Control System Failure Research Articles

Fault diagnosis of wet clutch control system of tractor hydrostatic power split continuously variable transmission

A hydrostatic power split continuously variable transmission (CVT) for a tractor often has multiple ranges to improve transmission efficiency. However, a failure of the wet-clutch control system will lead to interruption of tractor power and even endanger driving safety. To improve the reliability of CVT tractors, methods for diagnosing faults in the wet-clutch control system were studied. A test bench was built and the clutch engagement pressure was measured under different fault modes. For these time series data, statistics such as the mean, variance, kurtosis etc. were selected as features in the analysis. An improved Gaussian naive Bayes algorithm based on a time window as well as principal component analysis were used to classify the different fault modes of the clutch control system. Finally, the performance of the algorithm was analyzed. A test with multiple faults was run, as was a comparison with traditional algorithms. By optimizing the time window for data interception, the classification accuracy of the Gaussian naive Bayes algorithm for normal operation reached 97% and reached 100% for the fault modes. The average accuracy and recall rate of fault diagnosis were 98.2% and 89.4%, respectively, which are better than the results for a support vector machine, the k-nearest neighbors algorithm, or the decision tree algorithm. Importantly, the results show that the clutch pressure fluctuations during the shift by a tractor CVT can be used for the fault diagnosis of a clutch control system.

Data-Driven Fault-Tolerant Control for Discrete-Time Systems based on LMI

Actuator failure of control systems is one of the main factors causing instability and performance degradation. Over the past few decades, fault-tolerant control strategies have been introduced to improve the performance of control systems against failure. The current fault-tolerant control approaches are mostly model-based, however, model identification is time-costly and costly. In this paper, a data-driven fault-tolerant control method for discrete-time systems with actuator faults is designed. Using the input and output data collected directly from the system, the data-driven method develops the fault-tolerant control strategy for discrete-time systems with unknown or complex model. Moreover, the stability condition of the strategy is derived based on linear matrix inequality (LMI). Finally, a simulation is presented to demonstrate the effectiveness of the data-driven fault-tolerant control strategy, using an aircraft dynamic system model with actuator failure.

MODERN SAFETY REQUIREMENTS FOR INDUSTRIAL EQUIPMENT MANAGEMENT SYSTEMS (Part 2. Safety indicators of control systems)

Purpose: Analysis and determination of the main modern international safety requirements that must be met in the design, development and operation of industrial equipment management systems, as well as confirmation of the need for further improvement of the domestic regulatory framework in this area. Methodology/approach: Performed analysis of the requirements of modern international standards (IEC 62061 and IEC 61508) on the safety of electrical, electronic and programmable electronic control systems for industrial equipment and the existing sequence of protection against hazards; the algorithm of step-by-step realization of control systems and the basic features of the organization of their structures at the level of functional blocks and subsystems for maintenance of necessary level of completeness of functional safety are defined; the peculiarities of the process of design and development of each of the subsystems and the algorithm of its execution are analyzed; defined algorithms for estimating the probability of dangerous accidental hardware failures for the recommended basic architecture of subsystems (type A, B, C and D) and for the control system itself; provided recommendations on the composition of the specification of safety requirements in the design of control systems; reviewed software requirements. Conclusions: The analysis of the features of functioning and application of modern international safety standards, which must be observed in the design, development and operation of industrial equipment management systems convincingly confirms the relevance and need for further improvement of domestic regulations in this area. Research results: Modern requirements for the organization of the control system structure at the level of functional units and subsystems to ensure the required level of completeness of functional safety of electrical, electronic and programmable electronic control systems for industrial equipment are determined, as well as features of application the of algorithms for estimating the probability of dangerous accidental failures of control systems and their subsystems. Practical implications: The development and implementation of relevant national standards based on IEC 62061 and IEC 61508 should accelerate the further development of technical progress in Ukraine in the field of industrial safety. Originality/value: Defining the main features of the functioning of modern international safety standards, which must be observed in the design, development and operation of industrial equipment control systems; Appropriate recommendations for their practical application are provided; Substantiated and confirmed the relevance and importance of the development of relevant harmonized national standards based on the standards IEC 62061 and IEC 61508.

