Self-diagnosis Function Research Articles

Self-diagnosis of structural damage in self-powered piezoelectric composites

At present, nondestructive testing and non-self-powered structure health monitoring methods are usually used to judge the damage of fiber reinforced composites. However, these methods have some limitations due to the lack of real-time characteristics, the need for external power supply or the complex structure of sensor. In this work, the piezoelectric nanogenerator mechanism was integrated into the traditional composites to develop the piezoelectric composite with damage self-diagnosis function. The piezoelectric composites can realize structural health monitoring and damage localization without reducing the original mechanical properties. The effects of PVDF and barium titanate on the mechanical properties of the composites were investigated by experiments and simulations. Furthermore, the damage self-diagnosis characteristics of composites under bending load and impact load were studied. The algebraic relationship between the damage area and the open circuit voltage under impact load was established. In addition, the damage localization of composite materials is realized by designing an Application (APP). In general, this work has successfully set a precedent for the application of nanogenerator mechanism to the self-powered and self-diagnosis of composite damage, which has the potential to be used in any field related to composites, such as aerospace, etc.

The Research of Complex Product Design Process Model under the Concept of Self-Recovery

The working environment of contemporary mechanical products is becoming more complex, and the working conditions are becoming more extreme. This has led to a significant increase in the frequency of problems in mechanical products. In order to reduce the frequency of human repair after problems, the application of the self-recovery concept has become a hot research topic in the area of smart design. However, the current application of the self-recovery concept is mostly limited to the structural and parametric levels, with less research at the functional level, which may lead to a waste of resources within products. To solve this problem, this research combines the functional-level product research method with the self-recovery concept and establishes a design process model of complex products under functional self-recovery. This model extends the application scope of the self-recovery concept and improves the efficiency of resource utilization in the product. The design process model has six steps. First, according to the user requirements and the existing product, the initial function solving is carried out, and the initial function model of the product is established. Next, the main functions of the product are determined based on the initial function model of the product. Then, according to the determined main functions of the product, combined with the parameters marked in the function structure, the self-diagnosis function is designed. After that, the LT matrix and effect library are used to design the self-regulation function corresponding to the main functions, and the parameters are used to screen the self-regulation function design scheme. Finally, according to the design scheme of the self-diagnosis function and self-regulation function, the functional period oriented to self-recovery is constructed to ensure the realization of the main functions of the product. The effectiveness of the design process model is proved through the design process of an intelligent photovoltaic power generation system at the end of the paper.

Safety analysis of signal quality bits in nuclear power plant distributed control systems based on system-theoretic process analysis method

As a part of self-diagnosis functions, the instrumentation signal quality bit (SQB) is widely introduced in engineering applications, especially in nuclear power plant (NPP) distributed control systems (DCSs). However, the introduction of SQB significantly increases the DCS software complexity and may potentially be unsafe against its design intention. To reduce unscheduled shutdown accidents caused by potential unsafety, it is necessary to conduct a systematic safety analysis on the SQB. Therefore, this paper selects a CPR1000 NPP unscheduled shutdown accident as the research object to abstractly model and reproduce. The system-theoretic process analysis method is applied to analyze the SQBs involved in the unscheduled shutdown accident, which provides a way to identify the behavior of the system components, the interactions between them, and the safety constraints from the perspective of the whole NPP. Therefore, the weaknesses and potential factors affecting safe NPP operation are located, and countermeasures can be proposed. The safety analysis process can inform the identification of potentially unsafe scenarios and complement the verification and validation of the DCS software. Finally, the NPP economy should be improved while maintaining its reliable and safe operation.

