1608results about "Material capacitance" patented technology

The embodiment of the invention provides a soil nutrient spectrum detection and regulation method and system, and belongs to the technical field of soil nutrient spectrum detection and regulation. The method comprises the following steps: collecting soil multispectral original data and environmental data, generating a calibration matrix and a nonlinear correction parameter, executing optical reflectivity conversion, and synchronously fusing a time domain reflectometry dielectric constant and a spectral moisture index to obtain fused moisture content; selecting a nutrient diagnosis characteristic wave band pair to obtain a moisture inhibition type spectral index; and predicting the soil nutrient content by using a pre-trained transfer learning model to obtain a soil nutrient content prediction value, and performing fertilization regulation and control based on the fertilization decision risk coefficient. According to the invention, extreme soil moisture measurement deviation is solved through a soil type adaptive moisture fusion technology; through multi-source risk quantitative decision and PID self-adaptive regulation and control, the fertilization amount can be dynamically optimized, execution safety is guaranteed, and a detection-decision-execution precision agriculture closed loop is formed.

The invention relates to the technical field of water pollution detection, in particular to a water quality pollution multi-dimensional analysis system which comprises the following steps: synchronously measuring an ultraviolet-visible absorption spectrum of a water sample to be detected and scattered light intensity in an orthogonal direction, and deducting spectrum baseline interference caused by suspended particulate matters in the water sample through a correction algorithm; the interferents in the water sample are selectively converted and degraded by applying a programmed potential to the inflowing water sample to be detected; the reverse pulse is periodically applied, so that the online regeneration function of the electrode is realized; analyzing the spectral data by adopting a multivariate correction algorithm, and calculating the concentration of the target pollutant; the calculation residual error of the multivariate correction algorithm is analyzed, new interference and system performance drift of current measurement are diagnosed, and a corresponding system state code is generated; and responding to the system state code, automatically starting and carrying out state checking and multi-point calibration on the instrument, and using a calibration result to update the analysis model. Through multi-dimensional perception and closed-loop operation, accuracy and reliability of water quality monitoring are guaranteed.

The invention discloses a farmland environment multi-parameter intelligent monitoring system and method based on Internet of Things, particularly relates to the technical field of agricultural Internet of Things monitoring, and is used for solving the problem of stress resistance evaluation distortion caused by neglecting crop physiological recovery hysteresis in the prior art. Collecting soil water content data in real time through an Internet of Things sensor, and extracting a soil water content change rate when a preset threshold value is reached; secondly, constructing a space-time gradient matrix based on different soil layer water deficit rates, and generating a stress cumulative intensity index through principal component analysis and information entropy fusion; then analyzing a coupling relationship between the soil moisture change rate and the stress accumulation effect in the historical stress event on physiological recovery delay to generate a recovery delay coefficient; the physiological state lag degree is evaluated by combining the stomatal conductance change rate ratio of the stress period and the recovery period and the recovery delay coefficient; and finally, dynamically prolonging the irrigation execution time according to the lag degree until the irrigation execution time is lower than a set tolerance value, thereby remarkably improving the reliability of crop stress resistance test data.

The invention relates to the technical field of livestock breeding, in particular to a cow manure automatic scoring system and method.The cow manure automatic scoring system comprises an image acquisition unit, a physical property sensor, a chemical component detection module and a data processing unit.The image acquisition unit is used for capturing the form, color and fiber residue of manure; the physical property sensor is used for measuring the water content of excrement and evaluating the viscosity and hardness of the excrement; the chemical component detection module comprises a near infrared spectrum analysis unit and an electrochemical sensor unit; and the data processing unit is used for integrating an AI algorithm, realizing multi-source data fusion and scoring, and uploading the data to the cloud management platform through the communication module. Therefore, the problems that in the prior art, manual scoring is subjective, low in efficiency and difficult to quantify, diseases are difficult to find early due to the lack of rapid component detection means, and accurate nutrition regulation and control are difficult to achieve due to the fact that scoring data are difficult to integrate into a breeding system are solved.

