Fabrication of Hierarchical MOF-Derived NiCo2S4@Mo-Doped Co-LDH Arrays for High-Energy-Density Asymmetric Supercapacitors.

The rational fabrication of composite structures made of mixed components has shown great potential for boosting the energy density of supercapacitors. Herein, an elaborate hierarchical MOF-derived NiCo2S4@Mo-doped Co-LDH arrays hybrid electrode was fabricated through a step-wise method. By leveraging the synergistic effects of a uniform array of NiCo2S4 nanowires as the core and an MOF-derived porous shell, the NiCo2S4@Mo-doped Co-LDH hybrid electrode demonstrates an exceptional specific capacitance of 3049.3 F g-1 at 1 A g-1. Even at a higher current density of 20 A g-1, the capacitance remains high at 2458.8 F g-1. Moreover, the electrode exhibits remarkable cycling stability, with 91% of the initial capacitance maintained after 10,000 cycles at 10 A g-1. Additionally, the as-fabricated asymmetric supercapacitor (ASC) based on the NiCo2S4@Mo-doped Co-LDH electrode achieves an impressive energy density of 97.5 Wh kg-1 at a power density of 835.6 W kg-1. These findings provide a promising approach for the development of hybrid-structured electrodes, enabling the realization of high-energy-density asymmetric supercapacitors.

Hierarchical Lotus-Seedpod-Derived Porous Activated Carbon Encapsulated with NiCo2S4 for a High-Performance All-Solid-State Asymmetric Supercapacitor.

Converting biowaste into carbon-based supercapacitor materials provides a new solution for high-performance and environmentally friendly energy storage applications. Herein, the hierarchical PAC/NiCo2S4 composite structure was fabricated through the combination of activation and sulfuration treatments. The PAC/NiCo2S4 electrode garnered advantages from its hierarchical structure and hollow architecture, resulting in a notable specific capacitance (1217.2 F g-1 at 1.25 A g-1) and superior cycling stability. Moreover, a novel all-solid-state asymmetric supercapacitor (ASC) was successfully constructed, utilizing PAC/NiCo2S4 as the cathode and PAC as the anode. The resultant device exhibited exceptionally high energy (49.7 Wh kg-1) and power density (4785.5 W kg-1), indicating the potential of this biomass-derived, hierarchical PAC/NiCo2S4 composite structure for employment in high-performance supercapacitors.

A self-powered sensor for drill pipe capable of monitoring rotation speed and direction based on triboelectric nanogenerator.

The rotation speed and direction of the drill pipe are the key parameters to control the drilling process, which need to be measured in real-time. Here, a self-powered drill pipe sensor that can measure the rotation speed and direction based on the triboelectric nanogenerators is proposed in this research. The basic working principle is that the single-electrode triboelectric nanogenerator will output the sawtooth signal during the rotation of the drill pipe, so the rotation speed can be measured by counting the signal pulse frequency, and then, the rotation direction can be realized by judging the direction of the tooth tip of the sawtooth signals. Test results show that the measurement range is 0-1000 rpm, the measurement error is less than 4%, the sensitivity is 0.0167 Hz/rpm, and the linearity is 3.5%. Further tests show that the maximum output voltage, current, and power are 21 V, 900 nA, and 3.35 µW, respectively, when a 107 Ω load resistance is connected in series. In addition, the working condition reliability tests show that the working temperature is less than 150 °C and the working relative humidity is less than 90%, with high reliability, which is very suitable for the drilling environments.

A self-powered vibration sensor for downhole drilling tools based on hybrid electromagnetic-triboelectric nanogenerator.

The vibration of downhole drilling tools is important to the drilling process, which needs to be measured in real time. Here, a self-powered vibration sensor for downhole drilling tools based on a hybrid electromagnetic-triboelectric nanogenerator is proposed in this research. The sensor has high reliability because the triboelectric nanogenerator (TENG) and the electromagnetic generator (EMG) parts of the sensor can be used as vibration sensors alone, and it may also supply power to other micro-power measurements while drilling instruments when the TENG and the EMG are used in parallel to increase the output power. Test results show that for the TENG part, the maximum output voltage, current, and power are 14 V, 5.2 µA, and 3.2 µW, respectively, with a 1 MΩ resistance in series, and for the EMG part, they are 1.22 V, 33 µA, and 21.8 mW, respectively, with a 10 Ω resistance in series. Further tests show that the measurement range of both the TENG and EMG is 0-11 Hz, the measurement error of both is less than ±5%, and both can work normally in the temperature range of less than 250 °C. In addition, this research also builds a wireless vibration data transmission system based on the sensor, which shows the potential for use in the wireless sensing field.

