662results about "Thermometers using value differences" patented technology

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 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 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.

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 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.

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.

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.

The invention relates to the technical field of cable monitoring, and discloses a cable joint temperature monitoring method and a cable joint, and the method comprises the steps: obtaining the real-time insulating layer temperature data of the cable joint based on a miniature temperature sensor, and obtaining the real-time environment data of the cable joint based on an auxiliary sensor; comparing the real-time insulating layer temperature data with a real-time environment temperature value, and determining the thermal radiation direction of the cable joint; determining a temperature difference value between the real-time insulating layer temperature data and the real-time environment temperature value, and determining a predicted temperature value of the conductor crimping layer according to the temperature difference value based on the heat radiation direction; determining a predicted temperature change rate of the conductor crimping layer according to the predicted temperature value; the real-time load current of the cable connector is obtained, and the real-time temperature change rate is determined; and determining a difference ratio between the predicted temperature change rate and the real-time temperature change rate, and judging whether the temperature monitoring of the cable joint is abnormal or not. According to the invention, accurate temperature prediction and reliable abnormity judgment of the cable joint are realized.

The invention discloses an automatic spraying control method and system for a fuel tank, and the method comprises the steps: obtaining the temperature monitoring data of the fuel tank, and carrying out the prediction, and obtaining the temperature prediction data; evaluating the high-temperature degree of the fuel tank based on the temperature prediction data to obtain a high-temperature degree evaluation value, and setting an initial control condition of the automatic spraying device according to the high-temperature degree evaluation value; determining temperature change characteristics of the fuel tank within a period of time after spraying, and determining a temperature change coefficient of the fuel tank based on the temperature change characteristics; and determining a control correction coefficient of the automatic spraying device based on the temperature change coefficient, and correcting an initial control condition of the automatic spraying device according to the control correction coefficient. By analyzing the temperature response characteristics in the spraying process and dynamically optimizing the control parameters, a complete monitoring-prediction-control-feedback closed loop is formed, the control precision is remarkably improved, timely and effective intervention is ensured when risks occur, energy and resources are saved, and unnecessary resource waste and equipment abrasion are avoided.

A water heating system includes a first heating chamber arranged in parallel with a second heating chamber; a first temperature sensor positioned to sense a first temperature in the first heating chamber; a second temperature sensor positioned to sense a second temperature in the second heating chamber; and a controller configured to: determine a first temperature value based on a first sensor signal from the first temperature sensor, determine a second temperature value based on a second sensor signal from the second temperature sensor, compute a differential between the first temperature value and the second temperature value, determine that scale buildup is indicated in response to the differential exceeding a first threshold, and initiate a corrective action in response to determining that scale buildup is indicated.

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.

According to the mass concrete temperature field self-adaptive thermoelectric coordinated regulation and control system and method, the temperature difference between the inside and the outside of mass concrete is reduced through active directional heat transfer and self-adaptive thermal resistance regulation. The flexible thermoelectric thin film device prepared by the invention has high flexibility, high thermoelectric efficiency and strong environmental adaptability, and can meet the temperature control requirement of mass concrete, and the manufacturing process is compatible with the existing microelectronic processing technology, so that the flexible thermoelectric thin film device has large-scale production potential; the flexible thermoelectric device is attached to the surface of concrete, directional transmission of heat between the concrete and the thermoelectric module from a high-temperature area to a low-temperature area is achieved by switching the current direction through the Peltier effect, temperature balance is achieved completely through the active thermoelectric effect and passive heat conduction optimization, the temperature lag and durability defects of a phase change material are avoided, and the service life of the concrete is prolonged. And the heat transfer efficiency is improved through the heat conductivity coefficient gradient and the thermally induced variation characteristic of the gradient heat conduction interface material layer.

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 discloses a high-low voltage power distribution cabinet heat dissipation control method and system based on the Internet of Things, and the method comprises the steps: carrying out the real-time temperature collection of a plurality of part positions in a high-low voltage power distribution cabinet through an Internet of Things sensor array, and obtaining a temperature data set; generating a thermal distribution diagram in the high-low voltage power distribution cabinet according to the temperature data set, and generating a heat flow distribution matrix according to the thermal distribution diagram; generating a risk distribution map according to the heat flow distribution matrix; designing a geometric structure of a heat flow guide channel of the high-low voltage power distribution cabinet according to the risk distribution diagram to obtain channel layout parameters; and determining a heat dissipation scheme of the high-low voltage power distribution cabinet according to the channel layout parameters, and performing heat dissipation control on the high-low voltage power distribution cabinet based on the heat dissipation scheme.

Provided is an indoor fire source localization method for high-rise buildings based on glass surface temperature, including the following steps: arranging an array of m wireless thermocouples on an outer surface of glass; measuring horizontal distances from a centrally positioned wireless thermocouple in the arranged array of wireless thermocouples to both side walls of a fire room; acquiring temperature data signals at preset time intervals t and transmitting the acquired temperature data to a data processing terminal for averaging; using averaged real-time glass temperature data and the horizontal distances from the centrally positioned wireless thermocouple to the two side walls as input data to form an input dataset, and feeding the dataset into a trained prediction program integrating a multilayer perceptron (MLP) and a k-nearest neighbors (KNN) algorithm; and determining a predicted fire source location block through backpropagation and category voting.

