Thermal imaging study to determine the operational condition of a conveyor belt drive system structure

energies Article Thermal Imaging Study to Determine the Operational Condition of a Conveyor Belt Drive System Structure Dawid Szurgacz 1,2,* , Sergey Zhironkin 3,4,5 , Stefan Vöth 6, JiˇríPokorný7, A.J.S. (Sam) Spearing 8, Michal Cehlár9, Marta Stempniak 10 and Leszek Sobik 11   Citation: Szurgacz, D.; Zhironkin, S.; Vöth, S.; Pokorný, J.; Spearing, A.J.S.; Cehlár, M.; Stempniak, M.; Sobik, L. Thermal Imaging Study to Determine the Operational Condition of a Conveyor Belt Drive System Structure. Energies 2021,14, 3258. https://doi.org/10.3390/en14113258 Academic Editor: Nikolaos Koukouzas Received: 13 April 2021 Accepted: 26 May 2021 Published: 2 June 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Center of Hydraulics DOH Ltd., 41-906 Bytom, Poland 2Polska Grupa Górnicza S.A., ul. Powsta´nców 30, 40-039 Katowice, Poland 3Department of Trade and Marketing, Siberian Federal University, 79 Svobodny Av., 660041 Krasnoyarsk, Russia; [email protected]u 4Department of Open Pit Mining, T.F. Gorbachev Kuzbass State Technical University, 28 Vesennya St., 650000 Kemerovo, Russia 5School of Core Engineering Education, National Research Tomsk Polytechnic University, 30 Lenina St., 634050 Tomsk, Russia 6Technische Hochschule Georg Agricola (THGA), Westhoffstraβe 15, 44791 Bochum, Germany; [email protected] 7Faculty of Safety Engineering, VSB–Technical University of Ostrava, Lumírova 13/630, 700 30 Ostrava-Výškovice, Czech Republic; [email protected] 8School of Mines, China University of Mining and Technology, 1 Daxue Road, Tongshan District, Xuzhou 221116, China; [email protected] 9Institute of Earth Sources, Faculty of Mining, Ecology, Process Technologies and Geotechnology, Technical University of Košice, Letná9, 042 00 Košice, Slovakia; [email protected] 10 Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15, 50-421 Wroclaw, Poland; [email protected] 11 KWK ROW Ruch Chwałowice, ul., 44-206 Rybnik, Poland; [email protected] *Correspondence: dawidszur[email protected] Abstract: The paper discusses the results of a study carried out to determine the thermal condition of a conveyor power unit using a thermal imaging camera. The tests covered conveyors in the main haulage system carrying coal from a longwall. The measurements were taken with a thermal imaging diagnostic method which measures infrared radiation emitted by an object. This technology provides a means of assessing the imminence and severity of a possible failure or damage. The method is a non-contact measuring technique and offers great advantages in an underground mine. The thermograms were analysed by comparing the temperature distribution. An analysis of the operating time of the conveyors was also carried out and the causes of the thermal condition were determined. The main purpose of the research was to detect changes in thermal state during the operation of a belt conveyor that could indicate failure and permit early maintenance and eliminate the chance of a fire. The article also discusses the construction and principle of operation of a thermal imaging camera. The findings obtained from the research analysis on determining the thermal condition of the conveyor drive unit are a valuable source of information for the mine’s maintenance service. Keywords: thermal imaging; belt conveyor; diagnostics; underground mining; mechanical failure; preventative maintenance 1. Introduction The discovery of infrared radiation gave rise to the science of thermography. It was discovered in 1800 by Friedrich Wilhelm Herschel, an English astronomer. In the second half of the 19th century, the following scientists, Kirchoff, Boltzman, Wiena and Planck, whose research laid the foundation for the development of thermal imaging, deepened the knowledge of thermal imaging. The first applications were for the military, where the Energies 2021,14, 3258. https://doi.org/10.3390/en14113258 https://www.mdpi.com/journal/energies Energies 2021,14, 3258 2 of 18 first infrared indicators were built in the mid-20th century. In the 1960s, the first thermal imaging device appeared, which today is a thermal imaging camera [1–4]. Thermal imaging measures an object body whose temperature is higher than zero because it emits thermal radiation. This thermal radiation is the part of the electromagnetic spectrum; its wavelength falls between 760 and 1 mm. This radiation is detected and measured by the thermal imaging device in two different ways—when the thermal detector absorbs infrared radiation completely (of any wavelength) and when the photon detector reacts only to radiation of a specific wavelength. The detector of a thermal imaging camera enables the energy of infrared radiation to be changed into an electrical signal. In the individual signal processing modules, the signal is amplified, converted into digital form and converted into the temperature value of the individual points of the image matrix. This is how a map of the distribution (thermogram) of the temperature of the object under investigation is created [5–8]. The thermal imaging camera works on the principle of converting infrared radiation that can be emitted or reflected by an object, into an electrical signal and later into an image displayed on a computer monitor. The camera is composed of an optical system, an infrared radiation detector, electronic amplification, processing and a visualization path [9,10]. Belt conveyors are mechanical, hydraulic or pneumatic means of transport, they operate in continuous or cyclic motion. Their purpose is to transport the excavated material over often considerable distances, with varying conveying speeds, capacities and conveyor belt lines. In