13028results about "Thermometer applications" patented technology

The invention discloses a distribution line fault intelligent diagnosis method based on multi-source information fusion, and belongs to the technical field of power system fault detection and diagnosis, and the method comprises the steps: obtaining distribution line data and meteorological data; superposing the distribution line data with the meteorological data to generate a space-time fusion feature matrix based on the wire space displacement; dynamically adjusting a preset initial threshold value by using the space-time fusion feature matrix; and performing multi-round verification on the abnormal fluctuation of the electrical parameters of the line according to the fault judgment threshold, generating a fault positioning instruction, performing real-time matching with the topological structure of the line, correcting the priority queue of the fault section based on the switching action feedback data of the feeder terminal, and triggering the fault removal action matched with the priority. According to the method, spatial-temporal feature fusion of current, voltage, weather and spatial displacement data and a dynamic threshold adjustment mechanism are adopted, the fault type can be accurately identified, the fault section can be positioned in real time, and the diagnosis precision and the response speed in a complex environment are remarkably improved.

The invention relates to the technical field of data processing, and discloses a safety detection method and system of an energy storage system and a storage medium. The method comprises the steps that voltage, current, temperature and internal resistance data of the energy storage system are collected to form a basic monitoring data set, and a preprocessed data sequence is generated through data preprocessing; mapping the preprocessed data sequence to a multi-dimensional feature space to obtain a target feature set; establishing a security detection model through the target feature set; generating a risk assessment report based on the security detection model; and analyzing system performance according to the evaluation report and outputting a maintenance scheme. According to the invention, intelligent analysis and accurate fault diagnosis of multi-parameter data of the energy storage system are realized. The intelligent monitoring and early warning of the safety state of the energy storage system are realized by establishing a multi-level analysis framework with the functions of feature extraction, intelligent diagnosis, fault early warning and the like and comprehensively evaluating the system state in combination with a deep learning algorithm.

A prism for reflecting a laser includes: a single mounting cap at a first end of the prism, and first to seventh trihedral corner (TC) reflectors, each including a reflective surface including: three side edges, and three corners at respective intercept points between the side edges, wherein the seventh TC reflector, among the first to seventh TC reflectors, is on a second end of the prism opposite to the first end of the prism.

The invention provides a high-temperature chemical pipeline defect detection system and method based on magnetostrictive ultrasonic guided waves, and relates to the technical field of high-temperature chemical pipeline defect detection.The method comprises the steps that magnetostrictive excitation signals are applied, the propagation process of the guided waves in a pipeline is calculated through numerical simulation, and the amplitude and phase information of guided wave signals is obtained; performing time-frequency domain analysis on the guided wave signal, extracting group velocities and phase velocities of guided waves in different modes, determining frequency dispersion characteristics of the guided waves, and evaluating the influence of a high-temperature environment on guided wave propagation; processing the received guided wave signal by adopting a modal decomposition and reconstruction algorithm to obtain a corrected guided wave signal; and carrying out feature extraction and parameter estimation on the corrected guided wave signal to obtain the position, size and type information of the pipeline defect. According to the invention, the problem of multilayer heterogeneous pipeline guided wave detection in a high-temperature environment is solved, the accuracy and reliability of defect detection are improved, and an effective method is provided for pipeline health monitoring and safety assessment.

The invention belongs to the technical field of engineering supervision, and discloses a concrete strength measurement system and method for civil construction engineering, and the method comprises the following steps: a test point planning module determines the number and position of detection points; the route planning module plans a running route of the detection mechanism; the detection mechanism sequentially moves to each detection point position according to the planned route; the positioning module analyzes the distance from the ultrasonic probe to the laser; the ultrasonic probe A is aligned with the ultrasonic probe B; the ultrasonic probe A and the ultrasonic probe B scan a concrete building; detecting the strength of the concrete building by using a rebound apparatus; the humidity acquisition module acquires humidity data of concrete; the temperature acquisition module acquires environment temperature data; and the ultrasonic analysis module comprehensively calculates the concrete strength by combining the rebound value, the concrete humidity, the environment temperature and the ultrasonic detection sound velocity. According to the invention, concrete strength on-site detection can be carried out on a high-rise building; by integrating various data, the strength of the concrete can be evaluated more accurately.

