Trigger Time Research Articles

Validation of ΓKa for diagnostic radiography in three different hospitals in the Lambayeque region, Peru

Air Kerma was measured and compared with calculated air Kerma aiming to validate the use of air Kerma gamma factors. The air Kerma was measured in radiology departments in three hospitals at the Lambayeque region in Peru. In each department were obtained three times different radiographs, for each radiograph the X-ray operational parameters were recorded such us: voltage, current, and triggering time; the average values of these parameters, and the measured air Kerma were calculated. In addition was recorded the focal spot-to r distance, and the filter thickness. Monte Carlo methods were used to calculate the spectra, air Kerma, and Ambient dose equivalent for an X-ray tube (W target, Al2O3 filter) working to 40, 50, and 60 kV; these values and those previously reported were used to calculate the spectra mean energy, the air Kerma and the Ambient dose equivalent gamma factors in function of voltage. Mean values of measured voltage were used to calculate the gamma factors for air kerma and this with the current, and triggering time mean values, in addition to the focal spot-to-r distance, and the filter thickness were used to calculate the air Kerma. The relative difference between calculated air Kerma and the measured air Kerma varies from −6.84 to 10.82% at the Belen hospital, −2.22 to 9.64% at Las Mercedes hospital and from 0.41% to 6.30% at the Ferreñafe hospital; thus, calculated air Kerma values using the gamma factors were validated with measured air Kerma values. Air Kerma gamma factors can be used for dosimetric purposes using the operational features of the X-ray tube with W target and Al2O3 filter; in addition can be used during the design of primary barriers of radiology hall.

Visualization Experimental Study on In-Situ Triggered Displacement Mechanism by Microencapsulated Polymer in Porous Media

Summary Polymer flooding in deep reservoir profile control presents challenges in balancing injectivity and effective mobility control. To address this, we propose a solution by utilizing a microencapsulated polymer that can be easily injected and thickens over time. However, limited research has been conducted on the flow characteristics and the impact on oil mobilization by such profile control agents. In this study, we approximately simulated the time-varying flow process of microencapsulated polymer through in-situ triggered experiments at high temperature and pressure. The flow characteristics and oil displacement mechanism of the microencapsulated polymer under different trigger times were analyzed, and the displacement efficiency during the triggered viscosity enhancement process in porous media was quantitatively evaluated. The experimental results reveal that microencapsulated polymer exhibits a dual mechanism of near-wellbore reservoir particle temporary plugging and deep formation consistency control mechanisms. The transient aggregation of capsule particles alters the flow path, intensifying after expansion. The interaction between the microcapsule particles and the partially released polymer further enhances the resistance-enhancing property of the solution. The viscosity-enhanced microencapsulated polymer fluid improves the displacement efficiency. Microscopic oil displacement and coreflooding experiments resulted in a decrease in oil saturation of 39.5 and 18.33%, respectively. This study provides valuable microscopic insights into the flow behavior and oil displacement performance of microencapsulated polymer, offering essential guidance for optimizing oil reservoir extraction strategies.

A cost-effective alternative to accelerating rate calorimetry: Analyzing thermal runaways of lithium-ion batteries through thermocouples

In order to facilitate safety of heavy-duty batteries, approaches for studying thermal runaway (TR) need to be developed. So far, these have relied on accelerating rate calorimetry as a standard technique. This method, however, is costly, generally has size limitations, and is therefore of limited use for large format batteries. In this study, we examined the TR behavior of battery cells through a thermal propagation test at module level employing 157 Ah battery cells, using simple thermocouples. This constitutes one of the largest prismatic cell format analyzed to date, while the utilization of thermocouples enables a cost-effective method to study its TR. Parameters such as TR onset temperature, maximum temperature, heat release, and trigger time of the cells were comprehensively evaluated and compared, using this method. An onset temperature for TR at around 144 °C and a maximum temperature from 757 °C to 863 °C were observed. Heat release was estimated as 1.59 MJ per battery cell, deviating within ∼1 % compared to nail penetration tests. Moreover, six distinct stages during TR could be observed, in accordance with literature. This shows that the thermal propagation test using thermocouples is able to align well with other methods such as accelerating rate calorimetry, but is considerably easier to employ.

