1903 results about "Temperature measurement" patented technology

The invention discloses an intelligent self-monitoring temperature management system for a box-type substation, and relates to the technical field of intelligent power grid equipment monitoring. The problems that an existing system is large in temperature measurement deviation, low in reliability, delayed in early warning, inaccurate in hot spot positioning and extensive in heat dissipation control are solved. According to the scheme, multi-source signals are acquired in parallel through a data acquisition module, and a temperature time sequence is extracted; a boundary calibration module is adopted to fuse data to generate a three-dimensional boundary condition; the multi-physical field solving module obtains an internal temperature / stress field; the physical information prediction module is fused with a heat transfer physical constraint training graph neural network to predict a hotspot migration trend; the hierarchical scheduling module is used for solving a fan and oil pump collaborative optimization instruction in real time based on model predictive control; according to the invention, the accuracy of internal temperature monitoring of the box transformer substation, the reliability of hot spot prediction and the accuracy of heat dissipation control are remarkably improved, the insulation life of equipment is effectively prolonged, and the operation safety and reliability of the system are improved.

The invention relates to the technical field of bolt tightening, and provides an intelligent bolt tightening control method and system based on axial force measurement. Comprising the steps of collecting bolt identification and process parameter data, collecting temperature measurement data, and obtaining sound velocity compensation parameters and elastic modulus compensation parameters. And zero-load preloading data are collected and processed to generate zero-load baseline data, and a self-calibration model is obtained. Axial force data and ultrasonic echo data are collected, and an axial force fusion estimation result is obtained. And comparing an axial force fusion estimation result with target axial force data. And when in the target interval, fine twisting control is carried out based on model predictive control and a micro-stepping strategy, and the controllable damping unit is driven to carry out energy absorption and stopping. And acquiring an axial force fusion estimation result when the target axial force is reached, processing the data in the holding stage to obtain an axial force rebound check result, and if the axial force rebound check result exceeds the limit, performing secondary twisting control. According to the scheme, refinement and traceability of the bolt tightening process are achieved.

The invention discloses a PID temperature control system and method for a semiconductor etching machine, and relates to the field of temperature control, and the system comprises a coupling relation construction module, a temperature sensing confidence module, a decoupling compensation module, a coupling relation dynamic updating module, and a transient temperature change control module. According to the invention, by constructing the coupling relation matrix and the inverse matrix thereof, decoupling control of multi-area temperature control is realized, cross interference is effectively suppressed, and the temperature control precision is improved. And a multi-point temperature measurement fusion and anti-interference algorithm is introduced, so that the temperature measurement accuracy and the system robustness are enhanced. A response residual vector is associated with a control vector, and a coupling matrix is dynamically optimized, so that the system has self-learning and model self-adaption capabilities and adapts to working condition changes. And a transient temperature change quick response mechanism is set, so that the control priority can be improved and the PID parameters can be adjusted when the temperature changes suddenly, the response speed and the control stability of the system to abnormal temperature change are remarkably improved, and the thermal uniformity and the process consistency in the etching process are ensured.

The invention discloses a platinum resistor high-precision temperature measuring device capable of automatically identifying a wiring mode. The platinum resistor high-precision temperature measuring device comprises a power supply module, a signal detection module, an isolation module, a signal processing module and a cold end temperature measuring module. The power supply module supplies power to the signal detection and processing module. The signal detection module comprises a sensing probe, a wiring identification circuit, a constant current source, a measuring circuit and an analog-to-digital conversion circuit. The sensing probe measures the measured temperature, the wiring identification circuit automatically judges a two-wire system, a three-wire system or a four-wire system and feeds back a result, the constant current source provides positive and negative constant current excitation, and the measuring circuit collects and processes feedback voltage and then sends the feedback voltage to the analog-to-digital conversion circuit. The analog-to-digital conversion circuit is connected with the signal processing module through the isolation module, and the signal processing module calls a corresponding algorithm according to a wiring identification result and outputs final temperature data. According to the invention, high-precision temperature measurement at the grade of + / -0.02 DEG C can be realized in the range of-200 DEG C to 850 DEG C under the three / four-wire system and low-speed sampling conditions.

