Intelligent Test System Research Articles

Development of Intelligent Testing and Evaluation System for Fracturing Pump

Abstract Fracturing truck is the key technical equipment for oil and gas production stimulation. Fracturing pump of fracturing truck is subjected to high pressure load for a long time during use. Due to the influence of many factors such as transportation and equipment aging, the performance of fracturing pump in field use is reduced and the output power is insufficient. In order to realize the on-site inspection of fracturing pump, a set of intelligent inspection and evaluation system of fracturing pump is developed. Through the establishment of the hardware test platform and the development of the software system, the intelligent inspection and evaluation system of fracturing pump with the features of one-click automatic detection, automatic analysis of performance indicators, intelligent prediction and maintenance of health status is realized. The system can support the static pressure test, water power test and overpressure protection test of 140MPa ultra-high pressure fracturing pump. Experimental tests show that the test accuracy of the equipment can effectively meet the detection and evaluation needs of the field fracturing truck, ensure the normal function through static pressure and water power detection, and determine the safety of the equipment through overpressure protection detection, which greatly improves the effect and efficiency of fracturing operations.

A quantitative study of the effects of physical properties and external loads on the liquefaction of saturated sand based on an intelligent numerical cyclic triaxial test system

ABSTRACT Soil liquefaction would cause significant damage to the safety of cargo transportation. The aim of this article is to conduct a quantitative study of the influence of the main physical characteristic parameters of saturated sand and external loads on its liquefaction. On the basis of the physical cyclic triaxial test (CTT), the finite element simulation model and PSO-BP neural network prediction model and importance analysis model were optimised in this study. Based on this, an innovative intelligent numerical CTT system for saturated sand was constructed. The research results indicate the influence of external load, effective internal friction Angle and plasticity index on the liquefaction of saturated sand is significant, and the average weight is 40.15%, 29.15% and 25.05%, respectively. In this paper, the relevant research provides a theoretical basis for effective control of sand liquefaction and provides new ideas and feasible solutions for subsequent research on sand liquefaction.

Design and implementation of intelligent camshaft press-fit testing system

Abstract In order to improve the assembly efficiency and automation level of camshaft press-fit equipment for domestic enterprises and achieve data traceability, a smart camshaft real-time press-fit detection system based on C# has been designed and developed. The system adopts modular thinking for C# program design and interface design, collects pressure and displacement data during the press-fit process, forms curves, and uses regional determination methods to determine the results, in order to achieve the goal of press-fit detection. After the press-fit is completed, the press-fit result data and curve data are saved to the database, achieving data traceability. The system collects data from the upper computer and determines the press-fit result, reducing the workload of the equipment controller (PLC), improving assembly efficiency and detection accuracy, and is innovative to some extent. After testing, the system runs stably and reliably, providing a certain reference value for the intelligent transformation of press-fit equipment.

Estimation of Tire Side-Slip Angles Based on the Frequency Domain Lateral Acceleration Characteristics Inside Tires

The identification and control of tire side slip angle is the key to vehicle stability control. Intelligent tire technology based on the sensing of side-slip acceleration inside the tire provides a novel method for estimating the tire side-slip angle. This study proposed a method to estimate the tire side-slip angle by using the frequency domain lateral acceleration of the tire. First, an intelligent tire testing system was constructed by independently developing a special rim assembly and data collector. A three-axis accelerometer was placed on the right side of the tire, and the acceleration value was acquired by using a wired method with a sampling frequency of 50 kHz. Second, based on the constructed test system, a tire side deflection test was carried out on the Flat Trac bench. Through data analysis, it was found that the lateral acceleration was in the frequency domain of 400 Hz. As the side-slip angle increased from −4° to 4°, the vibration amplitude gradually decreased. Moreover, the vibration amplitude within 0.5~2 kHz was highly correlated with the side-slip angle. Subsequently, the vibration amplitude of the lateral acceleration within 2 kHz was extracted at an interval of 20 Hz as the feature point, and a frequency domain data set FDAy3 was established together with the vertical load and tire pressure. Finally, the support vector machine (SVM) algorithm was employed to make predictions on the data set. The grid search method was utilized to find the optimal parameter values of the model penalty factor c and radial basis kernel function coefficient g, which were 1.4142 and 0.0884, respectively. The results suggested that the root mean square error of the model prediction was 0.0806°, and the maximum estimated angle deviation of the prediction was 0.4587°. Meanwhile, the optimal prediction accuracy and real-time performance were achieved when the number of feature points and the feature frequency band were 25 and within 500 Hz, respectively. The findings of this study confirm that it is feasible to estimate the tire side-slip angle based on the frequency domain lateral acceleration of the tire, which provides a new method for tire side-slip angle estimation.