underground coal mines, they are the primary form of transport [ 11 , 12 ]. The drive systems used in mining can exclude or hinder diagnostic measurements. The results which are obtained by means of various measurements can be processed by dedicated software FLIR Tools [ 13 ]. Studies on the development of longwall conveyors are presented in works [ 14 – 22 ]—they are part of the innovative development of machinery and equipment [23–27]. The popularity of the thermal imaging method to assess the technical condition of belt conveyors in a mine has been increasing [ 28 ]. The first experimental studies using thermal imaging cameras were described in works [ 29 – 32 ], whose findings and the method developed contributed to minimising failures primarily in the mines of Polish State Mining and Metallurgical Combine (KGHM). Multiple diagnostic methods are recommended for costly machines and process lines [ 33 – 36 ]. Control testing can prevent the occurrence of fires, which are one of the most dangerous hazards in underground mines. Excavations in closed areas are subject to natural hazards, mainly methane [ 37 – 47 ] and fire [ 48 ]. They can cause serious damage to machinery and equipment, and even pose a threat to human health and life [49–51]. Based on the research carried out, the main causes of the thermal condition for the drive unit were defined as: belt slip in the drive, problems with optimal cooling of the drive, bearing friction, seizure of the brake system, seizure of the drive drums, and seizure of the pulleys. These causes are mainly generated in the contact zone: improper cooling of the drive unit, the drum coming into contact with the belt, or the pulley coming into contact with the belt. The main objective of this study was to identify the thermal condition of conveyor belt component structures and to analyse the risk of critical temperature increases. The tests were focussed on the drive unit, specifically the engine, the braking system and the gearbox. In order to measure the actual temperature distribution occurring in the main haulage belt conveyors, it was necessary to analyse the operating time of the belt conveyors and determine the cause of any thermal anomaly. The analysis of the working time of the main haulage conveyors was related to one working day in this study. The results are presented in the form of measurement images. They were developed using dedicated software. The obtained characteristics for the thermal state are presented in the form of diagrams. This paper presents a real-life example of a thermal condition survey for a measuring unit using a thermal imaging camera. Energies 2021,14, 3258 3 of 18 2. Materials and Methods The use of thermal imaging is a very important and useful research method because, as a method for object diagnosis, it allows fast, safe and also accurate measurements in even restrictive space [ 52 – 71 ]. In a deep mine environment, cameras can be used to work in smoky, dusty and dark environments. The use of the thermal imaging method in the mining industry offers a wide range of research opportunities in view of the heat production that takes place during the operation of all powered equipment. Factors such as ambient temperature, humidity, air velocity, air volume in the excavation and emissivity have a significant influence on the measurement results [ 72 ]. Using long-wave infrared radiation in the measurements, thermal radiation is recorded. The camera captures objects, people and high-temperature sources in limited or no visibility conditions [73–78]. Thermal imaging cameras use energy that increases as the temperature of an object increases, and can be obtained from any object whose temperature is above zero. The measurements result in a total temperature distribution over the background of the object, which can be seen by the colour variation in the measurement image. The advantages of thermal imaging cameras are that they are non-invasive and can locate faults invisible to the naked eye. The test with a thermal imaging camera is based on measuring the temperature from the external surface, where the temperature distribution is non-uniform [ 79 ]. In order to obtain the relevant quantities, an average is determined which forms the basis for fault finding as temperatures increase above the normal operating ones. In industry, thermography is used to control technological processes and, more specifically, the thermal state in order to predict and prevent failures. The image taken by the thermal imaging camera reflects the temperature of the device under examination and other surfaces, allowing the technical condition to be assessed. Equipment such as power grids, main fan stations, boilers for district heating and conveyor belts, among others, are examined using thermal imaging. In order to be considered reliable, the measurement must be carried out over a longer period of time and operate to its specification, e.g., the conveyor belt must be loaded with excavated material [80–90]. 2.1. Objective and Scope of the Study The objective of this study was to identify the thermal condition of an operational belt conveyor drive unit in an underground coal mine. The following tasks were completed: - tests and measurements on the conveyor drive unit, - an analysis of operating times of conveyors, - determination of the causes of the thermal condition for the construction of conveyors, - an analysis of the results and recommendations. 