Search Results (18)

Rubidium fountain clocks are operated by a control system. In this study, first, the control requirements of a rubidium fountain clock are analyzed; then, a control system is designed and divided into a timing sequence control system, a data acquisition system, and a servo control system. Multiple boards based on PCI extensions for the instrumentation (PXI) bus and Labwindows/CVI software 2019 are adopted. The timing sequence control system outputs 16 transistor–transistor logic (TTL) signals and three arbitrary waveforms. The results show that these signals are synchronized within 380 ns. Moreover, the digital locking frequency of the master laser is triggered by one of the timing signal, sweeping the laser frequency in a wide range during polarization gradient cooling. Two time-of-flight signals are acquired, and Ramsey fringes are scanned using the data acquisition system. An error signal is obtained every two cycles, and it is feed back to the frequency synthesizer and a high resolution offset generator using the servo control system. Then the frequency synthesizer is locked to the Ramsey center resonance. The rubidium atomic fountain clock exhibited a frequency stability of 7.4 × 10⁻¹⁶ at 86,400 s. Moreover, the phase of the Rb fountain clock is compared with that of UTC (NTSC) in real time, demonstrating a frequency drift of 0.00044 ns/day/day. The whole control system is full-featured, robust and flexible, thus satisfying the requirements of rubidium fountain clocks. Full article

For this study, a substitution principle-based impedance bridge has been developed to calibrate AC resistors in a four-terminal-pair (4TP) configuration. The calibration is performed in the full complex plane for resistances ranging from 100 mΩ to 400 Ω and frequencies of between 50 Hz and 20 kHz. The automated bridge is based on four resistors associated with two high-impedance stages. The balancing of the bridge is achieved by means of PXI modules. The bridge is automatically balanced via a simplex top-down algorithm. The new bridge is primarily used for the measurement chain of AC standard resistors defined in a 4TP configuration at LNE, which are used for routine customer calibrations. The traceability of LNE’s standard resistors when defined in a 4TP configuration is ensured by a measurement chain from a 1 kΩ reference resistor using the new bridge. The reference resistor was calibrated previously via comparison with a calculable resistor up to 20 kHz. The bridge was validated via comparison with calibration results obtained in 1983 and 2009. For a resistor of 1 Ω at 1 kHz, the uncertainty of the series resistance variation and the phase shift are less than 6 µΩ/Ω (k = 1) and 6 µrad (k = 1), respectively. Full article

Faults in solar photovoltaic (PV) modules often result from component damage, leading to voltage fluctuations and decreased stability in the power system. In this study, the original voltage signals of different PV modules show little variation. Therefore, a solution that combines symmetrized dot pattern (SDP) and AlexNet for fault detection in PV modules was proposed. This solution investigates three common faults: poor welding, cracking, and bypass diode failure, which can be applied to fault-free modules. First, a high-frequency signal was input into the PV module, and the raw signal was captured using an NI PXI-5105 high-speed data acquisition card. Next, we used SDP to process the signal and create images with specific snowflake-like features. These images were used as a basis for fault diagnosis. Finally, deep-learning algorithms were used to perform status detection on the PV module. This research also used 3200 training samples and 800 test samples (200 for each type) to evaluate a new method for diagnosing faults in PV modules. The results show that the accuracy of the new method reached 99.8%, surpassing traditional convolutional neural networks (CNN) and extension neural networks (ENN), whose accuracies were 99.5% and 91.75%, respectively. Furthermore, this study compares the proposed method with more traditional numerical fault diagnosis methods. SDP effectively extracts fault signals and presents them as images. With AlexNet used for fault identification, the method excels in accuracy, training time, and testing time, thereby enhancing the stability and reliability of future energy systems. Full article

This paper addresses the fault problem in distributed-four-wheel-drive electric vehicle drive systems. First, a fault-factor-based active fault diagnosis strategy is proposed. Second, a fault-tolerant controller is designed to reconstruct motor drive torque based on vehicle stability. This controller ensures that the vehicle maintains stability by providing fault-free motor output torque based on fault diagnosis results. To validate the effectiveness of the fault diagnosis and fault-tolerant control, SIL simulation is conducted using MATLAB/Simulink and CarSim. A hardware-in-the-loop (HIL) simulation platform with the highest confidence level is established based on NI PXI and CarSim RT. Through the HIL simulation experiments, it is shown that the proposed control strategy can accurately diagnose the operating state of the motor, rebuild the motor torque based on stability, and demonstrate robust stability when the drive system fails. Under various fault conditions, the maximum error in the vehicle lateral angular velocity is less than 0.017 rad/s and the maximum deviation in the lateral direction is less than 0.7 m. These findings substantiate the highly robust stability of the proposed method. Full article

