Fault Simulation Research Articles

Single-ended line fault location method for multi-terminal HVDC system based on optimized variational mode decomposition

In order to provide a backup plan for double-ended fault location scheme when data communication and synchronization are not effective or available, a single-ended fault location method is proposed using traveling wave (TW) theory. The time-frequency characteristics is utilized to extract fault feature for fault location estimation. Specifically, Variational Mode Decomposition (VMD) is adopted and further improved with singular entropy based parameter optimization and TW arrivals can be clearly identified via intrinsic mode function (IMF) result. In order to solve the issue of highly attenuated TW front, Teager Energy Operator (TEO) is used to visualize the singular points in IMF and the peaks in TEO spectrum indicate the fault TW arrivals. Moreover, frequency-dependent TW propagation velocity is determined by center frequency of selected IMF to enhance accuracy. The fault simulation is performed on the platform PSCAD/EMTDC based on example model of 15-bus CIGRE HVDC system and MATLAB is used for signal processing and algorithm development. The effectiveness and superiority of this method is verified with simulation study considering potential influence.

Mathematical diagnostic model of brake master cylinder of hydraulic brake system of automobile

The article considers a dynamic mathematical model of a new method of componentwise diagnosis of the brake master cylinder of a “tandem” type of the hydraulic brake system. We propose a variant of how simulated various faults affect the output parameters of brake process on the basis of mathematical modeling.

Research on Modeling and Simulation of Smart Substation Cyber-Physical System Considering Coupling Analysis

With the rapid development of Internet of Things and communication technologies, substations are becoming more intelligent, which brings opportunities for cyber attacks, threatens the safety of substations, and the high coupling of equipment in substations increases the threat. This paper analyzes and studies the information-physical characteristics and equipment coupling problems of smart substations, constructs a smart substation CPS model based on the balance equation of state quantity, and designs a line fault simulation example to verify the stability of the model.

Detecting Vibration Problems in Machines and Structures Using Motion Capturing by Camera

Vibration in rotating machines and structures is normally measured using accelerometers and other vibration sensors. For large machines and structures, the process of collecting vibration data is tedious and time-consuming due to the large number of points where vibration data must be measured. In this paper, a novel non-contact vibration measurement method has been introduced by using a high-speed camera as a vibration measurement device. This method has many advantages compared with the others. It has a low cost, easy to setup, and high automation. It also can be used for full-field measurement. Many tests have been accomplished to prove the validation of this method. The verification test has been accomplished by using the machinery faults simulator. It presented a reasonable validation that the operation deflection shapes (ODS) and the phase difference of any object can be successfully measured by using a high-speed camera. The mode shape tests have been accomplished by using the whirling of shaft apparatus device to extract the time domain, frequency domain, ODS, and phase differences for many points on the shaft at the first two critical speeds. The results proved that the high-speed camera can be used to detect the vibration signal in many different fault cases. It also proved that the high-speed camera can be used to detect the ODS and the phase angle difference. That gives the proposed method more robust and acceptance.

Mathematical Modelling and IoT Enabled Instrumentation for Simulation & Emulation of Induction Motor Faults

Simulation and emulation of electric motor faults are particularly useful to study, test, and evaluate the motor condition monitoring products based on the motor current signature and vibration analysis. Many researchers have proposed and developed several DAQ & computer-based simulation tools. This paper aims to develop a system to simulate and emulate the maximum types of faults which can occur in a three-phase induction motor. In this paper, an embedded system based induction motor fault simulator and the emulator is proposed and developed. The focus of this paper is to model the induction motor faults mathematically based on the motor current signature and vibration frequency spectrum, which are theoretically derived and proved by the early generation researchers and engineers. The novelty of the proposed approach is a cost-effective, portable, and handy tool for field evaluation of the motor condition monitoring products. This paper presents the hardware and software development for making a stand-alone motor faults simulator and emulator. The system employs a powerful high-end and powerful embedded system INTEL ATOM Minnow Board, which is built around E3826, Dual Core, and 1.46 GHz processor. A dedicated 4-channel Direct Digital Synthesizer (DDS) with 12-bit resolution along with software generates all three-phase induction motor faults for both MCSA and vibration analysis. The simulated and emulated faults signals are compared and evaluated against the Standards with the help of a digital storage oscilloscope.