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.

The invention relates to a boiler flue gas temperature dynamic compensation method based on CFD-reinforcement learning, and belongs to the technical field of boiler operation control. The method comprises the steps that boiler operation parameters and flue gas temperature data are collected in real time, a multi-scale coupling three-dimensional CFD model is constructed, a macroscopic gas-solid two-phase flow-combustion reaction-radiation heat transfer coupling algorithm and a microcosmic pulverized coal particle combustion dynamics algorithm are fused, and hearth and flue temperature distribution is simulated and output; building a CFD-reinforcement learning fusion agent based on a CFD model, taking similar working condition agent parameters as initial values, combining historical and virtual data staged training, and reinforcing the weight of a key temperature measurement point through a focusing regulation and control strategy; an echo state network-predictive control collaborative algorithm is adopted, real-time data are input to obtain an initial adjustment amount, and after security constraint optimization, a compensation execution mechanism is controlled to act. The flue gas temperature is accurately and dynamically compensated, the adaptability to complex working conditions is improved, and equipment safety and operation efficiency are both considered.

The invention discloses a multi-dimensional data-based temperature prediction method and system for a power integrated module, particularly relates to the technical field of temperature measurement, and is used for solving the problems of temperature field distortion and unreliable measurement result caused by thermal disturbance introduced by a sensor in temperature monitoring of an existing power integrated module. Multi-dimensional temperature data are formed by acquiring measurement data of a plurality of temperature sensors, a virtual heat flow path is reconstructed based on temperature gradient distribution, deviation degree analysis is carried out on the virtual heat flow path and an inherent structure heat flow path of a module so as to judge thermal disturbance influence, and reference isothermal surface topological structure features are acquired when disturbance occurs. A real-time isothermal surface is constructed, a thermal disturbance space position and an influence range are identified by detecting a curvature distribution sudden change area, a local thermal conductivity correction field is established to perform thermal field reconstruction on multi-dimensional temperature data to generate correction temperature field data, and finally a temperature change trend is analyzed according to the correction temperature field data to predict a future temperature state.

The invention relates to the technical field of switch cabinet temperature measurement, and discloses a method for measuring the temperature of a switch cabinet in real time through an infrared matrix based on multi-modal sensing. The method comprises the following steps: synchronously acquiring an infrared image sequence, an acoustic vibration signal and current waveform data of the switch cabinet through a multi-mode sensor array, and capturing equipment operation and temperature associated information; constructing a three-dimensional temperature field reconstruction mechanism model based on a heat conduction physical equation, outputting a theoretical temperature distribution value fitting a physical rule, processing multi-source data by using a spatial-temporal feature extraction network, and outputting a temperature prediction value reflecting a real-time working condition; inputting the two into a dynamic fusion module based on a Markov decision process to generate a fusion temperature distribution value, and generating a temperature anomaly positioning instruction through a rolling time domain optimization strategy according to the fusion temperature distribution value; when the deviation between the actual temperature sampling value and the fused temperature distribution value exceeds a preset threshold value, calibrating a network output layer parameter; and triggering a linkage control protocol of the switch cabinet protection system according to the abnormal positioning instruction.

The invention discloses a power equipment temperature monitoring and early warning system and method based on wireless communication, and relates to the technical field of temperature monitoring, the system comprises a wireless temperature measurement terminal box and a mobile terminal APP, the wireless temperature measurement terminal box and the mobile terminal APP establish communication connection based on a wireless network, and the wireless temperature measurement terminal box is fixedly installed on power equipment; the wireless temperature measurement terminal box comprises an electromagnetic environment judgment module which monitors and judges whether interference exists in the environment where power equipment is located in real time based on an electromagnetic sensor and synchronizes a result into a temperature drift compensation analysis module; and the temperature monitoring module monitors temperature data in the power equipment in real time based on a temperature sensor. Through electromagnetic environment judgment and temperature drift compensation, historical data and a model are combined to dynamically correct interfered temperature data, the influence of electromagnetic interference is eliminated, real-time monitoring is matched with graded alarm, hidden dangers can be found in time, response can be made according to risk grades, accidents are avoided, and wireless connection adapts to complex scenes.