Overall Scheme Design of Fault Diagnosis for Complex Electronic Systems

Traditional manual testing methods are no longer able to meet the maintenance needs of modern shipboard fire control system board-level circuits. Therefore, the development of intelligent and universal automatic test systems has become an important issue for shipboard fire control system fault detection. This article analyzes the performance and functional requirements of the automatic test system, develops the automatic test system based on PXI bus instruments, and designs an overall solution with signal time-frequency analysis capabilities that can carry out intelligent fault diagnosis for a variety of board-level circuits. On this basis, the design of hardware circuit and software solution is completed. The automatic test system was analyzed on hardware indicators and software functions. On the hardware side, the hardware resource selection was completed based on the hardware indicator requirements. On the software side, the overall software architecture design and the design of each functional module were completed based on the system software functional requirements. Finally, the composition and functions of each module of the system software and the overall operation process are introduced.

Intelligent adaptive testing system

Intelligent adaptive testing system

Retracted: Design and Implementation of a Machine Learning-Based English Intelligent Test System

Retracted: Design and Implementation of a Machine Learning-Based English Intelligent Test System

Intelligent Dynamic Test System for Vehicle Engine Based on 5G Internet of Things

With the development of the automobile industry, the improvement of the reliability test level and the intelligent fault diagnosis level of the engine, as the heart component of the automobile and the assembly with the highest failure rate, becomes more and more important. In a context where technology is being upgraded, the development of intelligent automotive engine inspection system based on IoT thinking is set to become the major trend in the future. The objective of this article would be to have better knowledge about smart car engine system in the 5G IoT era. It is also through the study, a dynamic testing and characterization of the engine. The performance of the automobile engine, especially the dynamic performance, is further optimized. In this article, we focus on the PUMAOPEN test system of AVL and the system under test, the state management of the test process, and the intelligent transformation of key components. The results show that: studies and analyses the dynamic working conditions of intelligent vehicles on the Internet of Things, and compares the dynamic working conditions with the steady working conditions from qualitative to quantitative. By analyzing the influence of throttle opening change rate and speed change rate on dynamic performance and engine dynamic torque estimation, the fast sensing and response-ability in the engine testing process is improved. When the engine is accelerated by the experimental method presented in this article, and when the throttle opening is more than 30% and the engine speed varies at 100 and 200 rpm/s, the output value of the torque is higher than the output value of the steady-state torque or has little difference with the output value of the steady-state torque, and tends to be stable. In deceleration performance, the dynamic output torque of the engine is asymmetric. And it will deviate from the steady-state output torque, showing different dynamic response characteristics in different working sections. Throttle delay, overshoot characteristics, mechanical inertia, inflation coefficient, air–fuel ratio, and ignition advance angle when engine speed changes sharply will make engine dynamic characteristics deviate from steady-state characteristics.

Intelligent Vehicle Engine Dynamic Test System Based on Internet of Things

In the context of technological modernization in the field of automotive engine testing, the development of an intelligent automotive engine testing system based on IQ has become an important trend in the future. This paper mainly studies the development of engine test software platform, the technical control of test process conditions, and the intelligent conversion of important components such as temporary fuel flow meters. By comparing the traditional bench test system and the dynamic test system based on the Internet of Things, the efficiency of data information transmission, information security, perception ability, and response speed between them are compared, and the intelligent dynamic engine detection based on the Internet of Things is found. The system is more secure and more efficient in information transmission, with a 12% increase in perception performance and a 48% increase in system response time. This also fully shows that the intelligent dynamic engine detection system based on the Internet of Things will be more suitable for current equipment and can also be detected more accurately, which can realize effective supervision of the running status of the test prototype and remote online feedback of the analysis results, and solve the engine test process. It solves the problem of efficient, reliable, and safe transmission and transmission of data and information between all levels and layers, and improves the ability of rapid perception and response in the process of engine testing.

A Study on the Design of English Speaking Examination System Based on SSM Framework

At present, the teaching, training, and assessment programs of English speaking courses in schools are basically carried out by the teaching method of face-to-face teaching by teachers, especially in the English speaking assessment; students and teachers communicate with each other to answer questions, while the students’ performance is subjectively judged by the school English teachers. This model not only consumes the teaching resources of school English teachers but also cannot ensure the uniformity of grading standards. To this end, this paper designs and proposes an English speaking test system with the aim of building an intelligent speaking test system by designing a speech recognition deepening frequency processing function through SSM framework combined with JSP technology and deep learning theory. The English speaking test system designed in this paper integrates several open source frameworks, adopts modular design, and divides it into two subsystems, student-side module system and teacher-side module system for system framework design, and finally, this system is tested for functionality. The system was designed and implemented through the framework description, functional description, and functional testing of this system, and finally, the English speaking test system was designed and implemented. The system is designed and implemented to change the traditional one-to-one mode of school teaching, save teachers’ manpower, strengthen the content of intensive training for students’ English proficiency and improve the frequency of exams, facilitate school administrators and English teachers to evaluate the effectiveness of their teaching implementation, and develop corresponding effective individualized teaching and guidance strategies for schools to provide convenience, which can greatly reduce the recognized labor intensity of English teachers and provide a correct evaluation of students, a correct evaluation of the level, and other roles.