Self‐triggered control for linear systems based on hierarchical reinforcement learning

AbstractIn this article, we propose a model‐free self‐triggered control approach for linear systems using a hierarchical policy framework. This framework splits the self‐triggered control approach into top and bottom‐level policies. The top‐level policy generates a triggering time interval based on an initial control strategy, while the bottom‐level policy creates a control inputs guided by the top‐level sub‐goal. This division ensures that both strategies have their own independent tasks and optimization goals, facilitating a model‐free iterative design process for self‐triggered control. The present structure integrates with a dual‐Actor Critic algorithm, utilizing two interconnected neural networks to approximate control and trigger policies. It reflects the framework of hierarchical reinforcement learning, wherein top‐level policies guide bottom‐level decision‐making. It fosters the model‐free design of self‐triggered controller, thereby enhancing the efficiency of the learning process. To validate the effectiveness of our proposed method, we conduct a series of numerical simulations.

Distance Measurement of Contra-Rotating Rotor Blades with Ultrasonic Transducers.

Coaxial rotor helicopters have great potential in civilian and commercial uses, with many advantages, but challenges remain in the accurate measurement of rotor blades' distance to prevent blade collision. In this paper, a blade tip distance measurement method based on ultrasonic measurement window and phase triggering is proposed, and the triggering time of the transmitter is studied. Due to the complexity of the measured signal, bandpass filtering and a time-of-flight (TOF) estimation based on the power density of the received signal are utilised. The method is tested on an experimental test platform with a pair of 200 kHz ultrasonic transducers. The experimental results show that the maximum ranging error is less than 1.0% for the blade tip distance in a range of 100-1000 mm. Compared with the amplitude threshold method, the proposed TOF estimation method works well on the received signal with a low SNR and improves the ranging accuracy by about 5 mm when the blade tip distance is larger than 500 mm. This study provides a good reference for the accurate measurement of rotor blade tip distance, and gives a solution for ranging high-speed rotating objects.

Data-Driven SiC MOSFET Active Gate Driving for 380V/3A LVDC System Protection Employing Recurrent Deep Neural Network

This article proposed a Gated-Recurrent Learning Deep Neural Network (GRL-DNN) to predict the gate driving sequence of SiC-MOSFET in a 380 V/3A Low Voltage DC microgrid (LVDC). It is devised that the proposed intelligent fuse Active Gate Driving (AGD) requires a current limitation of 3 A to avoid fault and excess power loss. During over-current conditions in microgrid the proposed data-driven Intelligent Fuse (iFuse) acts as a circuit breaker with current limitation. The proposed GRL-DNN switching model training dataset is obtained for various operating condition in MATLAB. Training features like gate triggering, temperature, over-current magnitude, and tripping time are obtained by the proposed circuitry sequence predictor model in LTspice. By obtaining large solution space, without any delay automatic AGD can cutoff over-current in LVDC microgrid system. By comparing with conventional gate driving solid state fuse by Angelov model, the proposed iFuse integrated merits like fast reaction, accurate tripping, and high reliability to any system for improving fault protection. Online data analysis was carried to validate the outcome of the proposed iFuse AGD in hardware-in-loop simulation. The conducted real-time scaled-down experiment under over-current conditions on 380 V/3A LVDC system shows the proposed GRL-DNN based iFuse as a valuable active gate driving component for protection.

Dynamic protocol-based sliding mode control for nonlinear semi-Markovian jump systems with deterministic switching

This study investigates the sliding mode control for semi-Markov jump systems with dynamic self-triggered protocol. Utilizing an average dwell time strategy, the variation of semi-Markov chain is regulated by a deterministic switching signal. To improve transmission efficiency and achieve better control performance, a dynamic self-triggered protocol is developed, which predicts the next triggered time based on the current sampled data, obviating the need for dedicated hardware to continuously monitor system states and eliminating the Zeno phenomenon. A sliding mode controller related to the self-triggered protocol is proposed, which ensures the finite-time reachability. Based on the proposed self-triggered protocol and Lyapunov theory, a sufficient criterion is established to guarantee mean-square exponential stability under partial unknown transition rates. Finally, the effectiveness of the proposed method is verified through simulation examples.

Observer-based event-triggered time-varying formation control of linear multi-agent systems with distributed infinite delays

Compared with bounded delays, distributed infinite delays are more general in practical systems. Event-triggered control can effectively reduce energy consumption and communication costs. This paper addresses time-varying formation control of general linear multi-agent systems with distributed infinite delays in both of their inputs and outputs. An observer-based event-triggered formation control protocol considering distributed infinite delays is proposed, which is related to the combined observed information and some formation compensation signals at triggering time instants. By utilizing inequality techniques, the desired time-varying formation can be implemented while Zeno-behavior is excluded. Some numerical simulations are carried out for demonstrating the validity of theoretical results.

