1126results about "Thermometers using value differences" patented technology

A method and apparatus for measuring optical turbulence using an unmanned aerial vehicle are provided. The unmanned aerial vehicle may include a central body, at least one motor operatively connected to the central body, a mounting element, a three-dimensional anemometer mounted on the mounting element, a first differential temperature sensor mounted on the mounting element, a second differential temperature sensor mounted to the mounting element, and a base mounted to the central body via a payload mounting interface including a first barometric pressure sensor, a central processing board, memory operatively connected to the central processing board, and a processor configured to generate refractive-index structure coefficient information.

A multispectral light field imaging system includes a primary lens, a microlens array, a first relay lens, a dichroic lens, a second relay lens, a third relay lens, a first image sensor, a first filter, a second image sensor and a second filter, wherein the microlens array is located at an image plane of the primary lens; the first relay lens together with the second relay lens and the third relay lens forms a 1:1 relay lens group imaging system on a spectral band 1 light path and a spectral band 2 light path respectively; the dichroic lens forms an included angle of 45° with a light axis; the first image sensor is located at a focal plane of the second relay lens, and the second image sensor is located at a focal plane of the third relay lens.

The invention discloses a temperature monitoring method for a photovoltaic grid-connected cabinet, and particularly relates to the technical field of photovoltaic grid-connected cabinets. The method comprises the following steps: arranging multiple types of temperature sensors in a grid-connected cabinet, collecting real-time temperature data, constructing a heat distribution model, comparing a current heat map with a historical steady-state heat field template, and identifying heat field offset and an atypical temperature rise trend; when the system detects that early warning is not triggered by an existing measuring point in a heat abnormal area, redundancy alarm logic is automatically started, temperature abnormal early warning is generated, and the speculated abnormal heat source position is recorded; according to the method, the sensing capability of the thermal anomaly in the blind area of the sensor is effectively improved, and the safety and the intelligent level of the system are enhanced.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The present disclosure is of an atmospheric characterization system that has a central processing board that has a first and a second communication interface. Further, the atmospheric characterization system further has a first precision temperature sensor that is communicatively coupled to the central processing board via the first communication interface and positioned a distance from a first side of the processing board, wherein the precision temperature measures a first temperature and transfers data indicative of the first temperature to the central processing board. In addition, the atmospheric characterization system has a second precision temperature sensor that is communicatively coupled to the central processing board via the second communication interface and positioned the distance from a second opposing side of the processing board such that the first precision temperature sensor and the second precision temperature sensor are equidistance from the processing board and a distance between the first precision sensor and the second precision sensor is a predetermined distance, r, and the second precision temperature sensor measures a second temperature and transfers data indicative of the second temperature to the central processing board simultaneously with the transferring of the first temperature. Additionally, the atmospheric characterization system has a processor that receives the first temperature and the second temperature and calculates a value indicative of atmospheric turbulence based upon the first temperature and the second temperature, wherein the value indicative of the atmospheric turbulence is used for designing, modifying, calibrating, or correcting an optical system.

The invention relates to the technical field of medical cyclotrons, in particular to a medical cyclotron magnetic field intensity adjusting method based on temperature compensation, and the method comprises the following steps: in the process of adjusting the magnetic field intensity of a main magnet based on temperature information, obtaining a temperature variation threshold: collecting the temperature on the surface of the main magnet in real time; determining a temperature difference coefficient, a temperature anomalous coefficient, a temperature abnormal coefficient and a trend approximate value of each acquisition moment; comprehensively analyzing the temperature values acquired by all the sensors, and determining the temperature difference degree and difference factor of each sensor at each acquisition moment; determining the avoiding adjustment value of each sensor at each acquisition moment; and acquiring a temperature variation threshold value at each acquisition moment. The invention aims to solve the problem that the magnetic field intensity of the cyclotron cannot be adjusted according to the actual environment temperature, so that the beam stability and the beam extraction efficiency in the operation process of the medical cyclotron are improved.