Development of self-powered bubble velocity sensor for gas-liquid two-phase flow based on triboelectric nanogenerator.

Bubble velocity of gas-liquid two-phase flow in coalbed methane well is an key parameter for formulating coalbed methane drainage technology. In this paper, a self-powered bubble velocity sensor (GLT-TENG) of two-phase flow, which is composed of distributed copper electrodes and low-density polyethylene wrapped in an outer layer, is proposed and analyzed based on triboelectric nanogenerator. Test results show that the measurement range is 0-0.49 m s-1 with a measurement error less than 6% when the GLT-TENG is used to measure a single bubble, but the measurement errors are inversely proportional to the time interval (the ratio of distance to speed difference) between the two bubbles when the GLT-TENG is used to measure continuous bubbles, and the measurement accuracy can reach 100% when the bubble time interval is greater than 0.3 s. The maximum output can be achieved when the bubble velocity impulse is 6200 cm3 · cm s-1, that is, the maximum output voltage and current are 0.38 V and 6.3 nA, respectively, and the maximum output power is 0.64 pW when the external load is 50 MΩ. In addition, the temperature and pulverized coal tests show that GLT-TENG has a good signal-to-noise ratio in the coalbed methane well environment, which can meet the actual working conditions.

Development of gas-liquid two-phase flow pattern sensor of coalbed methane based on the principle of triboelectric nanogenerator.

During the mining of coalbed methane (CBM), real-time measurement conducted by a gas-liquid two-phase flow pattern sensor is one of the key steps in the development of a reasonable discharge and mining system. In this study, a self-powered flow pattern sensor based on the triboelectric nanogenerator (TENG) was proposed and analyzed. The basic principle is as follows: when the sensor is impacted by the bubbles of the two-phase flow, triboelectric charges are generated due to the contact between the copper electrode, which plays the dual roles of electrode and positive triboelectric material, and the PTFE which acts as negative triboelectric material. This is transferred to produce voltage signals, thus realizing the measurement of the bubbles. On this basis, the characteristics and duration of the bubbles were further analyzed to measure the two-phase flow pattern. In addition, relevant characteristic parameters of the sensor were determined through analysis and experiment; when the product of the volume and velocity of the bubbles is greater than [Formula: see text] and the impact frequency is less than 0.45 Hz, the sensor can be used normally. We also explored the possibility of using the sensor to collect the impact energy of the bubbles to be used by other devices. As indicated by subsequent experiments on the sensor, it performs in a stable manner and can be used to measure the gas-liquid two-phase flow pattern, showing broad application prospects in the field of CBM.

An Enhanced Detection System of Drill Rod Bending Degree Based on Two-Dimensional Laser.

Drill rod straightness has to be strictly controlled and the maximum bending degree detection needs to be used in the straightening process. The mechanical bending degree measurement depends on machinery instruments and workers' experience, often with low efficiency and precision. While the optical inspection, as a non-contact detection method, with higher precision and lower installation accuracy requirements, is frequently applied in the online detection system. Based on this, an enhanced bending degree detection system for a drill rod is proposed in this paper. Compared to the existing detection system, the main progress is to use a two-dimensional laser to quickly obtain arc profile data and fit with ellipse. Segment inspection idea is also utilized is this system as the camera that could obtain the whole drill rod in one shot needs extremely high resolution and price. A specialized algorithm is designed to fit the cross-section shape and whole centerline displacement based on the least square method. Some laboratory tests are conducted to verify this detection system, findings of which are compared to manual measured results. The maximum bending degree error is 2.14 mm and the maximum position error is 8.21 mm, which are both within the tolerance of error. Those results show the feasibility and precision of this enhanced detection system.

Self-Powered Speed Sensor for Turbodrills Based on Triboelectric Nanogenerator.

Turbodrills play an important role in underground energy mining. The downhole rotational speed of turbodrills is one of the key parameters for controlling the drilling technology. Therefore, it is necessary to measure the rotational speed of the turbodrills in real time. However, there is no dedicated speed sensor for the working environment of turbodrills at present. Therefore, based on the working principle of triboelectric nanogenerator (TENG), a self-powered speed sensor which can measure the speed of the turbodrills is proposed in this study. Besides, since the sensor is self-powered, it can operate without power supply. According to the laboratory test results, the measurement error of the sensor is less than 5%. In addition, the self-powered performance of the sensor was also explored in this study. The test shows that the maximum generating voltage of the sensor is about 27 V, the maximum current is about 7 µA, the maximum power is about 2 × 10-4 W, and the generated electricity can supply power for ten LED (light-emitting diode), which not only meets the power supply requirements of the sensor itself, but also makes it possible to further power other underground instruments.