A Lagrangian perspective on the lifecycle and cloud radiative effect of deep convective clouds over Africa

Abstract. The anvil clouds of tropical deep convection have large radiative effects in both the shortwave (SW) and longwave (LW) spectra with the average magnitudes of both over 100 W m−2. Despite this, due to the opposite sign of these fluxes, the net average of the anvil cloud radiative effect (CRE) over the tropics is observed to be neutral. Research into the response of the anvil CRE to climate change has primarily focused on the feedbacks of anvil cloud height and anvil cloud area, in particular regarding the LW feedback. However, tropical deep convection over land has a strong diurnal cycle which may couple with the shortwave component of the anvil cloud radiative effect. As this diurnal cycle is poorly represented in climate models it is vital to gain a better understanding of how its changes impact the anvil CRE. To study the connection between the deep convective cloud (DCC) lifecycle and CRE, we investigate the behaviour of both isolated and organised DCCs in a 4-month case study over sub-Saharan Africa (May–August 2016). Using a novel cloud tracking algorithm, we detect and track growing convective cores and their associated anvil clouds using geostationary satellite observations from the Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI). Retrieved cloud properties and derived broadband radiative fluxes are provided by the Community Cloud retrieval for CLimate (CC4CL) algorithm. By collecting the cloud properties of the tracked DCCs, we produce a dataset of anvil cloud properties along their lifetimes. While the majority of DCCs tracked in this dataset are isolated, with only a single core, the overall coverage of anvil clouds is dominated by those of clustered, multi-core anvils due to their larger areas and lifetimes. We find that the anvil cloud CRE of our tracked DCCs has a bimodal distribution. The interaction between the lifecycles of DCCs and the diurnal cycle of insolation results in a wide range of the SW anvil CRE, while the LW component remains in a comparatively narrow range of values. The CRE of individual anvil clouds varies widely, with isolated DCCs tending to have large negative or positive CREs, while larger, organised systems tend to have a CRE closer to 0. Despite this, we find that the net anvil cloud CRE across all tracked DCCs is close to neutral (−0.94 ± 0.91 W m−2). Changes in the lifecycle of DCCs, such as shifts in the time of triggering, or the length of the dissipating phase, could have large impacts on the SW anvil CRE and lead to complex responses that are not considered by theories of LW anvil CRE feedbacks.

Adaptive sampling artificial-actual control for non-zero-sum games of constrained systems

Considering physical constraints encountered by actuators, this paper addresses the non-zero-sum game of continuous nonlinear systems with symmetric and asymmetric input constraints through aperiodic sampling artificial-actual control. Initially, the artificial system built by the improved Elman dynamic neural networks (EDNNs) has artificial-actual interaction with the physical system, which provides a new perspective for predicting the system state. By constantly learning and adjusting parameters, EDNNs can gradually approximate the dynamic behavior of the real system to achieve more effective control. Aiming at accommodating diverse input constraints, the non-quadratic value function constructed from a smoothly bounded function is devised. Then, the polynomial parameterized adaptive dynamic programming (ADP) is employed to approximate the solution of the coupled Hamilton–Jacobi equation (HJE), deriving optimal control laws for two players. To improve the efficiency of data communication, three adaptive sampling mechanisms including event-triggered mechanism (ETM) with relative threshold, dynamic ETM (DETM) and self-triggered mechanism (STM) are introduced in turn during the iterative learning process of control sequences. DETM further extends sampling intervals by incorporating internal dynamic variables, while STM determines the next trigger time through soft calculation without hardware monitoring. All three trigger modes can ensure the system stability while avoiding the Zeno phenomenon, and relevant proofs are given. Finally, the simulation validates the effectiveness of the designed algorithm and highlights the unique characteristics of each trigger mode.