The invention relates to the field of environmental monitoring, and discloses a comprehensive soil detection method, which comprises the following steps: S1, deploying a multi-parameter sensor network, and dynamically configuring node density and a communication protocol according to soil heterogeneity and environmental interference factors; s2, abnormal data cleaning of three-level joint verification is executed, wherein single-parameter statistical verification, multi-parameter materialization association verification and historical pollution mode matching are included; s3, realizing adaptive sampling control by adopting a three-layer decision model, wherein the adaptive sampling control comprises rule driving adjustment, reinforcement learning optimization and sudden pollution emergency response; and S4, based on dynamic weight distribution and nonlinear effect modeling, calculating a soil health index (SHI). According to the invention, through a heterogeneity-driven node density adaptive technology and in combination with LoRa-ZigBee dual-mode communication dynamic switching, compared with an existing single protocol networking scheme, the problem of data fault caused by signal attenuation under a complex terrain is solved.

The invention provides an abnormal blood sampling inspection data evaluation processing method and system of a blood sampling system. Wherein the diffusion track dynamic state of an anticoagulant-blood contact surface in a blood sampling tube is tracked in real time, dielectric response waveform distortion characteristics on the two sides are synchronously collected through a capacitance sensor array, and diffusion form parameters are generated; curvature sudden change is analyzed to trigger an acoustic fluid device to modulate audio frequency and flow velocity, and a composite disturbance field is formed; performing capacitance axial scanning on the disturbed mixed fluid, extracting phase angle offset and gradient abrupt change point coordinates, and constructing a dielectric anomaly three-dimensional map; matching a standard dielectric model, positioning a coordinate set of a concentration gradient imbalance area and a coordinate set of an eddy current attenuation area, and generating an anticoagulant abnormal index and a mixed defect matrix in combination with phase angle offset difference; and establishing a data anomaly degree evaluation function based on the anomaly index and the defect matrix, dynamically associating a clinical error threshold, and outputting a test evaluation result. According to the invention, anticoagulant diffusion can be monitored in real time, and the mixing quality error can be accurately evaluated.

The invention discloses a method for predicting the damage of a prestressed concrete cylinder pipe in a complex environment, and relates to the technical field of pipeline structure health monitoring, and the method comprises the steps: collecting multi-physical field data through deploying multiple types of sensors, transmitting the data to a central monitoring system in a wireless manner, carrying out the standardized preprocessing, and obtaining a multi-source fusion data set; a salt migration driving index dsa, a stress disturbance induction index yry and an electrochemical activity potential index che are constructed, a comprehensive corrosion risk index SCR is obtained, and corrosion behavior evaluation is carried out. And when the corrosion behavior is evaluated as a disturbance sign, a corrosion change prediction index CAR is further calculated according to time sequence evolution forming a corrosion risk index SCR, grading evaluation and transition identification of the corrosion state are realized, an evaluation result is stored in a database, and a corrosion risk evolution trend is presented through a visual chart. The method supports early warning and emergency response decision making, and has high adaptability and engineering practicability without adding hardware.

A non-invasive liquid integrity monitoring system using dielectric fingerprinting and machine learning to detect and identify contamination in sealed containers is described. The system may employ externally-mounted sensors that measure dielectric properties through electromagnetic interrogation, comparing measurements against baseline signatures to detect deviations indicating contamination, tampering, or degradation. Industry-specific ML models enable identification of specific contaminants with confidence, providing alerts without breaching container integrity.

The invention provides an oil-immersed transformer cooling oil state online monitoring system and a self-calibration method based on multi-modal sensing and deep learning, and belongs to the technical field of intelligent operation and maintenance of power equipment, and the system comprises an embedded sensing array unit, a self-adaptive dynamic calibration unit, an edge intelligent analysis unit and a cloud collaborative optimization platform unit. According to the invention, full-dimension sensing is realized, physical (flow velocity / temperature), chemical (gas / moisture) and mechanical (particle pollution) states of oil are covered at the same time, detection parameters are expanded to more than 12 items, self-calibration anti-interference is realized, and a long-term measurement error is controlled within + / -1.5% through reference oil sample comparison and an environment compensation algorithm.