2.2. Analysed Main Haulage Conveyors The main haulage belt conveyors used in the study transported the excavated coal from the longwall. The longwall mining was carried out conventionally with roof caving. The longwall was equipped with a powered roof support, a double-drum shearer and a scraper conveyor. The length of the longwall is 238 m and the panel length is 480 m. The thickness of the seam is between 2.5 and 3.1 m, with a slope between 23 ◦ and 25 ◦ . The main haulage system from the longwall transports the excavated material to a 1000 m 3 silo located in the mining shaft area. The analysed haulage system consists of six belt conveyors with a total length of 1846 m. The parameters of the analysed main haulage are presented in Table 1and their location in Figure 1. Energies 2021,14, 3258 4 of 18 Table 1. Technical parameters of the analysed main haulage system. Number of the Conveyor Type of the Conveyor Power (kW) Belt Width (m) Belt Length (m) Performance Maximum (t/h) PT-1 Intermet-1200 2 ×250 1.2 480 1388 PT-2 Vacat-1400 3 ×315 1.4 420 1512 PT-3 Intermet-1200 2 ×160 1.2 80 1220 PT-4 Pioma-1200 2 ×250 1.2 140 1220 PT-5 Pioma-1200 2 ×250 1.2 260 1134 PT-II Pioma-1400 2 ×250 1.4 410 1500 PT-I Bogda-1400 2 ×132 1.4 56 1500 Energies 2021, 14, x FOR PEER REVIEW 4 of 18 Figure 1. Layout of the conveyors of the main haulage system, (PT—a belt conveyor). Table 1. Technical parameters of the analysed main haulage system. Number of the Conveyor Type of the Conveyor Powe r (kW) Belt Width (m) Belt Length (m) Performance Maximum (t/h) PT-1 Intermet-1200 2 × 250 1.2 480 1388 PT-2 Vacat-1400 3 × 315 1.4 420 1512 PT-3 Intermet-1200 2 × 160 1.2 80 1220 PT-4 Pioma-1200 2 × 250 1.2 140 1220 PT-5 Pioma-1200 2 × 250 1.2 260 1134 PT-II Pioma-1400 2 × 250 1.4 410 1500 PT-I Bogda-1400 2 × 132 1.4 56 1500 The conveyor routes are made of coils supported on lower trestles, which are spaced every 3 m and each has two Ø 133 mm pulleys (Figure 2b), they serve to guide the lower belt in a V arrangement with a constant inclination angle of 10° and variable advance (−2°, 0°, 2°). The upper band is guided along the triangular supports to form a trough with an angle of 35° (Figure 2a). Each of the side pulleys of the top support has an oblique 2° leadout in the belt direction and a belt distance of 1.2 m. Figure 1. Layout of the conveyors of the main haulage system, (PT—a belt conveyor). The conveyor routes are made of coils supported on lower trestles, which are spaced every 3 m and each has two Ø 133 mm pulleys (Figure 2b), they serve to guide the lower belt in a V arrangement with a constant inclination angle of 10 ◦ and variable advance ( − 2 ◦ , 0 ◦ , 2 ◦ ). The upper band is guided along the triangular supports to form a trough with an angle of 35 ◦ (Figure 2a). Each of the side pulleys of the top support has an oblique 2 ◦ lead-out in the belt direction and a belt distance of 1.2 m. Energies 2021,14, 3258 5 of 18 Energies 2021, 14, x FOR PEER REVIEW 5 of 18 (a) (b) Figure 2. Support structure of the conveyor route: (a) The upper belt forms a trough with an angle of 35°; (b) View of the upper and lower belt routing. 2.3. Description of the Measuring Apparatus A thermal imaging camera (shown in Figure 3a,b) works by processing infrared radiation that is emitted or reflected by objects. The resulting electrical signal is transformed into an image viewed on a monitor. The camera is built of an optical system, an infrared detector, a visualisation circuit and electronic amplification. The camera reads the measurement of any object with a temperature above zero without relative 0 °C, which is a source of infrared radiation, and its intensity depends on the temperature and surface features of a given object. The range of detection (sensing), recognition and observation identification depends mainly on three parameters: the viewing angle of the camera, thermal resolution and number of detectors in the array [91]. The devices shown in Figure 3 are equipped with a laser pointer that allows the temperature to be recorded at a specific point during the measurement from the object or location. A pyrometer (Figure 3c) is used for non-contact temperature measurement. It works by analysing the thermal radiation emitted by the objects as a whole. (a) (b) (c) Figure 3. The measuring equipment used in the study of the thermal condition of the belt conveyor drive unit: (a) Dräger UFC 9000 thermal imaging karma; (b) FLIR i60 thermal imaging camera; (c) FLUKE 561 pyrometer. 2.4. Design of the Conveyor Drive Unit The drive unit consists of a gearbox, clutch and motor connected via the coupling case. The conveyor drive drums are driven by drive units. The transmission of the takeoff torque from the gearbox to the drums is affected by means of couplings. The drive unit is built on a drive drum module. The gearbox is attached to the drive body via an Figure 2. Support structure of the conveyor route: ( a ) The upper belt forms a trough with an angle of 35◦; (b) View of the upper and lower belt routing. 2.3. Description of the Measuring Apparatus A thermal imaging camera (shown in Figure 3a,b) works by processing infrared radiation that is emitted or reflected by objects. The resulting electrical signal is transformed into an image viewed on a monitor. The camera is built of an optical system, an infrared detector, a visualisation circuit and electronic amplification. The camera reads the measurement of any object with a temperature above zero without relative 0 ◦ C, which is a source of infrared radiation, and its intensity depends on the temperature and surface features of a given object. The range of detection (sensing), recognition and observation identification depends mainly on three parameters: the viewing angle of the camera, thermal resolution and number of detectors in the array [ 91 ]. The devices shown in Figure 3are equipped with a laser pointer that allows the temperature to be recorded at a specific point during the measurement from the object or location. A pyrometer (Figure 3c) is used for non-contact temperature measurement. It works by analysing the thermal radiation emitted by the objects as a whole. Energies 2021, 14, x FOR PEER REVIEW 5 of 18 (a) (b) Figure 2. Support structure of the conveyor route: (a) The upper belt forms a trough with an angle of 35°; (b) View of the upper and lower belt routing. 