The effects of real-time waveform analysis software on patient ventilator synchronization during pressure support ventilation: a randomized crossover physiological study

BackgroundPatient-ventilator asynchrony commonly occurs during pressure support ventilation (PSV). IntelliSync + software (Hamilton Medical AG, Bonaduz, Switzerland) is a new ventilation technology that continuously analyzes ventilator waveforms to detect the beginning and end of patient inspiration in real time. This study aimed to evaluate the physiological effect of IntelliSync + software on inspiratory trigger delay time, delta airway (Paw) and esophageal (Pes) pressure drop during the trigger phase, airway occlusion pressure at 0.1 s (P0.1), and hemodynamic variables.MethodsA randomized crossover physiologic study was conducted in 14 mechanically ventilated patients under PSV. Patients were randomly assigned to receive conventional flow trigger and cycling, inspiratory trigger synchronization (I-sync), cycle synchronization (C-sync), and inspiratory trigger and cycle synchronization (I/C-sync) for 15 min at each step. Other ventilator settings were kept constant. Paw, Pes, airflow, P0.1, respiratory rate, SpO2, and hemodynamic variables were recorded. The primary outcome was inspiratory trigger and cycle delay time between each intervention. Secondary outcomes were delta Paw and Pes drop during the trigger phase, P0.1, SpO2, and hemodynamic variables.ResultsThe time to initiate the trigger was significantly shorter with I-sync compared to baseline (208.9±91.7 vs. 301.4±131.7 msec; P = 0.002) and I/C-sync compared to baseline (222.8±94.0 vs. 301.4±131.7 msec; P = 0.005). The I/C-sync group had significantly lower delta Paw and Pes drop during the trigger phase compared to C-sync group (-0.7±0.4 vs. -1.2±0.8 cmH2O; P = 0.028 and − 1.8±2.2 vs. -2.8±3.2 cmH2O; P = 0.011, respectively). No statistically significant differences were found in cycle delay time, P0.1 and other physiological variables between the groups.ConclusionsIntelliSync + software reduced inspiratory trigger delay time compared to the conventional flow trigger system during PSV mode. However, no significant improvements in cycle delay time and other physiological variables were observed with IntelliSync + software.Trial registrationThis study was registered in the Thai Clinical Trial Registry (TCTR20200528003; date of registration 28/05/2020).

Naked Forward Shock Seen in the TeV Afterglow Data of GRB 221009A

We explore the implications of the light curve of the early TeV gamma-ray afterglow of GRB 221009A reported by the LHAASO Collaboration. We show that the reported offset of the reference time, T *, allows the determination of the activation time of the main jet component, which occurs approximately 200 s after the Gamma-ray Burst Monitor (GBM) trigger time and closely precedes the moment at which GBM was saturated. We find that while the LHAASO data do not exclude the homogeneous circumburst medium scenario, the progenitor wind scenario looks preferable, finding excellent agreement with the expected size of the stellar bubble. We conclude that the initial growth of the light curve is dominated by processes internal to the jet or by gamma-gamma attenuation on the photons emitted during the prompt phase. Namely, either the activation of the acceleration process or the decrease of internal gamma-gamma absorption can naturally explain the initial rapid flux increase. The subsequent slow flux growth phase observed up to T * + 18 s can be related to the process of particle accumulation in the production region. The duration of this phase allows an almost parameter-independent determination of the jet’s initial Lorentz factor, Γ0 ≈ 600, and magnetic field strength, B′∼0.3G . These values appear to match well those previously revealed through spectral modeling of the GRB emission.

Trigger transceiver and timing control system for ADITYA-U tokamak

The trigger transceiver and timing control system described in this study is developed to generate multiple triggers with varying delays to synchronize various subsystems with plasma discharges in the ADITYA Upgrade (ADITYA-U) tokamak (Ghosh et al., 2016) [1]. The Toroidal Field Power Supply (TFPS) is a fundamental component for each plasma discharge in the ADITYA-U, which generates a master trigger pulse for the particular discharge. The rise time of Toroidal Field Power Supply is 2 s and the loop voltage which is required to initiate the plasma discharge begins at 2.4 s after the master trigger. So the loop voltage is time-stamped at t = 0 and the master trigger from TFPS is time-stamped at t = −2.4 s and considered as a pre-trigger. Apart from this master trigger at t = −2.4 s, two more pre-trigger pulses, one at ∼ −40 ms and another at ∼ −4 ms, prior to the initiation of loop voltage trigger are generated by the power supply. These pre-trigger pulses generated by TFPS constitute the backbone of the entire discharge timing sequence, and they operate/control/initiate numerous ADITYA-U subsystems such as the gas puffing system, data acquisition system, radio frequency pre-ionization and heating system, plasma position control, and so on. So a suitable trigger generator system was needed to be developed in which three pre-trigger pulses (time stamped @ −2.4 s, −40 ms, and −4 ms prior to the loop voltage trigger) arriving from the TFPS may be selected and altered based on the experimental needs. To cater these requirements in ADITYA-U, a trigger transceiver and timing control system has been developed. The system has been successfully operated over ∼6000 discharges of ADITYA-U and functioned satisfactorily in all discharges in daily experiments with no failures. This study will discuss the detailed design elements and implementation of the Trigger Transceiver and Timing Control System for ADITYA-U plasma operations.

