Fire risk assessment method and system for conveyor belt based on surface element analysis

Abstract

This application relates to the field of conveyor belt fire technology, and provides a method and system for assessing the fire hazard of conveyor belts based on surface elemental analysis. In this method, the degradation degree index of the target conveyor belt is calculated by analyzing the changes in the content of surface constituent elements over wear time. Once the degradation degree index passes reliability verification, a constructed degradation-combustion prediction model is used to calculate the fire risk index of the target conveyor belt over wear time. This avoids interference from environmental factors such as underground dust and humidity in traditional assessment methods, enabling full life-cycle assessment and diagnosis of conveyor belts under different wear states before a fire occurs, overcoming the lag in traditional early warning methods.

Description

Technical Field

[0001] This application relates to the field of conveyor belt fire technology, and in particular to a method and system for assessing the fire hazard of conveyor belts based on surface element analysis. Background Technology

[0002] Conveyor belt fires are a major hidden danger in coal mine safety production, and wear is one of the key factors leading to the degradation of the flame-retardant properties of conveyor belts and causing fires. With the increasing automation and intelligence of coal mines, belt conveyors have become core equipment for coal transportation. However, the harsh working conditions of high temperature, high humidity, and continuous mechanical friction underground easily lead to wear and cracking of the conveyor belt surface, significantly reducing its flame-retardant properties and increasing the risk of fire. Major accidents caused by conveyor belt wear have fully exposed the current lack of understanding of the correlation mechanism between conveyor belt wear and fire, as well as the lack of early risk warning capabilities. Summary of the Invention

[0003] The purpose of this application is to provide a method and system for assessing the fire hazard of conveyor belts based on surface element analysis, so as to solve or alleviate the problems existing in the prior art.

[0004] To achieve the above objectives, this application provides the following technical solution:

[0005] This application provides a method for assessing the fire hazard of conveyor belts based on surface elemental analysis, including:

[0006] The surface composition elements of the target conveyor belt during wear time The content change was used to calculate the wear time of the target conveyor belt. The degradation degree index;

[0007] Response to the target conveyor belt during wear time The degradation index was verified for reliability by measuring the wear time of the target conveyor belt. The degradation degree index was used to calculate the wear rate of the target conveyor belt during the wear time using a constructed degradation and combustion prediction model. The fire risk index.

[0008] Preferably, a degradation degree index model is constructed:

[0009]

[0010] Calculate the wear time of the target conveyor belt Degradation index ;

[0011] In the formula, The target conveyor belt at wear time The surface content of chlorine, carbon, and oxygen elements. These are the initial elemental contents of chlorine, carbon, and oxygen on the surface of the target conveyor belt, respectively. The degradation weighting coefficient of the target conveyor belt affected by the dechlorination reaction. The degradation weighting coefficient is the factor by which the target conveyor belt is affected by the oxidation reaction.

[0012] Preferably, the target conveyor belt is obtained. Wear samples with different wear gradients were analyzed by energy dispersive spectroscopy. The elemental contents of chlorine, carbon, and oxygen on the surface of wear samples with different wear gradients were calculated using a degradation degree index model. Degradation index of each wear sample under its respective wear gradient;

[0013] right After normalizing the degradation degree index and corresponding mass loss of wear samples with different wear gradients, the degradation wear model of the target conveyor belt is obtained by fitting a linear function.

[0014] Preferably, a degradation wear model is used to assess the wear time of the target conveyor belt. The wear degree is predicted to obtain the predicted wear quality of the target conveyor belt;

[0015] Response to the predicted wear quality of the target conveyor belt and the target conveyor belt at wear time If the error of the measured mass loss at a given time is less than or equal to the preset mass threshold, then the target conveyor belt is determined to be at the wear time. The degradation degree index has been verified for reliability.

[0016] The preferred degradation combustion prediction model is:

[0017]

[0018] In the formula, For the target conveyor belt during wear time The time to reach peak heat release rate when a fire occurs. For the target conveyor belt during wear time Fire growth index during a fire. For the target conveyor belt during wear time Total heat release during a fire; All are fitting constants; For the target conveyor belt during wear time The degradation degree index.