The invention discloses a tower grounding grid multi-frequency composite wave electric field imaging and soil environment medium diagnosis method, which comprises the following steps of: generating a composite excitation signal through superposition of a low-frequency sine wave and a high-frequency CHIRP square wave, and collecting multi-dimensional data such as voltage / current response, soil temperature and humidity, electric field intensity and the like in combination with a distributed sensor array; separating signal features by using wavelet transform and extracting impedance information of a target frequency point; a multi-grid homotopy algorithm is adopted to realize grounding grid three-dimensional resistivity distribution reconstruction, corrosion spots and abnormal areas are marked, and high-precision positioning of underground conductors is completed through UWB radar or a capacitance detector; meanwhile, based on the information entropy maximization optimization frequency band combination, the grounding grid state is comprehensively evaluated in combination with a multi-parameter fusion model. The method has the non-contact patrol capability, the unmanned aerial vehicle carries equipment to scan the grounding grid, the detection efficiency and convenience are remarkably improved, and an efficient and accurate solution is provided for guaranteeing safe operation of the power grid.

According to one embodiment, a sensor includes a structure. The structure includes a first layer, a first film including a first film region, and a first intermediate layer including a first partial region. The first partial region is between the first layer and the first film region. A volume of the first layer is changeable depending on a detection target around the structure. The first film includes silicon and oxygen. The first intermediate layer includes at least one selected from the group consisting of Pd, Pt and Ti.

The invention provides a farmland soil multi-parameter real-time monitoring system and method based on the Internet of Things. The system comprises a sensor module, a sensor collaborative scheduling module, a data transmission module, a data processing and storage module, an intelligent decision module, a user interaction module and a power supply module. Soil monitoring data, meteorological satellite information and historical yield records are fused, deep learning, a decision tree and a nutrient balance algorithm are combined, an accurate fertilization and irrigation scheme is generated, maintenance decision optimization is achieved, the water and fertilizer utilization efficiency is improved, and resource waste caused by extensive management is reduced; through dynamic sampling, data cross validation, sensor fault self-diagnosis and multi-source data fusion, the system can make a decision, effectively solves the defects of an existing system in the aspects of monitoring precision, data reliability, equipment endurance and decision refinement, and provides an efficient and reliable monitoring and management scheme for precision agriculture.

The invention discloses a micro-water density monitoring method and system based on multi-sensor fusion compensation, and relates to the field of power equipment safety. According to the micro-water density monitoring method based on multi-sensor fusion compensation, parameters are collected in real time through a micro-water collector composed of a ceramic heater, a humidity-sensitive capacitor collection sheet, a dew point sensor, a pressure sensor and a temperature sensor; a signal conditioning circuit and an analog-to-digital conversion module are integrated by adopting a four-layer PCB (Printed Circuit Board), and the micro-water collector is heated for multiple times by a main controller; carrying out digital filtering processing, cross validation operation and operation of eliminating influence of environment temperature on the acquired parameters; the measurement precision is improved through a sensor self-calibration mechanism, finally standardized micro-water density data are output, and an early warning function is triggered based on a multi-level threshold value. According to the invention, the problems of low precision and poor reliability of the measured micro-water density in the prior art are solved. Therefore, the accuracy of micro-water density measurement under complex working conditions is effectively improved, and data support is provided for predictive maintenance of intelligent equipment.

The invention discloses a switchable graded sampling pre-construction control method for dust and a detection device. The method comprises the following steps: synchronously acquiring data through multiple types of sensors, constructing a condensation risk prediction model, calculating a condensation risk index RI and dividing risk grades; based on the risk level, dynamically adjusting the target power of the heating wire, the blowback period of the air pump and the airflow speed, and cooperatively triggering an electrode cleaning and trapping filter screen switching program; after cleaning is completed, follow-up control parameters are dynamically adjusted; and closed-loop control is formed. According to the method, the temperature and humidity sensor is arranged in the external environment to obtain background parameters, the airflow velocity sensor is used for sensing the working condition change of the air pump, and a dynamic condensation risk prediction model is established, so that excessive heating is avoided fundamentally, and evaporation loss of semi-volatile substances is prevented; therefore, the accuracy of a dust concentration detection result is remarkably improved in an extreme humidity environment.

The invention discloses a method for predicting long-term creep of cement paste based on dielectric constants, which comprises the following steps of: finding out a relationship between a dielectric constant real part and a long-term creep modulus of the cement paste, firstly measuring the dielectric constant real part and the creep modulus, fitting to construct a corresponding function relational expression, verifying the constructed function expression, and finally predicting the long-term creep of the cement paste based on the dielectric constants. After the accuracy is verified, the method is applied to the long-term creep prediction of the cement paste. According to the method, the function relational expression related to the dielectric constant real part and the long-term creep modulus of the cement paste is established, the function relational expression can accurately predict the long-term creep of the cement paste, the corresponding creep modulus is obtained, and the precision of the prediction result can effectively meet the construction requirement; the whole prediction process is simple and easy to operate, the prediction precision of the long-term creep of the cement paste is greatly improved, the creep deformation of a stressed component of a building structure in a long-term stressed state can be controllably monitored, and then safe operation of an engineering structure is guaranteed.