Performance optimization of the transient thermoelectric cooling for the temperature control of the chip working under dynamic power

The thermoelectric cooler (TEC) operating under the transient mode showed a stronger short term cooling effect than that of the steady state mode. In this study, a chip cooling experimental setup with the chip modeled by a ceramic heater was constructed using a commercial Bi2Te3-based TEC. A transient three-dimensional numerical model was established for the system optimization. The impacts of the pulse voltage amplitude, pulse voltage trigger time, pulse voltage time span, and the power magnitude of the chip on the peak temperature of the chip were analyzed in detail. The results showed that the experimental and numerical simulations were in high agreement with an error of only 3.6 %. When a pulse voltage of 12 V was applied to the TEC, the experimental results showed that the peak temperature of the chip with a pulse power of 48 W was reduced by 15.3 °C, while the simulation results demonstrated a reduction of 15.6 °C. The increase in the pulse voltage width and the pulse thermal power resulted in a larger temperature reduction. The transient cooling effect of the TEC presented a promising solution for temperature regulation in modern chips operating under dynamic power conditions.

A study on motion characteristics of the forced vibration of a floating body in two-degree-of-freedom machine gun system with impact and momentum offset

Floating technology is an emerging firearm recoil reduction technique. Firearms utilizing this technology differ significantly from traditional firearm systems, featuring distinctive characteristics of a two-degree-of-freedom system. This paper presents a novel model for this floating principle machine gun, incorporating a bi-directional buffer spring. The model is established and validated against experimental results. The experiment reveals both the floating body and the automaton body exhibit quasi-harmonic motion with some randomness. An observed impact and momentum offset between the floating body and the automaton body show an offset efficiency of 29%. The stiffness of the two springs is thoroughly analyzed regarding its influence on the floating characteristics, especially the backward ending state of the bi-direction floating body, offset efficiency, and triggering consistency. Increasing the stiffness of the bi-direction floating spring raises the bi-direction floating body’s motion frequency, resulting in a delayed phase at triggering time. Likewise, augmenting the automaton spring stiffness increases its motion frequency and advances the bi-direction floating body’s phase at triggering time. These adjustments affect the relative phase between the bi-direction floating body and the automaton body, thus impacting the backward ending state, offset efficiency, and consistency.

Compensating trigger jitter and time interval error measurement for digital sampling oscilloscopes with hardware design on FPGA

This paper presents the creation and realization of a precision time base (PTB) for mitigating jitter and measuring time interval error (TIE) in digital sampling oscilloscopes (DSO), achieved through the utilization of a field programmable gate array (FPGA). Our proposed method focuses on mitigating jitter through PTB, which involves the sampling of two reference channels having a phase shift of approximately 90∘ (at quadrature) for an accurate timebase correction. Through extensive experimentation and analysis, we were able to achieve a reduction in root mean square (RMS) jitter, minimizing it to around 260 fs. This outcome demonstrates the effectiveness of our approach in enhancing the accuracy and reliability of DSO measurements. Expanding on the application of our previously proposed technique, we demonstrate that the same sampling error correction approach can be utilized for TIE measurement. By sampling a large amount of data at either the rising or falling edge of a sinusoidal signal, TIE can be accurately evaluated. This extension enhances the versatility of our FPGA-based implementation by enabling comprehensive TIE analysis alongside PTB compensation in DSOs.

Switching-like event-triggered control of uncertain NCSs under delay distribution and DoS attacks

The paper addresses the switching-like event-triggered control for uncertain networked control systems with time-varying delay under DoS attacks. First of all, to reduce the communication burden, a switching-like event-triggered mechanism is designed to automatically select the trigger condition according to whether the system is under DoS attacks, which have the advantage of reducing the number of data packets transmitted. Secondly, unlike the traditional assumption of time-varying delay, here it satisfies the condition that the probability is known, and combines the networked control systems to propose a novel time-delay system model, which can obtain a larger upper bound on the delay. Then, by using both the Lyapunov functional method and linear matrix inequality technique, we obtain sufficient conditions of uncertain networked control systems to achieve exponentially stable in the mean square sense. Furthermore, under the common limitations of the maximum continuous packet losses caused by the DoS attacks and delay, the stability criterion is derived, which can be used to estimate the communication parameters and security controller gain. Finally, through two simulation examples, the larger upper bound of time delay, less trigger times, faster convergence rate are obtained, which verify the validity of our theoretical analysis.

