scholarly journals A Virtual Instrument System for Determining Sugar Degree of Honey

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Qijun Wu ◽  
Xun Gong
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Optical Activity ◽  
Virtual Instrument ◽  
Activity Measurement ◽  
Optical Instrument ◽  
Measurement Results ◽  
Automatic Acquisition ◽  
Man Machine Dialogue ◽  
Improved Accuracy

This study established a LabVIEW-based virtual instrument system to measure optical activity through the communication of conventional optical instrument with computer via RS232 port. This system realized the functions for automatic acquisition, real-time display, data processing, results playback, and so forth. Therefore, it improved accuracy of the measurement results by avoiding the artificial operation, cumbersome data processing, and the artificial error in optical activity measurement. The system was applied to the analysis of the batch inspection on the sugar degree of honey. The results obtained were satisfying. Moreover, it showed advantages such as friendly man-machine dialogue, simple operation, and easily expanded functions.

Study on the Portable Plate Stiffness Tester Based on LabVIEW

2014 ◽  
Vol 556-562 ◽  
pp. 6403-6406
Author(s):  
Li Wei ◽  
Yu Jing Guo
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Virtual Instrument ◽  
Force Sensor ◽  
Frame Structure ◽  
Displacement Sensor ◽  
Development Platform ◽  
Data Acquisition Card ◽  
Efficient Data ◽  
And Storage

Usually the covering part of large frame structure is heavy and it is difficult to measure the stiffness of the covering part. In this paper, it makes use of virtual instrument instead of traditional instrument. In addition, it adopts LabVIEW as development platform and the hardware includes stepping motor, data acquisition card of NI, force sensor and displacement sensor, etc. The portable plate stiffness tester is developed successfully, which is applied to industrial field. It is normative and accuracy for the quantitative evaluation of the covering parts stiffness, which plays an important role for guiding production. LabVIEW development platform relative to traditional instrument has many advantages, such as real-time display and storage, efficient data processing and powerful database management and so on.

scholarly journals The real-time big data processing method based on LSTM or GRU for the smart job shop production process

2020 ◽  
Vol 14 ◽  
pp. 174830262096239 ◽  
Author(s):  
Chuang Wang ◽  
Wenbo Du ◽  
Zhixiang Zhu ◽  
Zhifeng Yue
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Production Process ◽  
Real Time ◽  
Job Shop ◽  
Production Data ◽  
Time Data ◽  
Big Data Processing ◽  
The Real ◽  
Data Processing Method

With the wide application of intelligent sensors and internet of things (IoT) in the smart job shop, a large number of real-time production data is collected. Accurate analysis of the collected data can help producers to make effective decisions. Compared with the traditional data processing methods, artificial intelligence, as the main big data analysis method, is more and more applied to the manufacturing industry. However, the ability of different AI models to process real-time data of smart job shop production is also different. Based on this, a real-time big data processing method for the job shop production process based on Long Short-Term Memory (LSTM) and Gate Recurrent Unit (GRU) is proposed. This method uses the historical production data extracted by the IoT job shop as the original data set, and after data preprocessing, uses the LSTM and GRU model to train and predict the real-time data of the job shop. Through the description and implementation of the model, it is compared with KNN, DT and traditional neural network model. The results show that in the real-time big data processing of production process, the performance of the LSTM and GRU models is superior to the traditional neural network, K nearest neighbor (KNN), decision tree (DT). When the performance is similar to LSTM, the training time of GRU is much lower than LSTM model.

A New Approach of Expanding Data Processing Ability for Configuration Monitoring Software MCGS Based on OLE

2011 ◽  
Vol 65 ◽  
pp. 295-298 ◽  
Author(s):  
Fan Yang ◽  
Cai Li Zhang
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Monitoring System ◽  
Programming Language ◽  
Configuration Software ◽  
Time Data ◽  
Software Configuration ◽  
Processing Ability ◽  
Significant Performance ◽  
Monitoring Software

Considering the insufficient ability of data processing existed in configuration software, a scheme integrated both advantages of advanced programming language and configuration software is provided. In this scheme real-time data acquisition and complex processing are achieved by advanced programming language, the human-computer interface and other functions of the monitoring system are achieved by configuration software. Configuration software achieves the purpose of expanding data processing ability by data communications between advanced programming language and configuration software based on OLE technology. The practical application result indicates that the data processing ability of configuration software can be effectively expanded based on OLE technology, which has well stability and real-time, and can play significant performance in complex parameters and data processing related monitoring system.

scholarly journals Initial operation and data processing on a system for real-time evaluation of Thomson scattering signals on the Large Helical Device

2021 ◽  
Vol 92 (6) ◽  
pp. 063523
Author(s):  
K. C. Hammond ◽  
F. M. Laggner ◽  
A. Diallo ◽  
S. Doskoczynski ◽  
C. Freeman ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Thomson Scattering ◽  
Initial Operation ◽  
Time Evaluation

scholarly journals Big Data Usage Patterns in the Health Care Domain: A Use Case Driven Approach Applied to the Assessment of Vaccination Benefits and Risks

2014 ◽  
Vol 23 (01) ◽  
pp. 27-35 ◽  
Author(s):  
S. de Lusignan ◽  
S-T. Liaw ◽  
C. Kuziemsky ◽  
F. Mold ◽  
P. Krause ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Real Time ◽  
Predictive Analytics ◽  
Regulatory Compliance ◽  
Use Cases ◽  
Data Sources ◽  
Use Case ◽  
Crowd Sourcing ◽  
Big Data Processing

Summary Background: Generally benefits and risks of vaccines can be determined from studies carried out as part of regulatory compliance, followed by surveillance of routine data; however there are some rarer and more long term events that require new methods. Big data generated by increasingly affordable personalised computing, and from pervasive computing devices is rapidly growing and low cost, high volume, cloud computing makes the processing of these data inexpensive. Objective: To describe how big data and related analytical methods might be applied to assess the benefits and risks of vaccines. Method: We reviewed the literature on the use of big data to improve health, applied to generic vaccine use cases, that illustrate benefits and risks of vaccination. We defined a use case as the interaction between a user and an information system to achieve a goal. We used flu vaccination and pre-school childhood immunisation as exemplars. Results: We reviewed three big data use cases relevant to assessing vaccine benefits and risks: (i) Big data processing using crowd-sourcing, distributed big data processing, and predictive analytics, (ii) Data integration from heterogeneous big data sources, e.g. the increasing range of devices in the “internet of things”, and (iii) Real-time monitoring for the direct monitoring of epidemics as well as vaccine effects via social media and other data sources. Conclusions: Big data raises new ethical dilemmas, though its analysis methods can bring complementary real-time capabilities for monitoring epidemics and assessing vaccine benefit-risk balance.

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