2.3. Description of the Measuring Apparatus A thermal imaging camera (shown in Figure 3a,b) works by processing infrared radiation that is emitted or reflected by objects. The resulting electrical signal is transformed into an image viewed on a monitor. The camera is built of an optical system, an infrared detector, a visualisation circuit and electronic amplification. The camera reads the measurement of any object with a temperature above zero without relative 0 °C, which is a source of infrared radiation, and its intensity depends on the temperature and surface features of a given object. The range of detection (sensing), recognition and observation identification depends mainly on three parameters: the viewing angle of the camera, thermal resolution and number of detectors in the array [91]. The devices shown in Figure 3 are equipped with a laser pointer that allows the temperature to be recorded at a specific point during the measurement from the object or location. A pyrometer (Figure 3c) is used for non-contact temperature measurement. It works by analysing the thermal radiation emitted by the objects as a whole. (a) (b) (c) Figure 3. The measuring equipment used in the study of the thermal condition of the belt conveyor drive unit: (a) Dräger UFC 9000 thermal imaging karma; (b) FLIR i60 thermal imaging camera; (c) FLUKE 561 pyrometer. 2.4. Design of the Conveyor Drive Unit The drive unit consists of a gearbox, clutch and motor connected via the coupling case. The conveyor drive drums are driven by drive units. The transmission of the takeoff torque from the gearbox to the drums is affected by means of couplings. The drive unit is built on a drive drum module. The gearbox is attached to the drive body via an Figure 3. The measuring equipment used in the study of the thermal condition of the belt conveyor drive unit: ( a ) Dräger UFC 9000 thermal imaging karma; (b) FLIR i60 thermal imaging camera; (c) FLUKE 561 pyrometer. 2.4. Design of the Conveyor Drive Unit The drive unit consists of a gearbox, clutch and motor connected via the coupling case. The conveyor drive drums are driven by drive units. The transmission of the take-off torque from the gearbox to the drums is affected by means of couplings. The drive unit is built on Energies 2021,14, 3258 6 of 18 a drive drum module. The gearbox is attached to the drive body via an intermediate plate. Drive units consisting of motors and gearboxes require water cooling. Figure 4shows an example of the construction of the drive unit. Energies 2021, 14, x FOR PEER REVIEW 6 of 18 intermediate plate. Drive units consisting of motors and gearboxes require water cooling. Figure 4 shows an example of the construction of the drive unit. Figure 4. Conveyor drive unit, where; 1—engine, 2—left brake system (I), 3—left gearbox (I), 4— right gearbox (II), 5—right brake system (II), 6—engine, 7—foundation. 3. Results It can be quite difficult to carry out measurements using a thermal imaging camera for this purpose in an underground mine. One of the main factors that influence the result is the prevailing dust in the excavation. The correct temperature range for the drive unit is influenced by the length of the route, the variable load, and the size of the drive drums. The main problem during the research was to obtain a suitable measuring distance. Conveyor drive components such as the motor, gearbox and braking system are built into a recess due to the dimensions of the workings. For major conveyor installations, a fixed thermal imaging device could be used and data sent to a central control room for continuous monitoring. Exceeding a threshold temperature, predetermined from field data, could trigger an alarm, for example. Maintenance personnel could then be sent to the unit to investigate the temperature anomaly and conduct preventative maintenance if needed. The following parameters were introduced to minimise measurement interference: emissivity, humidity, ambient temperature, and the distance of the camera from the object. Each of these measurements was additionally determined using a pyrometer type device. It was not possible to place the measuring equipment on a tripod due to the dimensional constraints of the excavation. The measured air temperature at the drive locations varied between 22 and 30 °C. The measurements taken were sequential, with a frequency of 5 min. The entire measurement session for a single test object lasted approximately 60 min, resulting in 12 measurements. 3.1. Analysis of the Working Time of the Main Conveyors The operating time of the main haulage conveyors depends on many factors, including the mine’s operating system and planned daily tonnage. The main haulage unit under analysis operates on a five-shift system. This is characterised by four mining shifts and a fifth maintenance shift. A maintenance-related stoppage of the conveyors to perform necessary checks or repairs is made between 5:30 and 8:00 a.m. The working time of the main haulage conveyors was analysed by data collected from the ZEFIR system. This system performs the function of continuous supervision of mine operations, for the operational management, alerting, documentation and analysis of the production process. Figure 5 shows a visualisation of the working time of the analysed main haulage conveyors, and Table 2 presents a summary of the effective use of the working time of the analysed belt conveyors. Figure 4. Conveyor drive unit, where; 1—engine, 2—left brake system (I), 3—left gearbox (I), 4—right gearbox (II), 5—right brake system (II), 6—engine, 7—foundation. 