Improved Metaheuristic Optimization Algorithm Applied to Hydrogen Fuel Cell and Photovoltaic Cell Parameter Extraction

As carriers of green energy, proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells are complex and nonlinear multivariate systems. For simulation analysis, optimization control, efficacy prediction, and fault diagnosis, it is crucial to rapidly and accurately establish reliability modules and extract parameters from the system modules. This study employed three types of particle swarm optimization (PSO) algorithms to find the optimal parameters of two energy models by minimizing the sum squared errors (SSE) and roots mean squared errors (RMSE). The three algorithms are inertia weight PSO, constriction PSO, and momentum PSO. The obtained calculation results of these three algorithms were compared with those obtained using algorithms from other relevant studies. This study revealed that the use of momentum PSO enables rapid convergence (under 30 convergence times) and the most accurate modeling and yields the most stable parameter extraction (SSE of PEMFC is 2.0656, RMSE of PV cells is 8.839 · 10−4). In summary, momentum PSO is the algorithm that is most suitable for system parameter identification with multiple dimensions and complex modules.

GMC sparse enhancement diagnostic method based on the tunable Q-factor wavelet transform for detecting faults in rotating machines

In mechanical fault diagnosis, weak fault feature extraction via traditional method is easily disturbed by strong background noises. In order to enhance the feature extraction performance, a novel sparsity-enhanced signal denoising method based on the combination of generalized minimax-concave penalty and tunable Q-factor wavelet transform is developed in this paper. Aiming at matching the transient fault features, the proposed method constructs an effective sparse optimization objective function for mechanical fault diagnosis. It is also proved that the non-convex controllable parameters can guarantee the overall convexity of the objective function under certain constraints. The proximal algorithm is used to solve the unconstrained optimization problem. Finally, the results of the simulation and practical fault experiment verify the effectiveness of the proposed method in the machinery fault diagnosis.

Equivalent Faults under Launch-on-Shift (LOS) Tests with Equal Primary Input Vectors

A recent work showed that it is possible to transform a single-cycle test for stuck-at faults into a launch-on-shift (LOS) test that is guaranteed to detect the same stuck-at faults without any logic or fault simulation. The LOS test also detects transition faults. This was used for obtaining a compact LOS test set that detects both types of faults. In the scenario where LOS tests are used for both stuck-at and transition faults, this article observes that, under certain conditions, the detection of a stuck-at fault guarantees the detection of a corresponding transition fault. This implies that the two faults are equivalent under LOS tests. Equivalence can be used for reducing the set of target faults for test generation and test compaction. The article develops this notion of equivalence under LOS tests with equal primary input vectors and provides an efficient procedure for identifying it. It presents experimental results to demonstrate that such equivalences exist in benchmark circuits, and shows an unexpected effect on a test compaction procedure.

Fault Simulation and Diagnosis Technology of Hydraulic System for Hydraulic Support

Fault Simulation and Diagnosis Technology of Hydraulic System for Hydraulic Support

A Satellite Incipient Fault Detection Method Based on Local Optimum Projection Vector and Kullback-Leibler Divergence

Timely and effective detection of potential incipient faults in satellites plays an important role in improving their availability and extending their service life. In this paper, the problem of detecting incipient faults using projection vector (PV) and Kullback-Leibler (KL) divergence is studied in the context of detecting incipient faults in satellites. Under the assumption that the variables obey a multidimensional Gaussian distribution and using KL divergence to detect incipient faults, this paper models the optimum PV for detecting incipient faults as an optimization problem. It proves that the PVs obtained by principal component analysis (PCA) are not necessarily the optimum PV for detecting incipient faults. It then compares the on-line probability density function (PDF) with the reference PDF for detecting incipient faults on the local optimum PV. A numerical example and a real satellite fault case were used to assess the validity and superiority of the method proposed in this paper over conventional methods. Since the method takes into account the characteristics of the actual incipient faults, it is more adaptable to various possible incipient faults. Fault detection rates of three simulated faults and the real satellite fault are 98%, 84%, 93% and 92%, respectively.

Fault Diagnosis of Intershaft Bearing Using Variational Mode Decomposition with TAGA Optimization

To efficiently extract the features of aeroengine intershaft bearing faults with weak signal, the variational mode decomposition (VMD) method based on the tolerant adaptive genetic algorithm (TAGA) (TAGA-VMD) is proposed by introducing the idea of tolerance into the traditional adaptive genetic algorithm in this paper. In this method, the tolerant genetic algorithm was adopted to find the optimum empirical parameters K and α of VMD. A fault simulation experiment system of intershaft bearings was built for the inner ring fault and outer ring fault of bearings to verify the proposed TAGA-VMD method. The results show that the proposed method can effectively extract the fault feature frequency of intershaft bearings, and the error between the extracted fault feature frequency and the theoretical value of fault frequency is less than 0.1%. The efforts of this study provide one promising fault feature extraction approach for aeroengine intershaft bearing fault diagnosis with weak signal.