The invention relates to the technical field of fault diagnosis, in particular to a big data-based bus duct fault diagnosis system, which comprises a data synchronization module, an anomaly identification module, an amplitude judgment module, a traceability positioning module and a risk classification module. According to the invention, automatic synchronization of multi-node data is realized through a time correlation mode, layered discrimination is carried out on an abnormal working condition state by means of continuous comparison of data streams, dynamic identification of node parameter fluctuation is realized through interval adjustment and trend aggregation, and abnormal signals are positioned and traced in a link topology. The node operation risk is comprehensively researched and judged in combination with historical and real-time parameters, linkage analysis and active classification of multi-dimensional information are formed, efficient connection of links such as monitoring, recognition, tracing and classification is promoted, operation and maintenance decision and data full-process response are supported, node difference judgment and risk prompt in a complex scene are facilitated, and the method is suitable for popularization and application. And intelligent operation and maintenance of power supply system data driving are improved.

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 relates to the technical field of fault detection, in particular to an intelligent photovoltaic junction box testing method and system, and the method specifically comprises the steps: constructing a voltage and current dissimilarity index based on the data changes of the current and voltage of an intelligent photovoltaic junction box at adjacent moments, and constructing an electrical parameter abnormal coefficient through combining the correlation between the voltage and the environment temperature; based on the correlation between the internal temperature of the photovoltaic junction box and the time sequence of other parameters, the fault confidence coefficient of the photovoltaic junction box is constructed in combination with the electrical parameter abnormal coefficient; according to the method and the device, the anomaly detection of the photovoltaic junction box is carried out based on the fault confidence coefficient, the influence of environmental factors on related data of the photovoltaic junction box is reduced, the problem that when temperature threshold detection is carried out in an existing photovoltaic junction box detection technology, threshold setting is unreasonable, and false detection is easily caused is solved, the detection precision of the photovoltaic junction box is improved, and false detection is avoided.

The invention discloses a solar street lamp illumination intensity self-adaptive adjusting method, and particularly relates to the technical field of solar street lamps. Calculating a discharge depth nonlinear index according to the nonlinear characteristics of a discharge rate decrease coefficient, an internal resistance increment coefficient and a temperature distribution difference coefficient, timely capturing the nonlinear characteristics of the voltage fluctuation of the battery along with the increase of the discharge depth, and evaluating the electric quantity condition of the storage battery and the nonlinear discharge fluctuation degree of the battery. Meanwhile, according to a light source attenuation coefficient, a metal corrosion coefficient and an insulating layer damage coefficient, a hidden danger evaluation index of the solar street lamp is calculated, the potential fault risk after the street lamp is used for a long time is recognized in time, the brightness is properly adjusted according to the hidden danger degree, and safe and stable operation of a street lamp system is ensured; and correcting the brightness curve according to the discharge depth nonlinear index and the solar street lamp hidden danger evaluation index, so that the system can adapt to the complex characteristics of battery discharge and the street lamp aging effect.

The invention relates to the technical field of equipment maintenance, in particular to a distribution box remote diagnosis and maintenance system which comprises a voltage deviation detection module, a node hot stacking identification module, a channel stability classification module, a contact aging trend evaluation module and a period adjustment trigger module. According to the method, peak value change of effective voltage in each channel period in the distribution box is collected and compared with a preset criterion so as to accurately identify an abnormal discharge unit and accurately position a potential risk channel, and the change rate of equivalent series capacitance, contact conductance and contact resistance of a node is continuously sampled in a non-power-on state so as to accurately identify the potential risk channel. According to the method, multi-parameter same-trend change characteristics are determined, the contact aging process is accurately evaluated by integrating the parameter trend, the node trend and the maintenance plan period remaining time are subjected to cross comparison, the maintenance task advance opportunity is automatically judged, the maintenance plan is actively adjusted, the node fault missing detection risk is effectively reduced, and the maintenance timeliness and accuracy are remarkably improved.