The invention provides a thermocouple temperature measurement adaptive anti-interference method and system applied to an instrument, and relates to the technical field of temperature measurement and control, and the method comprises the steps: obtaining an original thermocouple temperature measurement signal generated by a thermocouple body, carrying out the cold end compensation of the original thermocouple temperature measurement signal, and obtaining a standard thermocouple temperature measurement signal; respectively processing the standard thermocouple temperature measurement signals to obtain corrected thermocouple temperature measurement signals; the corrected thermocouple temperature measurement signal and the closed-loop manipulated variable are used as observed quantities to be input into the extended state disturbance model, an unknown equivalent disturbance quantity corresponding to the corrected thermocouple temperature measurement signal is obtained, and a predicted temperature deviation value and a predicted equivalent disturbance quantity are obtained through an extended state observer; and dynamically adjusting the gain of the PID controller by using a fuzzy self-tuning algorithm, carrying out superposition processing on the PID control quantity and the compensation quantity corresponding to the predicted equivalent disturbance quantity, and compensating the temperature controller by using a temperature regulation and control instruction. According to the invention, the steady-state disturbance suppression capability and the response speed can be improved.

The invention provides a substation safety intelligent monitoring method based on infrared binocular vision, which comprises the following steps: acquiring an infrared radiation image, a visible light image and environmental parameters of equipment, and accurately inverting the real temperature of the equipment after eliminating environmental interference in combination with a depth distance calculation and physical compensation model; a historical time sequence of a real temperature is used to construct a multi-dimensional state vector fusing a thermal feature, a spatial feature and an environment feature, and intelligent classification evaluation of the security risk of the transformer substation is realized through an improved decision tree model. Meanwhile, a time sequence prediction model is introduced to predict the temperature rise trend of the equipment, the remaining time for reaching an early warning threshold value is calculated, and a dynamic grading early warning report is generated. According to the method, the temperature measurement precision and the risk identification accuracy are effectively improved, early warning and active prevention and control of the operation state of the equipment are realized, and the operation safety and the intelligent operation and maintenance level of the transformer substation are remarkably improved.

The invention provides a temperature compensation method and system of a mass flowmeter, and relates to the technical field of mass flowmeters.The method comprises the steps that a space temperature field and a strain field covering a whole measuring pipe body are obtained, and a distributed heat-force coupling state is constructed; configuring a primary disturbance parameter set, projecting the primary disturbance parameter set to a natural vibration mode space, and constructing an equivalent temperature disturbance quantity; configuring the excitation frequency of dual-frequency vibration excitation; inputting a double-frequency response result into a temperature-flow decoupling model, and inversely constructing a temperature compensation factor; calculating an original estimated value of the flow, constructing a temperature compensation amount, fusing the original estimated value of the flow, and outputting a measurement result. The technical problem that in the prior art, due to the fact that single-point temperature measurement cannot accurately decouple the temperature effect under the complex working condition, measurement of the mass flow meter is inaccurate is solved, the space temperature field and the strain field of the whole measurement pipe body are obtained, self-adaptive compensation is conducted on sensitivity drifting of the measurement pipe, and the measurement accuracy is improved. And the measurement precision of the mass flow meter is improved.

The invention provides an electric kettle heating control method and system based on intelligent temperature control, and relates to the technical field of household appliances. A multi-dimensional temperature measurement module is introduced, a plurality of high-precision temperature sensors are distributed at different positions in an electric kettle, and temperature distribution information of the different positions in the kettle can be obtained in real time; and local temperature misjudgment caused by a single sensor is effectively avoided. Meanwhile, the water level detection module can accurately measure the real-time water volume. On the basis, the system can dynamically distribute contribution indexes of all temperature measurement point positions according to the real-time water quantity, the heating power is adjusted in real time in combination with a PID algorithm, the temperature control precision and stability are remarkably improved, temperature misjudgment is reduced, accurate control over the heating process is achieved, and it is ensured that the water temperature can accurately reach the target temperature set by a user.