Fault-based Built-in Self-test and Evaluation of Phase Locked Loops

With the increasing pressure to obtain near-zero defect rates for the automotive industry, there is a need to explore built-in self-test and other non-traditional test techniques for embedded mixed-signal components, such as PLLs, DC-DC converters, and data converters. This article presents a very low-cost built-in self-test technique for PLLs specifically designed for fault detection. The methodology relies on exciting the PLL loop in one location via a pseudo-random signal with noise characteristics and observing the response from another location in the loop via all digital circuitry, thereby inducing low area and performance overhead. The BIST circuit along with a PLL under test is designed in 65 nm technology. Fault simulations performed at the transistor and system-level show that the majority of non-catastrophic faults that result in parametric failures can be detected with the proposed approach.

Diagnosis of mechanical defects using a hybrid method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and optimized wavelet multi-resolution analysis (OWMRA): experimental study

The early detection of defects in rotating machines before their severity reaches an intolerable threshold has become the priority of the maintenance crew, hence the need to apply or even adapt new reliable methods that can meet this requirement. In this paper, a hybrid approach based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the optimized wavelet multi-resolution analysis (OWMRA), and the Hilbert transform is proposed. The proposed approach is initially applied on experimental signals measured on faulty bearings of the Machinery Fault Simulator (MFS) test rig. Two types of defects are considered: on the outer race and on the inner race. An industrial application carried out on a production machine validates on a large scale, exceeding that of the laboratory, the proposed method. It was then possible to detect potential faults on a turbo-alternator group GZ 1164.2 operating in real industrial conditions in the largest fertilizer products company in Algeria. The obtained results show the power of the proposed approach to get reconstructed signals less noisy, containing more information and highlighting the precise nature of the defect and its severity in different configurations, regardless of its type. Finally, the main contribution of this study is to show that the application of the proposed approach is very practical on signals measured on real industrial rotating machines to detect the potential mechanical faults.

Fault Simulation and Formal Analysis in Functional Safety CPU FMEDA Campaign

In accordance with safety requirements of industrial control, a functional safety CPU is designed targeting controller IC used in State Grid. Functional safety verification flow based on FMEDA is setup for the project, which totally comply with IEC61508. In this paper, fault injection with fault simulation and formal analysis flow of functional safety verification is introduced in detail, which is set up for calculation of diagnose coverage on random hardware failure. Employment of formal method completes 2-3 weeks fault analysis in 52 hours, which improved diagnose coverage convergence.

Wide Area Measurement System in the IEEE-14 Bus System using Multiobjective Shortest Path Algorithm for Fault Analysis

In a large-scale interconnected power system network, few challenges exist in evaluating and maintaining the overall system stability. The power system’s ability to supply all types of loads during natural disasters or faults has yet to be addressed. This work focuses on developing a wide-area measurement system to manage and control the power system under all operating conditions. The IEEE-14 bus system was modeled in PSCAD software for simulating nineteen types of fault based on multi-objective shortest path algorithm. To manage the wide area measurement, the research must comprehend the working principle of the multi-objective shortest path algorithm, whereby the proposed method will determine the new path for the IEEE-14 bus system. To evaluate the performance of the multi-objective shortest path algorithm, all sections of the IEEE-14 bus system were simulated with faults. The distances of the normal path (without simulated fault) and the new path (with simulated fault) were recorded. Based on the recorded data, it was found that the location of the fault has significant influence on the shortest path of the buses connected to each other.

Triple module redundancy reliability framework design based on heterogeneous multi-core processor

Abstract To solve the problem of commercial device with weak anti-SEU ability and traditional radiation hardened device with slow processing speed, this article proposes a novel system-level collaborative triple module redundancy (TMR) design to mitigate single event upset (SEU) on the advanced heterogeneous processor. Based on Xilinx Zynq Ultrascale+ MPSoC, we combine TMR with rolling back, watchdog and scrubbing technique between heterogeneous cores which are Arm Cortex-A53 and Field Programmable Gate Array (FPGA). This combination brings us a promising result of fault identification and correction according to the simulation of the single channel data fault and the double channel data fault. It costs 27%-44% more time to process error and the system has relatively low resource utilization rate and power consumption. Moreover, it can also apply to general heterogeneous quad-core System on Chip (SoC) with FPGA processor’s anti-SEU design and provides some ideas for further study of system level radiation-resistant chips’ design.