The invention discloses a soil nitrogen leaching capacity monitoring method based on a frequency domain reflectometry, and relates to the technical field of soil water environment monitoring, in particular to a nitrogen leaching online monitoring method based on the frequency domain reflectometry (FDR), the Darcy law and a Van Genuchten (VG) model. And a monitoring method with high precision and sensitivity, multi-parameter synchronous detection and low cost is provided for the soil nitrogen leaching capacity. Comprising the following steps: 1, collecting and pretreating a soil sample; 2, placing the treated soil sample in a soil experiment cylinder; 3, inserting the multi-parameter sensors into the soil experiment cylinder in a layered manner; 4, 1000 ml of water is injected, and data acquisition is carried out; and 5, realizing soil nitrogen leaching capacity monitoring in combination with a Darcy law and a VG model.

The invention discloses a cable insulation moisture content estimation method, system and equipment based on relaxation frequency distribution and a medium, and relates to the technical field of cable insulation moisture content estimation.The cable insulation moisture content estimation method based on relaxation frequency distribution is characterized by comprising the steps that a cable sample is prepared; obtaining a relaxation current sequence by adopting a dielectric response analysis method, calculating relaxation current data by adopting an integral equation theory to obtain a relaxation frequency distribution function, and extracting characteristic parameters; establishing a moisture content estimation empirical formula, and establishing a moisture content estimation model; and estimating the moisture content of the cable sample according to the moisture content estimation model to obtain an estimation result. According to the invention, the cable does not need to be cut or disassembled or a special device does not need to be used for complex testing, and the method is suitable for monitoring a large-range power network. The method has high adaptability and can be widely applied to different scenes of a power system.

The invention provides a Laplace-DLTS stabilization inversion method and system, and the method comprises the steps: applying a pulse bias voltage to a tested semiconductor device, and collecting a transient capacitance signal of the tested semiconductor device; the transient capacitance signal is preprocessed; performing inverse Laplacian transformation processing on the preprocessed transient capacitance signal, and introducing at least one of non-negative constraint, sparsity constraint, physical prior constraint and time window segmentation constraint in an inversion process; carrying out optimization processing on the obtained inversion result, and judging the stability of the inversion result; and extracting a deep energy level trap parameter based on the inversion result, and outputting the deep energy level trap parameter and the processed transient spectrum data. At least one, preferably at least two, constraint conditions are introduced in the inverse Laplacian inversion process, so that the influence of noise and abnormal peaks on the inversion result is effectively inhibited, and the stability, physical consistency and parameter extraction reliability of the inversion are improved.

The invention provides a volume tube phase flow state monitoring device and method based on electrical capacitance tomography. Firstly, the invention proposes that an ECT method is introduced into a volume tube to realize gas-liquid two-phase flow distribution state detection for the first time, and breaks through the technical bottleneck that real-time monitoring of an internal flow state cannot be realized by a traditional method. And secondly, non-contact, total-cross-section and dynamic sensing of the phase state of the fluid in the volume pipe is achieved, and higher adaptability and safety are achieved. Meanwhile, the method supports volume fraction estimation and time sequence change analysis, and provides a reference basis for flow metering, working condition diagnosis, anomaly detection and the like. Finally, the technical blank of a traditional volumetric method device in the aspect of multiphase flow measurement precision guarantee is made up, and good engineering practicability and popularization value are achieved.

The invention provides a graphene-based capacitive sensor for detecting the moisture content in lubricating oil, a preparation method of the graphene-based capacitive sensor and a method for detecting the moisture content in the lubricating oil, and belongs to the technical field of moisture content detection. The graphene-based capacitive sensor for detecting the moisture content in the lubricating oil comprises a graphene-based electrode and a gold nanoparticle layer which are arranged in a laminated manner, the graphene-based electrode comprises a laser-induced graphene film and doped nanoparticles loaded on the surface and in pores of the laser-induced graphene film, and the doped nanoparticles are silver nanoparticles and copper oxide particle clusters; array holes are formed in the gold nanoparticle layer, the diameter of holes in the array holes is larger than the diameter of water molecules and smaller than the diameter of lubricating oil molecules, and the depth of the holes in the array holes is consistent with the thickness of the gold nanoparticle layer. The graphene-based capacitive sensor can realize real-time online detection of the moisture content in the lubricating oil, and is high in detection sensitivity and simple to operate.

