The grain size rating is a key indicator for evaluating the microstructural properties of metallic materials. However, challenges such as the presence of twins, precipitates, and blurred grain boundaries complicate accurate and efficient grain size measurements. To address these issues, we propose a grain boundary segmentation network that combines a multisupervised signal network with multiple attention mechanisms. On the one hand, the integration of edge loss in the encoder makes the network focus more on the grain boundary regions. On the other hand, the multiple attention mechanism better integrates the low-level and high-level features of the image, enabling accurate grain boundary localization. Additionally, we design an orientation fit closure method to obtain closed-grain images. This method combines fracture boundary pixel path search with principal component analysis to determine the boundary extension direction. Finally, a quantitative analysis module is designed on the basis of GB/T 6394. The experimental results indicate that the rating results of the grain boundary images processed by the segmentation network and postprocessing are in close agreement with those provided by professional inspectors. The error for all test samples is within +/- 0.5 grades, providing objective and accurate data for the analysis of the physical properties of metallic materials.

The precise measurement of the circular saw blade matrix's dimensions is critical for optimising cutting performance in industrial applications. To overcome the limitations of existing contact and non-contact methods, this paper presents a machine vision-based approach that integrates sophisticated image preprocessing, geometric compensation, and robust feature extraction. A novel thickness-compensated perspective correction technique is employed to rectify image distortions between the top and bottom surfaces of the central aperture, reducing measurement error to 0.014 mm. For the positioning holes, a dual-constraint contour screening approach based on area and distance is implemented to isolate valid edge points, followed by nonlinear least-squares circle fitting. To address inaccuracies at indistinct or intricate tooth edges, an indirect feature extraction method utilising connected-component analysis is proposed, which effectively identifies and quantifies both functional and protective teeth. Comparative investigations with a high-precision coordinate measuring machine show maximum dimensional deviations of 0.02 mm and a discrete-feature recognition accuracy of 100%. The repeatability was maintained within +/- 0.1 mm across six sample batches. The results confirm that the proposed system meets the stringent accuracy and stability requirements for industrial inspection, providing a scalable and adaptable solution for quality control in circular saw blade production.

The grain size rating is a crucial indicator for evaluating the microstructural properties of metallic materials. Although deep learning is increasingly used for metallographic image analysis, most existing methods rely heavily on large quantities of high-quality annotated data. To address this limitation, we propose a lightweight framework for measuring grain size that integrates a data-efficient segmentation network with optimized postprocessing. Specifically, the encoder is first pretrained on a large set of unlabeled data via a masked autoencoder (MAE) to strengthen its ability to capture fine-grained image features. The entire segmentation network is then fine-tuned on a small annotated dataset. Furthermore, a local watershed optimization algorithm is proposed to obtain closed-grain images, where optimization is applied only to fractured boundary regions, thereby reducing the computational cost. Finally, a quantitative analysis module is developed in accordance with GB/T 6394. The experimental results indicate that the grain size ratings obtained from the proposed framework are in close agreement with those provided by professional inspectors. Across all test samples, the deviations remain within +/- 0.5 grades, which demonstrates the reliability of the method. These results suggest that the framework can provide objective and accurate data to support the microstructural characterization of metallic materials.

Surface defects strongly affect the stability and service life of bearing balls. In this Letter, I present a monocular line scan vision-based detection system for detecting surface defects on bearing balls. An optical system was designed to solve the problems of nondevelopability, large spherical curvature, and high reflection of bearing ball surfaces. The principle of light illuminating bearing balls was developed. By analyzing the motion unfolding trajectory curve, I propose a line scanning unfolding process and image acquisition scheme for the whole surface of the bearing ball. According to the unfolding principle, I have established a mathematical model of the whole-surface bearing ball unfolding process and developed a simulation. Experiments were performed to capture the surface image of bearing balls. A defect detection algorithm for spatiotemporal image is developed. A subtraction operation is used to enhance the defect information. Spatial–temporal resolution normalization is developed to make the scale of spatiotemporal image uniform and extract the surface defects. The experimental results show that the detection resolution of the crack defects is approximately 0.001 mm2, and the crack defect detection rate is 100%, which demonstrates that the proposed method has high detection accuracy.

Aqueous ammonium-ion batteries are promising candidates for grid-scale energy storage owing to their non-flammability, eco-friendliness, and low-cost. Nevertheless, their further development suffers from electrolyte/electrode instability and limited energy density. Herein, we develop an aqueous ammonium-bromine/ion battery composed of 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) organic materials as the anode, Br2/Br− redox couple as the cathode, and ionic liquid-functionalized aqueous solution as the electrolyte. The experimental investigation and theoretical calculation results reveal that two organic cations (TPA+ and BMIM+) in the functionalized electrolyte can insert into the PTCDA anode with different intercalation chemistry, which enhances the reversibility of NH4+ storage. Furthermore, organic cations not only construct a hydrophobic interfacial layer to expel water molecules from the anode surface, but also stabilize the active species at the cathode side by forming a solid complexation phase. Consequently, the as-developed aqueous ammonium-bromine/ion batteries present satisfactory electrochemical performance at both room temperature and low temperature, which promotes its potential application in grid-scale energy storage.