The invention discloses a temperature and gas detection system and method based on an ultraviolet to near infrared spectrum, relates to the technical field of spectral measurement, and solves the technical problems that the space in a smelting furnace is occupied and the complexity of the system is increased due to the fact that two sets of independent equipment are adopted for temperature measurement and environment monitoring in the smelting process respectively in the prior art. The method comprises the following steps: acquiring spontaneous radiation light of a to-be-detected target; carrying out dispersive light splitting on the spontaneous radiation light to obtain spectral data of a full wave band from ultraviolet light to near-infrared light; performing denoising processing on the spectral data to obtain a spectrum of the to-be-detected target; obtaining temperature data according to the spectral analysis of the to-be-detected target; calculating based on the spectrum and a pre-established spectrum database to obtain gas concentration; the temperature of the to-be-measured target can be accurately measured, and the measurement accuracy is improved.

According to the infrared fast patrol method based on task sequence control provided by the invention, the robot is guided to pre-adjust the pan-tilt angle and the infrared focal length during advancing through task sequence planning, and the target is intelligently positioned by synchronously utilizing the equipment template library, so that continuous temperature measurement during movement is realized; performing multi-view infrared image comparative analysis on the temperature exceeding equipment through a multi-angle abnormity rechecking strategy; abnormal equipment outside a preset point location is positioned in real time in combination with a laser point cloud map and space coordinate conversion, the parking time of the robot is eliminated, the temperature measurement efficiency is improved, environmental interference is effectively eliminated, the misjudgment rate is reduced, and a high-timeliness and high-reliability global temperature monitoring defense line is constructed for safe operation of industrial equipment.

The invention provides a temperature measurement system and compensation method of non-direct contact fluid, and relates to the technical field of temperature detection. The temperature measurement system comprises a dynamic compensation module, a steady-state deviation compensation module and a steady-state judgment module, the temperature sensor collects the temperature value of fluid which is not in direct contact with the temperature sensor, and the temperature value is subjected to hysteresis compensation through the dynamic compensation module. The steady state judgment module judges whether the temperature is in a steady state or not according to the temperature value subjected to hysteresis compensation, and if not, the temperature value subjected to hysteresis compensation is output; if yes, a steady-state deviation compensation module carries out steady-state deviation compensation on the temperature value after hysteresis compensation and then outputs the temperature value. The temperature measurement system can effectively improve the accuracy and response characteristics of non-contact fluid temperature measurement by combining dual mechanisms of dynamic compensation and steady-state deviation compensation.

The invention provides a food pre-cooling temperature prediction method and device based on deep learning, and the method is characterized in that the method comprises the steps: obtaining the temperature time sequence data of a plurality of temperature measurement points based on the given technological parameter data measurement in the ventilation pre-cooling process of target food; preprocessing the temperature time sequence data to obtain a temperature fusion feature sequence; and inputting the temperature fusion feature sequence into a fusion deep learning model, and outputting a temperature prediction result. According to the method, errors caused by manual intervention are reduced, and the precision of temperature prediction in food ventilation and precooling is remarkably improved.

A temperature probe is mountable within a thermowell having an inner bore having an end shape at an end. The temperature probe includes a probe body configured to be mounted within a thermowell. A temperature sensitive element is disposed within the probe body and has an electrical characteristic that varies with temperature. An end cap is connected to the probe body and has a surface profile shaped to match the end shape of the bore of the thermowell. A temperature measurement system is also provided that employs a thermowell and a temperature probe having a geometrically matching end cap.

