamically capturing early abnormal symptoms of a short circuit port, the hysteresis problem of traditional single-parameter threshold monitoring is solved, conversion from passive response to active defense is achieved, and the comprehensiveness and timeliness of operation state monitoring are improved; and meanwhile, based on a historical fault database and a real-time evolution model, a health index is generated and a fault path is predicted, so that maintenance personnel can pre-judge a development trend and a time window of potential risks in advance, and sudden equipment accidents are avoided.

The invention provides a wavelength division multiplexing-fused multi-core optical fiber temperature detection method and system. Wherein the broadband light source is divided into multiple wavelength channels through wavelength division multiplexing, and a wavelength-fiber core mapping relation is established, so that each fiber core of the multi-core optical fiber transmits a single-wavelength optical signal. An optical fiber is integrated to the surface of an object according to a three-dimensional path, each fiber core covers a plurality of sensing sub-areas, the wavelength drift amount caused by temperature is extracted by detecting the attenuation characteristic of an optical signal at a bending position, the wavelength drift amount is converted into a temperature value in combination with a calibration curve, and a temperature gradient model bound with the fiber core position is constructed. And further performing spatial solution by using fiber core spacing, wavelength mapping and transmission time delay parameters, establishing a corresponding relationship between the coordinates of the sensing sub-regions and the temperature, and finally reconstructing three-dimensional temperature field distribution. According to the technical scheme provided by the invention, high-resolution dynamic reconstruction and gradient analysis of a three-dimensional temperature field on a complex surface are realized through wavelength-space two-dimensional decoupling.

The invention provides a bridge structure monitoring method and device based on a microwave deformation radar, and relates to the technical field of bridge structure monitoring, and the method comprises the steps: obtaining the multi-point three-dimensional displacement data of a bridge structure through the microwave deformation radar, carrying out the thermal expansion pseudo displacement compensation and multi-point space smoothing through combining with temperature information, and obtaining a displacement field after environment correction; secondly, extracting a vertical component and separating the vertical component into a static deformation component and a dynamic vibration component by adopting variational mode decomposition; further analyzing and identifying a decoupling region through a time window coherence coefficient, performing recursive quantitative analysis, bispectrum analysis and energy distribution entropy calculation on a dynamic signal of the region, and constructing a high-order damage sensitive feature set; and finally, the dynamic characteristics and the static curvature change are fused to form a comprehensive degradation degree index, the deviation degree is judged according to working condition classification and the mahalanobis distance, and multi-dimensional and cross-working-condition degradation identification and risk early warning of the bridge structure are achieved.

The invention discloses a cable life dynamic evaluation system based on multi-physics field coupling, and particularly relates to the field of industrial automation and control systems, which comprises a multi-physics field sensing module, a coupling analysis engine module, a dynamic life evaluation module, a digital twin interaction module and an environmental interference suppression module, through a distributed optical fiber temperature sensor, a capacitive electric field sensor and a magnetostrictive stress sensor, temperature, electric field, magnetic field and mechanical stress data of a cable are collected in real time, multi-physical field characteristics and a cable defect database are matched in real time by using a cross-scale dynamic association algorithm, a damage state is evaluated, and the cable defect detection accuracy is improved. A time sequence neural network architecture is adopted to predict the remaining life, model self-correction is achieved through digital twin comparison, interference is suppressed in combination with an environment-physical field coupling compensation matrix, sensing and evaluation of the health state of the cable, life prediction and continuous optimization of the model are achieved, and the efficiency of cable life evaluation is improved.

The invention relates to a thermal coupling over-reduced order prediction method and system for a multi-component assembled nonlinear system. The method comprises the following steps: collecting multi-scale physical field data; constructing an intrinsic orthogonal decomposition basis function space of a temperature field and a stress field, and establishing a double-field coupling constraint equation; constructing contact thermal resistance parameterized proxy models of a cylinder contact area, a bolt area and a free deformation area by adopting a domain discrete empirical interpolation method; constructing a parametric intrinsic mode tensor network to obtain a decline model which is used for realizing real-time reconstruction of a mode basis function through acquired tensor slices in an online stage; performing dynamic inversion based on a modal basis function reconstruction result, and outputting a predicted transient displacement field, a predicted temperature gradient field and a predicted contact stress field; and obtaining real-time parameters, and calculating a residual error with a corresponding prediction result so as to dynamically update the primary function and interpolation point distribution. Compared with the prior art, the real-time prediction of the transient thermal coupling of the multi-component contact system is realized on the premise of ensuring the precision.