A power tool including a motor, an impulse assembly configured to be driven by the motor, a temperature sensor, and a controller. The temperature sensor is configured to output a signal related to a temperature of the power tool. The temperature of the power tool is correlated to a temperature of a fluid within the impulse assembly. The controller is connected to the temperature sensor. The controller is configured to determine the temperature of the power tool based the signal from the temperature sensor, and control, in response to the temperature of the power tool being greater than a temperature threshold, the power tool based on the temperature of the power tool.

A heat sensor assembly for a power distribution system is disclosed. The assembly comprises: a cable, containing a plurality of at least three heat sensors arranged along the length of the cable, each of the heat sensors being spaced from the next by an interval: an end module at a first end of the cable, the end module having a corresponding plurality of terminal pairs, each terminal pair being dedicated to one of the heat sensors; circuitry inside the cable, connecting each of the heat sensors across a corresponding one of the terminal pairs such that each terminal pair outputs a temperature signal indicative of the temperature sensed by the corresponding heat sensor; and a controller configured to receive the temperature signal from each terminal pair and to compare the temperature signals against one another to determine whether the temperature sensed by any one of the heat sensors differs from that sensed by the other heat sensors by more than a predetermined threshold (ΔTALARM), and if so to generate an alarm signal.

The invention discloses a high-voltage cable joint temperature online monitoring method based on sensor data fusion. The method comprises the following steps: data acquisition: acquiring a first temperature data sequence T1i, a second temperature data sequence T2i and an environment temperature data sequence Ei of a plurality of temperature sensors at the position of a high-voltage cable joint; data fusion: fusing the data to generate a fused temperature data sequence Fi; abnormal detection: calculating a temperature change coefficient, a temperature difference coefficient and a temperature change rate of each temperature sensor according to the fused temperature data sequence Fi, and generating an abnormal quantized value Qi of each temperature sensor; and judging result generation: comparing the abnormal quantized value Qi with a preset threshold value Qth, and judging whether each temperature sensor has a temperature abnormal condition or not. According to the invention, by fusing the data from the plurality of temperature sensors and the environment temperature information, the accuracy and reliability of temperature monitoring are improved, and the anti-interference capability and the intelligent level of the system are enhanced.

The invention relates to the technical field of power electronic device diagnosis, and discloses a reverse conducting IGBT intelligent power module fault automatic diagnosis method and system. The method comprises the following steps: acquiring multi-source monitoring data including a grid voltage waveform, a collector current waveform and a shell temperature change curve when the power module operates; then establishing a dynamic feature extraction model, performing time domain and frequency domain conjoint analysis on the multi-source monitoring data, and generating a feature parameter set; then constructing a fault feature space, and mapping the feature parameter set to a high-dimensional space to form a feature vector distribution diagram; carrying out regional division on the feature vector distribution map by adopting a self-adaptive clustering algorithm, and identifying an abnormal feature aggregation region; and finally, comparing the abnormal feature gathering area with a preset fault feature library through a mode matching engine, and outputting a fault type identification result. According to the method, multi-source data can be integrated to realize dynamic feature extraction and adaptive fault identification, and the real-time performance and accuracy of fault diagnosis are improved.

The invention relates to the technical field of power modules, and discloses a power module detection method and system based on temperature measurement, and the method comprises the steps: obtaining the temperature data of an air inlet outside a power module, in a heat dissipation channel, other units outside the heat dissipation channel, and beside the air inlet, and calculating an air inlet temperature value, a channel temperature value, a unit temperature value, and an inlet temperature value; and calculating a curve matching value of the two thermal difference temperature value change curves according to the thermal difference temperature values, the first thermal difference temperature value and the second thermal difference temperature value, comparing the curve matching value with a preset reference matching value, and if the curve matching value is smaller than the preset reference matching value, performing early warning prompt. The temperature conditions of different positions of the power module are comprehensively considered, the detection deviation is reduced, the accuracy of temperature state detection is improved, the temperature abnormal change trend is captured, potential faults are found in advance, and reliable guarantee is provided for stable operation of the power module.