Fiber Bragg Grating Smart Material and Structural Health Monitoring System Based on Digital Twin Drive

The damage self‐diagnosis function puts forward higher requirements for the research and development of intelligent structural health monitoring, and in most cases, it is necessary to monitor the load first, especially the monitoring of the impact load. The development of smart materials and structures is based on advanced sensing systems. In order to achieve this purpose, a high‐speed demodulation system based on fiber grating with double long period grating is studied, and then, a damage self‐diagnosis system based on fiber grating is constructed. The system can realize the strain distribution and impact load monitoring of the structure. After quantitative analysis of the signal, an advanced information identification method is used to realize the impact load location. This paper focuses on the data preprocessing process of bridge health monitoring. In view of the characteristics of high data complexity, large amount of data, and many noise components in the process of structural monitoring, this paper adopts basic data cleaning for the original data set, including data dimensionless and missing value processing. Based on the digital twin technology, the composition of the digital twin KNN model of bridge swivel construction monitoring and management is analyzed, and the digital twin system architecture of bridge swivel construction monitoring and management is built. The function display of the monitoring platform, including setting a variety of permission login modes, displaying BIM model, geographic information, and weather environment; monitoring data entry and addition, deletion, and modification; data chart analysis and export; and email warning, to verify the feasibility of the application of digital twin technology in bridge monitoring, and the advantages of the intelligent monitoring system are obtained. The strain error is found to be less than 15.48 μℇ in the research, which is within the range of the fiber grating. This method can effectively monitor and forecast these distributed, nonlinear, strongly coupled, multivariable, and time‐varying complex structures. By monitoring bridges, the original monitoring data of bridges can be obtained, and scientific research data and analysis services can be provided. In particular, the damage caused by shock and vibration is monitored, so that the accumulation of damage can be detected before it threatens the safety of the structure, so that the damaged structure can be repaired in time to ensure the safe operation of the structure.

Possibility of creating composite materials with self-diagnosis function based on the effect of mechanoluminescence

The increasing productivity of modern information processing systems opens up new possibilities for various technical devices. The ability to very quickly analyze a large amount of information allows you to constantly improve technical systems, including autonomous ones. Sensors or primary converters are used to obtain information about the surrounding world or external influences in technical systems. However, modern technologies make it possible to create materials with desired properties - composite materials. The programmable properties of materials can be strength, rigidity, resistance to mechanical, chemical and temperature influences, but it is especially worth noting the possibility of obtaining materials with specified informative properties. These materials include composites containing mechanoluminescent substances. Such materials can simultaneously be housings of any devices or enclosing structures, they can be parts of load-bearing structures of buildings and structures and at the same time play the role of shock and destruction sensors. Using such materials, you can create panels with a self-diagnostic function.

A Small Diameter Ultrasonic Water Meter With Self-Diagnosis Function and Self-Adaptive Technology

Ultrasonic water meters have current widespread problems of poor site adaptability, low measurement accuracy, and poor stability. A high-precision intelligent ultrasonic water meter with self-diagnosis function and adaptive technology was proposed in this paper, which is focus on improving the measurement accuracy and repeatability of the small pipe diameters. The hardware circuit design of the ultrasonic water meter studied in this paper adopts the low-power STM32L053 microcontroller with Cortex-M0 core architecture and the high-precision 11 ps time resolution timing chip TDC-GP30 to complete the metering function. The software combines pulse width ratio and amplitude voltage measurement technology to make the water meter have self-diagnosis function, avoid measurement errors caused by accidental factors, improve adaptability and measurement accuracy, also the application of adaptive measurement period method is used to improve measurement repeatability. The software adopts the moving average filtering algorithm, which effectively reduces the fluctuation of the time-of-flight(ToF) difference and improve the measurement accuracy of the flow point in the low zone (between the minimum flow and the boundary flow). The experimental verification results show that the accuracy of the small-caliber ultrasonic water meter can reach within ±1.5 %, and the repeatability is less than 0.5 %. In the face of fluid disturbances, adaptive technology is used in this water meter to adjust the measurement period and carry out self-diagnostic function research, and automatically respond to deal with abnormal faults, thereby realizing the demand for intelligence.