The invention discloses a wireless temperature measuring device suitable for a semiconductor vacuum chamber, and belongs to the technical field of wafer temperature measurement, a device main body comprises an upper silicon wafer and a lower silicon wafer, a wireless temperature measuring assembly is arranged between the upper silicon wafer and the lower silicon wafer, and the wireless temperature measuring assembly is composed of a circuit, a temperature measuring device, a battery and a master controller. The circuit is arranged between the upper silicon wafer and the lower silicon wafer, the temperature measuring device, the battery and the master controller are all electrically connected with the circuit, and the upper silicon wafer and the lower silicon wafer are bonded through high-temperature bonding glue; during specific implementation, temperature measurement is performed on the interior of the wafer through the temperature measurement device, obtained temperature data are uploaded to a cloud end through the master control, the battery is a power supply of the temperature measurement device and the master control, the wireless temperature measurement device can eliminate partial pollution caused by wired temperature measurement during use, through holes are prevented from being formed in the processing chamber, and the processing efficiency is improved. And the manufacturing difficulty is reduced and the temperature measurement effect is good.

The invention relates to the technical field of semiconductors, and discloses a full-temperature-zone polynomial digital temperature compensation method and system based on an SOI chip, and the method comprises the steps: obtaining the temperature frequency data of a preset temperature zone of a target SOI chip, fitting a full-temperature-zone curve, extracting a critical point of the temperature zone, dividing a segmented compensation interval according to the critical point, and obtaining the temperature frequency data of the preset temperature zone of the target SOI chip; the method comprises the following steps: calculating frequency drift amounts under different voltages to construct a full-automatic test framework, acquiring an environment temperature parameter and an instantaneous temperature value by using the framework, analyzing a temperature compensation vector of a segmented compensation interval, further monitoring a signal frequency interval output by a chip, extracting a phase noise parameter, calculating a frequency offset error amount with a preset value, and calculating the frequency offset error amount. And analyzing an error source, optimizing a polynomial compensation order, and collecting temperature drift suppression data to generate a full temperature region compensation report. According to the invention, the performance stability of the chip in a complex environment can be improved.

The invention relates to the technical field of concrete pouring, in particular to a concrete pouring homogeneity detection system and method based on sensing data, and aims at achieving efficient and accurate concrete pouring homogeneity evaluation and defect detection. The system comprises a multi-sensor sensing module, a multi-sensor data conversion and transmission module and a concrete homogeneity evaluation module, the multi-sensor sensing module comprises a temperature sensor, an ultrasonic sensor and a vibration sensor; the multi-sensing data conversion and transmission module is used for acquiring multi-sensing data and performing data type conversion and transmission on the multi-sensing data; and the concrete homogeneity evaluation module is used for constructing a concrete pouring homogeneity evaluation model to detect and evaluate the homogeneity and defects in the concrete pouring process. According to the invention, detection and evaluation of the concrete pouring homogeneity are realized through combination of multi-sensing data, and the accuracy of detection of the concrete pouring homogeneity is improved.

A prism for reflecting a laser includes: a single mounting cap at a first end of the prism, and first to seventh trihedral corner (TC) reflectors, each including a reflective surface including: three side edges, and three corners at respective intercept points between the side edges, wherein the seventh TC reflector, among the first to seventh TC reflectors, is on a second end of the prism opposite to the first end of the prism.

The invention discloses a server heat dissipation device and a heat dissipation control method.The surface of a server mainboard is divided into a core heat dissipation area, a transition heat dissipation area and an edge heat dissipation area, and the method comprises the steps that real-time temperature data of all the areas are synchronously collected through a temperature detection module; constructing a three-dimensional temperature field distribution map containing temperature gradient and heat flow direction; then thermodynamic parameter calculation is carried out, temperature time sequence change characteristics of all the partitions are extracted, and a thermal diffusion path in a future set time period is predicted by fusing the temperature time sequence change characteristics and the thermodynamic parameters; a control instruction set is generated according to the predicted thermal diffusion path, the actual heat dissipation response is monitored through an acoustic sensor in the execution process, monitoring data and the predicted thermal diffusion path are dynamically compared, and control parameters of the control instruction set are updated till all the partitions reach the target temperature threshold value; and the sudden temperature change is pre-judged, the hot spot elimination response time is shortened, and the collaborative breakthrough of the heat dissipation efficiency and the energy consumption control of the high-density server cluster is realized.

The invention relates to the technical field of high-voltage connectors, and discloses a high-voltage connector fault prediction method and system based on thermal management, and the method comprises the steps: collecting the temperature distribution data and electric signal transmission characteristic data of a high-voltage connector, and building a thermal-electric coupling network model comprising a temperature node and a signal transmission node; separating and optimizing the transmission characteristic function to obtain a temperature-transmission characteristic mapping relation; gaussian process regression calculation is carried out on the temperature time sequence data to obtain temperature dynamic characteristic statistical characteristics; inputting the statistical characteristics of the dynamic temperature characteristics into a specified time delay thermal management neural network for signal transmission delay prediction to obtain delay prediction characteristic parameters; according to the method, the weighted error value in the transmission feature space is calculated, and the signal transmission delay is dynamically adjusted to obtain the compensated signal transmission delay parameter, so that the accurate prediction of the signal transmission delay is realized, and the accuracy and robustness of the compensation effect are improved.