AHU sensor minor fault detection based on piecewise ensemble empirical mode decomposition and an improved combined neural network

Faulty or inaccurate sensors may lead to increased energy consumption, thermal discomfort, and even failure of control systems. An improved piecewise ensemble empirical mode decomposition (PEEMD)-improved combined neural network (CoNN) is presented for air handling unit sensor fault detection. Piecewise ensemble empirical mode decomposition is used to enhance data quality by denoising raw data sets. The coupling relationship between variables is determined through a data-driven method, and the variables with the lowest correlation between the basic neural network and the auxiliary neural network are removed to reduce the dimensionality of the system, which can shorten detection times. Based on the CoNN, a modified relative error is proposed to improve the fault detection rate, which is called MOCoNN. The results show that, compared to CoNN, the fault detection rate of PEEMD-MOCoNN improved by 49.21%, 34.85%, 90.70%, and 18.60% in the 5%–10% minor bias fault and 0.01/unit–0.02/unit hidden drift fault. Meanwhile, in the same fault condition, the fault detection rate of PEEMD-MOCoNN improved by 43.41%–85.71% and 16.16%–54.65% compared with those of empirical mode decomposition threshold denoising principal component analysis and kernel principal component analysis and double layer bidirectional long short-term memory, respectively.

Proteinopathies as Hallmarks of Impaired Gene Expression, Proteostasis and Mitochondrial Function in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal adult-onset neurodegenerative disease characterized by progressive degeneration of upper and lower motor neurons. As with the majority of neurodegenerative diseases, the pathological hallmarks of ALS involve proteinopathies which lead to the formation of various polyubiquitylated protein aggregates in neurons and glia. ALS is a highly heterogeneous disease, with both familial and sporadic forms arising from the convergence of multiple disease mechanisms, many of which remain elusive. There has been considerable research effort invested into exploring these disease mechanisms and in recent years dysregulation of RNA metabolism and mitochondrial function have emerged as of crucial importance to the onset and development of ALS proteinopathies. Widespread alterations of the RNA metabolism and post-translational processing of proteins lead to the disruption of multiple biological pathways. Abnormal mitochondrial structure, impaired ATP production, dysregulation of energy metabolism and calcium homeostasis as well as apoptosis have been implicated in the neurodegenerative process. Dysfunctional mitochondria further accumulate in ALS motor neurons and reflect a wider failure of cellular quality control systems, including mitophagy and other autophagic processes. Here, we review the evidence for RNA and mitochondrial dysfunction as some of the earliest critical pathophysiological events leading to the development of ALS proteinopathies, explore their relative pathological contributions and their points of convergence with other key disease mechanisms. This review will focus primarily on mutations in genes causing four major types of ALS (C9ORF72, SOD1, TARDBP/TDP-43, and FUS) and in protein homeostasis genes (SQSTM1, OPTN, VCP, and UBQLN2) as well as sporadic forms of the disease. Finally, we will look to the future of ALS research and how an improved understanding of central mechanisms underpinning proteinopathies might inform research directions and have implications for the development of novel therapeutic approaches.

Efficiency of control in regional self-government of the Slovak Republic

The importance of high quality public sector control is an obvious fact – without efficient and effective control system, the risk of wasting public funds is critical. The goal of this article was to evaluate efficiency of internal control systems on the level of regional self-administration in the Slovakia. The findings clearly document many problems related to the performance of regional control bodies and on this basis purposes and possible actions are proposed. From the point of view of "fiscal rules", the research, for example, pointed to an exceptionally poor situation in compliance with the rules and conditions of budgetary management in the Bystrica region in the period 2006-2009. The research also proves that one of the key problems of nonconceptual and non-transparent asset management of regions is confusing and disadvantageous asset sales. The quantitative analysis suggests that the efficiency (intensity) of the functioning of regional control systems does not have a direct impact on the monitored output indicators. The implemented DEA also indicates the low effectivity of the internal control systems of the regions. Our findings fully prove that there are no truly efficient systems of external and internal control at the level of self-governing regions in Slovakia. The factor of high autonomy of regions in the financial management and disposal of assets in connection with the identified high degree of failure of the regional control system generates a clear need to strengthen the system of internal control of regions, based on systemic and procedural changes.