Analysis and Prediction of Body Test Results Based on Improved Backpropagation Neural Network Algorithm

The mining and analysis of student achievement data is of great importance to teaching management. Using the relevant data of college students’ physical fitness test and sports performance as the object of research, a BP neural network model is developed to predict performance. Based on BP neural network, an algorithm for predicting students’ endurance performance is proposed, which is applied to the sunshine long-distance intelligent sports testing system at Hangzhou Dianzi University. The nonlinear relationship between students’ performance in sunshine running and endurance performance is determined, and students’ performance in sunshine running is used to predict their endurance performance the following year. Experimental results indicate that the accuracy of the model is above 85%. At the same time, the prediction results are combined with the Internet of things technology to produce a student sports prescription management system, which sets different sunshine running parameters for students with different predicted results and provides personalized sports prescriptions for students with different physical conditions, which has extensive and far-reaching application value.

FRI165 - The upper limit of normal of alanine aminotransferase (ALT) in diagnosing liver disease and fibrosis by the Intelligent Liver Function Test (iLFT) system

FRI165 - The upper limit of normal of alanine aminotransferase (ALT) in diagnosing liver disease and fibrosis by the Intelligent Liver Function Test (iLFT) system

Design and Implementation of a Machine Learning-Based English Intelligent Test System

Examination is a particularly important part of the students’ whole learning process. Therefore, this paper designs and develops an online examination system. This paper studies an examination recommendation algorithm based on a machine learning neural network model. The algorithm can recommend problems for students according to students’ error history, error prone, and knowledge poor problems. Experiments also show that the recommendation algorithm studied in this paper improves the recommendation effect compared with several other similar algorithms.

An intelligent testing system development based on the shingle algorithm for assessing humanities students' academic achievements.

Computer-based testing of humanities students has some inconveniences and difficulties, where the whole learning process is practically based on communicative methods. In this regard, one needs such a testing system, which would allow one to ask open-ended questions, and students would be able to enter detailed answers. Despite the popularity of using the shingle algorithm in determining plagiarism, few researchers have attempted to use it in assessing the academic achievements of students. In this regard, the aim of this study was to develop an intelligent testing system based on the shingle algorithm in assessing the academic achievements of humanities students. Taking into account that during testing humanities students will formulate answers of their own understanding, the developed system should be able to determine the degree of their identity to the correct answer. At the same time, answers with a high degree of correspondence to the answer stored in the dictionary should also be entered in the database as one of the variants of the correct answer. The shingle algorithm, stemming, and MD5 hashing algorithms were used to achieve this goal. The performance of the algorithm was evaluated in terms of degree of matching (S), completeness (P), F-measure and performance (t). The experiment involved 120 humanities students in 2–3 courses at the age of 18–20 years, including 80 girls and 40 boys. It was found that the effectiveness of the developed algorithm is achieved at the optimal time t = 77% and the degree of compliance of the final grade F = 77%. In this case, the final score of the F-measure fully reflects the result at the proportion of truthfulness equal to 0.5 and is directly proportional to the degree of compliance (S) and completeness (P) of use. It is found that a high value of the matching degree (S) is achieved with a smaller shingle length, while with a larger shingle length the matching degree decreases, thus, the probability of finding the same phrase in two documents increases. In addition, with smaller shingle lengths, the time spent calculating checksums is longer, and with larger shingle lengths, the time spent calculating checksums is shorter. Calculations showed that the optimal shingle algorithm efficiency was at the length of the shingle N = 5 of the average data processing time. The results of this study show that the developed algorithm can be included in pedagogical practice in order to objectively assess the learning achievements of humanities students, taking into account their communicative and cognitive abilities. In the future, the developed algorithm can also be used in other areas requiring text analysis, in particular for checking plagiarism.

IDF21-0225 Research on influencing factors of dynamic plantar pressure in diabetic patients based on intelligent shoe system

Background: The abnormal size and distribution of plantar pressure in diabetic patients is an important factor affecting the formation of foot ulcers, which can predict the occurrence of foot ulcers in patients early. The intelligent shoe testing system makes up for the shortage of force measuring plate and force measuring table, continuously and dynamically monitoring the patient’s plantar pressure parameters for a long time. When there is a disease condition in the foot of a diabetic patient, the foot function appears abnormal, causing abnormal changes in plantar pressure.