The invention relates to the technical field of power equipment detection, in particular to a method for detecting turn-to-turn short circuit of an iron core reactor, which is used for solving the problems that the turn-to-turn short circuit risk of the iron core reactor cannot be comprehensively evaluated, the state change of equipment cannot be captured in real time and the sensitivity and accuracy of turn-to-turn short circuit risk monitoring are reduced in the prior art. According to the method, the inter-turn short circuit risk of the iron core reactor is comprehensively evaluated by integrating the operating current, the direct-current resistance, the inductance value and the temperature parameters of key parts, and the state change of equipment is captured in real time by dynamically calculating the change rate of each parameter, so that the monitoring sensitivity and accuracy are remarkably improved; the logistic regression model trained based on historical data can accurately predict the turn-to-turn short circuit probability, automatic risk monitoring is achieved, manual intervention is reduced, and the misjudgment rate is reduced.

The invention discloses a fire positioning method based on heat source gradient identification, and belongs to the technical field of fire positioning, and the method specifically comprises the steps: obtaining a two-dimensional temperature distribution image of a fire scene; drawing an isotherm, and marking a potential fire source area based on a preset temperature threshold value; calculating the area of each potential fire source region, screening out an undetermined region from the potential fire source regions, calculating the temperature change rate of a central isotherm of the undetermined region in unit time, and screening out a candidate region from the undetermined region; marking a plurality of points on the peripheral isotherm of the candidate area at equal intervals, generating a temperature gradient path in the reverse direction of the temperature gradient based on each point, calculating the temperature gradient of each path, obtaining the candidate area with the temperature gradient mean value larger than a threshold value, and marking the candidate area as an initial fire source area; continuously drawing vertical lines into the central isotherm from a tangent line of the intersection point on the central isotherm, and marking the intersection point of the vertical lines as an initial fire source center point; according to the invention, rapid positioning of the initial fire source center in the fire scene is realized.

The invention provides a data co-processing method and system for a linear servo actuator. The method comprises the following steps: firstly, acquiring a multi-level temperature data set of a key heat source area in the linear servo actuator; performing dynamic coupling analysis processing on the multi-level temperature data set based on a thermal field prediction model to generate a temperature change trend prediction result; a dynamic heat dissipation strategy grade is matched according to the temperature change trend prediction result and real-time load current data, a heat dissipation execution control instruction is generated, and temperature feedback data in the heat dissipation process is monitored in real time; and based on a comparison result of the temperature feedback data and a preset temperature threshold, triggering a thermal failure protection mechanism to adjust the execution priority of the composite heat dissipation operation. According to the invention, power output can be reduced, external active heat dissipation control is triggered, equipment shutdown and other related instructions which are in effective contact with an abnormal working state can be triggered, so that the risk of equipment damage caused by abnormal operation of the actuator is effectively reduced, and the reliability and stability of the system are improved.

The invention discloses a temperature sensing and radio frequency identification circuit integrated temperature measurement method and system, which are applied to the technical field of temperature sensor data processing, and the method comprises the steps: obtaining the response time when each temperature sensing node collects the temperature according to a corresponding first preset sampling frequency, and the signal transmission delay time of a corresponding radio frequency identification chip; correcting response time by using a compensation matrix constructed according to the signal transmission delay time sequence to obtain an adjusted response time sequence, and respectively determining a sampling configuration scheme and reference task bearing capacity corresponding to the temperature sensing node according to the adjusted response time sequence and equipment parameters; and carrying out temperature acquisition, and carrying out interpolation reconstruction and optimization on the acquired temperature value to obtain optimized temperature data. According to the method, the response speed of the distributed temperature sensing system is adjusted, and the sampling strategy is adjusted in combination with the dynamic change of the distribution characteristics of the temperature field, so that the temperature monitoring precision is improved.