A disposable smart microfluidic platform integrated with on-chip flow sensors

Microfluidic devices are powerful tools for biological, biomedical, chemical, and pharmaceutical applications, but their commercialization is still hindered by the lack of methods to automatically control fluid flow in a low-cost, simple, accurate, and safe manner. This study introduces a disposable smart microfluidic platform (DIS-μChip), which can be fully automated and utilized for a wide range of applications. On-chip microfluidic flow sensors are integrated with the platform and placed at all inlet and outlet channels, thereby allowing the DIS-μChip to be fully automated with a pressure control system. Furthermore, these confer a self-diagnosis function through monitoring of all the input and output flow rates. The DIS-μChip consists of a disposable polymeric microchannel superstrate and a permanent multifunctional substrate, which could be assembled and disassembled using only vacuum pressure. The superstrate was fabricated by combining a polydimethylsiloxane microchannel structure with a polyethylene terephthalate (PET) thin film. The substrate contains sense electrodes for the on-chip-integrated flow sensors and functional components for creating an energy field, which can penetrate the PET thin film and manipulate the fluid in the microchannels of the superstrate. Owing to the film-chip technique, the superstrate was disposable and could prevent biological cross-contamination, which cannot be realized with conventional flow sensors. The usefulness of the DIS-μChip was demonstrated by using it to isolate circulating tumor cells from the blood of patients with pancreatic cancer and to obtain cancer-specific genetic information from them with droplet digital PCR.

Functional materials based on the effect of mechanoluminescence for monitoring the state of load-bearing structures

Researches of light-generating converters based on zinc sulfide allowed us to describe the physical nature of the light signal. The description of the physical nature of light generation by semiconductors is based on the band theory of conductivity. This allowed us to determine the conditions for the possibility of registering mechanical impacts using mechanoluminescent pulse pressure sensors. One of the important conditions, as it turned out, is the presence of manganese impurities in the material, which become centers of light emission. Also a necessary condition for the appearance of luminescence is the hardness of the sensor element, it facilitates the transfer of mechanical stress to the crystal lattice of mechanoluminescent material and the changes in it with the release of energy as light. This property of these materials allows them to operate in generator mode and convert mechanical action into an optical signal without additional energy sources. As a result, theoretical and experimental data on the possibility of detecting pulsed mechanical action using distributed mechanoluminescent converters were obtained. As one of the directions of application of such converters, it is proposed to create composite materials with the insertion of light-conducting fibers with longitudinal light transmission, covered with mecanoluminophore particles. This will allow to create composite materials with a self-diagnosis function and the ability to connect to optical data channels for continuous monitoring of the technical condition of load-bearing structures of buildings. Such materials are devoid of such disadvantages as: the need for power supply or a reference light stream, sensitivity to electromagnetic interference, and a low degree of embeddability in the structure, inherent in the devices currently used.

In-Vehicle Diagnostic System for Prognostics and OTA Updates of Automated/Autonomous Vehicles

<div class="section abstract"><div class="htmlview paragraph">The increasing complexity of microcontroller-based automotive E/E systems that control road-vehicles and non-road mobile machinery comes with increased self-diagnosis functions and diagnosability via external test equipment (diagnostic tester).</div><div class="htmlview paragraph">Technicians in the development, production and service depend on diagnostic test equipment that is connected to the E/E system and performs diagnostic communication. Examples of use cases of diagnostic communication include but are not limited to condition monitoring, data acquisition, (guided) fault finding and flash programming.</div><div class="htmlview paragraph">More and more functions of a modern vehicle are realized by software (firmware). Powerful multicore servers replace the numerous control units and many control unit functions can be performed directly by smart sensors and actuators.</div><div class="htmlview paragraph">New E/E system architectures come with increased self-diagnostic capabilities. They automatically perform tests, log diagnostic data and push such data for prognostics purposes and condition (health) monitoring to the cloud. They also support over-the-air firmware updates (FOTA).</div><div class="htmlview paragraph">This paper describes the components of an E/E system that is equipped with an in-vehicle diagnostic tester. The tester consists of standardized components, including MVCI-Server (ISO 22900), ODX (ISO 22901), OTX (ISO 13209) and UDS on IP (ISO 14229-5). The paper includes a description of cybersecurity measures to protect the vehicle against malicious attacks.</div></div>

Finite element approaching analysis of load localization and identification for smart structures