The invention discloses a signal reconstruction and noise suppression method and system for a distributed Raman temperature measurement sensing system, and the method comprises the steps: obtaining original anti-Stokes light and Stokes light time domain signals of the distributed Raman temperature measurement sensing system, and constructing a space-time signal matrix; performing preprocessing and data enhancement on the space-time signal matrix; constructing a dual-path feature fusion network for Raman signal reconstruction and noise suppression, and initializing the network; defining a loss function fusing temperature physical constraints, and training the dual-path feature fusion network; and inputting an original Raman signal to be processed into the trained network, outputting the reconstructed anti-Stokes and Stokes signals with the high signal-to-noise ratio, and carrying out temperature demodulation according to the anti-Stokes and Stokes signals with the high signal-to-noise ratio. While the spatial resolution is maintained or improved, the noise of the Raman temperature measurement system is effectively suppressed, especially the real signal of a temperature abrupt change point can be recovered, the temperature demodulation precision, stability and reliability are improved, and reliable data are provided for infrastructure safety monitoring.

The invention discloses a cable temperature detection method, which comprises the following steps: laying distributed optical fibers along a to-be-monitored cable, synchronously obtaining whole-line temperature, vibration sound wave signals and load current data, and carrying out dynamic compensation and correction on a temperature measurement value; on the basis of multi-source information fusion, abnormal points are accurately positioned, a cable multi-physical field digital twinborn model is constructed, a health index reflecting the insulation condition is calculated in real time, and quantitative evaluation of local and overall states is achieved; further simulating different load scenes to predict the time when the insulation performance is degraded to a failure threshold value, so as to output probability distribution of the remaining service life of the cable; according to the method, the whole-process intelligentization from accurate temperature measurement and abnormal positioning to state evaluation and life prediction is realized, and the perspectiveness and reliability of cable operation and maintenance are remarkably improved.

The invention relates to the technical field of infrared measurement, in particular to an intelligent calibration method and system for temperature measurement of an infrared sensor, and the method comprises the steps: enabling an infrared camera to align with a blackbody radiation source to form a calibration scene, collecting the output of a plurality of groups of pixels under different radiation temperatures and different internal part temperature states, fitting a temperature signal response model containing an exponential term and a bias term according to least square to obtain amplitude, exponential, temperature offset and output bias parameters; during measurement, a thermal image containing a target object and two reference blackbody sources is obtained, and parameters such as emissivity, environment equivalent radiation temperature, transmission medium and optical transmission, camera temperature and the like are synchronously obtained; performing non-uniformity and offset correction and abnormal pixel replacement on the thermal image; the initial temperature is inverted based on radiation transfer decomposition and compensation of internal radiation of the camera; and carrying out statistical averaging on the temperatures of the two blackbody reference regions to obtain a double-point correction coefficient, and outputting correction temperature or temperature distribution. According to the method, the problems that temperature inversion model parameters are difficult to adaptively update along with working conditions and on-site temperature measurement errors are difficult to effectively suppress when an existing infrared sensor array is in a long-distance non-contact temperature measurement scene can be solved.

The invention discloses a distributed optical fiber temperature measurement verification device and method.The device comprises a constant temperature device, a lifting device, a measurement and control host and automatic verification software, the constant temperature device comprises a constant temperature bath and a constant temperature control device, the constant temperature bath comprises a mixing area and a working area, the lifting device drives a test tool to ascend and descend, and the test tool fixes a temperature measurement optical cable; the temperature measurement optical cable is connected with the temperature measurement host, the temperature measurement host feeds back a temperature measurement value to the measurement and control host, the measurement and control host compares the measurement value with a temperature value of a medium in the constant temperature device, and distributed optical fiber temperature measurement verification is achieved. The method passes a temperature measurement range and accuracy test; performing a temperature resolution test; performing a spatial resolution test; testing positioning accuracy; a single-channel test time test comprises six tests, data are automatically collected and analyzed, and a verification report is generated. The device is reasonable in structural design and high in universality, automatic control over the verification process is achieved, data collection, analysis, calculation and report generation are all automatically completed, and verification efficiency is improved.