[0019] This embodiment also provides a conveyor belt fire hazard assessment system based on surface element analysis. The system uses any of the above-described conveyor belt fire hazard assessment methods based on surface element analysis to predict the fire risk of a target conveyor belt. The system includes:

[0020] The elemental degradation calculation unit is configured to calculate the surface composition elements of the target conveyor belt over time. The content change was used to calculate the wear time of the target conveyor belt. The degradation degree index;

[0021] Fire risk prediction unit, configured to respond to target conveyor belt wear time The degradation index was verified for reliability by measuring the wear time of the target conveyor belt. The degradation degree index was used to calculate the wear rate of the target conveyor belt during the wear time using a constructed degradation and combustion prediction model. The fire risk index.

[0022] Beneficial effects:

[0023] The conveyor belt fire hazard assessment method and system based on surface element analysis provided in this application's embodiments assess the fire hazard of the target conveyor belt by analyzing the surface constituent elements over time. The content change was used to calculate the wear time of the target conveyor belt. The degradation degree index, when the target conveyor belt is worn for a certain period of time. The degradation index was verified for reliability by measuring the wear time of the target conveyor belt. The degradation degree index was used to calculate the wear rate of the target conveyor belt during the wear time using a constructed degradation and combustion prediction model. The fire risk index.

[0024] Therefore, quantitative assessment of conveyor belts based on changes in surface element content has strong anti-interference capabilities, avoiding interference from environmental factors such as underground dust and humidity that affect traditional assessment methods, thus effectively improving assessment reliability. Moreover, by analyzing changes in surface element content of the target conveyor belt, early and quantitative assessment of conveyor belt fire risk under different wear conditions can be achieved. On the one hand, the condition of the conveyor belt can be diagnosed before a fire occurs, enabling early diagnosis and classification of conveyor belt fire risk and overcoming the lag of traditional early warning methods. On the other hand, it can conduct a full life cycle assessment of the conveyor belt, enabling real-time and accurate assessment of the evolution of risk status caused by the increased wear and tear over time. Attached Figure Description

[0025] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. Wherein:

[0026] Figure 1 This is a flowchart illustrating a method for assessing the fire hazard of a conveyor belt based on surface elemental analysis, according to some embodiments of this application.

[0027] Figure 2 This is a schematic diagram showing the relationship between the degradation index and peak heat release rate of a PVG conveyor belt according to some embodiments of this application;

[0028] Figure 3 This is a schematic diagram showing the relationship between the degradation index of a PVG conveyor belt and the time to reach the peak heat release rate, according to some embodiments of this application.

[0029] Figure 4 This is a schematic diagram illustrating the relationship between the degradation index and the fire growth index of a PVG conveyor belt according to some embodiments of this application;

[0030] Figure 5 This is a schematic diagram illustrating the relationship between the degradation index and total heat release of a PVG conveyor belt according to some embodiments of this application;

[0031] Figure 6 This is a schematic diagram of a conveyor belt fire hazard assessment system based on surface element analysis, provided according to some embodiments of this application. Detailed Implementation

[0032] The present application will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. In fact, those skilled in the art will understand that modifications and variations can be made to the present application without departing from the scope or spirit of the present application. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention should fall within the scope of protection of the embodiments of the present invention.

[0033] During long-term operation, coal mine conveyor belts experience surface wear due to continuous friction with components such as idlers and drums. This leads to significant changes in their microstructure and chemical composition, affecting their thermal decomposition behavior and flame-retardant properties. Current technologies for conveyor belt fire monitoring primarily rely on characteristic signals during the fire's occurrence (such as...). The system will detect and alarm if the concentration of a marker gas increases abnormally or the local temperature rises sharply.

[0034] Such methods are essentially response mechanisms based on "after-the-fact" (after a fire occurs) or "during-the-fire" (during a fire) conditions, lacking a quantitative assessment of the evolution of fire risk caused by wear and tear on the conveyor belt throughout its entire life cycle. For example, existing technologies typically use similar simulation experiments or numerical simulations to reveal the temperature field distribution, marker gas migration patterns, and image characteristics during a fire, and then design the layout of downhole monitoring systems and establish early warning models based on the obtained patterns.