Evaluation of flood risk as a step in determining the “Acceptable Risk” criteria. Case study: Dengkeng River, Klaten, Central Java

The planning of a flood control system in Indonesia is based on the planning criteria issued by the Ministry of Public Works. Flood control planning is based on flood discharge with a specific return period depending on the order of the river and the number of protected populations. Flood events in areas where the flood control system has been planned continue to occur almost every year, meaning that the probability of being exceeded is not as planned. This study is intended to evaluate the criteria for the magnitude of the designed flood discharge in flood control planning that considers the acceptable risk. Potential risks are evaluated against system reliability. The probability of failure of the flood control system occurs if the resistance is smaller than the load expressed as a performance function. By knowing the performance function associated with the level of flood risk, then the flood discharge can be selected with the appropriate return period according to the acceptable risk.

Application of spectrum analysis technology in health management of vehicle control system

With the increasing complexity of vehicle control system, the failure rate has also been enhanced accordingly. Through traditional maintenance techniques, only the intact state of the qualitative vehicle control system can be achieved, and functions such as analyzing and predicting the hidden failure and technical state of vehicle control system, health management, etc., cannot be realized, which seriously restricts the formation of maintenance efficiency. According to the signal characteristics of the vehicle control system, the electric signal spectrum analysis method is used to realize intelligent detection, evaluation, management, fault prediction and diagnosis of vehicle control system performance indicators, so as to ensure vehicle control system is always in good condition, has a very important significance to improve the maintenance support ability of vehicle control system.

RANCANG BANGUN SISTEM PEMUTUS ARUS SEBAGAI PENGAMAN TEMPERATUR BERLEBIH PADA INKUBATOR BAYI

Several countries in the world, including Indonesia, have reported baby-care accidents in the baby incubator due to the failure of the temperature control system to maintain a stable temperature. Therefore, this study reports the design of an circuit breaker system as an over-temperature safety in a baby incubator. Experimentally, the prototype consists of hardware design, software design, and testing system design. The hardware design has four main part, sensing layer using PT1000 as a temperature sensor, data processing layer using an ESP32 microcontroller, a circuit breaker system using a solid-state relay as an electronic switching, and LCD as a display. System testing has been done by evaluating the temperature readings on a prototype against the HTC-02 digital thermometer instrument and carried out in the electromedical engineering laboratory. The results show the accuracy of the temperature parameter is 99% and the circuit breaker system is able to cut the current from the power supply to the appliance when the temperature is more than 39°C which is indicated by an incandescent lamp "off" where this is equivalent to a heater at the baby incubator is in the "off" condition. From the results of this test, it can be concluded that the circuit breaker system as a safety over temperature in the baby incubator has functioned according to the design.Recommended the development of this prototype needs to be followed up by testing on low-tech baby incubators available at basic health care facilities so as to improve technology readiness to be effective in the community.

Using extended Kalman filter for failure detection and prognostic of degradation process in feedback control system

In this article, we study a new approach to predict failures in feedback control system and particularly in actuators. However, we use two-tank control system with a proportional–integral–derivative controller for controlling a process variable. In practice, the actuator is a dynamic operating component in a random environment. Moreover, its capacity decreases over time and becomes valuable information for reliability analysis. The loss of capacity which is related to degradation, either normally or in an accelerated manner, depends on different operational conditions of the feedback control system and environmental factors. For this reason, to improve its working condition, a service life time analysis is necessary. Obviously, one has to predict the trend of future system characteristics, such as the reliability, which is measured by the estimate value of remaining useful life. In this situation, we use the stochastic gamma process model to describe the degradation behavior of the actuator. Generally, the algorithm of extended Kalman filter is a widely used method to overcome the difficulties of estimating the state vector in a nonlinear model of two-tank control system. This algorithm gives an innovation vector or prediction residual which contains fault information, when the system is failed. The prediction residuals can be recursively computed for diagnosis by the generalized likelihood ratio test. However, we use the generalized likelihood ratio test algorithm to estimate the moment at which the prognostic started. Finally, a practical case study is given to show the effectiveness of the proposed approaches for failure detection. Obviously, the simulation results show that the degradation path of the actuator capacity is estimated and the reliability based on remaining useful life predicted is analyzed.