The invention discloses an integrated temperature sensing method and system based on a high-efficiency fusion architecture, and relates to the technical field of intelligent sensing, and the method comprises the steps: carrying out the grid division of a target monitoring region, recognizing a temperature gradient change abnormal region in real time, and dynamically increasing the sensor deployment density of the region; a distance weight concept is further introduced, the distance weight of adjacent sensors is calculated according to the layout of a sensor array, the sensors with unreasonable positions are dynamically adjusted, and in the monitoring process, abnormal areas are continuously recognized, the layout of the sensors is adjusted, data deviation is corrected, and the collection frequency is adaptively adjusted. By adopting the embodiment of the invention, the temperature abnormal region can be dynamically identified, the data fusion logic can be optimized, the reduction precision of the temperature field distribution can be improved, and the data error caused by unreasonable sensor layout or transmission delay can be reduced.

The invention provides an annealing monitoring method of bonding wire annealing equipment, electronic equipment and a medium, and relates to the technical field of annealing monitoring of the bonding wire annealing equipment, and the method comprises the steps: obtaining a temperature sequence obtained by collecting the temperature of a bonding wire in a preset sliding time window through each temperature sensor; obtaining an average temperature and a temperature fluctuation rate corresponding to each temperature sequence; obtaining an abnormal temperature sequence list B; if m is equal to 0, determining that annealing of the bonding wire in the preset sliding time window meets a preset annealing condition; otherwise, determining that the annealing of the bonding wire in the preset sliding time window does not meet the preset annealing condition; according to B, determining an abnormal area and an abnormal reason corresponding to the bonding wire in the annealing process of the bonding wire; according to the method, the consistency of the annealing quality of the bonding wire and the production efficiency can be remarkably improved, and the material performance defect and the yield loss caused by abnormal annealing are reduced.

Aspects of the disclosure relate to an integrated circuit that operates temperature or fault monitoring of one or more electronic components. An apparatus may include a first temperature sensor and a second temperature sensor at different locations. The first temperature sensor and the second temperature sensor may be positioned at different locations in order to have a comparative numeric relationship that is indicative of whether there is a fault in an electronic component during a baseline period.

In an example, an electronic device includes an electronic component with a temperature sensor to measure a first operating temperature of the electronic component at a first operating state having a first power value; and measure a second operating temperature of the electronic component at a second operating state having a second power value. The electronic device includes a controller to determine a first delta between the first operating temperature and an ambient temperature and determine a second delta between the second operating temperature and the ambient temperature. The controller is to determine a thermal resistance value and provide a notification when difference between a target thermal resistance value and the thermal resistance value exceeds a threshold.

The invention relates to the technical field of energy consumption monitoring, in particular to a grease processing energy consumption monitoring system which comprises a temperature difference input sensing module, an energy consumption fluctuation extraction module, an abnormal attribution recognition module, a single-point mutation screening module and a partition early warning module. According to the invention, through deep analysis of the energy consumption data in the continuous time period, a specific section with abnormal energy consumption can be identified, the risks of energy waste and equipment overload are effectively prevented, and through analysis of the association between the energy consumption of equipment operation and the working mode, data support is provided for equipment maintenance and energy saving. Through detailed recording and analysis of specific data of an abnormal section, energy management personnel can rapidly locate problem reasons, shorten response time, formulate more targeted improvement measures, monitor single-point sudden change and refine monitoring granularity, so that energy consumption of each key device is strictly monitored, and the monitoring efficiency is improved. And the chain reaction risk caused by abnormal energy consumption is reduced.

The invention provides a method for detecting the furnace temperature uniformity of a roller hearth type heat treatment furnace. The method is applied to a roller hearth type heat treatment furnace system comprising a furnace body, a heating device, a temperature sensor array and a medical service big data management system. The method comprises the steps that a temperature sensor array containing 14 measuring points is arranged at a specific position of a furnace body, and a furnace temperature data recording black box is fixed to the lower right corner of the furnace body; controlling the heating device to heat to a target process temperature of 920 DEG C and keeping the temperature constant for 30 minutes; the temperature data of the whole furnace area is collected every five minutes; and calculating a reference temperature and an absolute deviation value set of each measurement point through a medical service big data system, and evaluating the temperature field uniformity of the furnace body. And when the deviation exceeds a threshold value, the system generates a correction parameter group containing a heating zone power compensation coefficient and a refractory material density gradient value, and executes power redistribution or thermal insulation layer enhancement operation. High-precision detection and dynamic optimization of the temperature field uniformity of the roller hearth type heat treatment furnace can be realized, and the stability of a heat treatment process and the consistency of product quality are improved.

The invention provides a reservoir environment monitoring method and system, and belongs to the field of reservoir water quality monitoring. The method comprises the following steps: acquiring vertical temperature time sequence data and a plurality of layered fluctuation coefficients under a plurality of depth intervals; setting a water quality sensor monitoring frequency, and obtaining a first water quality parameter of the first depth interval; configuring a prediction resource based on the first layered fluctuation coefficient, predicting a water quality parameter of a second depth interval according to the first water quality parameter and the first layered fluctuation coefficient, and verifying to obtain a prediction error coefficient; and performing layer-by-layer prediction according to the prediction error coefficient and the layered fluctuation coefficient until the water quality parameter of the target depth and the reservoir environment monitoring result are obtained. The technical problems of inaccurate target depth water quality monitoring and high cost caused by the fact that a water quality sensor cannot realize full-depth coverage in the prior art are solved, and the technical effects of accurately monitoring the target depth water quality and reducing the deployment cost of the sensor are achieved through temperature stratified fluctuation analysis and layer-by-layer prediction error compensation.