The increased need for renewable energy systems to generate power, store energy, and connect energy storage devices with applications has become a major challenge. Energy storage using batteries is most appropriate for energy sources like solar, wind, etc. A non-isolated three-port DC–DC-converter energy conversion unit is implemented feeding the brushless DCmotor drive. In this paper, a non-isolated three-port converter is designed and simulated for battery energy storage, interfaced with an output drive. Based on the requirements, the power extracted from the solar panel during the daytime is used to charge the batteries through the three-port converter. The proposed three-port converter is analyzed in terms of operating principles and power flow. An FPGA-based NI LabView PXI with SbRio interface is used to develop the suggested approach’s control hardware, and prototype model results are obtained to test the proposed three-port converter control system’s effectiveness and practicality. The overall efficiency of the converter’s output improves as a result. The success rate is 96.5 percent while charging an ESS, 98.1 percent when discharging an ESS, and 95.7 percent overall. Full article

The traditional electronic braking system (EBS) of a commercial vehicle has the problems of sluggish pressure response, large dynamic error and unsatisfactory braking effect during braking. First, a novel EBS system based on electronic pneumatic valves (EPV) module is designed, which integrated the control of each pneumatic valve. Secondly, the hardware of the EBS bottom controller and the air pressure closed-loop control are carried out. A kind of similar to PWM (SPWM) air pressure control method is proposed. By controlling the opening and closing time of the solenoid valves, the brake air pressure could be precisely regulated, and the dynamic response characteristics of the system are improved. Eventually, commercial vehicle air brake hardware in the loop (HIL) test platform based on LabVIEW and NI-PXI system is built to verify the effectiveness of the EBS dynamic response characteristics. The experimental results showed that the continuous control of EBS solenoid valves is realized by using the SPWM control method, and the fine dynamic response characteristics of EBS air pressure closed-loop control are ensured. Full article

Variance-component models are an indispensable tool for statisticians wanting to capture both random and fixed model effects. They have applications in a wide range of scientific disciplines. While maximum likelihood estimation (MLE) is the most popular method for estimating the variance-component model parameters, it is numerically challenging for large data sets. In this article, we consider the class of coordinate descent (CD) algorithms for computing the MLE. We show that a basic implementation of coordinate descent is numerically costly to implement and does not easily satisfy the standard theoretical conditions for convergence. We instead propose two parameter-expanded versions of CD, called PX-CD and PXI-CD. These novel algorithms not only converge faster than existing competitors (MM and EM algorithms) but are also more amenable to convergence analysis. PX-CD and PXI-CD are particularly well-suited for large data sets—namely, as the scale of the model increases, the performance gap between the parameter-expanded CD algorithms and the current competitor methods increases. Full article

The photovoltaic (PV) module is a key technological advancement in renewable energy. When the PV modules fail, the overall generating efficiency will decrease, and the power system’s operation will be influenced. Hence, detecting the fault type when the PV modules are failing becomes important. This study proposed a hybrid algorithm by combining the symmetrized dot pattern (SDP) with a convolutional neural network (CNN) for PV module fault recognition. Three common faults are discussed, including poor welding, breakage, and bypass diode failure. Moreover, a fault-free module was added to the experiment for comparison. First, a high-frequency square signal was imported into the PV module, and the original signal was captured by the NI PXI-5105 high-speed data acquisition (DAQ) card for the hardware architecture. Afterward, the signal was imported into the SDP for calculation to create a snowflake image as the image feature for fault diagnosis. Finally, the PV module fault recognition was performed using CNN. There were 3200 test data records in this study, and 800 data records (200 data records of each fault) were used as test samples. The test results show that the recognition accuracy was as high as 99.88%. It is better than the traditional ENN algorithm, having an accuracy of 91.75%. Therefore, while capturing the fault signals effectively and displaying them in images, the proposed method accurately recognizes the PV modules’ fault types. Full article

In the currently used primary impedance measuring systems, there is a need to compare standards with ratios different from 1:1, e.g., in order to transfer the value to multiples or submultiples of the basic quantity. Unfortunately, the commercial PXI sampling systems used to measure the voltage ratio in the impedance bridge, although they provide adequate resolution, show a considerable non-linearity of the measurement. This leads to significant error of the impedance ratio measurement. Experimental studies of commercial PXI digitizers used in primary impedance metrology are presented in the paper. The scope of the work includes presentation of the sampling measurement system hardware used in electronic synchronous impedance bridges and studies of the parameters that affect the applicability of PXI digitizers in high-precision measuring instruments. Nonlinearity errors of digitizers on boards NI PXI-4461 and NI PXI-4462 were measured and appropriate conclusions regarding possible corrections of the errors were drawn. Full article

This paper proposes a new fast time-delay estimation (TDE) method based on polynomial inversion which addresses the challenges arising from the requirements for high-precision, low-computational-complexity synchronization error estimation in wideband large-scale antenna systems (LSASs). In this work, we use the convex parabolic extreme point equation as the timing error detector (TED), and develop a polynomial inversion-based function to characterize the one-to-one mapping relationship between true time delay (TTD) and TED estimates using the least square (LS) method, then obtain the time-delay difference with a high accuracy and high computational efficiency. The results of the performance analysis indicate that the Mean Square Error (MSE) of the proposed algorithm is less than 1 dB away from the Cramer–Rao lower bound (CRLB), which is produced in this paper, while adding a few multipliers compared to the convex parabolic interpolation method. Finally, a further example illustrates that the proposed algorithm can achieve a synchronization error of less than 5 ps between channels based on the NI PXI broadband multichannel acquisition platform. Full article