Performance of an Advanced Intelligent Control Strategy in a Dynamic Positioning (DP) System Applied to a Semisubmersible Drilling Platform

Oil drilling and extraction platforms are currently being used in many offshore areas around the world. Whilst those operating in shallow seas are secured to the seabed, for deeper water operations, Dynamic Positioning (DP) is essential for the platforms to maintain their position within a safe zone. Operating DP requires intelligent and reliable control systems. Nearly all DP accidents have been caused by a combination of technical and human failures; however, according to the International Marine Contractors Association (IMCA) DP Incidents Analysis, DP control and thruster system failures have been the leading causes of incidents over the last ten years. This paper will investigate potential operational improvements for DP system accuracy by adding a Predictive Neural Network (PNN) control algorithm in the thruster allocation along with a nonlinear Proportional Integral derivative (PID) motion control system. A DP system’s performance on a drilling platform in oil and gas deep-water fields and subject to real weather conditions is simulated with these advanced control methods. The techniques are developed for enhancing the safety and reliability of DP operations to improve the positioning accuracy, which may allow faster response to a critical situation during DP drilling operations. The semisubmersible drilling platform’s simulation results using the PNN strategy show improved control of the platform’s positioning.

Reliability analysis on the train control system in the CTCS-3 operating mode

Purpose This paper aims to study the reliability of the high-speed train operation control system in the Chinese Train Control System Level 3 (CTCS-3) operating mode. Design/methodology/approach Dynamic fault tree and Bayesian network method are adopted to analyze the reliability and weakness of the CTCS-3 system. Findings First, a physical architecture and data flow diagram of the CTCS-3 system are established according to the typical structure and functions of the CTCS-3 system. Second, the dynamic fault tree of the CTCS-3 system is constructed. Considering the prior probability of the bottom event and the existence of dynamic redundancy, the dynamic fault tree is transformed into a Bayesian net. The reliability of the CTCS-3 system is carried out based on the prior probability and the weakness that affects the reliability of the system based on the posterior probability is also analyzed by the Bayesian network. Finally, it is disclosed that the impact of the on-board subsystem on the reliability of the CTCS-3 system is generally greater than that of the ground subsystem. The two weakest modules in the onboard subsystem are the driver-machine interface (DMI) and balise transmission module (BTM) and the weakest one in the ground subsystem is Balise. The analysis results are generally consistent with the malfunctions in the field operation of China’s high-speed railway. Originality/value (1) By reasoning, the reliability of the train operation control system in the CTCS-3 operating mode meets the standard requirements. (2) Through backward reasoning, it is found that the failure of the onboard subsystem leads to a greater probability of failure of the train control system. (3) The DMI, BTM and automatic train protection computer unit modules are weak components in the onboard subsystem. Vital digit input&output, train interface unit and train security gateway are rarely involved in previous research, the result in this paper shows that these three modules are also weak components in the subsystem, which requires attention.

Mitochondria Homeostasis and Oxidant/Antioxidant Balance in Skeletal Muscle-Do Myokines Play a Role?

Mitochondria are the cellular powerhouses that generate adenosine triphosphate (ATP) to substantiate various biochemical activities. Instead of being a static intracellular structure, they are dynamic organelles that perform constant structural and functional remodeling in response to different metabolic stresses. In situations that require a high ATP supply, new mitochondria are assembled (mitochondrial biogenesis) or formed by fusing the existing mitochondria (mitochondrial fusion) to maximize the oxidative capacity. On the other hand, nutrient overload may produce detrimental metabolites such as reactive oxidative species (ROS) that wreck the organelle, leading to the split of damaged mitochondria (mitofission) for clearance (mitophagy). These vital processes are tightly regulated by a sophisticated quality control system involving energy sensing, intracellular membrane interaction, autophagy, and proteasomal degradation to optimize the number of healthy mitochondria. The effective mitochondrial surveillance is particularly important to skeletal muscle fitness because of its large tissue mass as well as its high metabolic activities for supporting the intensive myofiber contractility. Indeed, the failure of the mitochondrial quality control system in skeletal muscle is associated with diseases such as insulin resistance, aging, and muscle wasting. While the mitochondrial dynamics in cells are believed to be intrinsically controlled by the energy content and nutrient availability, other upstream regulators such as hormonal signals from distal organs or factors generated by the muscle itself may also play a critical role. It is now clear that skeletal muscle actively participates in systemic energy homeostasis via producing hundreds of myokines. Acting either as autocrine/paracrine or circulating hormones to crosstalk with other organs, these secretory myokines regulate a large number of physiological activities including insulin sensitivity, fuel utilization, cell differentiation, and appetite behavior. In this article, we will review the mechanism of myokines in mitochondrial quality control and ROS balance, and discuss their translational potential.