Automated Inspection of Defects in Optical Fiber Connector End Face Using Novel Morphology Approaches.

Increasing deployment of optical fiber networks and the need for reliable high bandwidth make the task of inspecting optical fiber connector end faces a crucial process that must not be neglected. Traditional end face inspections are usually performed by manual visual methods, which are low in efficiency and poor in precision for long-term industrial applications. More seriously, the inspection results cannot be quantified for subsequent analysis. Aiming at the characteristics of typical defects in the inspection process for optical fiber end faces, we propose a novel method, “difference of min-max ranking filtering” (DO2MR), for detection of region-based defects, e.g., dirt, oil, contamination, pits, and chips, and a special model, a “linear enhancement inspector” (LEI), for the detection of scratches. The DO2MR is a morphology method that intends to determine whether a pixel belongs to a defective region by comparing the difference of gray values of pixels in the neighborhood around the pixel. The LEI is also a morphology method that is designed to search for scratches at different orientations with a special linear detector. These two approaches can be easily integrated into optical inspection equipment for automatic quality verification. As far as we know, this is the first time that complete defect detection methods for optical fiber end faces are available in the literature. Experimental results demonstrate that the proposed DO2MR and LEI models yield good comprehensive performance with high precision and accepted recall rates, and the image-level detection accuracies reach 96.0 and 89.3%, respectively.

Automatic Fabric Defect Detection with a Multi-Scale Convolutional Denoising Autoencoder Network Model.

Fabric defect detection is a necessary and essential step of quality control in the textile manufacturing industry. Traditional fabric inspections are usually performed by manual visual methods, which are low in efficiency and poor in precision for long-term industrial applications. In this paper, we propose an unsupervised learning-based automated approach to detect and localize fabric defects without any manual intervention. This approach is used to reconstruct image patches with a convolutional denoising autoencoder network at multiple Gaussian pyramid levels and to synthesize detection results from the corresponding resolution channels. The reconstruction residual of each image patch is used as the indicator for direct pixel-wise prediction. By segmenting and synthesizing the reconstruction residual map at each resolution level, the final inspection result can be generated. This newly developed method has several prominent advantages for fabric defect detection. First, it can be trained with only a small amount of defect-free samples. This is especially important for situations in which collecting large amounts of defective samples is difficult and impracticable. Second, owing to the multi-modal integration strategy, it is relatively more robust and accurate compared to general inspection methods (the results at each resolution level can be viewed as a modality). Third, according to our results, it can address multiple types of textile fabrics, from simple to more complex. Experimental results demonstrate that the proposed model is robust and yields good overall performance with high precision and acceptable recall rates.

Enhanced Automated Guidance System for Horizontal Auger Boring Based on Image Processing.

Horizontal auger boring (HAB) is a widely used trenchless technology for the high-accuracy installation of gravity or pressure pipelines on line and grade. Differing from other pipeline installations, HAB requires a more precise and automated guidance system for use in a practical project. This paper proposes an economic and enhanced automated optical guidance system, based on optimization research of light-emitting diode (LED) light target and five automated image processing bore-path deviation algorithms. An LED light target was optimized for many qualities, including light color, filter plate color, luminous intensity, and LED layout. The image preprocessing algorithm, direction location algorithm, angle measurement algorithm, deflection detection algorithm, and auto-focus algorithm, compiled in MATLAB, are used to automate image processing for deflection computing and judging. After multiple indoor experiments, this guidance system is applied in a project of hot water pipeline installation, with accuracy controlled within 2 mm in 48-m distance, providing accurate line and grade controls and verifying the feasibility and reliability of the guidance system.

Horizontal Directional Drilling-Length Detection Technology While Drilling Based on Bi-Electro-Magnetic Sensing.