Cable termination anomaly detection method (200), comprising: placing at least a temperature sensor (2) near a cable termination (1) having a cooling / insulating fluid (7) so as to measure temperatures of a plurality of measuring points (S1-SE); measuring (201) by said temperature sensor (2) and at different measuring times a plurality of groups of temperature values (TGt1-TGtM). The method further comprises: acquiring the plurality of groups of temperature values (TGt1-TGtM) and constructing (203) an axial temperature distribution (ATD(zn)) expressing a one-to-one correspondence between estimated temperature values obtained from the plurality of groups of temperature values (TGt1-TGtM) and height values along a longitudinal axis (A1) of the cable termination.

A temperature calibration system includes: an inspection apparatus to adjust temperature of an inspection target in a placement part and inspect the inspection target; and a surface thermometer, and is configured to calibrate temperature sensors in the placement part. The inspection apparatus includes: a carriage to move the placement part in X-, Y-, and Z-axis directions; and a controller to perform a calibration process to measurement values of the temperature sensors. The surface thermometer is configured to contact a placement surface of the placement part and detect a surface temperature of the placement surface. The controller is configured to: control the carriage to contact the surface thermometer with a detection position of the placement surface of the placement part; detect the surface temperature of the detection position by the surface thermometer; and calibrate the measurement value of the temperature sensor corresponding to the detection position based on the surface temperature.

The invention relates to the technical field of power supplies, and provides an emergency starting power supply detection method and system, and the method comprises the steps: obtaining continuously inputted input voltage data, continuously outputted output current data and temperature change data of an emergency starting power supply in a preset time period; inputting the input voltage data and the output current data into a preset detection model to obtain power supply state information, comparing the temperature change data with a preset temperature threshold to obtain temperature comparison data, and performing health state evaluation on the emergency starting power supply in combination with the power supply state information to obtain a power supply health state. And performing fault diagnosis on the emergency starting power supply according to the power supply health state to obtain a diagnosis result, and generating a detection report of the emergency starting power supply based on the diagnosis result. By comprehensively acquiring and analyzing the input voltage data, the output current data and the temperature change data, the problem that the health state and potential faults of the emergency starting power supply cannot be diagnosed and evaluated under the condition that the environment temperature change is large is solved.

The invention relates to the technical field of electric data processing, in particular to an intelligent heat dissipation method and system for an outdoor advertising machine. The method comprises the following steps: taking a data point of a descending trend in a power supply power monitoring curve as a first analysis point; screening maximum value points on each heat source temperature monitoring curve to obtain a second analysis point; a first correction value is obtained on the basis of the first analysis point. And obtaining the possibility of the main heat source and screening out the main heat source. And taking an extreme point with obvious change on the heat source temperature monitoring curve of the main heat source as a second analysis point for analysis to obtain response delay. And adjusting a state transition matrix according to the final correction, and compensating internal temperature monitoring data by using a Kalman filtering algorithm to obtain an accurate heat dissipation strategy. According to the method, the state transition matrix in the Kalman filtering algorithm is effectively adjusted, so that the internal temperature data of the advertising machine is accurately compensated, and an effective heat dissipation strategy is obtained.

Disclosed in the present invention are a multispectral light field imaging system, and a three-dimensional temperature field measurement method and measurement system. The multispectral light field imaging system comprises: a primary lens, a micro-lens array, a first relay lens, a dichroic mirror, a second relay lens, a third relay lens, a first image sensor, a first optical filter, a second image sensor and a second optical filter, wherein the micro-lens array is located at an image plane of the primary lens; the first relay lens, the second relay lens and the third relay lens together form a 1:1 relay lens group imaging system on an optical path of a spectral band I and an optical path of a spectral band II; an angle of 45° is formed between the dichroic mirror and an optical axis; and the first image sensor is located at a focal plane of the second relay lens, and the second image sensor is located at a focal plane of the third relay lens. The present invention realizes the collection of multispectral light field data while maintaining the amount of light field data of each spectrum unchanged, such that an instantaneous three-dimensional temperature field of a flow field can be measured.