The invention provides an explosion-proof electric appliance overcurrent and temperature rise wireless test system and method based on ultrasonic communication, and relates to the technical field of explosion-proof electric appliance temperature rise tests. The system comprises a temperature acquisition device, an ultrasonic through-wall communication device, an overcurrent protection time acquisition device, a data receiving and storing device and a digital display operation table, wherein the output end of the temperature acquisition device is connected with the input end of the ultrasonic through-wall communication device, the output end of the ultrasonic through-wall communication device is connected with the input end of the data receiving and storing device through wireless communication, and the output end of the overcurrent protection time acquisition device is connected with the input end of the data receiving and storing device; and the data receiving memory is connected with the digital display console through a bidirectional data channel. According to the invention, the anti-interference performance and the test precision of temperature measurement are enhanced, and the multi-node distributed monitoring capability is provided through multi-channel data transmission, so that the overall efficiency of the internal temperature and overcurrent protection monitoring of the explosion-proof electric appliance is greatly improved.

The invention discloses a temperature anomaly identification method, a control device and a battery system, and relates to the technical field of battery management, and the method comprises the steps: obtaining the temperature values of a plurality of temperature measurement points in the battery system; acquiring a difference value of the temperature values of the same temperature measurement point at two adjacent acquisition moments, and judging whether the temperature measurement point has temperature jump according to the difference value; and / or, acquiring an average temperature value of the temperature values of the plurality of temperature measurement points at the same acquisition moment, and judging whether the battery system has uneven temperature distribution or not according to the deviation between each temperature measurement point and the average temperature value. According to the invention, the temperature change of the plurality of battery cell positions is monitored in real time, and according to the temperature difference of the same temperature measurement point at adjacent moments and the deviation of different temperature measurement points at the same moment, the temperature jump and uneven temperature distribution abnormity of the battery system can be quickly and accurately identified, so that the temperature abnormity can be found and early warned in time, and the battery thermal runaway accident can be effectively avoided.

The invention discloses a high-carbon ferro-chrome smelting control method based on a submerged arc furnace, and relates to the field of high-carbon ferro-chrome smelting control, and the high-carbon ferro-chrome smelting control method comprises the following steps: constructing a three-dimensional temperature measurement network, generating temperature field distribution in the furnace based on three-dimensional space coordinates of all temperature measurement points, and further extracting boundary position coordinates and volume change trend of a molten pool; the method comprises the following steps: performing matching degree calculation on an electrode position impedance gradient curve and a molten pool boundary change trend to diagnose the structural stability of a crucible area, calculating the partial pressure ratio of key components based on hearth pressure, and comprehensively diagnosing the overall health state grade of the furnace condition in the furnace in combination with the structural stability state of the crucible area in the furnace; according to the diagnosed overall health state grade of the furnace condition, the proportion of the chromium ore, the coke and the flux is dynamically adjusted, accurate sensing of the multi-dimensional state in the furnace and grading diagnosis of the furnace condition are achieved, the problems of insufficient reduction of raw materials, waste of the chromium ore and the like can be avoided in time, and the product purity and the smelting stability are guaranteed.

The invention discloses a mass concrete temperature measurement early warning method and system, and belongs to the technical field of building engineering construction, and the method comprises the following steps: arranging a plurality of temperature sensor nodes in concrete through three-dimensional distributed real-time temperature collection, and collecting temperature data; performing temperature field reconstruction by using an edge computing gateway to generate a three-dimensional temperature cloud picture in the concrete; using an LSTM neural network to predict a future temperature change curve; calculating the temperature difference and the temperature rise rate of each node and the surface layer in real time, and dynamically determining a threshold value; and triggering multi-stage early warning, automatically starting a cooling system and pushing alarm information. According to the system, high-precision reconstruction of a three-dimensional temperature field in concrete and accurate prediction of a temperature change trend can be realized, generation of temperature cracks is effectively prevented through dynamic threshold determination and a multi-stage early warning mechanism, and the safety and durability of a mass concrete structure are ensured.