The invention relates to the technical field of circuit detection, discloses a power transmission line thermochromic wire clamp heating early warning method and system, effectively solves the problem of data acquisition distortion in a strong electromagnetic environment, and improves the accuracy of state evaluation through multi-source data fusion. The dynamically adjusted early warning model reduces the risk of false alarm and missing alarm caused by equipment aging, the intelligent decision support module shortens the fault handling response time, the data closed-loop mechanism ensures the reliability of the system in the whole life cycle, and the reliability of the system in the whole life cycle is improved through multi-sensor cooperative monitoring and edge calculation processing. And the influence of environmental factors on data acquisition is reduced. The two-channel transmission architecture guarantees the data transmission integrity under different network conditions, the CRC verification mechanism effectively recognizes and corrects transmission errors, a high-quality data basis is provided for a subsequent early warning model, the abnormal data recollection mechanism avoids data missing caused by single collection failure, and continuous and stable operation of the monitoring system is ensured.

The invention discloses a grinding machine internal part temperature anomaly detection method based on vibration signal analysis, which comprises the following steps that grinding data are collected through sensor deployment, and the sensors comprise a temperature sensor, a vibration sensor, an infrared thermal imaging sensor, a magnetic resistance current sensor and an inductance type particle sensor; carrying out preprocessing and feature extraction on the collected data; model construction and training are carried out based on data of preprocessing and feature extraction; according to the method, the abnormal condition of the temperature of the part is predicted by detecting the vibration signal of the internal part, the content of metal particles in lubricating oil is detected through the oil analysis sensor, and the abrasion degree of the bearing is judged in combination with the vibration signal. And motor current harmonic characteristics are monitored, and overload or rotor imbalance problems are identified.

The invention relates to the technical field of ring main unit monitoring, and discloses a ring main unit online monitoring system based on multi-state quantity sensing. The system comprises an acquisition module used for acquiring a temperature signal and a partial discharge signal and obtaining state quantity data; the calibration module is electrically connected with the acquisition module and is used for preprocessing and calibrating the state quantity data; the analysis module is electrically connected with the calibration module and is used for performing multi-dimensional analysis on temperature and discharge characteristics; the transmission module is electrically connected with the analysis module and is used for data transmission and fusion processing; the early warning module is electrically connected with the transmission module and is used for performing multi-stage early warning analysis; and the adjusting module is electrically connected with the early warning module and is used for dynamically adjusting the monitoring parameters. According to the invention, accurate evaluation and timely early warning of the equipment operation state are realized, and the technical problems of low accuracy and poor adaptability of a single state quantity monitoring method are solved.

The invention relates to the technical field of electrical variable measurement, in particular to a frequency converter fault detection method and system, and the method comprises the steps: obtaining A-phase current data, temperature data and torque data of a frequency converter at each collection moment; obtaining each current sub-sequence, determining the cycle difference of the current based on the dispersion degree of the distribution condition of the current data in all the current sub-sequences, and determining the waveform change value of the current by combining the difference of the corresponding torque data between each screened current sub-sequence and the adjacent current sub-sequence; respectively determining fundamental frequency indexes of the normal current data and the current data to be detected; determining a deviation value of the current; the temperature rising speed, the stability condition when the temperature reaches the maximum value and whether the rapid temperature rising is caused by load changes or not are analyzed, and the abnormal temperature rising value of the temperature is determined; and performing fault detection on the frequency converter. The invention aims to improve the open-circuit fault detection precision of the frequency converter.

The invention discloses an intelligent water quality monitoring device based on Internet of Things, relates to the technical field of environmental monitoring, and aims to analyze a complex nonlinear relationship in water quality data, accurately predict a water quality change trend and identify potential water quality problems in advance through a deep learning model and a system. The dynamic weight calculation module can dynamically adjust the importance of water quality parameters according to real-time data and environmental changes, the monitoring precision and adaptability are improved, an intelligent feedback mechanism automatically adjusts the sampling frequency and the sensor position when an early warning signal is triggered, accurate monitoring of the water quality changes is ensured, and the monitoring accuracy is improved. The Internet of Things technology supports real-time transmission of water quality data and analysis results to the cloud, managers can check water quality states, historical trends and early warning records through a remote monitoring interface, the response capability and management efficiency of the system are improved, and the intelligent water quality monitoring device has the advantages of being high in precision, high in intelligence and high in adaptability.