[0035] However, regardless of whether the monitoring system layout scheme or early warning model is designed using similar simulation experiments or numerical simulation methods, the early warning mechanism suffers from a significant lag. Currently, the vast majority of methods are based on detecting signs of an already occurring fire, such as marker gases (…). (e.g., excessive concentration of gas or temperature) or a rapid increase in local temperature. This mechanism essentially only triggers the alarm after sufficient conditions for a fire have been met, or even after it has begun to develop. In special environments such as high-gas mines, the disaster process is extremely rapid. Current technology relies on the physicochemical signals (such as gas and temperature) generated when a fire has already occurred or is about to occur. There is a time delay from detection to alarm. In high-risk locations such as high-gas mines, the disaster develops rapidly, and the window from alarm to loss of control is extremely short. Personnel often find it difficult to effectively handle the situation within this very short time window, which can easily lead to the escalation of the accident and poses an extremely high risk.

[0036] Secondly, existing methods, whether similarity simulation experiments or numerical simulations, focus on reproducing and summarizing patterns of phenomena after a fire occurs. They cannot be directly used for real-time early warning and lack the ability to assess the dynamic fire risk of conveyor belts throughout their entire life cycle. Current technologies typically treat conveyor belts as static objects, ignoring the dynamic evolution of their fire hazard with usage time, wear levels, load conditions, and maintenance status. Therefore, early diagnosis and predictive warning of fire risks at different service stages of conveyor belts are impossible; responses are only reactive after risks accumulate to a critical state.

[0037] In addition, the underground environment is complex. Dust, water vapor, and equipment exhaust gases can easily pollute and interfere with the marker gas and optical sensors, leading to frequent false alarms and reducing the reliability and availability of the system. Moreover, existing methods mostly rely on a single parameter (such as a certain gas) for judgment. Point sensors cannot fully cover the entire conveyor belt, resulting in blind spots in detection and early warning, and making it easy to miss or delay alarms.

[0038] Based on this, this embodiment provides a method for assessing the fire hazard of conveyor belts based on surface elemental analysis. By constructing a quantitative index characterizing the degree of surface degradation of the conveyor belt—the degradation degree index—and establishing a predictive model between the degradation degree index and key combustion behavior parameters of conveyor belt fires, early diagnosis and classification of conveyor belt fire risks can be achieved. This method can accurately assess the quantitative relationship between conveyor belt wear and fire hazard at an early stage, which is of great significance for predictive maintenance and fire prevention. Figures 1 to 5 As shown, the method includes:

[0039] Step S101: The surface components of the target conveyor belt during wear time The content change was used to calculate the wear time of the target conveyor belt. The degradation degree index.

[0040] In this embodiment, the surface element content of the target conveyor belt is determined using an energy dispersive spectroscopy (EDS) instrument. Specifically, the usage time of the target conveyor belt is measured. The content of carbon, oxygen, and chlorine on the surface of the target conveyor belt after wear, as well as the content of carbon, oxygen, and chlorine on the surface of the target conveyor belt in its initial state (i.e., before wear), are used to calculate the wear time of the target conveyor belt. The degradation degree index.

[0041] For PVC and PVG conveyor belts, degradation mainly occurs through the removal of hydrogen chloride (H2O). (Bond cleavage) begins, releasing and directly reduce Content; In this process, the oxidation damage of the target conveyor belt occurs subsequently or simultaneously. Oxygen enters through microcracks and defect sites caused by wear, leading to the formation of oxygen-containing functional groups (such as carbonyl and hydroxyl groups) on the carbon backbone. Therefore, by changing the ratio of surface carbon to oxygen, rather than simply changing the oxygen content, the impact of material loss or localized carbonization of the target conveyor belt matrix is ​​effectively reduced, highlighting the oxidation specificity of the target conveyor belt.

[0042] Specifically, through the constructed degradation degree index model:

[0043]

[0044] Calculate the wear time of the target conveyor belt Degradation index In the formula, The target conveyor belt at wear time The surface content of chlorine, carbon, and oxygen elements. These are the initial elemental contents of chlorine, carbon, and oxygen on the surface of the target conveyor belt, respectively. The degradation weighting coefficient of the target conveyor belt affected by the dechlorination reaction. The degradation weighting coefficient is the factor by which the target conveyor belt is affected by the oxidation reaction.

[0045] By calculating the wear time of the target conveyor belt The degradation degree index fully reflects the loss of flame retardant (chlorine) by utilizing the change in chlorine content on the surface of the target conveyor belt. It uses the change in the ratio of carbon to oxygen on the surface of the target conveyor belt, rather than simply the change in oxygen content, to more accurately reveal the material oxidation and degradation process of the target conveyor belt, effectively reducing interference from carbonization or matrix loss of the target conveyor belt.