For the center aperture and outer diameter of circular saw blades, most of them rely on caliper detection, which is inefficient and easy to produce errors. In this paper, the Hough circle detection algorithm is improved, and the detection efficiency of the algorithm is improved by dividing four edge zones and randomly selecting candidate points from three edge regions, which reduces the number of samplings points and improves the detection efficiency of the algorithm. The improved Hough circle detection algorithm is used to detect the center aperture and outer diameter of the circular saw blade, which greatly reduces the inspection time. Experiments show that the detection method has the advantages of high measurement accuracy and fast detection speed and has a wide application prospect in the measurement of geometric parameters of circular saw blades, and is suitable for the parameter measurement of disc parts.

The quenching of the core of a circular saw determines the stress, hardness and flatness of the saw, which greatly affect its cutting performance. We have designed a new heat-treatment production line to model the quenching process, in which the quenching performance is determined by the position of the circular saw core on the quenching platen. In this short communication, we propose a circular saw core localization system based on machine vision that can be applied during the quenching process. In the proposed system, a perspective transformation method is applied to transform the captured oblique-view image into a vertical-view image. Then, a support vector machine is used to classify two types of circular saws. An image processing algorithm is applied to extract the circular saw core from the vertical-view image. The Hough transform is used to detect the center of the circle. Finally, the maximum overlapping region algorithm is used to obtain the accurate position of the circular saw on the quenching platen. To verify the robustness and universality of the circular saw localization system, we tested circular saw cores under different conditions. The test results show that in a real quenching scenario, the proposed system exhibits high localization accuracy and universality. This system can be effectively applied for quenching process monitoring in industry.

Attitude measurements are important parameters for condition monitoring of precision machines. We develop an angle measurement method based on monocular line scan vision to dynamically measure the attitude of shafts. The proposed measurement system, which consists of a single line scan camera, a parallel laser light source, and a triangular mirror, does not require fixation of a sensor on the shaft. The measurement system uses the line scan camera to capture the projection of the shaft. The light source is diffused by a cylindrical lens to yield parallel directional light. Then the parallel directional light is reflected by a fixed-angle mirror and projected onto the projection plane. The captured image can be considered a discrete time sequence. The attitude measurement principle based on linear monocular vision is derived. A double light-spot centroid algorithm is developed to obtain the centroid coordinates of the projection points. The proposed method is investigated by a simulation and experiment. The proposed method can also monitor the vibration of the shaft. The experimental results prove that the proposed method is effective and highly accurate.

Metal-free aqueous batteries are promising candidates for grid-scale energy storage owing to their inherent safety, low cost, and cost effectiveness. The battery chemistry based on fast NH4+ diffusion kinetics avoids unfavorable generation of inactive metallic byproducts. However, their practical applications have been impeded by electrolyte instability and the intrinsic drawbacks of current electrodes. Herein, we propose an aqueous ammonium-iodine battery by using a chaotropic electrolyte, 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA) anode, and iodine composite (I2@CC) cathode. Experimental investigations and theoretical calculations reveal that the chaotropic electrolyte not only enhances electrolyte stability through modulating the H-bond structure but also facilitates the formation of a hydrophobic cationic sieve (HCS) on the anode, which ensures the electrolyte/electrode stability and high reversibility of the anode. Additionally, the Cl--containing electrolyte can support the consecutive I+/I0 reaction on the cathode by forming [IClx]1-x interhalogen. The as-assembled aqueous ammonium-iodine batteries (AIBs) based on NH4+ accommodation at the anode and I+/I0 redox reaction at the cathode can deliver superior electrochemical performance at room temperature and low temperature (-20 °C). This study provides a strategic insight into developing metal-free aqueous batteries with electrolyte modulation.

Rapid proton transport in solid‐hosts promotes a new chemistry in achieving high‐rate Faradaic electrodes. Exploring the possibility of hydronium intercalation is essential for advancing proton‐based charge storage. Nevertheless, this is yet to be revealed. Herein, a new host is reported of hexagonal molybdates, (A 2 O) x ·MoO 3 ·(H 2 O) y (A = Na + , NH 4 + ), and hydronium (de)intercalation is demonstrated with experiments. Hexagonal molybdates show a battery‐type initial reduction followed by intercalation pseudocapacitance. Fast rate of 200 C (40 A g −1 ) and long lifespan of 30 000 cycles are achieved in electrodes of monocrystals even over 200 µm. Solid‐state nuclear magnetic resonance confirms hydronium intercalations, and operando measurements using electrochemical quartz crystal microbalance and synchrotron X‐ray diffraction disclose distinct intercalation behaviours in different electrolyte concentrations. Remarkably, characterizations of the cycled electrodes show nearly identical structures and suggest equilibrium products are minimally influenced by the extent of proton solvation. These results offer new insights into proton electrochemistry and will advance correlated high‐power batteries and beyond.