The invention discloses a method and system for optimizing temperature uniformity of a hearth of a temperature isostatic pressing machine, and the method comprises the steps: arranging a plurality of layers of temperature measurement planes and a temperature monitoring network in the hearth, collecting all-region temperature data in real time, calculating three-dimensional temperature field distribution and uniformity indexes, generating a heater power regulation and control instruction in combination with the indexes, and controlling the temperature uniformity of the hearth of the temperature isostatic pressing machine. And dynamically adjusting the output power of the partitioned independent controllable heater array. According to the method, the whole area of a hearth is covered through multi-layer temperature measurement, temperature uniformity is evaluated through quantitative indexes, prospective power compensation is achieved with the help of a predictive control algorithm, control parameters are optimized through a thermodynamic simulation model, the problems that a traditional temperature isostatic pressing machine is incomplete in temperature monitoring and poor in heating regulation and control pertinence are solved, and the temperature isostatic pressing efficiency is improved. And the temperature uniformity of the hearth is greatly improved, the heating consistency of workpieces is guaranteed, and the device is suitable for a warm isostatic pressing machining scene of high-precision material forming.

The invention relates to a cable early-stage fault parameter extraction method and system fusing temperature rise process data, and relates to the technical field of cable fault monitoring, and the method comprises the steps: receiving multi-node temperature rise data uploaded by a temperature measurement optical fiber for a to-be-detected cable in a conduction state, comparing the multi-node temperature rise data with a cable rated condition, extracting deviation information with a standard temperature rise curve, and calculating the temperature rise process data of the to-be-detected cable; setting first and second fault characteristic indexes; drawing up a fault parameter extraction atlas in combination with the deviation information and the first and second fault characteristic indexes; and according to the attenuation coefficient, the early fault calorific value under different equivalent insulation resistances is taken as a core association feature, a fault influence range is evaluated, and a dynamic threshold adjustment rule is used for fault reminding. The cable fault detection method solves the problems that in traditional cable fault detection, early fault feature capture is not sensitive, missing detection is prone to occurring, and the fault judgment accuracy is insufficient due to the fact that the cable operation state and environmental factors are not fully combined.

The invention relates to the technical field of temperature sensors, in particular to a temperature sensor dynamic response acceleration method and system for medical liver testing, and the method comprises the steps: collecting an original temperature measurement sequence outputted by a main temperature sensor in a first target region in real time, synchronously acquiring a reference temperature sequence output by a reference temperature sensor located in a second target area; and based on the physical characteristics of the main temperature sensor and the heat exchange characteristics of the liver tissue, constructing a sensor and liver tissue dynamic response model containing key dynamic parameter vectors. The dynamic response model of the sensor and the liver tissue is constructed, the dynamic characteristics of the sensor and the tissue in the current environment can be accurately quantified, thermal inertia and conduction delay are actively compensated from the algorithm level through the model inverse function, the real-time performance of temperature monitoring is remarkably improved, and the temperature monitoring accuracy is improved. And a timely and reliable feedback signal is provided for closed-loop control.

The invention relates to the technical field of air conditioner control, in particular to an air conditioner control method and system based on multi-sensor fusion, a first temperature sensor obtains the temperature of a single point, and a second temperature sensor obtains temperature array data; based on a frame difference filtering algorithm, the number of indoor people and human body coordinate positions are detected, disturbance of the human body temperature to the environment temperature is filtered, the temperature of the first temperature sensor and the temperature of the second temperature sensor are fused through a weighted average method, and the indoor average temperature is obtained; and controlling the power of the compressor and adjusting the angle of the air guide strip according to the temperature difference between the indoor average temperature and the set temperature. Errors caused by a traditional single temperature measurement mode are effectively avoided, the indoor environment temperature detection precision is improved, the number of people in a room and human body coordinate position information can be detected in real time, interference of human body temperature on environment temperature measurement can be removed, the intelligent sensing capacity of an air conditioner system is achieved, and the indoor environment temperature detection precision is improved. And the somatosensory comfort of the user is improved.