3. Results It can be quite difficult to carry out measurements using a thermal imaging camera for this purpose in an underground mine. One of the main factors that influence the result is the prevailing dust in the excavation. The correct temperature range for the drive unit is influenced by the length of the route, the variable load, and the size of the drive drums. The main problem during the research was to obtain a suitable measuring distance. Conveyor drive components such as the motor, gearbox and braking system are built into a recess due to the dimensions of the workings. For major conveyor installations, a fixed thermal imaging device could be used and data sent to a central control room for continuous monitoring. Exceeding a threshold temperature, predetermined from field data, could trigger an alarm, for example. Maintenance personnel could then be sent to the unit to investigate the temperature anomaly and conduct preventative maintenance if needed. The following parameters were introduced to minimise measurement interference: emissivity, humidity, ambient temperature, and the distance of the camera from the object. Each of these measurements was additionally determined using a pyrometer type device. It was not possible to place the measuring equipment on a tripod due to the dimensional constraints of the excavation. The measured air temperature at the drive locations varied between 22 and 30 ◦ C. The measurements taken were sequential, with a frequency of 5 min. The entire measurement session for a single test object lasted approximately 60 min, resulting in 12 measurements. 3.1. Analysis of the Working Time of the Main Conveyors The operating time of the main haulage conveyors depends on many factors, including the mine’s operating system and planned daily tonnage. The main haulage unit under analysis operates on a five-shift system. This is characterised by four mining shifts and a fifth maintenance shift. A maintenance-related stoppage of the conveyors to perform necessary checks or repairs is made between 5:30 and 8:00 a.m. The working time of the main haulage conveyors was analysed by data collected from the ZEFIR system. This system performs the function of continuous supervision of mine operations, for the operational management, alerting, documentation and analysis of the production process. Figure 5shows a visualisation of the working time of the analysed main haulage conveyors, and Table 2presents a summary of the effective use of the working time of the analysed belt conveyors. Energies 2021,14, 3258 7 of 18 Energies 2021, 14, x FOR PEER REVIEW 7 of 18 Figure 5. Graph for the operating time of the main haulage belt conveyors, where: 1—the operating time (it is in motion) of the conveyor belt, 0—the idle time (the machine is halted). The diagram (Figure 5) illustrates the operation of the main haulage belt conveyors on a daily basis. It allows us to view the stoppages that have occurred during its daily operation. The belt conveyors whose running time measurement is shown in the above diagram are explained in Table 2. Table 2. Measuring the running time of the main haulage belt conveyors. No. of the Conveyor Type Location Working Time (min) Stoppage Duration (min) PT-I 1-400 Haulage drift/III 1300 140 PT-II 1-400 Haulage drift 2, S-type 1297 143 PT-2 1-400 Collective ramp, E-type/III 698 742 PT-1 1-200 Belt gallery 2/III 916 524 PT-3 1-200 Primary gallery/III 1282 158 PT-4 1-200 Drift III east, level 700 1290 150 PT-5 1-200 Haulage drift 3/III 1291 149 3.2. Inspection of a Conveyor Drive Unit Using a Thermal Imaging Camera Testing of the individual drive units of the main haulage conveyors was carried out two hours after start-up of the morning shift. All conveyors tested were loaded with excavated coal material. It was assumed that the temperature value should stabilize after this time from the start up. Obtaining a series of measurement images from a single conveyor drive during sixty minutes of operation allowed us to calculate the minimum and maximum temperatures for the drive unit. The unit consists of the motor, gearbox and brake system. The construction of the drive, including the drums, was omitted from measurements. The tested constructions of the drive system consisted of two drive units, one in the left-hand version (II drive) and one in the right-hand version (I drive). Two thermal imaging cameras—FLIR 60 and Dräger UCF 9000—were used in the study. The measurement series taken on the equipment made it possible to locate the hottest areas within the drive structure. The following thermograms (Figures 6 and 7) show the recorded temperatures for selected drive units from the conveyors analysed. Figure 5. Graph for the operating time of the main haulage belt conveyors, where: 1—the operating time (it is in motion) of the conveyor belt, 0—the idle time (the machine is halted). Table 2. Measuring the running time of the main haulage belt conveyors. No. of the Conveyor Type Location Working Time (min) Stoppage Duration (min) PT-I 1-400 Haulage drift/III 1300 140 PT-II 1-400 Haulage drift 2, S-type 1297 143 PT-2 1-400 Collective ramp, E-type/III 698 742 PT-1 1-200 Belt gallery 2/III 916 524 PT-3 1-200 Primary gallery/III 1282 158 PT-4 1-200 Drift III east, level 700 1290 150 PT-5 1-200 Haulage drift 3/III 1291 149 The diagram (Figure 5) illustrates the operation of the main haulage belt conveyors on a daily basis. It allows us to view the stoppages that have occurred during its daily operation. The belt conveyors whose running time measurement is shown in the above diagram are explained in Table 2. 