The invention relates to a deep energy level transient spectrum data processing method based on dictionary learning. The method comprises the following steps: acquiring transient capacitance signals of a sample at different temperatures by using deep energy level transient spectrum equipment; establishing an Arrhenius equation that the defect emissivity changes along with the temperature; the defect emissivity under each group of values is calculated according to all possible values of the coefficient of the exhaustion Arrhenius equation; constructing a dictionary matrix based on the defect emissivity amplitude introducing Arrhenius constraint, and reconstructing a transient capacitance signal by using the dictionary matrix; and constructing a convex optimization problem, solving a dictionary index variable which enables a reconstruction signal of the transient capacitor to be closest to an acquisition signal, and extracting a non-zero solution in the dictionary index variable to obtain a corresponding defect emissivity amplitude spectrum. According to the method, the detection precision of the deep energy level defect can be improved by introducing the Arrhenius constraint relation.

The invention provides a sea surface oil spill GNSS reflection signal simulation system and method, and the method comprises the steps: building an oil spill sea surface dielectric constant module, determining the effective dielectric constant of an oil spill sea surface, and obtaining a Fresnel reflection coefficient; establishing an oil spill sea surface rough spectrum module, obtaining a model of a sea wave spectrum of the oil spill sea surface according to a traditional model of the sea wave spectrum and the influence of oil spill on the sea wave spectrum, and obtaining a surface spectral density function and a surface root-mean-square height; establishing a microwave scattering module of the oil spill sea surface, and determining a microwave scattering coefficient according to the Fresnel reflection coefficient, the surface spectral density function and the surface root-mean-square height; a DDM simulation module is established, and a DDM waveform is obtained through simulation according to the GNSS signal parameters and the microwave scattering coefficients; and the DDM waveform is obtained through simulation of each module. According to the simulation system and method, a unified mathematical model is established to describe the relation between the oil film and the GNSS reflection signal, and accurate simulation of the influence of the oil film on the GNSS reflection signal is achieved.

The invention relates to the technical field of automobile electrical detection, provides an automobile wire harness wire insulation skin damage detection method and system, and aims to solve the technical problem that a certain loop insulation skin damage position point is difficult to find in the prior art. Comprising a plane capacitance sensor used for measuring capacitance change between the plane capacitance sensor and a to-be-measured wire harness to obtain a charge signal used for representing the damage state of an insulating material of the to-be-measured wire harness; the charge amplifier is used for performing voltage conversion and amplification processing on the charge signal to obtain a voltage signal; the impedance analyzer is used for calculating impedance through the voltage signal and the current signal, drawing a Bode diagram based on the obtained impedance, and performing index parameter extraction on the Bode diagram to obtain various index parameters; and the upper computer is used for carrying out feature extraction on the multiple index parameters to obtain feature data, and analyzing the damage state of the insulating material of the wire harness to be detected according to the feature data to obtain a detection result.

The invention discloses a rock-fill concrete pouring liquid level and compactness monitoring and evaluating method, and relates to the technical field of concrete construction. According to the invention, the compactness sensing probes are uniformly distributed in the warehouse, so that the whole warehouse surface can be comprehensively monitored. The probes are wrapped by high-strength and high-toughness materials, it is ensured that the probes cannot be damaged in the construction process, a three-dimensional Thiessen polygon method is adopted for segmenting the areas in the bin, each compactness sensing probe corresponds to one associated area, the segmentation method can adapt to irregular polygon boundaries, it is ensured that only one representative measuring point exists in each area, and the accuracy of the detection result is improved. Whether the probes are buried by the concrete or densely filled can be judged in real time through the numerical value change of the compactness sensing probes, and the liquid level position of the self-compacting concrete can be calculated according to the states of all the probes.

