For online quality control of car engine production, pneumatic measurement instrument plays an unshakeable role in measuring diameters inside engine block because of its portability and high-accuracy. To the limitation of its measuring principle, however, the working space between the pneumatic device and measured surface is too small to require manual operation. This lowers the measuring efficiency and becomes an obstacle to perform automatic measurement. In this article, a high-speed, automatic measuring system is proposed to take the place of pneumatic devices by using a laser-based measuring unit. The measuring unit is considered as a set of several measuring modules, where each of them acts like a single bore gauge and is made of four laser triangulation sensors (LTSs), which are installed on different positions and in opposite directions. The spatial relationship among these LTSs was calibrated before measurements. Sampling points from measured shaft holes can be collected by the measuring unit. A unified mathematical model was established for both calibration and measurement. Based on the established model, the relative pose between the measuring unit and measured workpiece does not impact the measuring accuracy. This frees the measuring unit from accurate positioning or adjustment, and makes it possible to realize fast and automatic measurement. The proposed system and method were finally validated by experiments.

The laser triangulation method is one of the most advanced methods for large inner diameter measurement. Our research group proposed a kind of inner diameter measuring device that is principally composed of three laser displacement sensors known to be fixed in the same plane measurement position. It is necessary to calibrate the direction of the laser beams that are emitted by laser displacement sensors because they do not meet the theoretical model accurately. For the purpose of calibrating the direction of laser beams, a calibration method and mathematical model were proposed. The inner diameter measuring device is equipped with the spindle of the machine tool. The laser beams rotate and translate in the plane and constitute the rotary rays which are driven to scan the inner surface of the ring gauge. The direction calibration of the laser beams can be completed by the sensors’ distance information and corresponding data processing method. The corresponding error sources are analyzed and the validity of the method is verified. After the calibration, the measurement error of the inner diameter measuring device reduced from $\pm 25\mathsf{\mu }\mathrm{m}$ to $\pm 15\mathsf{\mu }\mathrm{m}$ and the relative error was not more than 0.011%.

The connecting rod is a critical part inside the marine engine. The inspection of its important parameters is directly related to the assembly and quality of the marine engine. A coordinate measuring machine (CMM) is a conventional choice to measure the parameters of a connecting rod. However, CMM requires significant resources in time and cost, which leads researchers into in-situ measurement. This article presents a fast and in-situ measuring method by using a laser-based measuring head. Two measuring strategies are adopted in the inspection process. For positional measurements (such as the hole–center distance), whose accuracy requirement is generally low, the coordinate system of the numerical control (NC) machine is combined with the measuring head to acquire the positional parameters. For dimensional measurements (such as inner diameters), whose accuracy requirement is rather high, the NC machine is used just as transportation. Note that the measuring head has the ability to perform the dimension inspection independently. The accuracy of the measuring head is high enough to meet the dimensional accuracy requirements. Experiments are performed to validate the proposed method. The measuring error of the inner diameters is from 5 μm to 7 μm. The measuring error of hole–center distance is within 15 μm. The measurement of all these parameters can be done within 1 min.

Cylindricity is a crucial factor to estimate the manufacturing quality of large rotary parts. However, existing measurement systems can hardly deal with the precise cylindricity measurement challenges posed by large dimensions and great weights. In this article, a novel measurement system along with an improved error separation model and efficient solution algorithm for large rotary parts is proposed. Concretely, the innovative research includes three parts. First, a precise cylindricity measurement system with large variable ranges is proposed. Different from traditional workpiece rotation means, a sensor rotation system for data acquisition is designed to be independent of the air-bearing platform for workpiece centering. This contributes to stable and precise measurement under high-load and field conditions. Second, a more sophisticated and accurate measurement model is established, and the model-based error separation method is presented, which enables more accurate separation of error sources, such as eccentricity, measuring line offset, and workpiece axis tilt. Finally, a differential evolution growth algorithm (DEG), which is able to balance global search ability and local information utilization, is put forward to improve the efficiency and accuracy of model fitting in the error separation process. The proposed measurement system, model, and algorithm are all verified by simulations and experiments.

Unsupervised real-time stereo matching is of great research value in robot navigation due to its independence from ground truth and real-time efficiency. The core challenge lies in the design of loss functions that can provide accurate guidance and the efficient network architectures. The commonly used photometric loss is prone to provide incorrect guidance because of the influence of reflection, left-right color inconsistency, low texture, and occlusion. As a weak supplement, the smoothness loss can ameliorate the multi-solution problems caused by low texture, but it is not effective for strong incorrect guidance caused by the other problems. In order to provide more accurate and powerful supplementary guidance, a 3D planar segmentation loss is proposed with advancements in addressing the strong incorrect guidance problem, which could be generally integrated into traditional unsupervised training losses. Furthermore, the real-time stereo matching approach of the hierarchical iterative tile refinement network is applied to unsupervised stereo matching, with necessary modifications to address the detrimental architectures that hinder its performance in unsupervised training. Experimental results verify the effectiveness of the 3D planar segmentation loss and the network modification. The proposed pipeline achieves competitive accuracy compared to existing unsupervised stereo matching methods while maintaining real-time efficiency.