Multiple Open-Circuit Fault Diagnosis for Back-to-Back Converter of PMSG Wind Generation System Based on Instantaneous Amplitude Estimation

To increase the reliability and availability of wind turbines, a new diagnosis method was proposed for multiple open-circuit faults in the back-to-back converters of turbines using permanent magnet synchronous generators (PMSGs). This method is the first to use the instantaneous amplitude (IA) as the principal quantity for formulating diagnostic variables that can distinguish different states of any switch accurately without being affected by speed variations. The method also uses the weighted sliding Hilbert transform (WSHT) to estimate the IA to remove the influence of end effects and carry the information of multiple open-circuit faults. To locate faulty switches, a localization method using signal samples adaptive processing was employed to eliminate the influence of speed changes. Finally, combining these diagnostic variables with identification thresholds makes it possible to detect and locate 21 open-circuit fault combinations for the PMSG-side and grid-side converters. Compared to the conventional fault diagnosis methods, simulation and experimental results showed that the proposed method more efficiently and reliably detects and locates multiple open-circuit faults of PMSG wind power converters.

Fault Detection Method and Simulation Based on Abnormal Data Analysis in Wireless Sensor Networks

With the rapid development of Internet of things and information technology, wireless sensor network technology is widely used in industrial monitoring. However, limited by the architecture characteristics, software and hardware characteristics, and complex external environmental factors of wireless sensor networks, there are often serious abnormalities in the monitoring data of wireless sensor networks, which further affect the judgment and response of users. Based on this, this paper optimizes and improves the fault detection algorithm of related abnormal data analysis in wireless sensor networks from two angles and verifies the algorithm at the same time. In the first level, aiming at the problem of insufficient spatial cooperation faced by the network abnormal data detection level, this paper first establishes a stable neighbor screening model based on the wireless network and filters and analyzes the reliability of the network cooperative data nodes and then establishes the detection data stability evaluation model by using the spatiotemporal correlation corresponding to the data nodes. Realize abnormal data detection. On the second level, aiming at the problem of wireless network abnormal event detection, this paper proposes a spatial clustering optimization algorithm, which mainly clusters the detection data flow in the wireless network time window through the clustering algorithm, and analyzes the clustering data, so as to realize the detection of network abnormal events, so as to retain the characteristics of events and further classify the abnormal data events. This paper will verify the realizability and superiority of the improved optimization algorithm through simulation technology. Experiments show that the fault detection rate based on abnormal data analysis is as high as 97%, which is 5% higher than the traditional fault detection rate. At the same time, the corresponding fault false detection rate is low and controlled below 1%. The efficiency of this algorithm is about 10% higher than that of the traditional algorithm.

Results of Simulation of Faults of Starter Batteries

During the operation of the battery, its parameters change, declining with the rate affected by the natural aging processes or faults. To obtain information about changes in the parameters of the battery when the faults occur and develop, methods of their simulation have been developed. The change in the battery voltage under the influence of the reference load is determined to reduce the charging rate, oxidation of the pole terminals, and plates sulfatation. It is established that the health of state of old and faulty batteries at the same voltage differs significantly, which can be used to identify the technical condition of starter batteries.

Pareto Optimal Allocation of Flexible Fault Current Limiter Based on Multi-Objective Improved Bat Algorithm

With the sustainable growth in the integration of distributed generation units in the distribution network, the probability of the fault current level exceeding the rating of existing components increases. Cascaded H bridge fault current limiter is widely used in the power grid due to its advantage in inhibiting surge current flexibly. In order to equilibrate the objective functions of its cost, fault current mitigation effect, and the weighted load reliability index, a novel methodology is proposed to simultaneously optimize the location and size of the limiters in the distribution network. Therein, the sensitivity factor considering the Monte Carlo fault simulation model is introduced to reduce the search space and rank candidate locations referencing the actual conditions. And then, according to the candidate locations and considering different conflicting objective functions, a multi-objective improved bat algorithm is employed to obtain the Pareto optimal solution set. Also, life cycle cost and net present value are introduced to construct an economic model to access the scheme costs and service life. The proposed approach is verified using the modified IEEE 33-bus distribution systems with DGs and IEEE 30-bus Benchmark system. The results demonstrate that the proposed method exhibits higher efficiency in finding optimum solutions and provides a new economic configuration idea for the practical engineering application.