PurposeThe purpose of this paper is to propose a numerical approaching analysis method combining the sequential unconstrained minimization technique and finite element method to identify the loading condition and geometry of smart structures accurately.Design/methodology/approachA new load identification model is built and the finite element approaching method is proposed by the combination of finite element method and optimization technique.FindingsThe approaching algorithm has good convergence and fast approximation speed; the accuracy can meet the engineering requirements. The approaching model is simple, and the precision is controllable and it can be used to solve the load identification problem of the smart material structure.Originality/valueIn view of the cited papers, the information sensed by the smart structure is limited, discrete and contains certain errors. How to derive the cause from the limited, error-containing discrete information is an important problem that needs to be solved by the self-diagnosis function. A load identification model based on structural displacement response is established and a numerical approximation method is proposed by combining the finite element method with the optimization technique; the load magnitude and position of the structure are identified according to the displacement measurement values of the internal finite point in the structure under the load condition.

Retraction Note to: Self-Diagnosis of GFRP Composites Containing Carbon Powder and Fiber as Electrically Conductive Phases

The electrical characteristics of glass fiber reinforced plastic (GFRP) composites have been investigated in order to incorporate a self-diagnosis function suitable for monitoring the health of structural materials. The electrical conductivity was introduced by adding carbon powder (CP) or carbon fibers (CF) into GFRP rods and sheets. The self-diagnosis ability of the composites was evaluated by measuring the change in electrical resistance as a function of stress (or strain) in tensile tests. The resistance of CFGFRP changed only slightly at small strain levels and increased nonlinearly with the applied stress due to cutting of the fibers at higher levels. CPGFRP showed high sensitivity to stress and the resistance changed linearly over a wide strain range. During cyclic loading tests, a residual resistance was also observed in CPGFRP composites after unloading. The residual resistance increased with maximum applied strain, showing that it can be used as an indicator of previously applied strain or stress. It is concluded that the CPGFRP composite is a promising material for simple diagnosis of dynamic damage and cumulative strain.

INDUSTRY 4.0: Predictive Intelligent Maintenance for Production Equipment

In manufacturing, users increasingly demand comprehensive maintenance service in their production equipment in order to ensure high availability and to prevent downtimes in critical phases of the production processes, affecting customer delivery times. From the manufacturer’s point of view, it is vital to optimize and to improve the service provided to the final users, allowing appropriate maintenance planning and responding to the demand. Contrary to the classic preventive maintenance programs in use today, predictive maintenance improves the performance of the equipment, strengthening the business model of companies. Thanks to the inclusion of a set of sensing, condition monitoring, predictive analytics and distribute systems technologies, it is possible to perform and provide a remote technical assistance based on continuous monitoring and maintenance support from a distance. This paper shows the benefits and advantages to be achieved by the development of a comprehensive predictive maintenance, through the concept of Industry 4.0, and focuses on remote monitoring and self-diagnosis function of health condition for the equipment. However, the main emphasis of the work presents the data acquisition and analysis processes to develop predictive algorithms for machines in production.

A detecting method for spherical fuel elements in pebble-bed HTGR using eddy current detection

In pebble-bed high temperature gas-cooled reactors (HTGRs), spherical fuel elements move inside pipelines of a handling system, which should be controlled precisely. A detecting method for these elements is proposed in this paper, which is achieved by a detecting system with self-diagnosis function. Detecting signals are obtained by sensors installed outside pipes. A signal identification algorithm was designed for graphite ball detection. Electromagnetic simulations and detecting experiments were performed for system optimization and development of the method. The results show that the proposed method is capable for spherical fuel elements detection, and can be successfully used in practical application.

An MFC-based online monitoring and alert system for activated sludge process.

In this study, based on a simple, compact and submersible microbial fuel cell (MFC), a novel online monitoring and alert system with self-diagnosis function was established for the activated sludge (AS) process. Such a submersible MFC utilized organic substrates and oxygen in the AS reactor as the electron donor and acceptor respectively, and could provide an evaluation on the status of the AS reactor and thus give a reliable early warning of potential risks. In order to evaluate the reliability and sensitivity of this online monitoring and alert system, a series of tests were conducted to examine the response of this system to various shocks imposed on the AS reactor. The results indicate that this online monitoring and alert system was highly sensitive to the performance variations of the AS reactor. The stability, sensitivity and repeatability of this online system provide feasibility of being incorporated into current control systems of wastewater treatment plants to real-time monitor, diagnose, alert and control the AS process.

