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One of the most critical equipment used by mining companies is the belt conveyor. Thousands of kilometers of these elements are used for bulk material transportation. A belt conveyor system is composed of several components, and the maintenance process is not trivial and usually reactive. Thousands of dollars are lost per hour with the failure of a...
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... into consideration the enormous quantity of rollers in the mining industry, monitoring their condition be- comes a significant challenge. Figure 2 shows some of critical points to be monitored, including rollers. Rollers suffer from severe wear and demands a higher frequency of inspection. ...
Citations
... In the mining industry, belt conveyor systems are widely used to transport bulk materials [1], [2]. They have proven highly efficient and reliable for long-distance transportation of mining materials with relatively low operating costs. ...
... Frameworks for semi-autonomous inspections using thermal cameras have been suggested by Nascimento et al. [2] and Carvalho et al. [17], while Angelo et al. [48] developed an automated image capture method to identify roller faults. However, temperature-based fault detection can be time-consuming, potentially limiting these systems' practicality in fast-paced industrial settings where quick detection is essential. ...
The shift towards automated inspection methods represents considerable progress in conveyor system maintenance, enhancing safety and efficiency while posing challenges in data analysis and implementation costs. This study critically analyses sensor technologies and inspection methods for detecting faults in conveyor belt idlers, highlighting their essential role in preserving the operational integrity of industrial conveyor systems. By synthesizing various research findings, the study assesses the effectiveness of different sensor devices in identifying defects, including built-in sensors, fixed sensor options like acoustic, ultrasonic sensors, cameras, accelerometers, and Distributed Optical Fibre Sensors (DOFS), as well as mobile sensor systems. Our findings emphasize the accuracy of robot-based systems in identifying bearing defects, the comprehensive coverage provided by drones for medium-scale inspections, the constant monitoring offered by integrated idler sensors, and the ability of fixed sensors to detect mechanical faults despite environmental challenges. This research adds to the ongoing discussion on enhancing conveyor system dependability through technological advancements, providing insights into potential future developments that could further refine maintenance strategies in the sector.
... In many branches of industry, bulk materials are transported over short, medium, and long transport distances using continuously working conveyor systems, so-called belt conveyors [16][17][18]. The conveyor belt, see Figure 1, consists of a conveyor line 1 (assembled from steel assembled parts), which is fitted with conveyor rollers 2 [19] that support the conveyor belt 3 [20]. The endless loop of the conveyor belt circulates between two end drums. ...
... Machines 2023, 11, x FOR PEER REVIEW 3 of 28 (assembled from steel assembled parts), which is fitted with conveyor rollers 2 [19] that support the conveyor belt 3 [20]. The endless loop of the conveyor belt circulates between two end drums. ...
... These then vibrate as a result of the unbalanced mass when the rollers rotate. (assembled from steel assembled parts), which is fitted with conveyor rollers 2 [19] that support the conveyor belt 3 [20]. The endless loop of the conveyor belt circulates between two end drums. ...
This paper presents the basic structural parts, a 3D model, and the overall design of a laboratory machine, which was created to detect vibrations generated by the casing of a conveyor roller rotating at different speeds. The intention of the authors was to verify whether plastic brackets inserted into the structurally modified trestles of a fixed conveyor idler can reduce the vibration values transmitted from the rotating conveyor roller to the trestle of a fixed idler. Experimental vibration measurements taken on the non-rotating parts of conveyor rollers, performed on a laboratory machine according to ISO 10816, are suitable for characterizing their operating conditions with regard to trouble-free operation. The aim of this paper is to detect the vibrations of a rotating conveyor roller on a laboratory machine in the defined places of a fixed conveyor idler and also on the steel frame of a laboratory machine that represents the supporting track of a belt conveyor. Vibrations detected by piezoelectric acceleration sensors were recorded by a measuring apparatus and displayed in the environment of Dewesoft X software (version 10). The measurements show that the vibration values grow with the increasing speed of the conveyor roller rotation. Experimental measurements have proven the correctness of the assumption that the vibrations transmitted to the trestle of a fixed conveyor idler are lower by up to 40% when using plastic brackets into which the axle of the conveyor roller is attached, compared to the solution where the axle of the conveyor roller is inserted into the notches of a steel trestle.
... In many branches of industry, bulk materials are transported over short, medium and long transport distances using continuously working conveyor systems, the so-called belt conveyors [16][17][18]. The conveyor belt, see Figure 1, consists of a conveyor line 1 (assembled from steel assembled parts), which is fitted with conveyor rollers 2 [19] that support the conveyor belt 3 [20]. The endless loop of the conveyor belt circulates between two end drums. ...