As a typical thin plate part, a circular saw blade matrix is prone to deformation and cracking due to uneven surface cooling rate during heat treatment. Simultaneously, the traditional quenching method is easy to produce a low product qualification rate and serious environmental severe when processing thin plate parts. The quenching device designed in this paper is to achieve the non-contact quenching between the processed parts and the quenching medium through the heat transfer of the fluid in the cooling pipe. The structure design of the internal cooling channel will directly affect the temperature field distribution of the quenching device, thus determining the microstructure and final performance of the product. Therefore, based on the microstructure transformation mechanism and pipe network flow control theory, combined with the heat transfer theory and other relevant theoretical bases, this paper established the mathematical model of internal cooling system parameters. Finally, MATLAB is applied to solve the fluid network topology model. It provides a reliable and general research method for cooling pipe networks in quenching devices based on the “Solid Contact-Fluid Heat Transfer” Mode.

The flatness error is one of the critical parameters of a circular saw, which seriously affects the cutting performance. In this paper, the measurement of the circular saw flatness error based on a laser displacement sensor is proposed. For the tooth of a circular saw, the plane is discontinuous. According to the field detection demand of a circular saw, the authors collected Archimedean spiral three coordinate data of the circular saw using a laser displacement sensor. Considering the practical application of circular saw flatness detection, the authors have established an ideal plane model of the flatness based on the least-squares method to evaluate the flatness error of circular saws. The system has a maximum detection area of 400 mm × 400 mm, the measurement time is 80 s, and the measurement absolution accuracy is 10 μm.

The automatic recognition of pointers is of great significance for efficiently collecting measurements from industrial instruments. In this paper, an automatic pointer meter recognition system based on line scan vision is developed. A line scan camera is used to capture images of the pointer of a pointer meter. Light-spot centroid algorithm is implemented to determine the centroid position of the pointer. The captured images can record the dynamic movement of the pointer, thereby enabling condition monitoring in industrial processes. Experimental results show that the proposed pointer meter extraction method is robust against interference and that a characteristic segmentation classifier produces more accurate detection results than other approaches.

Pitch and yaw angular speed measurements are vitally important parameters for monitoring the condition of precision machines. In this letter, we propose a dynamic pitch and yaw angular speed measurement system based on line scan vision. The characteristic line scan image can be considered a discrete time sequence, and each column of pixels represents a different time. A double light-spot centroid and double Gaussian fitting algorithm are developed to obtain the centroid coordinates. Kalman data fusion is employed to enhance the accuracy of the obtained measurement results. The experimental results prove that the proposed method is effective and highly accuracy.

The general strain gradient theory of Mindlin is re-visited on the basis of a new set of higher-order metrics, which includes dilatation gradient, deviatoric stretch gradient, symmetric rotation gradient and curvature. A strain gradient bending theory for plane-strain beams is proposed based on the present strain gradient theory. The stress resultants are re-defined and the corresponding equilibrium equations and boundary conditions are derived for beams. The semi-inverse solution for a pure bending beam is obtained and the influence of the Poisson’s effect and strain gradient components on bending rigidity is investigated. As a contrast, the solution of the Bernoulli–Euler beam is also presented. The results demonstrate that when Poisson’s effect is ignored, the result of the plane-strain beam is consistent with that of the Bernoulli–Euler beam in the couple stress theory. While for the strain gradient theory, the bending rigidity of a plane-strain beam ignoring the Poisson’s effect is smaller than that of the Bernoulli–Euler beam due to the influence of the dilatation gradient and the deviatoric stretch gradient along the thickness direction of the beam. In addition, the influence of a strain gradient along the length direction on a bending rigidity is negligible.

Analog instruments are widely used in energy engineering. However, an analog instrument is only human-readable because it does not have a built-in digital communication interface. In power system, it is necessary not only to record the final output value but also to monitor the associated dynamic power process. The present paper develops an analog instrument pointer monitoring and parameter estimation system via line scan vision. A line scan camera is used to collect the dynamic process data of the analog instrument. The captured images can be regarded as a discrete temporal sequence. The light-spot centroid method is implemented to extract the initial pointer position. Data normalization is used to process the initial data. By analysing the system step response function, we construct a cost function, and Least-squares identification algorithm is used to estimate the damp and natural frequency. The proposed method monitors the dynamic process of the analog instrument with various inputs, such as sine signals and random signals, thereby enabling condition monitoring. Experimental prediction results show that the proposed estimation method is effective and robust.