The drilling length is an important parameter in the process of horizontal directional drilling (HDD) exploration and recovery, but there has been a lack of accurate, automatically obtained statistics regarding this parameter. Herein, a technique for real-time HDD length detection and a management system based on the electromagnetic detection method with a microprocessor and two magnetoresistive sensors employing the software LabVIEW are proposed. The basic principle is to detect the change in the magnetic-field strength near a current coil while the drill stem and drill-stem joint successively pass through the current coil forward or backward. The detection system consists of a hardware subsystem and a software subsystem. The hardware subsystem employs a single-chip microprocessor as the main controller. A current coil is installed in front of the clamping unit, and two magneto resistive sensors are installed on the sides of the coil symmetrically and perpendicular to the direction of movement of the drill pipe. Their responses are used to judge whether the drill-stem joint is passing through the clamping unit; then, the order of their responses is used to judge the movement direction. The software subsystem is composed of a visual software running on the host computer and a software running in the slave microprocessor. The host-computer software processes, displays, and saves the drilling-length data, whereas the slave microprocessor software operates the hardware system. A combined test demonstrated the feasibility of the entire drilling-length detection system.

Battery-Operated Atomic Emission Analyzer for Waterborne Arsenic Based on Atmospheric Pressure Glow Discharge Excitation Source.

In this paper, a sensitive atomic emission spectrometer (AES) based on a new low power and low argon consumption (<8 W, 100 mL min-1) miniature direct current (dc) atmospheric pressure glow discharge (APGD) plasma (3 mm × 5 mm) excitation source was developed for the determination of arsenic in water samples. In this method, arsenic in water was reduced to AsH3 by hydride generation (HG), which was then transported to the APGD source for excitation and detected by a compact CCD (charge-coupled device) microspectrometer. Different parameters affecting the APGD and the hydride generation reactions were investigated. The detection limit for arsenic with the proposed APGD-AES was 0.25 µg L-1, and the calibration curves were found to be linear up to 3 orders of magnitude. The proposed method was successfully applied to the determination of certified reference material (GBW08605), tap water, pond water, groundwater, and hot spring samples. Measurements from the APGD analyzer showed good agreement with the certified value/values obtained with well-established hydride generation atomic fluorescence spectrometry (HG-AFS). These results suggest that the developed robust, cost-effective, and fast analyzer can be used for field based arsenic determination and may provide an important tool for arsenic contamination and remediation programs.

The Development of a Gas-Liquid Two-Phase Flow Sensor Applicable to CBM Wellbore Annulus.

The measurement of wellbore annulus gas-liquid two-phase flow in CBM (coalbed methane) wells is of great significance for reasonably developing gas drainage and extraction processes, estimating CBM output, judging the operating conditions of CBM wells and analyzing stratum conditions. Hence, a specially designed sensor is urgently needed for real-time measurement of gas-liquid two-phase flow in CBM wellbore annulus. Existing flow sensors fail to meet the requirements of the operating conditions of CBM wellbore annulus due to such factors as an inapplicable measurement principle, larger size, poor sealability, high installation accuracy, and higher requirements for fluid media. Therefore, based on the principle of a target flowmeter, this paper designs a new two-phase flow sensor that can identify and automatically calibrate different flow patterns of two-phase flows. Upon the successful development of the new flow sensor, lab and field tests were carried out, and the results show that the newly designed sensor, with a measurement accuracy of ±2.5%, can adapt to the operating conditions of CBM wells and is reliable for long-term work.

Research on the Conductivity-Based Detection Principles of Bubbles in Two-Phase Flows and the Design of a Bubble Sensor for CBM Wells.

The parameters of gas-liquid two-phase flow bubbles in field coalbed methane (CBM) wells are of great significance for analyzing coalbed methane output, judging faults in CBM wells, and developing gas drainage and extraction processes, which stimulates an urgent need for detecting bubble parameters for CBM wells in the field. However, existing bubble detectors cannot meet the requirements of the working environments of CBM wells. Therefore, this paper reports findings on the principles of measuring the flow pattern, velocity, and volume of two-phase flow bubbles based on conductivity, from which a new bubble sensor was designed. The structural parameters and other parameters of the sensor were then computed, the "water film phenomenon" produced by the sensor was analyzed, and the appropriate materials for making the sensor were tested and selected. After the sensor was successfully devised, laboratory tests and field tests were performed, and the test results indicated that the sensor was highly reliable and could detect the flow patterns of two-phase flows, as well as the quantities, velocities, and volumes of bubbles. With a velocity measurement error of ±5% and a volume measurement error of ±7%, the sensor can meet the requirements of field use. Finally, the characteristics and deficiencies of the bubble sensor are summarized based on an analysis of the measurement errors and a comparison of existing bubble-measuring devices and the designed sensor.