The paper presents the basic structural parts, a 3D model and the overall design of a laboratory machine, which was created to detect vibrations generated by the casing of a conveyor roller ro-tating at different speeds. The intention of the authors was to verify whether plastic brackets in-serted into the structurally modified trestles of a fixed conveyor idler can reduce the vibration values transmitted from the rotating conveyor roller to the trestle of a fixed idler. Experimental vibration measurements taken on the non-rotating parts of conveyor rollers, performed on a laboratory machine according to ISO 10816, are suitable for characterizing their operating condi-tions with regard to trouble-free operation. The aim of this paper is to detect the vibrations of a rotating conveyor roller on a laboratory machine in the defined places of a fixed conveyor idler and also on the steel frame of a laboratory machine that represents the supporting track of a belt conveyor. Vibrations detected by piezoelectric acceleration sensors were recorded by a measur-ing apparatus and displayed in the environment of Dewesoft X software. The measurements show that the vibration values grow with the increasing speed of the conveyor roller rotation. Experimental measurements have proven the correctness of the assumption that the vibrations transmitted to the trestle of a fixed conveyor idler are lower by up to 40% when using plastic brackets into which the axle of the conveyor roller is attached, compared to the solution where the axle of the conveyor roller is inserted into the notches of a steel trestle.
... Despite a great deal of research, statistical data indicate that there is a significant percentage of jams of belt conveyor rollers that lead to stops and emergencies. The main cause of the ribbon fire on the linear part of the conveyor is the destruction of the roller bearing, increased energy consumption, roller friction on the belt, heating and damage to the conveyor belt [11]. The main reasons ( Fig. 1) for the failure of the rollers is jamming of the roller bearings resulting from their clogging with dust particles, and small lubrication during operation [12]. ...
... In the mining industry conventional mechanism is very effective, although, several add-ons in terms of technology could benefit the miner safety and optimize the production. For instance, Nascimento [3] has shown the expensive and tedious problem faced by yhr mining industry. Angelo et al. [4] has demonstrated the used of deep learning based object detection algorithms in the inspection of mining industry. ...
... As these systems have several components, a failure of one component can cause belt damage, economic loss, and death [4]. For example, a report from Brazil showed that from 2014 to 2016, fires caused by conveyor idler failures resulted in losses of approximately AUD one million, in addition to 600 h of downtime [5]. Potential faults and abnormalities in such systems must be identified and detected as soon as possible to minimize performance degradation and prevent dangerous situations before a sequence of damage can be catastrophic. ...
Due to increasing demands for ensuring the safety and reliability of a system, fault detection (FD) has received considerable attention in modern industries to monitor their machines. Bulk materials are transported worldwide using belt conveyors as an essential transport system. The majority of conveyor components are monitored continuously to ensure their reliability, but idlers remain a challenge to monitor due to the large number of idlers (rollers) distributed throughout the working environment. These idlers are prone to external noises or disturbances that cause a failure in the underlying system operations. The research community has begun using machine learning (ML) to detect idler’s defects to assist industries in responding to failures on time. Vibration and acoustic measurements are commonly employed to monitor the condition of idlers. However, there has been no comprehensive review of FD for belt conveyor idlers. This paper presents a recent review of acoustic and vibration signal-based fault detection for belt conveyor idlers using ML models. It also discusses major steps in the approaches, such as data collection, signal processing, feature extraction and selection, and ML model construction. Additionally, the paper provides an overview of the main components of belt conveyor systems, sources of defects in idlers, and a brief introduction to ML models. Finally, it highlights critical open challenges and provides future research directions.
... In this section, we firstly focus on the importance of application of robotic-based IRT for the reliability of conveyor systems in mining environments. The length of a conveyor belt in mining sites can reach several kilometers, while hundreds of idlers that support the belt, and the loads need to be monitored by technicians [34,35]. The manual condition monitoring methods are time-consuming and inaccurate due to low frequency of inspections. ...
Mechanical industrial infrastructures in mining sites must be monitored regularly. Conveyor systems are mechanical systems that are commonly used for safe and efficient transportation of bulk goods in mines. Regular inspection of conveyor systems is a challenging task for mining enterprises, as conveyor systems’ lengths can reach tens of kilometers, where several thousand idlers need to be monitored. Considering the harsh environmental conditions that can affect human health, manual inspection of conveyor systems can be extremely difficult. Hence, the authors proposed an automatic robotics-based inspection for condition monitoring of belt conveyor idlers using infrared images, instead of vibrations and acoustic signals that are commonly used for condition monitoring applications. The first step in the whole process is to segment the overheated idlers from the complex background. However, classical image segmentation techniques do not always deliver accurate results in the detection of target in infrared images with complex backgrounds. For improving the quality of captured infrared images, preprocessing stages are introduced. Afterward, an anomaly detection method based on an outlier detection technique is applied to the preprocessed image for the segmentation of hotspots. Due to the presence of different thermal sources in mining sites that can be captured and wrongly identified as overheated idlers, in this research, we address the overheated idler detection process as an image binary classification task. For this reason, a Convolutional Neural Network (CNN) was used for the binary classification of the segmented thermal images. The accuracy of the proposed condition monitoring technique was compared with our previous research. The metrics for the previous methodology reach a precision of 0.4590 and an F1 score of 0.6292. The metrics for the proposed method reach a precision of 0.9740 and an F1 score of 0.9782. The proposed classification method considerably improved our previous results in terms of the true identification of overheated idlers in the presence of complex backgrounds.