Disclosed herein is a sensors-as-a-service ecosystem. In use, the system includes functions for receiving first sensor data at a sensors as a service platform, where the first sensor data corresponds to a first level of capabilities for a first sensor. The system also receives a selection of a sensor upgrade for the first sensor and provisions enhanced sensor capabilities for the sensor upgrade based on the selection. Furthermore, the system sends a sensor update with the enhanced sensor capabilities from the sensors as a service platform to the first sensor. Finally, the system receives second sensor data from the first sensor at the sensors as a service platform, where the second sensor data corresponds to a second level of capabilities for the first sensor.

Methods, systems, and computer program products for implementing a soil analysis process. A set of soil data may be received at a device from one or more soil sensors. The one or more soil sensors may be coupled to a portion of an agricultural machine configured to be in contact with soil. The device may be configured to analyze soil when a portion of the one or more soil sensors is in contact with the soil. Spectral data and soil conductivity and / or capacitance data may be obtained based on the collected set of soil data. Analyzed soil data may be determined based on the spectral data and soil conductivity and / or capacitance data. The analyzed soil data may be provided to a user device configured to display a visual representation of at least part of the analyzed soil data.

The invention provides a virtual measurement method and device, and belongs to the technical field of semiconductor manufacturing. The method comprises the steps that surface topography parameters of M1 wafers in a wafer set are measured, a first measurement result of the M1 wafers is obtained, the wafer set comprises N continuous wafers in the same crystal bar, and the M1 wafers are wafers distributed on the crystal bar at intervals in the N wafers; the first measurement result is input to a pre-trained virtual measurement model, a second measurement result of M2 wafers is obtained, and the M2 wafers are wafers except the M1 wafers in the N wafers; and combining the first measurement result and the second measurement result to obtain a measurement result of the wafer set. And the accuracy of the measurement result is improved while the productivity resources are released.

The invention belongs to the technical field of constructional engineering detection, and discloses a building exterior wall water seepage measurement method and system.The method comprises the steps that humidity sensor arrays are arranged on the surface and inside an exterior wall, multi-point humidity original data are collected, abnormity correction and noise reduction are conducted, and a complete preprocessing data set is obtained; inputting the data into a diffusion modeling module, carrying out time sequence analysis and spatial distribution estimation, generating a water seepage diffusion characteristic matrix and extracting key diffusion parameters, calculating a predicted value in a penetration depth estimation model based on a parameter set, constructing a water seepage distribution curve, calling a risk judgment module, and comparing a predicted result with a safety threshold. And outputting the risk level. The system comprises a data acquisition and preprocessing module, a diffusion modeling and feature extraction module and a penetration estimation and risk assessment module. According to the invention, dynamic monitoring and grading risk assessment of external wall water seepage can be realized, and a reliable basis is provided for building maintenance and safety management.

The invention discloses a CMOS (Complementary Metal Oxide Semiconductor) process humidity sensor capacitor layout implementation method, which comprises the following steps of: arranging top-layer metals with equal width at equal intervals, and connecting strip-shaped metals to form a positive electrode; the top layer metal is formed by arranging the top layer metal with the same width at the same interval, and the strip-shaped metal is connected to form a negative electrode; negative electrode metal plates are inserted into gaps between the metal plates of the positive electrodes at equal intervals to form an interdigital capacitor; a secondary top layer metal strip is inserted into a gap between the positive electrode and the negative electrode of the capacitor; a dielectric material is spin-coated in a gap between the positive electrode and the negative electrode of the interdigital capacitor; the MEMS back-end processing technology compatible with the CMOS technology is adopted, the technology is mature and stable, the top metal aluminum of the CMOS technology is adopted for the electrodes, no new metal material is additionally added, and meanwhile the interdigital capacitor is higher in sensitivity, good in chemical stability and higher in response speed.

The invention discloses a multi-sensor fusion transformer insulating oil aging degree evaluation method. The method comprises the following steps: establishing an insulating oil aging degree comprehensive experiment platform; the method comprises the following steps: testing different aging degrees of transformer insulating oil through an insulating oil aging degree comprehensive experiment platform, and obtaining dielectric constants, pH values and light transmittance of the insulating oil under different aging degrees through multiple sensors; determining the weights of the dielectric constant, the pH value and the light transmittance by adopting an entropy method; and evaluating the aging degree of the transformer insulating oil based on the dielectric constant, the pH value, the light transmittance data and the weight thereof. According to the invention, a plurality of sensors are adopted to collect data and fuse the data, so that the aging degree of the transformer insulating oil can be accurately evaluated.