The invention relates to the technical field of data processing, in particular to a bridge construction structure health state real-time monitoring system, which acquires temperature data including temperatures at a plurality of moments at different positions of a bridge construction structure in real time in the pouring process of the bridge construction structure, and calculates the health state of the bridge construction structure according to the temperature data at the different positions. And determining the temperature change correlation between different positions at each moment, and determining the heat transfer influence degrees of the different positions at each moment according to the temperature change correlation, so as to determine the target temperature anomaly degrees of the different positions at each moment according to the temperature data of the different positions, the temperature change correlation and the heat transfer influence degrees. According to the temperature anomaly degree and the preset anomaly threshold, the health states of the different positions are determined, and the temperature change correlation and the heat transfer influence degree between the different positions are considered, so that the target temperature anomaly degree of the different positions is more accurate, and the monitoring accuracy of the health states is improved.

A short circuit identification method is provided for a sampling element of a battery management system. A temperature sensor is disposed in a battery management system to monitor a temperature of a discharge transistor, and the method includes: obtaining the temperature of the discharge transistor by using the temperature sensor, and calculating a temperature difference of the discharge transistor in a preset duration; comparing a discharge current obtained by using a sampling element with a preset current threshold; and determining that the sampling element is short-circuited. In embodiments of the present application, the temperature sensor is used to monitor the temperature change rate of the discharge transistor in the BMS system, it can be detected that only one sampling element has a short-circuit fault with reference to the discharge current obtained by the sampling element, and corresponding protection measures are taken, so that the BMS system runs safely and stably.

A hydrogen gas filling device includes a reception circuit, a difference calculation circuit, a filling speed calculation circuit, an accumulator, and a filing machine. The reception circuit is configured to receive, from a vehicle equipped with a tank to be filled with hydrogen gas and powered by the hydrogen gas, a value of a parameter of the vehicle. The difference calculation circuit is configured to calculate a difference between a predetermined value and the value of the parameter received from the vehicle. The filling speed calculation circuit is configured to calculate a filling speed of the hydrogen gas depending on the difference. The accumulator is configured to accumulate hydrogen gas. The filling machine is configured to fill the tank with the hydrogen gas from the accumulator at the calculated filling speed. A hydrogen gas filling method includes the operations noted above.

The present disclosure relates to a system (100) for acoustically detecting a temperature change, the system (100) comprising: at least one conversion element (10) for converting a temperature change into a characteristic sound; an acoustic sensor (40) configured to be mechanically connected to the structure (50) at a distance from the at least one conversion element (10); and a processor (42, 62) coupled to the acoustic sensor (40), in which the at least one conversion element (10) comprises an actuation portion (20) having at least one material having thermal expansion properties such that a change in temperature causes a movement of the actuation portion (20) that causes the conversion element (10) to generate a characteristic sound and conduct the characteristic sound into the structure (50), the acoustic sensor (40) is configured to record a characteristic sound generated by the conversion element (10) as a structural sound propagating through the structure (50), and the processor (42, 62) is configured to detect a temperature change based on the characteristic sound recorded by the acoustic sensor (40).

A failure detection method for battery racks (100, 400) is disclosed and includes: continuously computing a voltage difference data in a computation frequency; computing a standard deviation by using the voltage difference data retrieved from each battery rack (100, 400) up to present; obtaining a first voltage trend and a second voltage trend according to the voltage difference data in a first period and the voltage difference data in a second period when the standard deviation is greater than a preliminary-filtered threshold; computing an intersection of the first voltage trend and the second voltage trend to obtain a voltage trend status; computing a voltage slope according to the voltage difference data of the second period; and generating an alarm message when the voltage trend status is abnormal and the voltage slope is greater than a slope threshold, where the alarm message indicates the position of a battery cell (120, 420) occurring overvoltage status.