... Conveyor structures require permanent inspection and maintenance. Being the most common means used to transport bulk material in the mineral industry [1], and having extensions ranging from a dozen meters to several dozens of kilometers [2]. In recent years the inspection tasks have been subject of many researches aiming to modify this process to use autonomous robots instead of human inspectors [3] [4] [2] and [5]. ...
... Although the scenario described in II doesn't cover all possible conveyor belt structure environments existent, not even all environments in which the robots is expected to be used, it is still a very important scenario due to the large distances covered by this specific subset. Considering that a small conveyor belt of 150 meters has nearly 450 carrying rollers and 50 return rollers [1], it would be very inefficient to individually inspect each bearing from each roller in a kilometer scaled structure. ...
In this paper, a sliding mode control using a periodic search function strategy is used to drive a robot to the origin of a stationary sound source in an industrial inspection scenario. The robotic system is composed of a mobile base equipped with a manipulator arm. A extremum- seeking controller is designed to drive the cartesian position of the manipulator to the maximum of an unknown field that represents the source of the sound emitted by a damaged roller of a belt conveyor idler. Simulation results considering the kinematic model of the robot ROSI are presented with satisfactory results.
... Idlers are located along the conveyor, and the typical length of conveyors in mining tunnels could reach a kilometer [10]. Human inspections of idlers by walking along the belt is time-consuming, costly, and hazardous, as even a small conveyor of 150 m consists of nearly 450 carrying rollers and 50 return rollers that should be inspected individually [11]. ...
Conveying systems play an essential role in the continuous horizontal transportation of raw materials in mining sites. Regular inspections of conveyor system structures and their components, especially idlers, are essential for proper maintenance. Traditional inspection methods are labor-intensive and hazardous; therefore, robot-based thermography can be considered a quality assessment tool for the precise detection and localization of overheated idlers in opencast mining sites. This paper proposes an infrared image processing pipeline for the automatic detection and analysis of overheated idlers. The proposed image processing pipeline can be used for the identification of significant temperature anomalies such as hotspots and hot areas in infrared images. For the identification of such defects in idlers, firstly, the histogram of captured infrared images was analyzed and improved through the pre-processing stages. Afterward, the location of thermal anomalies in infrared images was extracted. Finally, for the validation of segmentation results, the shapes and locations of segmented hot spots were compared with RGB images that were synchronized by captured infrared images. A quantitative evaluation of the proposed method for the condition monitoring of belt conveyor idlers in an open-cast mining site shows the applicability of our approach.
... Moreover, it is time-consuming which then compensates the inspection frequency where the onset of failures with limited warming time can be unpredictable. A conveyor failure case study was reported in [13] of conveyor fire incident in Maritime Terminal of Ponta da Madeira, Brazil. The loss between 2014 and 2016 was estimated to be approximately AUD$1 million with 600 h of operational downtime. ...
Condition monitoring of mining conveyor is a highly essential task to ensure minimum disruption to the mining operational system. Failure of one or more conveyor components can result in significant operational downtime, economic loss, and safety risks. The current monitoring method still involves subjective measure from maintenance engineers, where at some cases, fault can be left undetected and leads into site incident. Therefore, there is a high demand for real-time condition monitoring technology to detect early fault on conveyor. In this study, the effective application of distributed optical fibre sensor (DOFS) was explored for long distance real-time condition monitoring of mining conveyor. The fault detection framework was developed by integrating and modifying the Isolation Forest algorithm to analyse optical signals for effective detection of defective idlers. Further, the optical signal was analysed to extract the damage progression of defective idler with time and space. The results were used to classify various levels of damage and to set appropriate damage thresholds. Also, software interface, that can be used to set the sensing parameters, to collect, analyse, and visualise the signal in real-time, was developed. Finally, the developed condition monitoring system was used to monitor a 1.6 km long section of a conveyor structure in Western Australia for a period of 10 months. The results and findings from the field monitoring were presented together with automated fault detection framework for condition monitoring of mining conveyor.