Implementation of Smart Car Infotainment System including Black Box and Self-diagnosis Function

Currently, most of cars are equipped with the car infotainment system. In addition, drivers install the additional functions which they want to. The car black box and self-diagnosis tool are remarkable functions among the additional function. If they install the additional functions in their own car, they almost pay purchasing cost. These functions give the convenience to drivers, but it is causing the complex problem and the economic burden. In this paper, we implement car infotainment system which integrates multiple function based on the android platform. Our aim is to solve the above mentioned problem by providing integrated multiple functions of car infotainment.

3A1-I05 暴走時の自己診断機能による制動運動を仮定したロボットエンドエフェクタと眼球の衝突確率の見積もり(安全・安心なRT構築を目指して)

Reasonable risk estimation is indispensable for building a safe human-robot coexistence system. Risks are estimated from the severity of harm and the probability of occurrence of harm in which we focus on the latter. Taking into consideration the possibility of avoiding or limiting harm, we propose a new method for estimating the collision probability between an end-effector tip and an eyeball when the robot goes out of control. With a self-diagnosis function, the robot makes the braking motion and comes to a complete stop. The method basically computes the intersection between the two volumes of the manipulability ellipsoid constructed through motions of the end-effector tip and a human eye.

Safety Voting System Based on D-S Evidence Theory

This thesis proposes a safety instrument system which is based on D-S evidence theory, including sensor, logic voting system and execution unit. While the logic voting system concludes the input circuit, processor, output circuit and the diagnosis module based on D-S evidence theory. According to the diagnosis module in multi-channel logic voting system and calculation based on D-S evidence theory, the interconnected feedback information can improve the reliability of the diagnosis. Therefore, the safety instrument system elaborated in this thesis can achieve system’s self-diagnosis function under the premise of using less hardware equipment and at the mean time acquiring advantages of low cost, reliability and high security. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3510 Full Text: PDF

900MHz 대역 RFID 리더 플랫폼에 관한 연구

The RFID market seems to grow mostly in the logistics and distribution areas. The areas and small sized work places requires multi-steps based system. In the environment, the performance of RFID READER is the most important factor. If RFID READER fails to operate frequency well, it will be difficult to apply RFID technology to work places and manage multi-readers used in a narrow place. This work reveals that making possible multiple readers environment and reporting the state of the entire upgrade are of significant in terms of the system`s functions. This thesis studied RFID reader platform with self-diagnosis function.

Study on Low-Temperature Properties of Self-Monitoring Asphalt Concrete

With the self-diagnosis function of the self-monitoring asphalt concrete, we can evaluate the health status of pavement according to feedback on the electrical signals when it is under variation load. In this paper, indirect tensile test and flexural modulus test were used to study the low-temperature properties of self-monitoring asphalt concrete. The test results show that the performance of self-monitoring asphalt concrete has a strong sense of temperature. The result of low-temperature properties provides a reference for the further study of self-monitoring asphalt concrete.

RFID리더의 자가 진단 기능에 관한 연구

본 논문을 통해 연구된 자가 진단 기능을 갖는 RFID 리더 platform은 자동 상태 인식 기능 및 보고 기능이 탑재되어 있고, 자동 업그레이드 기능과 복수 리더 환경에서 주파수 운영 정책을 사용하기 때문에 앞으로 시스템의 전체적인 운영 환경이 점점 대형화 되고, 멀티 환경에서의 활용도에서 많으며, 국내 RFID 시장 뿐 아니라 세계시장에서 많이 발생하는 요구를 충족할 수 있는 기술이다. RFID reader platform with self-diagnosis function studied in this paper has an automatic state recognition function, a report function, and an automatic upgrade function. Also, since it uses frequency operation policy in multiple reader environments, it will be frequently used in the large operation environment and multi-readers environment. Therefore, the technology can meet the demands not only in the domestic RFID market, but in the global market.