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Phase-measuring deflectometry (PMD) is a key measurement technology for specular surfaces form measurement. Compared with the phase measuring deflectometry techniques based on the conventional configuration, the near optical coaxial phase measuring deflectometry (NCPMD) can achieve compact configuration, light weight and insignificant measurement error caused by structure shadows by utilizing a plate beamsplitter. However, the introduction of the plate beamsplitter will make some influence of the measurement accuracy of the NCPMD system. In the one hand, the introduction of the plate beamsplitter can reduce the measurement accuracy of the NCPMD system due to the refractive of the ray between the two surfaces of the beamsplitter. In the other hand, due to the processing and manufacturing problems of the beamsplitter, there are inevitably certain unevenness errors on the upper and lower surfaces. In this paper, a virtual simulation system of NCPMD is established, and an error model of the NCPMD system by considering both the refraction influence and reflection influence of the plate beamsplitter is presented to analyse the shape reconstruction error caused by the plate beamsplitter.

The miniature sensor devices and power-efficient Body Area Networks (BANs) for Human Activity Recognition (HAR) have gained increasing interest in different fields, including Daily Life Assistants (DLAs), medical treatment, sports analysis, etc. The HAR systems normally collect data with wearable sensors and implement the computational tasks with a host machine, where real-time transmission and processing of sensor data raise a challenge for both the network and the host machine. This investigation focuses on the hardware/software co-design for optimized sensing and computing of wearable HAR sensor networks. The contributions include (1) design of a miniature wearable sensor node integrating a Micro-Electro-Mechanical System Inertial Measurement Unit (MEMS IMU) with a Bluetooth Low Energy (BLE) in-built Micro-Control Unit (MCU) for unobtrusive wearable sensing; (2) task-centric optimization of the computation by shifting data pre-processing and feature extraction to sensor nodes for in-situ computing, which reduces data transmission and relieves the load of the host machine; (3) optimization and evaluation of classification algorithms Particle Swarm Optimization-based Support Vector Machine (PSO-SVM) and Cross Validation-based K-Nearest Neighbors (CV-KNN) for HAR with the presented techniques. Finally, experimental studies were conducted with two sensor nodes worn on the wrist and elbow to verify the effectiveness of the recognition of 10 virtual handwriting activities, where 10 recruited participants each repeated an activity 5 times. The results demonstrate that the proposed system can implement HAR tasks effectively with an accuracy of 99.20 %.

Rotor imbalance is considered to be one of the main mechanical faults of rotating machinery; which may result in bearing damage and even catastrophic system failure. Recent progress in the Internet of Things (IoT) has promoted the application of novel sensing and computing techniques in the industry, and it is promising to employ novel IoT techniques for imbalance detection to avoid potential failures. Existing sensing techniques suffer from the impact of bearing structure dynamics, loss of accuracy during their lifetime, and security risks introduced by the sensor cabling and supports, which may, in turn, interfere with the machine operations due to inappropriate design and installation. This investigation provides an on-shaft machine wearable vibration sensing technique for effectively monitoring the running state of rotors while minimizing the interference with their operations. In this work, key investigations include the following: (1) theoretical modeling and an analysis of rotor imbalance, and its measurement with an on-shaft micro-electromechanical system (MEMS) accelerometer; (2) the development of a wirelessly powered, cordless on-shaft vibration measurement (OSVM) sensor for unobtrusive sensing of the vibration of rotating shafts; (3) the in-sensor computing design for optimizing the distribution of computing resources and decreasing data transmission. The tests and evaluation of the proposed techniques were conducted with a rotor test rig to demonstrate their feasibility. The presented investigation is a typical example of applying new sensing and computing paradigms to improve the flexibility and convenience of applications, which is a good reference for related investigations and practices. [ABSTRACT FROM AUTHOR]

Aiming at the shortcomings of single-sensor sensing information characterization ability, which is easily interfered with by external environmental factors, a method of intelligent perception is proposed in this paper. This method integrates multi-source and multi-level information, including spindle temperature field, spindle thermal deformation, operating parameters, and motor current. Firstly, the internal and external thermal-error-related signals of the spindle system are collected by sensors, and the feature parameters are extracted; then, the radial basis function (RBF) neural network is utilized to realize the preliminary integration of the feature parameters because of the advantages of the RBF neural network, which offers strong multi-dimensional solid nonlinear mapping ability and generalization ability. Thermal-error decision values are then generated by a weighted fusion of different pieces of evidence by considering uncertain information from multiple sources. The spindle thermal-error sensing experiment was based on the spindle system of the VMC850 (Yunnan Machine Tool Group Co., LTD, Yunnan, China) vertical machining center of the Yunnan Machine Tool Factory. Experiments were designed for thermal-error sensing of the spindle under constant speed (2000 r/min and 4000 r/min), standard variable speed, and stepped variable speed conditions. The experiment's results show that the prediction accuracy of the intelligent-sensing model with multi-source information fusion can reach 98.1%, 99.3%, 98.6%, and 98.8% under the above working conditions, respectively. The intelligent-perception model proposed in this paper has higher accuracy and lower residual error than the traditional BP neural network perception and wavelet neural network models. The research in this paper provides a theoretical basis for the operation, maintenance management, and performance optimization of machine tool spindle systems. [ABSTRACT FROM AUTHOR]