The invention relates to the technical field of seepage monitoring, and discloses a seepage monitoring system based on a hydraulic engineering project. The system collects water level, flow velocity, seepage flow, soil humidity, soil temperature and soil pressure data through a data collection module, a data analysis module calculates standard soil humidity, standard water flow velocity, standard soil pressure, standard soil temperature and standard seepage flow according to the data, establishes a mathematical model, calculates seepage abnormal indexes, and calculates the seepage abnormal indexes according to the standard soil humidity, the standard water flow velocity, the standard soil pressure, the standard soil temperature and the standard seepage flow. The risk assessment and early warning module performs threshold judgment on the seepage abnormal indexes, sends out an overrun signal when an overrun condition occurs, predicts a future seepage trend by using a moving average method at the moment, generates a future seepage trend broken line graph and a seepage risk assessment report, and uniformly transmits the future seepage trend broken line graph and the seepage risk assessment report to the emergency response module; and when the emergency response module receives the overrun signal, an emergency plan is started, and related managers are informed of the emergency plan, the future seepage trend broken line graph and the seepage risk assessment report in a short message mode.

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 relates to the technical field of power equipment monitoring, in particular to a 10kV cable joint temperature inversion correction method based on environmental heat exchange conditions, which comprises the following steps: measuring surface temperature data through a sensor array, and analyzing material layering characteristics in combination with X-ray imaging; then, establishing an electromagnetic-thermal-fluid field coupling model, and calculating a dynamic thermal resistance coefficient and a heat flow distortion index; thirdly, optimizing surface temperature distribution and iteratively updating thermal resistance parameters by utilizing a bidirectional feedback correction strategy, and finally generating a high-precision internal temperature field; through adaptive temperature compensation and multi-source data fusion, the accuracy of temperature prediction is improved, long-term monitoring errors are reduced, the method can be widely applied to intelligent operation and maintenance and fault early warning of cable joints, and the safety and stability of a power system are improved.

Disclosed is a disinfection lamp with an underwater light projection effect, comprising an upper lampshade, a lower lampshade, a lens lampshade and a tube for containing sustained release chlorine tablets, wherein a circuit board and a battery are arranged on the lens lampshade, a solar panel is mounted on the surface of the upper lampshade, a first light bead is arranged on the lower surface of the circuit board, a light diffuser is arranged at a position, corresponding to the first light bead, of a bottom of the lens lampshade, the first light bead is located in the light diffuser, and the lower lampshade is mounted at the bottom of the lens lampshade. The disinfection lamp can float on water, and the tube containing the sustained release chlorine tablets is immersed in water, such that a conventional water purification, sterilization and disinfection effect is realized.

The invention relates to the technical field of three-dimensional observation, in particular to a geological deformation three-dimensional observation system and method, and the method comprises the steps: multi-dimensional data collection: synchronously obtaining data, and collecting ground temperature gradient field data and underground water flow velocity field data of a monitoring region; data space-time calibration processing: performing space-time reference unification processing on the acquired data to generate a multi-source displacement data set after space-time calibration; cold door parameter extraction: generating an environment coupling parameter matrix based on ground temperature gradient field data and underground water flow velocity field data in multi-dimensional data acquisition; modeling a three-dimensional deformation field: generating an initial three-dimensional deformation field model; dynamic model correction: performing iterative correction on the initial three-dimensional deformation field model to generate an optimized three-dimensional deformation field model; and visual early warning output: generating an early warning signal with a risk level identifier. According to the method, a multi-source heterogeneous data fusion system is constructed, and a cold geological parameter dynamic compensation mechanism is combined, so that high-precision three-dimensional deformation field modeling and early warning are realized.

A floating thermometer with a disinfection device includes a shell, a temperature sensing device and a display device. An upper part of the shell is provided with a sealed first accommodating chamber, first accommodating chamber is arranged with a control device. A lower part of the shell is provided with a second accommodating chamber and a first through hole connected to the second accommodating chamber. The temperature sensing device is located on surface of the shell and electrically connected to the control device. The temperature sensing device is configured to be immersed in water to detect water temperature, generate an electrical signal, and transmit the electrical signal to the control device. The display device is located on upper surface of the shell and electrically connected to the control device. The control device receives the electrical signal and controls the display device to show temperature.