The invention relates to the technical field of power transformer state monitoring, and discloses a main transformer winding temperature rise on-line monitoring method and system, and the method comprises the steps: obtaining the calibration flight time of ultrasonic waves through an acoustic sensor array disposed on the outer wall of an oil tank in a quasi-isothermal state of a transformer; calculating a structure additional time delay which is caused by an internal fixed structure and does not change along with the temperature, and establishing an acoustic fingerprint for the transformer; during on-line monitoring, oil way net propagation time reflecting temperature change of the insulating oil is obtained from on-line flight time measured in real time; and then, based on the net propagation time of the oil way, an acoustic tomography algorithm is adopted to reconstruct internal two-dimensional or three-dimensional temperature field distribution, and the winding hot-spot temperature is finally and accurately calculated in combination with the real-time load current. According to the invention, through the acoustic fingerprint correction technology, the measurement interference of an internal fixed structure is eliminated, and non-intrusive, high-precision and visual online monitoring of the winding hot-spot temperature is realized.

The present disclosure provides a method for measuring flow velocity of multilayer groundwater using distributed optical fiber with point-source active heating, comprising: setting and optimizing field test parameters; conducting a background temperature monitoring test; performing a point-source active heating distributed temperature measurement test, including conducting multiple rounds of heating tests; denoising the obtained multi-point source thermal plume attenuation signal data of the groundwater; searching for the peak value of temperature-permeability curve based on an automatic multi-scale peak search algorithm; performing secondary processing on the peak data; estimating the groundwater flow velocity. The method of the present disclosure solves the problem that the existing groundwater flow velocity measurement technology cannot simultaneously measure multiple points and multiple layers, and it can avoid groundwater contamination during the measurement process.

The invention discloses a converter valve internal temperature monitoring and early warning method and system, and particularly relates to the technical field of converter valve temperature monitoring. Temperature sensors are arranged on a plurality of key heating units, local temperature data are collected in real time, a time sequence is built in combination with cooling water inlet and outlet temperature, a temperature trend prediction model is built based on temperature rise rate and temperature gradient change, local thermal runaway risks are accurately recognized, and a prediction result is compared with a grading threshold value, so that the local thermal runaway risk is determined. Multi-stage early warning signal output is realized, and a corresponding processing strategy is linked; under the extreme conditions that the local temperature is continuously and abnormally increased and the response of the cooling system is lagged, the system can trigger emergency shutdown protection in an override mode, device failure is avoided, the sensing capacity and response speed of local thermal faults are effectively improved, and the operation safety and the intelligent level of the converter valve system are remarkably improved.

The invention discloses a transformer multi-dimensional state sensing and diagnosing system, which comprises a multi-dimensional state sensing module for acquiring transformer multi-dimensional data in real time through various sensors; the data acquisition and processing module performs processing such as synchronous sampling and filtering on the data and extracts features; the state evaluation and fault diagnosis module evaluates a state and diagnoses a fault by using a three-dimensional evaluation model and a CNN-LSTM fusion model; the self-adaptive early warning module dynamically adjusts a threshold value according to an evaluation result and sends out multi-level early warning; the communication and interaction module realizes data encryption transmission, has a visual interface, and supports interaction diagnosis and remote configuration updating. The system can comprehensively collect data, accurately diagnose faults and efficiently early warn, is convenient to operate and maintain, and improves the operation reliability and the operation and maintenance efficiency of the transformer.

The invention provides a strain and temperature synchronous calibration method and device based on distributed optical fiber sensing, and relates to the technical field of optical fiber sensing calibration. Initial measurement node spacing and distribution density are obtained, reflected signals are captured according to simulated optical fiber layout, and time delay, intensity and phase change of the reflected signals are recorded; calculating a strain value and a temperature value of each measurement node, establishing a calibration model of a strain and temperature relationship, performing simulation by adopting a polynomial fitting method, obtaining and correcting real-time data, establishing a self-adaptive measurement node adjustment mechanism, and generating a calibration deviation coefficient by analyzing the deviation between the current monitoring data and a correction value. According to the invention, through the dynamic layout of the distributed optical fiber sensors and the self-adaptive measurement node adjustment mechanism, the high-precision calibration of the strain and the temperature of the key area of the structure is realized.

