Smart Inspection Research Articles

Fault Diagnosis of Power Transmission Lines Using a UAV-Mounted Smart Inspection System

Fault diagnosis of power transmission systems (PTSs) is crucial for ensuring the reliability of power grids because most grids are exposed to harsh environments. For integrity diagnosis of PTSs, this article proposes a nondestructive patrol inspection method that employs a smart inspection system (SIS) mounted on an unmanned aerial vehicle (UAV). This system overcomes the geographical limitations faced in accessing PTSs. The SIS includes an ultraviolet camera system that can detect partial discharges on the damaged surfaces of PTSs. The SIS is characterized by three main features. First, it employs an automatic line-tracking method based on image-processing methods. Second, defect locations are automatically estimated on the basis of the consistency of partial discharges, where consistency indicates the steadiness of corona discharges in one-dimensional global coordinates. Third, an alarm is triggered on the basis of the combination of the result from a statistical outlier detection method and the estimated partial discharge locations on a two-dimensional partial discharge map. Finally, a UAV equipped with the proposed system is field-tested for PTS inspection in the autopilot mode. Field tests conducted on ultrahigh-voltage PTSs confirmed the damage detection capabilities of the proposed method and demonstrated its effectiveness and convenience.

A Machine Learning Approach for Collaborative Robot Smart Manufacturing Inspection for Quality Control Systems

The 4th industrial revolution promotes the automatic inspection of all products towards a zero-defect and high-quality manufacturing. In this context, collaborative robotics, where humans and machines share the same space, comprises a suitable approach that allows combining the accuracy of a robot and the ability and flexibility of a human. This paper describes an innovative approach that uses a collaborative robot to support the smart inspection and corrective actions for quality control systems in the manufacturing process, complemented by an intelligent system that learns and adapts its behavior according to the inspected parts. This intelligent system that implements the reinforcement learning algorithm makes the approach more robust once it can learn and be adapted to the trajectory. In the preliminary experiments, it was used a UR3 robot equipped with a Force-Torque sensor that was trained to perform a path regarding a product quality inspection task.

A Framework for Post-Earthquake Response Planning in Emerging Seismic Regions: An Oklahoma Case Study

This paper presents a framework for establishing post-earthquake response protocols in regions facing emerging seismic hazards through a case study of Oklahoma bridges. First, it establishes the need for new attenuation models for the Oklahoma area because of the poor fit of current attenuation models. Then, two methods are established to inspect bridges after an earthquake: smart inspection radii and ShakeCast. The smart radii use a modified version of the Campbell (2003) attenuation model to determine seismic demand and a trigger S1 value to represent bridge capacity. This trigger S1 value is validated by calculating slight HAZUS fragility curves for past earthquakes. ShakeCast is an online resource from USGS that uses real-time ground motion data (i.e., a ShakeMap) as seismic demand and modified HAZUS fragility curves to represent bridge capacity. Because of better-informed data on the ground shaking levels, ShakeCast recommends significantly fewer inspections than inspection radii, translating to cost savings for the Oklahoma Department of Transportation.

Research on the Operation and Inspection System of UHV and Cross-Regional Distribution Network Based on Big Data Technology

With the development of UHV and cross-regional distribution network, the operation and inspection of electric transmission and transformation equipment need to use big data and other new technologies to build a smart grid operation and inspection system, in order to better support the operation and inspection business. This paper analyzes the new development situation of UHV and trans-area power grid and the demand of smart grid operation and inspection service under the new situation. Combining big data analysis technology with production command and management practice, based on data and business requirements, this paper puts forward the data architecture of intelligent operation and inspection system according to big data technology, gives the technical framework and technology selection of intelligent operation and inspection system, then analyzes the application framework of intelligent operation and inspection service. The whole architecture of intelligent operation and inspection system is proposed, which provides better support for the development and application of intelligent operation and inspection system through the key architecture design. It has far-reaching application value and broad application prospect.

Development of a 3D Pipe Robot for Smart Sensing and Inspection Using 3D Printing Technology

This 3D pipe inspection robot is capable of conducting fully autonomous pipe inspection, transmitting measured data to the monitoring end by wireless communication, drawing a 3D pipe routing map in real time, and detecting pipe anomalies. The robot is both lightweight and inexpensive because it is constructed by 3D printing. The main functions of the robot include calculating the robot posture using the measurements from the accelerometer and gyroscope module, drawing a 3D pipe routing map in real time, deciding the degree of contraction from pressure sensor module readings to detect abnormal expansion or contraction, and locating potential hazards in the pipe. The robot described in this paper is different from others in many ways. The freely extendable and contractible body structure allows the robot to easily adapt to pipes of various diameters. The wireless IP camera onboard transmits real-time videos and assists operators in looking for signs of damage or anomalies. This robot is practical and can be used for the inspection of damaged pipes, redrawing 3D pipe routing maps, and assisting in the regular maintenance of pipes underground or located within buildings, and may also be of use in rescue work and disasters, etc.

Automatic Inspection System of Small Plastic Gears Based on Machine Vision

Small plastic gear is generally made by injection molding.But the injection molding process and mold have problems with missing tooth, shrink, more material, less material and inaccurate roundness and so on. Furthermore, using manual inspection will appear phenomenon of low efficiency, false detection and leak detection. To solve these problems, this paper introduces an automatic inspection system of small plastic gears based on machine vision. The system consists of feeding and sorting machine control system and machine vision inspection system of the gear defects. Mechanical control use digital servo control technology to achieve automatic nesting, feeding, positioning of gear workpiece, and depend on the inspection result of machine vision system to sort. After acquired gear image through a camera, Machine vision system uses median filtering, binarization, edge detection algorithms to process image. Then the system adopts template matching algorithm to obtain the inspection result and send the result to the sorting controller, which achieve automatic smart inspection of gear. The automatic inspection system has accurate, efficient, intelligent and other advantages.

Application of smart system to textile industry: Preliminary design of a smart hanger for garment inspection

A smart inspection system, comprising three components, namely a smart hanger, a stitching-workmanship defect classification unit as well as a shade variation detection unit, is introduced for the textile industry. The preliminary design and optimization results of the smart hanger which stretches garments to provide enough tension to facilitate the inspection are presented. The hanger, with a Proportional and Derivative (PD) controller, is modeled as a four-link robot consisting of three revolute joints and one prismatic joint. The design objectives include (1) maximizing the link portions within “effective regions” at the final state, (2) minimizing the force or torque required to finish the stretching process, and (3) minimizing the settling time of the stretching process. In addition to control gains, the lengths of the four links as well as the desired movements of the joints are taken as design variables. The required transient behavior of the hanger is defined by the constraints on settling time and maximum overshoot. In order to prevent the clothes from being damaged by the links during the stretching process, geometrical constraints are imposed on the motions of the links. Optimization results, obtained by using the multi-objective genetic algorithm (MOGA), are presented in the form of Pareto solutions. After analysis, optimal parameters are selected and computer simulations are performed to investigate the transient behavior of the hanger. Satisfactory results are obtained, which provide a good foundation for the on going development of the smart inspection system.