Intelligent Body Measurement System (IBMS) in Colleges and Universities Based on Internet of Things(IOT) Technology

Nowadays, teenagers' physical quality is getting worse and worse. Therefore, the Party Central Committee has established the educational policy of "health first" as the guiding ideology. In order to fully implement the party's education policy, a wave of sports towards stadiums or playgrounds has swept across the country. However, schools lack effective management means and methods for large-scale sunshine sports. Therefore, many colleges and universities have put forward tough measures for students' middle and long-distance running in sunshine sports, requiring each student to complete a certain number of kilometers of long-distance running distance every semester, record students' long-distance running with manual recording method, and finally count it into students' total score as a course. This scheme provides a good entry point for the development of sunshine sports, but the disadvantages of manual recording method also appear: a large number of students, a large number of long-distance runs, a large amount of data, inconvenient statistics, and recording with notes, low efficiency, heavy workload of statisticians, and error prone. Therefore, this paper puts forward the design of College intelligent physical testing system based on IOT technology, and develops the college intelligent physical testing system. This paper discusses the design objectives and principles of the ibms and the overall design idea of the system software, and takes a university as an example to test the packet loss rate of the intelligent test system under the IOT technology and the body temperature index under different distances. The experimental results show that the packet loss rate is very low and almost negligible, and in terms of communication distance, there is no packet loss within 500m; The website is stable, the information is uploaded in time, the calculation accuracy is high, and the students' feedback is good; When the distance is 1m, the body temperature is 36.6℃, when the distance is 12M, the body temperature is 36.5℃, and the error is small. The system has good flexibility. The hardware test shows that the hardware equipment selection of this system is perfect, the function is perfect, and the stability and flexibility are very high.

Analysis and Research of Intelligent Test and Appraise System Based on ADO. NET

This paper expounds the research and development of ADO.NET object model, VB.NET development environment and other related technologies and intelligent test and appraise system, analyzes the practical significance of system research and development and use, discusses the research and development process of database setting, array application, random test, intelligent test and appraise, information interaction, score analysis and other functions, and carries out system practice test, function upgrade and application prospect analysis. The system has been continuously used in the practical training of specialized courses. The results show that the system has good practicability and is well received by teachers and students. It is worth upgrading, perfecting and popularizing.

Association of neonatal blood calcium levels with perinatal factors and neonatal urinary calcium levels measured by an intelligent urine test system

OBJECTIVE To study the association of neonatal blood calcium levels with perinatal factors and neonatal urinary calcium levels measured by an intelligent urine test system. METHODS The medical data of 96 full-term singleton neonates with mild diseases were collected by a cross-sectional survey, who were hospitalized in the Department of Neonatology, The First Affiliated Hospital of Xi'an Jiaotong University, from June to August 2018. Urinary calcium levels measured by an intelligent urine test system, total blood calcium levels, ionized calcium levels, and the mother's calcium and vitamin D supplementation during pregnancy were recorded. RESULTS Compared with the group without vitamin D supplementation for the mother (17 neonates), the group with vitamin D supplementation for the mother (79 neonates) had significantly higher levels of total blood calcium and ionized calcium (P 0.05). The hypothermia group (5 neonates) had a significantly lower level of total blood calcium than the normal body temperature group (91 neonates) (P < 0.05). There was a significantly positive correlation between the maternal blood total calcium level and the neonatal blood total calcium and ionized calcium levels (r=0.881 and 0.703 respectively; P < 0.05). The neonatal urinary calcium level measured by the intelligent urine test system was significantly correlated with the blood ionized calcium level (r=0.526, P=0.025). CONCLUSIONS Vitamin D supplementation during pregnancy can increase the blood levels of total calcium and ionized calcium in neonates, and calcium supplementation alone cannot increase the blood levels of total calcium or ionized calcium in neonates. Hypothermia in neonates might cause the reduction in blood calcium levels. The urinary calcium level measured by the intelligent urine test system is positively correlated with the blood level of ionized calcium.

Design of Intelligent Test System of Navigation Equipment for a Type of Airplane

Design of Intelligent Test System of Navigation Equipment for a Type of Airplane

Construction of intelligent testing system for electronic components

In order to solve the problems such as unreasonable plan, opaque process, insufficient flexibility and excessive manual participation in the process of screening, identification and quality consistency inspection of electronic components in China, a software and hardware construction scheme of intelligent detection system for electronic components is proposed, which integrates the cutting-edge technologies such as machine vision, deep learning, IOT(internet of things), data mining. Relying on the National Semiconductor Device Quality Supervision and Inspection Center, part of the construction work has been completed, and the information, automation and intelligence of the testing business have been realized.