[0046] Step S102, in response to the target conveyor belt during wear time The degradation index was verified for reliability by measuring the wear time of the target conveyor belt. The degradation degree index was used to calculate the wear rate of the target conveyor belt during the wear time using a constructed degradation and combustion prediction model. The fire risk index.

[0047] Furthermore, the mass loss of the target conveyor belt is used to assess the wear time of the target conveyor belt. The reliability of the degradation index was verified. First, the degradation degree index of the target conveyor belt was used. ( It is a positive integer. We constructed a degradation wear model of the target conveyor belt using wear samples with different wear gradients to predict the wear quality of the target conveyor belt.

[0048] Specifically, obtain from the target conveyor belt Wear samples with different wear gradients. For example, the obtained conveyor belt samples were uniformly polished using a flatbed grinder and standard sandpaper to ensure that the wear covered the entire surface of the conveyor belt sample. Mass loss was used as the control index for the degree of wear, and at least four wear gradients were set (e.g., for every reduction in mass...). Let each gradient be numbered. Then, the energy dispersive spectroscopy (EDS) was used to determine... The elemental contents of chlorine, carbon, and oxygen on the surface of wear samples with different wear gradients were calculated using a degradation degree index model. The degradation index of each wear sample under its respective wear gradient.

[0049] right After normalizing the degradation degree index and corresponding mass loss of wear samples with different wear gradients, a degradation wear model of the target conveyor belt was obtained by fitting a linear function. Next, samples from continuously operating coal mines were collected. Test the conveyor belt over time and calculate the continuous service life of the test conveyor belt. The degradation rate index over time is used to assess the continuous service life of the test conveyor belt through a degradation and wear model. The time-related mass loss is predicted, and the predicted mass loss of the test conveyor belt is compared with the actual mass loss obtained by weighing. If the error between the predicted mass loss and the actual mass loss is less than or equal to a preset mass threshold, the constructed degradation and wear model is deemed reliable and can be used to predict the mass loss of the target conveyor belt.

[0050] Furthermore, by using a degradation wear model, the wear time of the target conveyor belt was analyzed. The wear degree is predicted to obtain the predicted wear quality of the target conveyor belt; and the predicted wear quality of the target conveyor belt is compared with the wear time of the target conveyor belt. The measured mass loss at that time, for the target conveyor belt during wear time The reliability of the degradation index was verified. The predicted wear quality of the target conveyor belt was compared with the target conveyor belt's wear time. If the error of the measured mass loss at a given time is less than or equal to the mass threshold, then the target conveyor belt is determined to be at the wear time. The degradation degree index has been verified for reliability.

[0051] If the predicted wear quality of the target conveyor belt is different from the target conveyor belt at the wear time If the error of the measured mass loss exceeds the preset mass threshold, then the degradation weight coefficient in the degradation degree index model will be affected. Make corresponding adjustments ( ), recalculate the degradation index of the target conveyor belt and according to the adjusted degradation weighting coefficient. The degradation and wear model is updated, and the wear quality of the target conveyor belt is re-predicted and compared. This process is repeated cyclically until the target conveyor belt reaches the wear time target. The degradation degree index has been verified for reliability.

[0052] In this embodiment, combustion test samples of multiple wear gradients of the target conveyor belt are obtained and their degradation degree indices are calculated respectively. The edges of the combustion test samples are covered with aluminum foil to limit the edge burning effect. Combustion tests are conducted on multiple combustion test samples under the same heat radiation flux using a cone calorimeter. The combustion test parameters of the combustion test samples are obtained (including: peak heat release rate, time to reach peak heat release rate, total heat release, and fire growth index). The degradation degree index of the combustion test samples is regressed with the combustion test parameters to establish a degradation combustion prediction model of the target conveyor belt and quantitatively characterize the impact of the gradual degradation of the conveyor belt on the fire behavior of the conveyor belt.