Current applications of artificial intelligence in assisted reproductive technologies through the perspective of a patient's journey.

This review highlights the timely relevance of artificial intelligence in enhancing assisted reproductive technologies (ARTs), particularly in-vitro fertilization (IVF). It underscores artificial intelligence's potential in revolutionizing patient outcomes and operational efficiency by addressing challenges in fertility diagnoses and procedures. Recent advancements in artificial intelligence, including machine learning and predictive modeling, are making significant strides in optimizing IVF processes such as medication dosing, scheduling, and embryological assessments. Innovations include artificial intelligence augmented diagnostic testing, predictive modeling for treatment outcomes, scheduling optimization, dosing and protocol selection, follicular and hormone monitoring, trigger timing, and improved embryo selection. These developments promise to refine treatment approaches, enhance patient engagement, and increase the accuracy and scalability of fertility treatments. The integration of artificial intelligence into reproductive medicine offers profound implications for clinical practice and research. By facilitating personalized treatment plans, standardizing procedures, and improving the efficiency of fertility clinics, artificial intelligence technologies pave the way for value-based, accessible, and efficient fertility services. Despite the promise, the full potential of artificial intelligence in ART will require ongoing validation and ethical considerations to ensure equitable and effective implementation.

GOCI operation during the 10 years of sun interference in COMS

A practical approach has been studied to cope with the sun interference of Earth observation geostationary satellite and the results of 10-year satellite operation for preventing sun outage are presented with detailed analysis in this paper. The Communication Ocean Meteorological Satellite (COMS) is equipped with the Geostationary Ocean Color Imager (GOCI), which performs ocean observation mission in the geostationary orbit. After the launch of the COMS, this study was initiated to prevent image data loss due to sun interference in receiving GOCI image data at the ground station of the principle user site under the operation configuration of single satellite and single ground station. This paper fully covers the entire research and the operation process which have been conducted over the 10 years from 2011 to 2021, including unexpected changes of operational environment such as ground station antenna change and satellite longitude position change. The specific characteristics of sun interference on the COMS operation is analysed through the theoretical simulation on the strength and the occurrence time of sun interference affecting the GOCI image data reception. The simulation outcomes are used to specify trigger level, date and time of sun outage in the COMS operation. From the concept that the sun outage could be prevented by adjusting the GOCI imaging time in advance, a GOCI special operation plan was established for the practical way of the sun outage prevention that was optimized for the COMS mission and could be applied to actual satellite operation. The approach of this study is verified by confirming the success of the sun outage prevention after the execution of the GOCI special operation plan. The verification is based on the operation results of the satellite link Radio Frequency (RF) signal performance and the image reception success status which has been obtained during the 10 years of the COMS operation. And, this study shows good consistency between the simulation outcomes and the operational measurements as well as the operational flexibility that it is possible to cope with the sun outage successfully even in the unexpected operational changes during the 10 years.

Distributed Event-Triggered Quantized Fault-Tolerant Control of Linear Multiagent Systems With External Disturbances and Parameter Uncertainties.

In this article, the issue of fault-tolerant leader-following consensus under a distributed dynamic event-triggered mechanism is addressed for linear multiagent systems (MASs) in the presence of unknown parameter uncertainties, external disturbances, and actuator faults, including loss of effectiveness and bias, in which the mechanism is with quantized state measurements. Due to the fact that information is transmitted via a bandwidth-limited communication network, a quantized control scheme with a uniform quantizer is introduced for leader-following consensus. In order to decrease the communication load and save the limited communication network resources, a distributed event-triggered mechanism is studied for leader-following consensus problem of linear MASs with quantized state measurements. In the presence of actuator faults, external disturbances, and unknown parameter uncertainties, an adaptive coupling gain for the controller is presented. Based on the Lyapunov function approach, the stability of the closed-loop system and the convergence of consensus errors are proved. Furthermore, the Zeno behavior is excluded for the triggering time sequences. Finally, simulation studies are given to verify the effectiveness of the proposed event-triggered fault-tolerant control scheme.