The invention relates to a thermal runaway monitoring method and related equipment for a new energy automobile power battery, and the method comprises the following steps: carrying out the internal temperature monitoring of the new energy automobile power battery, and obtaining the three-dimensional thermal field distribution data; thermal characteristics are analyzed, thermal runaway precursor characteristics are identified, the thermal runaway probability is calculated, and a probability distribution diagram is generated; in combination with the heat spreading prediction model, obtaining heat spreading path prediction data; and determining the out-of-control risk level of the battery according to the data, and generating a corresponding early warning signal, thereby solving the technical problems that the existing monitoring method mostly depends on threshold judgment of a single parameter, and complex thermal field change in the power battery of the new energy automobile is difficult to comprehensively capture.

The invention relates to a detection and analysis method and system for an energy storage system, and aims to improve the state monitoring precision, the fault early warning capability and the response intelligence level of the system. The method comprises the following steps: firstly, synchronously acquiring and transmitting multi-source data in real time through a sensor network deployed in a battery module, a power conversion unit and a cooling system; and then, key dynamic features are extracted from the multi-source data, and dynamic feature state information of the energy storage system is comprehensively formed. And inputting the state information into a pre-trained deep learning model, and outputting a health state score and a fault probability of the system. Based on the evaluation result and the fault traceability information, the system triggers a multi-level early warning mechanism and executes an active response strategy, and after response execution, the system re-evaluates the health state in a closed loop mode and verifies the response effect; and if the improvement does not reach the expectation, making a decision to start an artificial diagnosis protocol. According to the invention, a complete process from dynamic perception, intelligent diagnosis and accurate response to closed-loop verification is realized, and the safety and reliability of operation of the energy storage system are improved.

The invention discloses a safety monitoring system of a high transverse support system for cable-stayed bridge man-shaped tower column construction, and relates to the technical field of bridge construction monitoring, the system comprises a creeping formwork integrated sensing module used for generating a point cloud model by using a mechanical arm integrated on a hydraulic creeping formwork platform and a laser radar scanning tower column curved surface, combining with a preset building information model coordinate, adaptively adjusting the mounting posture of the sensor, and outputting the mounting coordinate position of the sensor; the optical fiber sensing network module is used for collecting original strain and temperature data by using a distributed optical fiber sensor deployed along a main stress path of the support truss; an inertial navigation fusion positioning module; a digital twinning early warning module; and an edge calculation relay module. According to the invention, a full-process monitoring chain from data acquisition to risk early warning is constructed through cooperation of multiple modules, full-period and multi-dimensional dynamic control of construction of the human-shaped tower column high transverse support system is realized, and timely perception and overall control of potential risks are ensured.

The invention relates to the technical field of sensor demodulation, in particular to a dynamic demodulation method and system for an MEMS optical fiber multi-parameter sensor. The method comprises the following steps: deploying a high-speed parallel acquisition sensor for an MEMS optical fiber multi-parameter sensor, acquiring spectral reflection and spectral time domain data, and constructing an original multi-parameter spectral data set; performing signal separation processing on the original multi-parameter spectral data set based on a preset hybrid network to obtain a wavelength-light intensity matrix, an input layer based on the preset hybrid network being the original multi-parameter spectral data set, and an output layer being the wavelength-light intensity matrix; therefore, by constructing an integrated data flow of original spectrum data acquisition, feature decoupling, parameter fusion and performance evaluation, the problems of large coupling error, weak noise suppression and uncontrollable demodulation precision in a traditional optical fiber multi-parameter demodulation model are solved; and the demodulation accuracy and practicability of the MEMS optical fiber sensor under the multi-physical-quantity complex working condition are improved.

The invention provides a rock-soil body multi-field coupling intelligent monitoring system comprising a multi-field sensing device configured to monitor parameters of a deformation field, a seepage field, a temperature field and a stress field of a rock-soil body; the edge calculation and transmission device is configured to perform preprocessing and real-time transmission on the multi-field sensing data; and the intelligent decision-making device is configured to analyze the preprocessed data based on a multi-field coupling model and generate disaster early warning information. According to the rock-soil body multi-field coupling monitoring system and method provided by the invention, synchronous monitoring of a deformation field, a seepage field, a temperature field and a stress field is realized through the multi-field sensing device; real-time data processing is performed in combination with an edge calculation and transmission device, and a dynamic early warning mechanism is established by using an intelligent decision-making device, so that the technical problems of multi-field data space-time correlation failure, insufficient multi-source data fusion precision and poor early warning mechanism adaptability are effectively solved, and the geological disaster early warning method has the remarkable advantages of improving the geological disaster early warning accuracy and timeliness.