Nonlinear multivariable control of an integrated PEM fuel cell system with a DC-DC boost converter

The proton exchange membrane (PEM) fuel cell faces problem when there is an abrupt load demand that is common in transport/vehicle application. This is because of the slow response of underlying electrochemical and thermodynamic processes, abrupt voltage drop proportional to the increased power demand, control system failure, among others. To overcome this shortcoming and to ensure the uninterrupted power delivery, a DC-DC boost converter is coupled with the PEM fuel cell integrated system that additionally includes a few auxiliary subsystems along with a fuel recirculation and a heat exchange unit. For the controlled operation of the entire integrated complex system, a nonlinear observer-based sliding mode controller (SMC) is synthesized. To address a couple of major concerns involved in fuel cell operation, the control objectives are selected at stabilizing the fuel cell power, cathode air flow from the compressor and stack operating temperature. To have the knowledge of unmeasured state information, two nonlinear observers namely, extended Kalman filter (EKF) and sliding mode observer (SMO) are constructed using a low-order process model. The observer-based controller is simulated in MATLAB/SIMULINK environment for their comparative performance. Overall, the closed-loop response of the proposed SMO-SMC and EKF-SMC are found superior to a traditional PI controller.

Application of a Diffusion Charger to Quantify Real-Time Particle Emissions from Light-Duty Vehicles: a Comparison Study with a Particle Size Spectrometer

Measurement methods for vehicle-emitted particulate matter (PM) have evolved as vehicle emission standards have become more stringent. For example, the filter-based gravimetric method has been demonstrated feasible to measure emissions at levels below 1 mg/mi from light-duty vehicles. However, while regulatory methods and instruments for measuring PM emissions are rigorous and accurate, there is a need to continue evaluating alternatives for use in the laboratory, as well as simple and robust instruments for screening that can be used for detecting high emissions on the roadside and evaluating the effectiveness of repairs in support of inspection and maintenance (I/M) programs. This study investigated the performance of an aerosol diffusion charger (TSI Electrical Aerosol Detector) by comparing its raw signal (aerosol active surface area) and its conversion to particle number and mass emission rates with those reported or calculated from a multi-channel electrometer-based particle size spectrometer (TSI Engine Exhaust Particle Sizer) and various condensation particle counters (CPCs). Four light-duty vehicles were tested, including gasoline port fuel injection (PFI), gasoline direct injection (GDI), and a diesel vehicle equipped with a diesel particulate filter (DPF). Results show that the diffusion charger was responsive over a wide particle size and concentration range, exhibiting sufficient signal-to-noise ratio during transient measurements of the gasoline PFI vehicle and light-duty diesel vehicle with a DPF (both certified below 1 mg/mi). High sensitivity at low concentrations suggests that the diffusion charger may have potential for identifying failures of emission control systems at lower concentrations than methods designed to report real-time suspended particle number or mass metrics directly. Systematic and fundamental data from our study underscore the challenge with “black box” equipment calibrated to calculate total particle number and mass from surface area measurements based on constant unimodal fit parameters. Future work could focus on the applications from deploying active surface area monitors at the roadside or for using surface area measurements to evaluate repair effective in support of I/M programs.

Mathematical modeling of failure of port control systems

The need to increase the capacity of ports is due to the development of the Northern Sea Route as a national transport route of Russia in the Arctic, the National Program for the Development of the Far East, in the context of an increase in trade with other regions of Russia, as well as the reorientation of cargo flows from the Baltic ports to Russian ones in Primorsk, Ust-Luga and Vysotske. Increasing cargo turnover and ensuring the strategic economic interests of Russia requires the reconstruction of existing and construction of new modern port-industrial complexes, provided with advanced technologies, including the automation of logistics management processes, production and engineering systems. This article describes a method for mathematical modeling of the failure of control systems for automation of cargo terminals of ports. Since failures in the operation of automation systems lead to an increase in the load of cargo berths (terminals) of both sea and river port complexes, to a violation of logistics schemes, and as a consequence to an increase in costs. Modeling is carried out using methods of probability theory, in particular, the Poisson distribution law. A comparison of the empirical and theoretical failure rates of automation is performed using the Pearson criterion. The performed modeling will allow determining the technical and economic indicators of new construction, reconstruction or overhaul, in terms of the engineering systems of the facility, and optimize the automation processes.