The radio frequency (RF) laboratory hosted in the Corpuscular Physics Institute (IFIC) of the University of Valencia is designed to house a high-power and high-repetition-rate facility to test normal conduction RF accelerator cavities in the S-Band (2.9985 GHz) in order to perform R&D activities related to particle accelerator cavities. The system, which manages the entire process of RF signal generation, data acquisition and closed-loop control of the laboratory, is currently based on a modular and compact PXI platform system. This contribution details the development of a platform with similar features, but which is based on open architecture standards at both the hardware and software level. For this purpose, a complete system based on the μTCA platform has been developed. This new system must be able to work with accelerator cavities at other operating frequencies, such as 750 MHz, as well as to explore different options at firmware and software levels based on open-source codes. Full article

The components of OLED encapsulation with hermetic sealing and a 1026-day lifetime were measured by PXI-1033. The optimal characteristics were obtained when the thickness of the TPBi layer was 20 nm. This OLED obtained a maximum luminance (Lmax) of 25,849 cd/m² at a current density of 1242 mA/cm², an external quantum efficiency (EQE) of 2.28%, a current efficiency (CE) of 7.20 cd/A, and a power efficiency (PE) of 5.28 lm/W. The efficiency was enhanced by Lmax 17.2%/EQE 0.89%/CE 42.1%/PE 41.9%. The CIE coordinates of 0.32, 0.54 were all green OLED elements with wavelengths of 532 nm. The shear strain and leakage test gave results of 16 kgf and 8.92 × 10⁻⁹ mbar/s, respectively. The reliability test showed that the standard of MIL-STD-883 was obtained. Full article

With the rapid development of solar energy, the photovoltaic (PV) module fault detection plays an important role in knowing how to enhance the reliability of the solar photovoltaic system and knowing the fault type when a system problem occurs. Therefore, this paper proposed the hybrid algorithm of chaos synchronization detection method (CSDM) with convolutional neural network (CNN) for studying PV module fault detection. Four common PV module states were discussed, including the normal PV module, module breakage, module contact defectiveness and module bypass diode failure. First of all, the defects in 16 pieces of 20W monocrystalline silicon PV modules were preprocessed, and there were four pieces of each fault state. When the signal generator delivered high frequency voltage to the PV module, the original signal was measured and captured by the NI PXI-5105 high-speed data acquisition system (DAS) and was calculated by CSDM, to establish the chaos dynamic error map as the image feature of fault diagnosis. Finally, the CNN was employed for diagnosing the fault state of the PV module. The findings show that after entering 400 random fault data (100 data for each fault) into the proposed method for recognition, the recognition accuracy rate of the proposed method was as high as 99.5%, which is better than the traditional ENN algorithm that had a recognition rate of 86.75%. In addition, the advantage of the proposed algorithm is that the mass original measured data can be reduced by CSDM, the subtle changes in the output signals are captured effectively and displayed in images, and the PV module fault state is accurately recognized by CNN. Full article

The paper presents a method for digital compensation of the ratio and phase angle errors of a resistive voltage divider. The system consists of a separate electrical circuit of a resistive divider, and a digital compensation system based on National Instruments (NI) PCI eXtension for Instrumentation (PXI) PXI-5922 digital acquisition cards (DAQ). A novel approach to the real-time compensation is presented, using digital signal processing. The algorithm is based on Wiener filtering and finite-impulse-response (FIR) filters. The proposed digital compensation, using FIR digital filtration and NI PXI DAQs, gives maximum magnitude error below 400 ppm and the phase angle error below 4500 μrad, in the frequency band 50 Hz–100 kHz. The algorithm allows the fine-tuning of the compensation to adjust to the possible change in the original transfer function due to the aging of the components. Full article

Modular multilevel converters (MMCs), with their inherent features and advantages over other conventional converters, have gained popularity and remain an ongoing topic of research. Many scholars have solved issues related to the operation, control, protection, and reliability of MMCs using simulation software and small hardware prototypes. We propose a novel approach for an MMC controller design with real-time systems. By utilizing a key benefit of LabVIEW Multisim co-simulation, an MMC control algorithm that can be deployed on a field-programmable gate array (FPGA) was developed in LabVIEW. The complete circuit was designed in Multisim, and a co-simulation was performed to drive an MMC model. The benefit of this topology is that control algorithms can be designed in a LabVIEW FPGA and tested with the Multisim co-simulation circuit to obtain simulation results. Once the controller works and provides satisfactory results, the same algorithm can be deployed in any NI (National Instruments) FPGA-based controller, like a compact remote input/output (RIO), to control real-time MMCs designed in an NI PCI eXtensions for Instrumentation (PXI) system. This method saves time and provides flexibility for effectively designing control algorithms and implementing them in an FPGA for real-time model implementation. Full article