The invention discloses an energy storage lithium ion battery thermal runaway multistage early warning method and system, and belongs to the technical field of lithium battery safety. The method comprises the steps that a three-dimensional closed-loop optical fiber monitoring network is constructed, distributed temperature sensing optical fibers are laid along the side face, the top face and the side face of a battery, and areas which are not smaller than 20 mm away from the center of a safety valve and not smaller than 15 mm away from a tab welding point are actively avoided; acquiring centimeter-level temperature field data through an optical fiber demodulator; and the processor calculates the temperature rise rate R and the temperature gradient G in real time based on the temperature field, and performs composite condition early warning. The triggering condition of the early warning is that when the temperature T of any measuring point reaches a preset threshold value, one of the temperature rise rate R and the temperature gradient G reaches the preset threshold value, and the proportion of all abnormal areas exceeding the threshold value in the total laying length of the optical fiber is not less than 30%, the early warning of the corresponding level is triggered. According to the method, local benign fluctuation can be effectively filtered, the false alarm rate is greatly reduced, and earlier and more accurate thermal runaway early prediction is realized.

The invention discloses a cable optical fiber temperature measurement monitoring system based on big data AI fusion, particularly relates to the technical field of cable optical fiber temperature measurement monitoring, and aims to realize thermal-electric dynamic coupling monitoring through high-density distributed optical fiber temperature measurement and big data AI fusion modeling and introduction of current load synchronous acquisition, and realize high-density distributed optical fiber temperature measurement and big data AI fusion by means of time synchronization and space relocation processing. The method comprises the following steps: identifying a weak response signal of a thermal inertia hysteresis characteristic and an initial temperature rise stage, constructing a cross-scale time sequence recurrent neural network through multi-dimensional enhancement and vector fusion, outputting a continuous scoring sequence reflecting abnormal credibility, and constructing a risk factor group reflecting a fault evolution path in combination with a scoring fluctuation amplitude, a continuous period and a response delay characteristic, and carrying out positioning offset correction through correlation mapping of risk factors and along-cable temperature distribution and by utilizing a topological relation between optical fiber path coordinates and a cable space, and realizing space reverse projection of an abnormal peak value, thereby recovering an accurate position of a fault heat source and a latent hidden danger section.

The invention relates to the field of civil engineering structure health monitoring, in particular to a subsea tunnel damage intelligent monitoring and identification method based on acousto-optic collaborative perception. The method sequentially comprises the steps of deploying a three-dimensional acousto-optic sensing network, actively detecting sound waves, reconstructing a local sound velocity distribution cloud picture, identifying a sound velocity abnormal region, performing optical fiber response focusing sampling and establishing an intelligent damage diagnosis model. According to the method, the three-dimensional acoustic array and the distributed optical fiber grid are simultaneously deployed in the subsea tunnel structure, functional complementation is realized between the three-dimensional acoustic array and the distributed optical fiber grid, seamless cooperative sensing of crack coarse positioning and strain fine positioning is further realized, acoustic active detection, trigger type optical fiber high-frequency sampling and a temperature-strain decoupling algorithm are adopted, and the positioning precision of the subsea tunnel structure is improved. Seawater noise and thermal expansion interference are effectively eliminated, 'dry cracks' and'water seepage cracks' are accurately distinguished, real-time monitoring is carried out on a subsea tunnel structure, whole-process identification of micro-damage-expansion-failure is achieved, and an active early warning mechanism is established.

The invention provides a tunnel deformation monitoring system and method based on a distributed optical fiber sensing technology, and relates to the technical field of tunnel monitoring. A spiral winding type optical fiber is arranged in the longitudinal axis direction of the surface of a tunnel lining, a transverse optical fiber is arranged on a key section, and the data acquisition frequency is set to be 1Hz. Dividing the optical fiber into a plurality of data acquisition points at equal intervals, obtaining the real-time temperature and Brillouin frequency shift change of each point, measuring the temperature and strain sensitivity coefficient, and calculating the total strain; calculating long-term temperature strain compensation based on the long-term temperature component, generating an instantaneous temperature difference through the real-time temperature and the long-term temperature component, further calculating instantaneous temperature strain compensation, subtracting the two kinds of strain compensation from the total strain to obtain stress strain, and evaluating the deformation level of the tunnel based on the stress strain. And the accuracy of evaluation is judged through clustering analysis.

