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The purpose of this paper is to propose cuckoo optimization algorithm (COA)-based back propagation neural network (BPNN) to reduce the effect of the nonlinearities presented in laser triangulation displacement sensors. The 3D positioning and posture sensor allows access to the third dimension through depth measurement; the performance of the sensor varies according to the level of nonlinearities presented in the system, which leads to inaccuracies in measurement.

While applying optimization approach, the mathematical model and the relationship between the key parameters in the laser triangulation ranging and the indexes of the measuring system were analyzed.

Based on the performance of the parametric optimization method, the measurement repeatability reached 0.5 µm with an STD value within 0.17 µm, an expanded uncertainty of measurement was within 5 µm, the angle error variation of the object’s rotational plane was within 0.031 degrees and nonlinearity was recorded within 0.006 per cent in a full scale. The proposed approach reduced the effect of the nonlinearity presented in the sensor. Thus, the accuracy and speed of the sensor were greatly increased. The specifications of the optimized sensor meet the requirements for high-accuracy devices and allow wide range of industrial application.

In this paper, COA-based BPNN is proposed for laser triangulation displacement sensor optimization, on the basis of the mathematical model, clarifying the working space and working angle on the measurement system.

A laser‐based system has been developed to automatically measure complete inner profiles of various structures. The system uses a pointed laser source passing through a rotating optical device to obtain a series of distance measurements. To enhance the portability of the system, a hand‐held computer is selected to control the laser source and the rotating optical device. In addition to system control, the software associated with the handheld computer has also been developed to use the series distance measurements to construct a complete profile of the measured structure as well as to estimate the crosssectional area of the profile. The system can provide critical information for the construction industry and a variety of other commercial applications. The evaluation and analysis of measurement indicated that on accuracy within 4 per cent, for typical window designs and floor patterns, could be achieved. Recommendations for improvement of the system have also been included.

The printing process is the most critical step in surface mount assembly. To control and monitor printing, complex instrumentation is available for measuring the print consistency. This paper describes a novel robust method, which introduces critical variables defining print quality. Conventional measurement methods include only the volume and average height of solder paste. The limitations of using just these parameters are discussed and a new method is introduced. In our novel approach, the matrix is levelled first to take account of any tilt in the plane of the substrate surface. Then pseudo‐virtual object parameters are calculated. Major attributes of the proposed measurement method is its insensitivity to both the specific location of the printed deposit and the location of a specific defect. This algorithm, coupled with variables defined in the analysis package, delivers a new and flexible approach to the printed media.

Looks at the use of non‐contact displacement and vibration sensors and notes their value for difficult sensing measurements. Mentions various situations which may dictate the use of a non‐contact sensor. Focuses on fibre‐optic sensors and laser triangulation sensors. Concludes that practical uses for such devices are rapidly expanding.

In the context of fixed-wing aircraft wing assembly, there is a need for a rapid and precise measurement technique to determine the center distance between two double-hole components. This paper aims to propose an optical-based spatial point distance measurement technique using the spatial triangulation method. The purpose of this paper is to design a specialized measurement system, specifically a spherically mounted retroreflector nest (SMR nest), equipped with two laser displacement sensors and a rotary encoder as the core to achieve accurate distance measurements between the double holes.

To develop an efficient and accurate measurement system, the paper uses a combination of laser displacement sensors and a rotary encoder within the SMR nest. The system is designed, implemented and tested to meet the requirements of precise distance measurement. Software and hardware components have been developed and integrated for validation.

The optical-based distance measurement system achieves high precision at 0.04 mm and repeatability at 0.02 mm within a range of 412.084 mm to 1,590.591 mm. These results validate its suitability for efficient assembly processes, eliminating repetitive errors in aircraft wing assembly.

This paper proposes an optical-based spatial point distance measurement technique, as well as a unique design of a SMR nest and the introduction of two novel calibration techniques, all of which are validated by the developed software and hardware platform.

This paper aims to use 3D laser sensors to collect high‐density data that are required for defect detection and localization at high‐production rates in manufacturing facilities.

The high‐speed sensors use Ethernet communications to transport large amounts of data and resolve any synchronization issues.

Modern laser sensor technology provides the ability to detect and quantify defects in high‐volume manufacturing, wherever defects are located. Laser line sensors provide high speed, high‐density data for full surface inspection. Synchronization and communications issues are simplified by the FireSync™ platform, making system integration straightforward, and maximizing reliability.

This paper provides detailed 3D data at high speed and uses multiple (binocular) scanners to overcome problems of occlusion.

The purpose of this study is solving the hand–eye calibration issue for line structured light vision sensor. Only after hand–eye calibration the sensor measurement data can be applied to robot system.

In this paper, the hand–eye calibration methods are studied, respectively, for eye-in-hand and eye-to-hand. Firstly, the coordinates of the target point in robot system are obtained by tool centre point (TCP), then the robot is controlled to make the sensor measure the target point in multiple poses and the measurement data and pose data are obtained; finally, the sum of squared calibration errors is minimized by the least square method. Furthermore, the missing vector in the process of solving the transformation matrix is obtained by vector operation, and the complete matrix is obtained.

On this basis, the sensor measurement data can be easily and accurately converted to the robot coordinate system by matrix operation.

This method has no special requirement for robot pose control, and its calibration process is fast and efficient, with high precision and has practical popularized value.