Due to the disadvantages of traditional mercury thermometers, such as longer measurement time and necessity of contact with the human body, a thermometer that uses infrared sensors to detect temperature without contact is designed. The Infrared temperature sensor MLX90614 is designed to collect human or object temperature by the SCM to process the temperature into the LCD display and alarm when over-temperature. Using software design to complete the control of the system. The smart thermometer can achieve non-contact measurement, place the thermometer in the forehead for a few seconds to get the body temperature, to alarm once the set value is exceeded. The design temperature range is 0-55 °C, and temperature resolution is 0.1 °C.

/pdf/development-of-a-non-contact-infrared-thermometer-2y454kfpyb.pdf

Development of a Non-contact Infrared Thermometer

In view of the phenomenon of repeated development in data acquisition system, a universal data acquisition system was designed by using LabVIEW software based on NI-6358 data acquisition card Users could customize the conversion of each channel and store the configuration information through files A high-speed data acquisition and processing framework was proposed by combining state machine and production/consumer system, and it realized synchronous collection of 32 channels and display, convert, stored in real time The test and operation results showed that the system had high sampling rate, stable and reliable operation, and could meet the requirement of generality

Design of LabVIEW based general data acquisition system

In mechanical fault diagnosis of the high voltage circuit breakers (HVCBs), it is often expected that the fault type should be confirmed in time to avoid delaying the best time for mechanical fault diagnosis. The traditional diagnosis method of HVBC is not so profound for the identification of slight faults and does not consider the impact of the recall rate of fault samples on the fault diagnosis results. In this paper, we propose a method for HVCBs mechanical fault diagnosis utilizing variational mode decomposition (VMD) based on improved time segment energy entropy (ITSEE) and a new hybrid classifier. Firstly, the signal is decomposed into $K$ intrinsic mode functions (IMFs) via VMD to establish a component matrix. Secondly, the ITSEE method is used to calculate the energy entropy of the matrix in time domain and frequency domain, so as to better extract the features of slight fault types. Finally, an optimal hybrid classifier model combined of one-class support vector machine (OCSVM) and probabilistic neural network (PNN) is used to identify four types of vibration signals of HVCBs. The experimental results show that the accuracy of unknown samples is 98.75%, and the recall of fault type is 100%. The experimental results show the effectiveness of the method and have important application value for the diagnosis of HVBCs.

/pdf/mechanical-fault-diagnosis-of-high-voltage-circuit-breakers-dhw7yl91oj.pdf

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Utilizing VMD Based on Improved Time Segment Energy Entropy and a New Hybrid Classifier

Study of a dipping method for flip-chip flux coating

In this paper, we proposed a system to integrate optical and electronic instrumentation devices to predict a mode-locking fiber laser response, using a remote data acquisition with processing through an artificial neural network (ANN). The system is made up of an optical spectrum analyzer (OSA), oscilloscope (OSC), polarimeter (PAX), and the data acquisition automation through transmission control protocol/internet protocol (TCP/IP). A graphic user interface (GUI) was developed for automated data acquisition with the purpose to study the operational characteristics and stability at the passively mode-locked fiber laser (figure-eight laser, F8L) output. Moreover, the evolution of the polarization state and the behavior of the pulses are analyzed when polarization is changed by proper control plate adjustments. The data is processed using deep learning techniques, which provide the characteristics of the pulse at the output. Therefore, the parameter classification-identification is in accordance with the input polarization tilt used for the laser optimization.

https://www.mdpi.com/2079-9292/9/8/1181/pdf

Automated Data Acquisition System Using a Neural Network for Prediction Response in a Mode-Locked Fiber Laser

Based on LabVIEW, this paper presents a design scheme of data acquisition, which it proposes using computer and ordinary data collection card as the main hardware and LabVIEW as software development platform, thus constructs the virtual instrument system for signal acquisition. The system can realize synchronous data acquisition of single channel or multi-channel signal, as well as real-time display and preservation. The practice shows that this scheme can not only effectively play performance of ordinary data acquisition card, but also reduce greatly program development time and beautify interface through LabVIEW which has powerfully visual human-machine interface editor and graphical programming function.

Design of Data Acquisition System Based on LabVIEW

According to Dynamic Link Library (DLL), the common motion card was successfully run on Labview virtual platform, which can graphically compile program. Based on Labview8.6 platform, Leadtech SMC-6480 control card and Yaskawa SJME-02AMA41 servo motor were used as the hardware to realize multi-axes motion control. The results indicated that each axis has three motion models of automatic, manual and return-to-zero, which can switch mutually at any time.

Jun Hui Li

Papers

Design of Data Acquisition System Based on LabVIEW

Research of Multi-Axes Motion Control System Based on LabVIEW Platform