Digital twins-based smart manufacturing system design in Industry 4.0: A review

This article proposes a novel three-stage condition assessment scheme of rotating machinery using internal encoder data rather than traditional external vibration data. In this article, periodical group sparse derivatives (PGSD)-based signal denoising method is proposed to suppress the background noise, which incorporates the periodical group sparse derivative property of encoder signal and can be considered as an optimization problem. Moreover, the convexity condition of optimization problem is thoroughly investigated and an effective iterative algorithm is derived. After the PGSD-based signal denoising method, difference method (DM), and autoregressive (AR) filter are employed to convert the denoised encoder signal into intelligible speed information and remove the operation-related harmonic components. With the proposed method PGSD-DMAR, the periodical transient features are effectively extracted and the health condition of rotating machinery is successfully identified. The effectiveness and superiority of the PGSD-DMAR are verified via simulated signal and experimental data.

Sparsity-Based Algorithm for Condition Assessment of Rotating Machinery Using Internal Encoder Data

Digital twin applications in aviation industry: A review

Prediction of plant transpiration from environmental parameters and relative leaf area index using the random forest regression algorithm

Digital twin (DT), primarily a virtual replica of any conceivable physical entity, is a highly transformative technology with profound implications. Whether it be product development, design optimisation, performance improvement, or predictive maintenance, digital twins are changing the ways work is undertaken in various industries with multifarious business applications. Aerospace industry, including its manufacturing base, is one such keen adopter of digital twins with an unprecedented interest in their bespoke design, development, and implementation across wider operations and critical functions. This, however, comes with some misconceptions about the digital twin technology and lack of understanding with respect to its optimal implementation. For instance, equating a digital twin to an intelligent model while ignoring the essential components of data acquisition and visualisation, misleads the creators into building digital shadow or digital models, instead of the actual digital twin. This paper unfolds such intricacies of digital twin technology for the aerospace community in particular and others in general so as to remove the fallacies that affect their effective realisation for safety-critical systems. It comprises a comprehensive survey of digital twins and their constituent elements. Elaborating their characteristic state-of-the-art composition along with corresponding limitations, three dimensions of the future digital twins for the aerospace sector, termed as aero-Digital Twins (aero-DTs), are proposed as an outcome of this survey. These include the interactive, standardisation, and cognitive dimensions of digital twins, which if leveraged diligently could help the aero-DT research and development community quadruple the efficiency of existing and future aerospace systems as well as their associated processes. 

Digital Twin in Aerospace Industry: A Gentle Introduction

Contouring error detection for machine tools can be used to effectively evaluate their dynamic performances. For the state-of-the-art non-vision measurement devices, they have limitations on arbitrary and high cross-scale contouring error measurement (e.g., ball-bar and cross-grid encoder). Besides, error motions of irrelevant axes are inevitably introduced in the measurement process (e.g., ball-bar, R-test). The vision-based method provides a promising way to address the problems. In this paper, to further the study, a cost-effective monocular-vision-based two-dimensional arbitrary contouring error detection method is proposed. Compared to the existing vision-based method, the main progress is to use the idea of error distribution to simultaneously extend the measurable working range and traverse speed. The basic idea of the proposed method is to improve the measurable traverse speed by sacrificing field of view (FOV), and to deduce the wide range contouring error using priori information. Both experiments for the detection and compensation of contouring error are performed in a CNC machine tool. The contouring error detection results, in contrast to the cross-grid encoder, show that the average detecting error at feed rate of 5000 mm/min is about 4 μm, which verifies measurement accuracy and feasibility of the proposed method. Besides, the compensation results show that the maximum and average contouring error measured after compensation at 5000 mm/min decrease by 66.39% and 56.47%, respectively, which validate the potential of the proposed method in effectively improving machine tool's dynamic performance.

Monocular-vision-based contouring error detection and compensation for CNC machine tools

An active damping vibration control system for wind tunnel models

Full-field displacement perception and digital twins for core components play a crucial role in the precision manufacturing industry, such as aviation manufacturing. This paper presents a real-time full-field displacement perception method for the combination of online multipoint displacement monitoring and matrix completion theory. Firstly, a conceptual full-field displacement perception model based on the observed information of the multi-points is established. To obtain the full-field displacements of a core component, the component is divided into plentiful discrete points, including observed and unobserved points, based on which the relationship between the observed points and the full-field displacements is established. Then, the solution method of the full-field displacement perception model is proposed. Based on the matrix completion principle and the big data of the simulation, the optimization problem is employed to work out the model and, meanwhile, the pseudo-code is put forward. Finally, the full-field displacement perception experiments are performed. Repeated experiments show that the max error of the displacements calculated by the proposed method can be less than 0.094 mm and the median error can be less than 0.054 mm, while the average time frame can be less than 0.48 s, which is promising considering the high precision and efficiency requirements of the assembly of large aircraft.

A Displacement Field Perception Method for Component Digital Twin in Aircraft Assembly.

High precision position control is essential in the process of parts manufacturing and assembling, where eddy current displacement sensors (ECDSs) are widely used owing to the advantages of non-contact sensing, compact volume, and resistance to harsh conditions To solve the nonlinear characteristics of the sensors, a high-accuracy calibration method based on linearity adjustment is proposed for ECDSs in this paper, which markedly improves the calibration accuracy and then the measurement accuracy After matching the displacement value and the output voltage of the sensors, firstly, the sensitivity is adjusted according to the specified output range Then, the weighted support vector adjustment models with the optimal weight of the zero-scale, mid-scale and full-scale are established respectively to cyclically adjust the linearity of the output characteristic curve Finally, the final linearity adjustment model is obtained, and both the calibration accuracy and precision are verified by the established calibration system Experimental results show that the linearity of the output characteristic curve of ECDS adjusted by the calibration method reaches over 999%, increasing by 19–50% more than the one of the original In addition, the measurement accuracy improves from 11–25 μ m to 1–10 μ m in the range of 6mm, which provides a reliable guarantee for high accuracy displacement measurement

High-Accuracy Calibration Based on Linearity Adjustment for Eddy Current Displacement Sensor.

The invention relates to a random vibration simulation method of a vibration simulation system, belongs to the vibration simulation field, and relates to the random vibration simulation method of thevibration simulation system; the method uses the vibration simulation system to make random vibrations, and comprises the following steps: using a computer to form high frequency white noises, multiplying the high frequency white noises with a sine signal so as to obtain a pseudo-random signal, and using same as a target control signal; real time acquiring a pitching direction and yawing directionacceleration signal, using a signal amplifier to amplify the signal, and sending the signal to a pitching direction and yawing direction vibration generator, thus enabling the generator to form vibrations in the strut pitching and yawing directions. The vibration simulation system comprises a pitching direction and yawing direction acceleration sensor, the pitching direction and yawing directionvibration generator, an aircraft model, a force measuring balance, a strut, the computer, the signal amplifier, and a real time controller. The method can realize negative feedback control the vibration signals, thus improving the algorithm validity in a wind tunnel test and the wind tunnel test safety, and improving the vibration simulation precision.

Zhou Mengde

Papers

Monocular-vision-based contouring error detection and compensation for CNC machine tools

An active damping vibration control system for wind tunnel models

A Displacement Field Perception Method for Component Digital Twin in Aircraft Assembly.

High-Accuracy Calibration Based on Linearity Adjustment for Eddy Current Displacement Sensor.

Random vibration simulation method of vibration simulation system