3.2. Inspection of a Conveyor Drive Unit Using a Thermal Imaging Camera Testing of the individual drive units of the main haulage conveyors was carried out two hours after start-up of the morning shift. All conveyors tested were loaded with excavated coal material. It was assumed that the temperature value should stabilize after this time from the start up. Obtaining a series of measurement images from a single conveyor drive during sixty minutes of operation allowed us to calculate the minimum and maximum temperatures for the drive unit. The unit consists of the motor, gearbox and brake system. The construction of the drive, including the drums, was omitted from measurements. The tested constructions of the drive system consisted of two drive units, one in the left-hand version (II drive) and one in the right-hand version (I drive). Two thermal imaging cameras—FLIR 60 and Dräger UCF 9000—were used in the study. The measurement series taken on the equipment made it possible to locate the hottest areas within the drive structure. The following thermograms (Figures 6and 7) show the recorded temperatures for selected drive units from the conveyors analysed. Energies 2021,14, 3258 8 of 18 Energies 2021, 14, x FOR PEER REVIEW 8 of 18 (a) (b) (c) (d) (e) (f) Figure 6. Cont. Energies 2021,14, 3258 9 of 18 Energies 2021, 14, x FOR PEER REVIEW 9 of 18 (g) (h) (i) (j) Figure 6. A view from a measurement session made with a thermal imaging camera together with processing in the software FLIR Tools for (II) drive unit of belt conveyor PT-4 from the analysed main haulage, where heat distribution is presented for: (a) photo of the tested right gearbox (II); (b) thermogram with visible thermal effect for the right gearbox (II); (c,d) thermogram showing the heat distribution for the right gearbox (II); (e) photo of the tested right engine (II), (f) thermogram with visible thermal effect for the right engine (II); (g,h) thermogram showing the heat distribution for the right engine (II); (i,j) thermogram showing the heat distribution taken with the Dräger UFC 9000 camera. (a) (b) Figure 6. A view from a measurement session made with a thermal imaging camera together with processing in the software FLIR Tools for (II) drive unit of belt conveyor PT-4 from the analysed main haulage, where heat distribution is presented for: ( a ) photo of the tested right gearbox (II); ( b ) thermogram with visible thermal effect for the right gearbox (II); ( c , d ) thermogram showing the heat distribution for the right gearbox (II); ( e ) photo of the tested right engine (II), ( f ) thermogram with visible thermal effect for the right engine (II); ( g , h ) thermogram showing the heat distribution for the right engine (II); (i,j) thermogram showing the heat distribution taken with the Dräger UFC 9000 camera. Energies 2021, 14, x FOR PEER REVIEW 9 of 18 (g) (h) (i) (j) Figure 6. A view from a measurement session made with a thermal imaging camera together with processing in the software FLIR Tools for (II) drive unit of belt conveyor PT-4 from the analysed main haulage, where heat distribution is presented for: (a) photo of the tested right gearbox (II); (b) thermogram with visible thermal effect for the right gearbox (II); (c,d) thermogram showing the heat distribution for the right gearbox (II); (e) photo of the tested right engine (II), (f) thermogram with visible thermal effect for the right engine (II); (g,h) thermogram showing the heat distribution for the right engine (II); (i,j) thermogram showing the heat distribution taken with the Dräger UFC 9000 camera. (a) (b) Figure 7. Cont. Energies 2021,14, 3258 16 of 18 23. Kozłowski, T.; Wodecki, J.; Zimroz, R.; Bła˙ zej, R.; Hardygóra, M. A Diagnostics of Conveyor Belt Splices. Appl. Sci. 2020 ,10, 6259. [CrossRef] 24. Wodecki, J.; Góralczyk, M.; Krot, P.; Zi˛etek, B.; Szrek, J.; Worsa-Kozak, M.; Zimroz, R.; ´ Sliwi´nski, P.; Czajkowski, A. Process Monitoring in Heavy Duty Drilling Rigs—Data Acquisition System and Cycle Identification Algorithms. Energies 2020 ,13, 6748. [CrossRef] 25. Góralczyk, M.; Krot, P.; Zimroz, R.; Ogonowski, S. Increasing Energy Efficiency and Productivity of the Comminution Process in Tumbling Mills by Indirect Measurements of Internal Dynamics—An Overview. Energies 2020,13, 6735. [CrossRef] 26. Hebda-Sobkowicz, J.; Zimroz, R.; Wyłoma´nska, A. Selection of the Informative Frequency Band in a Bearing Fault Diagnosis in the Presence of Non-Gaussian Noise—Comparison of Recently Developed Methods. Appl. Sci. 2020,10, 2657. [CrossRef] 27. Schmidt, S.; Zimroz, R.; Chaari, F.; Heyns, P.S.; Haddar, M. A Simple Condition Monitoring Method for Gearboxes Operating in Impulsive Environments. Sensors 2020,20, 2115. [CrossRef] 28. Zi˛etek, B.; Banasiewicz, A.; Zimroz, R.; Szrek, J.; Gola, S. A Portable Environmental Data-Monitoring System for Air Hazard Evaluation in Deep Underground Mines. Energies 2020,13, 6331. [CrossRef] 29. Borkowski, P.J. Comminution of Copper Ores with the Use of a High-Pressure Water Jet. Energies 2020,13, 6274. [CrossRef] 30. Zimroz, R. Metody Adaptacyjne w Diagnostyce Układów Nap˛edowych Maszyn Górniczych; Oficyna Wydawnicza Politechniki: Wrocławskiej, Poland, 2010. 31. Bła˙ zej, R.; Sawicki, M.; Konieczna, M.; Kozłowski, T.; Kirjanów, A. Automatic analysis of themrograms as a means for estimating technical of a gear system. Diagnostyka 2016,2, 43–48. 32. Sawicki, M.; Stefaniak, P.; Zimroz, R.; Bła˙ zej, R. Badania eksperymentalne stanu technicznego elementów przeno´snika ta´smowego z wykorzystaniem metody termowizyjnych, Interdyscyplinarne zagadnienia w górnictwie i geologii. Interdyscyplinarne Zagadnienia w Górnictwie i Geologii 2013 , 203–211. Available online: http://diagbelt.pwr.edu.pl/Publikacje/J.Z.W.G.I.G._tomIV_2013 .pdf (accessed on 28 May 2021). 