Implementation of Memory in a System on a Chip with Built-In Self-Testing and Self-Healing

When manufacturing systems on a chip using modern technologies with highly integrated elements, problems arise in testing and repairing the internal memory. The original architecture of the fault-tolerant semiconductor memory with the given failure detection rate is proposed. At the same time, rather than the entire device being backed up only the elements that are most susceptible to failures are backed up, which reduces its weight and cost. The fault-tolerant memory design with automatic recovery is verified after quadruple failures. The fault-tolerant memory project is implemented in the M2S010-TQ144 chip of the system based on the SF2-Junior-KIT chip in the integrated development environment of Microsemi Libero SoC v11.8. The proposed architecture of fault-tolerant memory ensures the automatic recovery from the multiple failures of elements onboard spacecraft control systems using a built-in self-healing device without the use of fusible jumpers and the participation of maintenance personnel. In the semiconductor memory, when faults are detected, the data bits of the main array of storage cells in which failures occur are automatically replaced with the data emerging from the outputs of the spare array of storage cells. This improves reliability when performing multiple recovery cycles.

Process safety concerns in process system digitalization

While efforts to use digital solutions in process operations are gaining wider acceptance, there are serious safety concerns that need to be addressed when adopting digitalization. Process operations have evolved from batch operation to continuous operation, and from smaller plants to large-scale plants. Automation and digitalization of processes, especially in process monitoring, instrumentation, and control are becoming the norm. Safety issues have also evolved with these developments, from simple equipment failure to failure of process systems (equipment with electronic systems), monitoring and control systems, data encryption systems, and most recently, software systems. How these evolving process safety issues should be taught in the classroom to educate and train the next generation of chemical engineers is a challenge with an opportunity. If such issues are not taught in academia, this will create a gap between education and practice, which would have a negative impact on the overall safety of process facilities. Therefore, proactively converting this challenge to an educational opportunity and bringing digital process safety issues into the classroom are of paramount importance to help reinforce the concept of making process safety learning a conscious choice. This will hopefully lessen our reliance on learning from accidents. The current paper presents the need to incorporate digital process safety as part of the chemical engineering curriculum to adequately address the process industry’s emphasis on digital solutions in process operations.

Development of a Numeric Method to Validate the Reliability Improvement of Safety Critical Valves During Operation Through Online Monitoring Implementation

Online valve monitoring, also called “ValveWatch,” is a state-of-the-art method for improving the reliability of safety critical valves during operation. This well-known method has been used for almost two decades to reveal the possible failures of valves, actuators and control systems. This paper reviews some of the existing literature about ValveWatch technology to provide more detailed information about this online monitoring approach and its benefits. The possible causes and effects of failures associated with safety critical valves based on the existing literature are identified and summarized in this paper. Safety critical valves mainly include Emergency Shut Down and Process Shut Down (PSD) valves connected to Process Shut Down (PSD) systems. Three types of sensors that comprise part of the ValveWatch system will be identified and explained in this paper: the stain gauge, the dynamic pressure gauge and the static pressure gauge on the actuator. The function and logic of these three sensors are explained in this paper. All of the problems associated with valves, actuators and control system are identified and listed in a table and the probability of detecting these failures through visual inspection as well as online monitoring is assessed. A method of utilizing equations to calculate the probability of failure detection for valves, actuators, control system and the whole assembly through visual inspection as well as using sensors is developed. Additionally, the methodology given in functional safety and International Electrotechnical Commission 61,508 to calculate Diagnosis Coverage is used in this paper, and future research work to address condition monitoring for pressure safety valves and check valves is proposed. A Separate research is required to improve the reliability of the ValveWatch system.

Comparative study between propulsion control system failures of an electrical vehicle piloted by FOC and by DTC using dual-induction-motors structure

Comparative study between propulsion control system failures of an electrical vehicle piloted by FOC and by DTC using dual-induction-motors structure