With the rapid development of aerospace, high-speed train, and automotive industries, the demand for the measurement of high-precision specular components is increasing. The acquisition of high-precision three-dimensional (3D) data is conducive to improving the performance of and extending the service life of these components. However, the existing 3D measurement methods of specular surfaces are affected by the inherent limitation of the depth of field (DOF) of camera lenses. Based on the principle of paraxial reflection imaging of a concave mirror, this paper introduces a concave mirror into a phase measuring deflectometry (PMD) system and proposes an aided imaging PMD (AIPMD) based on a concave focusing mirror. The proposed system realizes the clear imaging of the encoded patterns and the surface under test in the DOF of the camera lens, simultaneously. Meanwhile, the iterative coefficient specular reconstruction algorithm is studied based on this system. The feasibility and accuracy of the proposed method are verified by simulations and experiments. [ABSTRACT FROM AUTHOR]

The camera and projector are indispensable hardware parts of a color fringe projection 3D measurement system. Chromatic aberration between different color channels of the projector and camera has an impact on the measurement accuracy of the color fringe projection 3D profile measurement. There are many studies on camera calibration, but the chromatic aberration of the projector remains a question deserving of further investigation. In view of the complex system architecture and theoretical derivation of the traditional projector radial chromatic aberration method, a phase target based on projector radial chromatic aberration measurement and the correction method are proposed in this paper. This method uses a liquid crystal display with a holographic projection film as the phase target. The liquid crystal display sequentially displays red, green, and blue horizontal and vertical sinusoidal fringe images. The projector projects red, green, and blue horizontal and vertical sinusoidal fringe images to the phase target in turn, and calculates the absolute phases of the display fringes and reflection fringes, respectively. Taking the green channel as the reference channel, a phase coordinate system is established based on the phases of the vertical and horizontal directions displayed on the display screen, using the phase of the reflection fringes on the display screen as the ideal phase value of the phase point. Then, the phase coordinate system of the red and blue channels is transferred to the green phase coordinate system to calculate the chromatic aberration of the red-green channels and the blue-green channels, and pre-compensation is conducted. Experimental results prove that this method can measure and calibrate the radial chromatic aberration of the projector without being affected by the image quality of the camera. The correction effect of this method is that the maximum chromatic aberration of the red-green channel decreases from 1.9591/pixel to 0.5759/pixel, and the average chromatic aberration decreases from 0.2555/pixel to 0.1865/pixel. In addition, blue-green channel maximum chromatic aberration decreased from 1.8906/pixel to 0.5938/pixel, and the average chromatic aberration decreased from 0.2347/pixel to 0.1907/pixel. This method can improve the projection quality for fringe projection 3D profile measurement technology. [ABSTRACT FROM AUTHOR]

We propose a method for accurately calibrating a telecentric structured light system consisting of a camera attached to a bilateral telecentric lens and a pin-hole projector. The proposed method can be split into two parts: axial calibration and transverse calibration. The first part is used for building the relationship between phase and depth by means of a planar plate with ring markers on its surface at several different positions in the measuring volume. The second part is used for establishing the relationship between transverse coordinates and pixel positions with the depth offered by a translation stage and the extracted ring centers. Compared with existing methods that require projector calibration, the proposed method can avoid a propagation of the correspondence error between the camera imaging plane and projector imaging plane, thus increasing calibration accuracy. The calibrated telecentric structured light system is further used for three-dimensional (3D) reconstructions of a planar, a ruled surface, and complex surfaces. Experimental results demonstrate that the proposed system calibration method can be used for accurate 3D measurement. [ABSTRACT FROM AUTHOR]

The itemized product identification, sensing and data integration are critical building blocks for the efficiency, flexibility, and potential intelligence of the Industrial Internet of Things (IIoT). The product sensing and data integration solutions usually suffer from the sophisticated sensor devices and their inflexible integration with the industrial processes, which may restrict the performance of industrial systems. To maintain an information link for convenient product data integration, this investigation presents a surface mountable dual-mode Radio Frequency Identification (RFID) sensor as a wirelessly powered information interface for simultaneous product identification, sensing, and data integration. The focus of this investigation includes: (1) the theory and hardware/software scheme for sensor-augmented RFID integrating Ultra-High Frequency (UHF) and High Frequency (HF) with Commercial-off-the-Shelf (COTS) devices; (2) integration of the UHF and HF energy and data interfaces to support both UHF and HF powering and sensing; (3) a data integration method supporting sensor data transmission using common UHF and HF readers without extra hardware or software cost; (4) proposal of a model for industrial integration with the proposed dual-mode RFID sensor. The experimental studies and exemplar application demonstrate the feasibility of the presented techniques for industrial integration. [ABSTRACT FROM AUTHOR]