33. Sawicki, M.; Stefaniak, P.; Zimroz, R.; Bła˙ zej, R.; Król, R. Wykorzystanie metod termowizyjnych do badania stanu technicznego układów nap˛edowych przeno´sników ta´smowych w O/ZG Polkowice-Sieroszowice. Interdyscyplinarne Zagadnienia w Górnictwie i Geologii 2014 , 177–183. Available online: http://labdiag.pwr.wroc.pl/radzim/papers/2014/Sawicki%20i%20inni_KDiMU\T1 \textquoteright14_vO.docx (accessed on 28 May 2021). 34. Zimroz, R.; Stefaniak, P.; Hardygóra, M. Wybrane zagadnienia diagnostyki procesów roboczych i stanu technicznego elementów maszyn górniczych. In˙ zynieria Maszyn. 2014,19, 7–16. 35. Hulewicz, A. Diagnostyka termowizyjna w elektrotechnice. Pozn. Univ. Technol. Acad. J. Electr. Eng. 2017 ,89, 259–269. [CrossRef] 36. Soroko, M. Termowizja w sporcie—Kontrola kontuzji siatkarzy. Acta Bio Opit. Informa. Med. 2010,1, 46–47. 37. Wittchen, W.; Mazur, A. Metoda termowizji jako narz˛edzie pomocnicze w procesach symulacji numerycznej. Prace IM ˙ Z. 2012 ,1, 188–191. 38. Minkina, W.; Rutkowski, P.; Wild, W. Podstawy pomiarów termowizyjnych. Cz˛e´s´c II—Współczesne rozwi ˛azania systemów termowizyjnych, bł˛edy metody. PAK 2000,1, 11–14. 39. Bartelus, W. Diagnostyka Maszyn Górniczych: Górnictwo Odkrywkowe; Wydawnictwo ´ Sl ˛ask: Katowice, Poland, 1998. 40. Tutak, M.; Brodny, J.; Szurgacz, D.; Sobik, L.; Zhironkin, S. The Impact of the Ventilation System on the Methane Release Hazard and Spontaneous Combustion of Coal in the Area of Exploitation—A Case Study. Energies 2020,13, 4891. [CrossRef] 41. Tutak, M. The Influence of the Permeability of the Fractures Zone Around the Heading on the Concentration and Distribution of Methane. Sustainability 2020,12, 16. [CrossRef] 42. Tutak, M.; Brodny, J. The Impact of the Strength of Roof Rocks on the Extent of the Zone with a High Risk of Spontaneous Coal Combustion for Fully Powered Longwalls Ventilated with the Y-Type System—A Case Study. Appl. Sci. 2019 ,9, 5315. [CrossRef] 43. Tutak, M.; Brodny, J. Forecasting Methane Emissions from Hard Coal Mines Including the Methane Drainage Process. Energies 2019,12, 3840. [CrossRef] 44. Tutak, M.; Brodny, J. Predicting Methane Concentration in Longwall Regions Using Artificial Neural Networks. Int. J. Environ. Res. Public Health 2019,16, 1406. [CrossRef] [PubMed] 45. Tutak, M.; Brodny, J. Analysis of the Impact of Auxiliary Ventilation Equipment on the Distribution and Concentration of Methane in the Tailgate. Energies 2018,11, 3076. [CrossRef] 46. Brodny, J.; Tutak, M. Analyzing Similarities between the European Union Countries in Terms of the Structure and Volume of Energy Production from Renewable Energy Sources. Energies 2020,13, 913. [CrossRef] 47. Brodny, J.; Tutak, M. Analysing the Utilisation Effectiveness of Mining Machines Using Independent Data Acquisition Systems: A Case Study. Energies 2019,12, 2505. [CrossRef] 48. Brodny, J.; Tutak, M. Exposure to Harmful Dusts on Fully Powered Longwall Coal Mines in Poland. Int. J. Environ. Res. Public Health 2018,15, 1846. [CrossRef] 49. Szurgacz, D.; Tutak, M.; Brodny, J.; Sobik, L.; Zhironkina, O. The Method of Combating Coal Spontaneous Combustion Hazard in Goafs—A Case Study. Energies 2020,13, 4538. [CrossRef] 50. Nowicki, J.; Hebda-Sobkowicz, J.; Zimroz, R.; Wylomanska, A. Local Defect Detection in Bearings in the Presence of Heavy-Tailed Noise and Spectral Overlapping of Informative and Non-Informative Impulses. Sensors 2020,20, 6444. [CrossRef] [PubMed] Energies 2021,14, 3258 17 of 18 51. Hebda-Sobkowicz, J.; Gola, S.; Zimroz, R.; Wyłoma´nska, A. Identification and Statistical Analysis of Impulse-Like Patterns of Carbon Monoxide Variation in Deep Underground Mines Associated with the Blasting Procedure. Sensors 2019 ,19, 2757. [CrossRef] 52. Polnik, B. Tests of a longwall shearer diagnostic system using infrared camera. Meas. Auto. Monit. 2015,6, 249–251. 53. Chajda, J.; Poloszyk, S.; Ró˙ za´nski, L. Termowizja w diagnostyce technicznej maszyn technologicznych. Arch. Technol. Masz. Automat. 1999,19, 65–82. 54. Gabry´s, R. Termografia w diagnostyce. Elektroinstalator 2017,4, 28–32. 55. Kuczy´nski, K. Bezkontaktowa diagnostyka urz ˛adze´n. Elektro Info 2010,11, 46–48. 56. ˙ Zabicki, D. Termowizja w diagnostyce maszyn i urz ˛adze´n elektroenergetycznych. Elektroinstalator 2016,3, 48–51. 57. Erazo-Aux, J.; Loaiza-Correa, H.; Restrepo-Giron, A.D.; Ibarra-Castanedo, C.; Maldague, X. Thermal imaging dataset from composite material academic samples inspected by pulsed thermography. Data Brief 2020,32, 106313. [CrossRef] [PubMed] 58. Paramasivam, B. Investigation on the effects of damping over the temperature distribution on internal turning bar using Infrared fusion thermal imager analysis via SmartView software. Measurement 2020,162, 107938. [CrossRef] 59. Tattersall, G.L.; Danner, R.M.; Chaves, J.A.; Levesque, D.L. Activity analysis of thermal imaging videos using a difference imaging approach. J. Ther. Biol. 2020,91, 102611. [CrossRef] 60. Carvalho, R.; Nascimento, R.; D’Angelo, T.; Delabrida, S.; Bianchi, A.G.C.; Oliveira, R.A.R.; Azpúrua, H.; Garcia, L.G.U. A UAV-Based Framework for Semi-Automated Thermographic Inspection of Belt Conveyors in the Mining Industry. Sensors 2020 , 20, 2243. [CrossRef] 61. Ghorbanzadeh, O.; Valizadeh Kamran, K.; Blaschke, T.; Aryal, J.; Naboureh, A.; Einali, J.; Bian, J. Spatial Prediction of Wildfire Susceptibility Using Field Survey GPS Data and Machine Learning Approaches. Fire 2019,2, 43. [CrossRef] 62. Oishi, Y.; Ishida, H.; Nakajima, T.Y.; Nakamura, R.; Matsunaga, T. The Impact of Different Support Vectors on GOSAT-2 CAI2 L2 Cloud Discrimination. Remote Sens. 2017,9, 1236. [CrossRef] 63. Ozotta, O.; Gerla, P.J. Mapping Groundwater Seepage in a Fen Using Thermal