The invention discloses a fault detonation simulation test method and platform for an extra-high voltage converter transformer network side bushing, and the method comprises the steps: providing a critical value calculation method for primary physical explosion and secondary chemical explosion of the extra-high voltage converter transformer network side bushing under different arc fault energy conditions; and the critical conditions of primary physical explosion and secondary chemical explosion can be accurately judged. According to the invention, the whole dynamic evolution process from rapid cracking of transformer oil and sudden pressure increase caused by converter transformer fault arc to superposition of physical explosion and explosion chemistry can be truly simulated, a grid-side bushing fault detonation critical discrimination method is provided, and technical parameters and theoretical support are provided for the explosion-proof and pressure-relief design of the converter transformer.

The invention relates to the technical field of structural stress precision measurement, in particular to a distributed optical fiber sensing-based steel structure stress monitoring method, which comprises the following steps of: 1, constructing a sensing optical fiber array in a steel structure node area; 2, injecting optical pulses into the sensing optical fiber array, and synchronously collecting Brillouin frequency shift signals and Raman scattering signals of all points; 3, temperature and mechanical strain are separated based on the reference optical fiber signals, global temperature compensation is adopted for the first optical fiber set, and temperature gradient compensation along the optical fiber path is adopted for the second optical fiber set; 4, decomposing the compensated mechanical strain into multidirectional strain components according to the spatial orientation of the optical fiber, and reconstructing a three-dimensional stress field through strain component fusion; and 5, dynamically judging the damage risk according to the local stress concentration coefficient and the change rate thereof in the stress field. And through the temperature compensation technology, the influence of the environment temperature change on the strain data is eliminated, and the reliability of the monitoring result is improved.

The invention discloses a temperature effect monitoring method and system for a metal roof, particularly relates to the technical field of building structure health monitoring, and is used for solving the problems of decoupling of temperature monitoring data and structural mechanical response, failure of a static early warning threshold and the like in the prior art. Acquiring three-dimensional temperature field data through a distributed temperature sensing network, and extracting a temperature gradient characteristic value from the three-dimensional temperature field data; a piezoelectric film sensor is used for collecting constraint point micro-vibration signals, and dynamic constraint reaction force spectrum characteristic values are extracted through signal transformation and manifold learning; establishing a temperature gradient and mechanical characteristic coupling model to generate a temperature stress evaluation value; dynamically adjusting an early warning threshold range according to the environmental parameters; when the evaluation value exceeds a threshold value, a structure safety early warning signal is output; multi-physical field coupling analysis of temperature field distribution and structural response is achieved, an environment-adaptive dynamic early warning mechanism is constructed, and the accuracy and reliability of metal roof temperature effect monitoring are remarkably improved.

The invention discloses a marine surveying and mapping method based on multi-beam sounding correction, and belongs to the technical field of marine surveying and mapping. The method comprises the following steps: acquiring sounding echo signals, sound wave propagation time delay data and temperature data through a multi-beam sonar array, an acoustic chromatography transceiving array and a laser Raman probe; and fusing the data to construct a dynamic refractive index field model, correcting sound ray refraction distortion by adopting an adaptive variable step size algorithm, carrying out weight allocation and data fusion on space-time adjacent beams to obtain high-confidence water depth, and generating an isobath topographic map. The problem of refraction distortion is solved through multi-source data fusion, the sound ray tracking step length is dynamically optimized, noise interference is suppressed through weighted fusion, and the precision and reliability of topographic surveying and mapping in complex environments such as a deep sea hydrothermal region are remarkably improved.

The invention relates to the technical field of industrial temperature measurement, in particular to a high-temperature heating body hearth temperature distribution measurement method, which comprises the following steps of: establishing a quantitative mapping relation model between real-time input electric power and theoretical heating intensity of a heating body; a limited number of temperature sensor arrays are arranged at key positions of the internal space of the hearth; synchronously acquiring a real-time temperature measurement value of the temperature sensor array and real-time input electric power data of the heating body; calculating and generating theoretical temperature field distribution covering the three-dimensional geometric model; obtaining a corrected temperature value; calculating the temperature residual error of the corrected temperature value and the theoretical temperature field distributed at the corresponding position of the sensor; expanding the discrete temperature residual error into a full-space three-dimensional residual error distribution field; and outputting the three-dimensional real-time temperature distribution field of the hearth. Dynamic lag compensation and convective heat transfer compensation algorithms are adopted, lag and errors in measured values can be corrected in real time, and it is ensured that measured data at high temperature have high response speed and accuracy.