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 discloses a power distribution system and method for a modular power supply, and aims to optimize power distribution through an intelligent means, improve the operation efficiency and stability of the system, and control a unit to check the states of all power supply modules, and evaluate the required total power output according to the load demand. Then, based on the capability of each module and a redundancy planning principle, an appropriate module combination is selected to meet the load requirement, and necessary voltage or current adjustment is carried out to ensure stable power supply. In the operation process, the control system continuously monitors the state and the overall performance of each module, and once a fault or an abnormal condition is detected, measures such as automatic switching to a standby module are taken immediately, so that the continuity and the safety of the system are ensured. In addition, through analysis and learning of historical data, the system can continuously optimize a power distribution strategy, and efficiency and reliability are further improved. And the ability of the system to deal with emergency situations is also enhanced.

The invention discloses a hydration heat monitoring and dynamic regulation and control method and system in a mass concrete pouring process, and relates to the technical field of concrete pouring, and the method comprises the steps: pre-burying a plurality of dual-mode temperature measurement probes in concrete, collecting dual-mode temperature field data in the concrete in real time, and synchronously collecting environmental parameters; carrying out preprocessing, dynamic weight distribution and data fusion on the obtained dual-mode temperature field data; according to the unsteady state heat transfer equation and the hydration heat model, a finite element heat conduction model is constructed, and the total hydration heat and the temperature difference trend are inverted through actually measured temperature field data; predicting a concrete core and surface temperature difference and a surface and environment temperature difference in a future set time period by combining an LSTM neural network model; and according to the predicted temperature difference result, the cooling water flow rate and the cooling water temperature are subjected to closed-loop regulation. Through the combination of dual-mode sensor temperature measurement and heat inversion, the hydration heat temperature difference in the concrete can be predicted in advance, a cooling scheme is regulated and controlled in real time in a linkage mode, and temperature stress cracks are avoided.

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention relates to the technical field of fire early warning, in particular to an electrical fire early warning method, device and equipment based on leakage current temperature detection. The method comprises the following steps: acquiring information data of electrical equipment; performing electrical equipment power line position positioning on the electrical equipment information data to generate electrical equipment power line position information data; performing leakage current sensor data acquisition on the electrical equipment power line position information data to obtain standard electrical equipment leakage current monitoring data; and performing maximum fluctuation curve segment confirmation on the leakage current monitoring data of the standard electrical equipment to obtain a maximum fluctuation curve of the leakage current of the electrical equipment. According to the invention, by introducing leakage current fluctuation mode identification, accurate power line positioning, intelligent anomaly detection and heat map analysis, the accuracy, response speed and positioning capability of the electrical fire early warning system are improved.

The invention discloses a bus duct trend analysis early warning method and system and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: determining N bus duct key positions, and arranging sensor groups on the N bus duct key positions respectively to obtain a sensor monitoring network; acquiring N pieces of temperature time sequence data and N pieces of current time sequence data; performing temperature difference calculation and current change rate calculation on the N pieces of temperature time sequence data to obtain N key position temperature change rates and N key position current change rates; carrying out integration trend analysis, and determining a bus duct abnormal operation trend result; and constructing an alarm mechanism, triggering the alarm mechanism based on a bus duct abnormal operation trend result to carry out classification matching, determining operation early warning parameters, and carrying out operation early warning control on the target bus duct. The technical problems of inaccurate monitoring of the running state of the bus duct and untimely early warning in the prior art are solved, and the technical effect of improving the accuracy and timeliness of running monitoring of the bus duct is achieved.

The invention discloses a mass concrete intelligent temperature monitoring system and method, and the system comprises a high-precision temperature sensor, a data collection node which is connected with the high-precision temperature sensor and is responsible for carrying out the primary processing and integration of temperature data collected by the sensor, and a data collection terminal which serves as a data convergence center of the whole monitoring system and is used for collecting the temperature data. The intelligent temperature monitoring system comprises a plurality of data acquisition nodes which are connected in a wired or wireless communication mode, a data monitoring platform which operates at a server end and is a core control and management unit of the whole intelligent temperature monitoring system, and a circulating water cooling control system which is composed of a cooling water pump, a cooling tower, a cooling water pipe network, a temperature control main station and the like. The cooling water pipe network is embedded in the concrete in advance to form a closed water circulation loop; the temperature control master station receives a cooling control instruction sent by the data monitoring platform, and adjusts the rotating speed of a cooling water pump and the working state of a cooling tower according to the instruction, so that the flow and temperature of cooling water in a cooling water pipe network are accurately controlled; through flowing of circulating water in the concrete, redundant heat in the concrete is taken away, effective regulation and control over the temperature in the concrete are achieved, key indexes such as the highest temperature and the temperature gradient of the concrete are controlled within a reasonable range all the time, and concrete cracks caused by temperature stress are avoided.

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.