Imaging. Geosciences 2021,11, 29. [CrossRef] 64. Resendiz-Ochoa, E.; Saucedo-Dorantes, J.J.; Benitez-Rangel, J.P.; Osornio-Rios, R.A.; Morales-Hernandez, L.A. Novel Methodology for Condition Monitoring of Gear Wear Using Supervised Learning and Infrared Thermography. Appl. Sci. 2020 ,10, 506. [CrossRef] 65. Milovanovi´c, B.; Banjad Peˇcur, I. Review of Active IR Thermography for Detection and Characterization of Defects in Reinforced Concrete. J. Imaging 2016,2, 11. [CrossRef] 66. Clark, M.R.; McCann, D.M.; Forde, M.C. Application of infrared thermography to the non-destructive testing of concrete and masonry bridge. NDT E Int. 2003,36, 265–275. [CrossRef] 67. Meola, C.; Boccardi, S.; Carlomagno, G.M. An Excursus on Infrared Thermography Imaging. J. Imaging 2016,2, 36. [CrossRef] 68. De Finis, R.; Palumbo, D.; Galietti, U. Mechanical Behaviour of Stainless Steels under Dynamic Loading: An Investigation with Thermal Methods. J. Imaging 2016,2, 32. [CrossRef] 69. Robinson, J.B.; Shearing, P.R.; Brett, D.J.L. Thermal Imaging of Electrochemical Power Systems: A Review. J. Imaging 2016 ,2, 2. [CrossRef] 70. Steen, K.A.; Villa-Henriksen, A.; Therkildsen, O.R.; Green, O. Automatic Detection of Animals in Mowing Operations Using Thermal Cameras. Sensors 2012,12, 7587–7597. [CrossRef] 71. Eisele, A.; Lau, I.; Hewson, R.; Carter, D.; Wheaton, B.; Ong, C.; Cudahy, T.J.; Chabrillat, S.; Kaufmann, H. Applicability of the Thermal Infrared Spectral Region for the Prediction of Soil Properties Across Semi-Arid Agricultural Landscapes. Remote Sens. 2012,4, 3265–3286. [CrossRef] 72. Malicki, W.; Miedzi´nski, B. Przydatno´s´c termowizji do diagnostyki technicznej urz ˛adze´n energomechanicznych w zakładach górniczych. Mechan. Automat. Górn. 2009,7, 34–38. 73. Fedorczak-Cisak, M.; Radziszewska-Zielina, E.; Orlik-Ko˙ zdo´n, B.; Steidl, T.; Tatara, T. Analysis of the Thermal Retrofitting Potential of the External Walls of Podhale’s Historical Timber Buildings in the Aspect of the Non-Deterioration of Their Technical Condition. Energies 2020,13, 4610. [CrossRef] 74. Kasprzyk-Kucewicz, T.; Szurko, A.; Stanek, A.; Siero´n, K.; Morawiec, T.; Cholewka, A. Usefulness in Developing an Optimal Training Program and Distinguishing between Performance Levels of the Athlete’s Body by Using of Thermal Imaging. Int. J. Environ. Res. Public Health 2020,17, 5698. [CrossRef] [PubMed] 75. Sieka´nski, P.; Pa´sko, S.; Malowany, K.; Malesa, M. Online Correction of the Mutual Miscalibration of Multimodal VIS–IR Sensors and 3D Data on a UAV Platform for Surveillance Applications. Remote Sens. 2019,11, 2469. [CrossRef] 76. Maj, M.; Ubysz, A.; Hammadeh, H.; Askifi, F. Non-Destructive Testing of Technical Conditions of RC Industrial Tall Chimneys Subjected to High Temperature. Materials 2019,12, 2027. [CrossRef] [PubMed] 77. Noszczyk, P.; Nowak, H. Inverse Contrast in Non-Destructive Materials Research by Using Active Thermography. Materials 2019 , 12, 835. [CrossRef] [PubMed] 78. Galla, S. A Thermographic Measurement Approach to Assess Supercapacitor Electrical Performances. Appl. Sci. 2017 ,7, 1247. [CrossRef] 79. Wernik, J. Investigation of Heat Loss from the Finned Housing of the Electric Motor of a Vacuum Pump. Appl. Sci. 2017 ,7, 1214. [CrossRef] Energies 2021,14, 3258 18 of 18 80. Nieoczym, A.; Longwic, R.; Lotko, W. Wst˛epna diagnostyka pojazdu z wykorzystaniem kamery termowizyjnej. Eksploatacja Testy 2017,6, 981–984. 81. Cheaito, R.; Gorham, C.S.; Misra, A.; Hattar, K.; Hopkins, P.E. Thermal conductivity measurements via time-domain thermoreflectance for the characterization of radiation induced damage. J. Mater. Res. 2015,30, 1403–1412. [CrossRef] 82. Dular, M.; Coutier-Delgosha, O. Thermodynamic effects during growth and collapse of a single cavitation bubble. J. Fluid Mecha. 2013,736, 44–66. [CrossRef] 83. Eriksson, P.; Andersson, J.Y.; Stemme, G. Thermal characterization of surface-micromachined silicon nitride membranes for thermal infrared detectors. J. Microele. Syst. 1997,6, 55–61. [CrossRef] 84. Krešák, J.; Peterka, P.; Kropuch, S.; Novák, L. Measurement of tight in steel ropes by a mean of thermovision. Measurement 2014 , 50, 93–98. [CrossRef] 85. Suszy´nski, Z.; ´ Swita, R.; Ło´s, J.; Zarzycka, M.B.; Kaleniecka, A.; Zarzycki, P.K. Fast assessment of planar chromatographic layers quality using pulse thermovision metod. J. Chromatogr. A 2014,1373, 211–215. [CrossRef] 86. Nadolny, K.; Plichta, J. Comparative method of thermovision temperature measurement in single-pass internal cylindrical grinding. Arch. Civ. Mech. Eng. 2006,4, 67–74. [CrossRef] 87. Ivanov, G.V.; Ivanov, V.G. Temperature and emissivity determination of small-size long-range object’s using staring Thermovision Cameras. Infrared Phys. Technol. 2013,60, 161–165. [CrossRef] 88. Sun, X.; Xu, H.; He, M.; Zhang, F. Experimental investigation of the occurrence of rockburst in a rock specimen through infrared thermography and acoustic emission. Int. J. Rock Mech. Min. Sci. 2017,93, 250–259. [CrossRef] 89. He, M.; Jia, X.; Gong, W.; Faramarzi, L. Physical modeling of an underground roadway excavation in vertically stratified rock using infrared thermography. Int. J. Rock Mech. Min. Sci. 2010,47, 1212–1221. [CrossRef] 90. Chan, W.T.; Sim, K.S.; Tso, C.P. Application of optical character recognition in thermal image processing. Infrared Phys. Technol. 2011,54, 353–366. [CrossRef] 91. Madura, H.; Sosnowski, T.; Bieszczad, G. Termowizyjne kamery obserwacyjne—Budowa, zastosowanie i krajowe mo˙ zliwo´sci realizacji. Przegl. Electrotech. 2014,9, 5–8. 92. Król, R. Metody Bada´n i Doboru Elementów Przeno´snika Ta´smowego z Uwzgl˛ednieniem Losowo Zmiennej Strugi Urobku; Wydział Geoin˙ zynierii, Górnictwa i Geologii Politechniki: Wrocławskiej, Poland, 2018.