This paper is intended to examine the dislocation and adiabatic shear mechanisms of 7055 aluminum alloy during cutting process with different cutting speeds. The result indicates that, at low cutting speeds, isometric dislocation cells appear, the dislocation cells are interconnected into dislocation cell blocks, and the dislocation movement is controlled by thermal activation; at high cutting speeds, dislocations mostly come in the form of elongated or not fully closed dislocation cells, and the dislocation movement is controlled by phonon drag; the width of an adiabatic shear band increases with the cutting speed, and low cutting speeds are more likely to result in microcracks. The precipitation-free zones on the grain boundary display a discontinuity under all cutting speeds; distribution and grain size of the precipitates also vary significantly.

In this paper, feedforward compensation and an internal model control (IMC) PID tuning method to maintain the yarn tension within a micro-boundary range are proposed. The proposed method can be used to improve the quality of products in textile industry. We first develop a mathematical model of the AC servo motor and yarn tension system. Based on the results of the mathematical model, an IMC PID controller is designed to control the microtension of the yarn. The proposed IMC-PID controller can be directly calculated from the time constant and time delay. Feedforward control is used to compensate for the linear velocity of the winding roller. To reduce the lateral vibrations of the yarn, we designed an active roller to nip the moving yarn. The active roller compensates for the variation in the diameter of the unwinding roller. The proposed method effectively improves the dynamics performance and the robustness of the system, and is appropriate for industrial application. Experimental instruments, including a tension sensor, an AC servo motor and a motion controller, equipped with a computer, are used to test the proposed method. The simulation and experimental results show the effectiveness of the proposed controller for the yarn microtension control system.

Abstract This paper is intended to examine the dynamic evolution of the metastable structure and nano precipitation of AA7055 under thermal deformation. Results indicate the second-phase particles produced will break up and spheroidize at low temperature. When the strain reached 0.4, precipitated η (MgZn2) was detected to occur and gradually coarsen. Under high temperature and high strain rate, not many second phase particles were left in the alloy and the particles were nearly spherical. Coarse rod-like T (Al2Mg3Zn3) particles appeared during thermal deformation, which would gradually coarsen and tend toward uniform orientation. There were also long rod-like S (Al2CuMg) particles and some nanoscale coarse particles. During thermal deformation, dislocations quickly proliferated, entangling into dislocation cells, and then formed subgrains through slipping and climbing. When the strain reached its maximum, large-angle grain boundaries were detected below 450°C, suggesting that dynamic recrystallizion had taken place. Below 300°C, however, only dynamic recovery took place. As the strain increased, the dislocation density reduced. Subgrains developed quite completely. The intergranular misorientation was modest. The subgrains were 0.2∼ 0.6 μm in size with quite straight boundaries, but these subgrains were not stable enough. The boundary angle also displayed a tendency of developing toward the 120°. According to the diffraction pattern of zonal axis [⥘11]Al, the orientation relationship of the η′ and η (MgZn2) particles to the aluminum matrix was (0001)η//(111)Al. Under high temperature (450°C), when the strain was 0.4, subgrains with relatively clear boundaries were observed. Under low temperature, at the same strain, subgrains in the alloy were still entangling dislocaion cell grains with high intragranular and boundary dislocation densities. A few subgrain boundaries were becoming clear. The subgrain boundaries were heavily curved. Quite a lot of the subgrain boundaries were still unclear. When the strain was 0.6, under high temperature, the subgrain boundaries began to transform toward 120° stable state. Subgrains began to grow. Under low temperature, in the same state, many dynamically recrystallized grains formed in the alloy structure. The grains were small in size with clear boundaries. Some of the subgrains were still in the nucleation stage of recrystallization nuclei. When the strain was 0.8, under deformation temperature 450°C, the dislocation density in the structure reduced significantly. Equiaxial or sub-equiaxial grains more than 0.5 μm in size were observed. Under low temperature, subgrains were fairly completely developed, though the boundaries were still unstable and tended to transform toward the 120° stable state, but the recrystallized grains were fine and sized 0.2∼0.6 μm. The dislocation density in the structure reduced. Yet low-density dislocation walls not having evolved into subgrain boundaries were still observed on the boundaries of a few grains.

Yarn speed and length are two important parameters in the winding process. A noncontact method is proposed to measure the speed and length of the microtension moving yarn automatically in the winding process. A moving yarn could vibrate sharply in the microtension range. With a line laser illuminating the moving yarn, a linear charge-coupled diode camera was used to capture the images. Based on different laser reflection of the yarn texture, we calculated the speed and length of the moving yarn by extracting different features of yarn texture. Yarns with different materials were used to prove the validity of the proposed method under different winding speed. Experiment works have been performed and compared with a direct contact sensor, and the results proved that the proposed method is effective. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)