[0053] Furthermore, the constructed degradation-combustion prediction model was validated through combustion experiments on a sample conveyor belt continuously in operation underground in a coal mine. Specifically, combustion experiments were conducted on the sample conveyor belt to obtain measured values ​​of the peak heat release rate, time to reach the peak heat release rate, total heat release, and fire growth index. These measured values ​​were then compared with the predicted values ​​obtained from the degradation-combustion prediction model. If the error between the two values ​​was within a reasonable range, the constructed degradation-combustion prediction model was considered reasonable; otherwise, the degradation weight coefficient was adjusted. Adjustments were made to update the degradation degree index model and the degradation combustion prediction model until the error between the measured combustion value of the sample conveyor belt and the predicted value obtained by the degradation combustion prediction model was less than or equal to the preset combustion error threshold.

[0054] Finally, based on the target conveyor belt's wear time The degradation degree index, which has passed reliability verification, is used to calculate the wear time of the target conveyor belt using a constructed degradation and combustion prediction model. The fire risk index. The degradation combustion prediction model is as follows:

[0055]

[0056] In the formula, For the target conveyor belt during wear time The time to reach peak heat release rate when a fire occurs. For the target conveyor belt during wear time Fire growth index during a fire. For the target conveyor belt during wear time Total heat release during a fire; All of these are fitting constants determined by regression analysis; For the target conveyor belt during wear time The degradation degree index.

[0057] In this embodiment, for PVC conveyor belts, in the early stage of degradation, dechlorination leads to a decrease in flame retardancy and an increase in peak heat release rate. After exceeding a certain critical value, the loss of combustible material becomes the dominant factor, and the peak heat release rate decreases instead. For PVG conveyor belts, due to the thicker protective layer, the degradation degree index and the peak heat release rate show a significant negative correlation, indicating that as wear intensifies, the consumption of flame retardant dominates its combustion behavior.

[0058] In this embodiment, a characteristic index model is constructed to quantitatively characterize the wear and degradation degree of conveyor belts. Surface elemental analysis is used to quantify the chemical nature of conveyor belt wear, rather than traditional physical dimensional measurements. This effectively reflects the loss of flame retardant (chlorine) and reveals the oxidative degradation process of the conveyor belt material at a deeper level, reducing interference from carbonization or matrix loss. It also avoids interference from environmental factors such as underground dust and humidity, which are common in traditional assessment methods, thus effectively improving the reliability of the assessment. Furthermore, the degradation degree index of the conveyor belt is directly correlated with conveyor belt wear and fire hazard. The degradation degree index is used to predict conveyor belt wear and fire risk, achieving a quantitative, graded, and real-time assessment of conveyor belt fire risk.

[0059] Compared with traditional physical signals after or during a fire (such as...) Compared to reactive or reactive response mechanisms that rely on detecting gas concentration and temperature, this embodiment constructs a degradation index based on changes in the surface chemical element content of the target conveyor belt. It then establishes a quantitative prediction model between this degradation index and fire risk, transforming conveyor belt fire assessment from traditional passive detection to proactive prediction. This allows for early, quantitative assessment of conveyor belt fire risk under different wear conditions before a fire occurs. On one hand, it enables pre-fire diagnosis of the conveyor belt's condition, achieving early diagnosis and classification of fire risk, overcoming the lag of traditional early warning methods and gaining valuable time for preventative maintenance and emergency response. On the other hand, it allows for full life-cycle assessment of the conveyor belt, enabling real-time and accurate assessment of the risk evolution caused by increased wear and tear over time. Furthermore, the assessment process requires no destructive testing, only non-contact measurement using an energy dispersive spectrometer, effectively reducing assessment costs and improving operational efficiency.

[0060] This embodiment also provides a conveyor belt fire hazard assessment system based on surface element analysis. The fire risk prediction of a target conveyor belt is performed using the conveyor belt fire hazard assessment system based on surface element analysis from any of the above embodiments. Figure 6 As shown, the system includes:

[0061] Element degradation calculation unit 601 is configured to calculate the surface composition elements of the target conveyor belt during wear time. The content change was used to calculate the wear time of the target conveyor belt. The degradation degree index;

[0062] Fire risk prediction unit 602 is configured to respond to the target conveyor belt during wear time. The degradation index was verified for reliability by measuring the wear time of the target conveyor belt. The degradation degree index was used to calculate the wear rate of the target conveyor belt during the wear time using a constructed degradation and combustion prediction model. The fire risk index.

[0063] The conveyor belt fire hazard assessment system based on surface element analysis provided in this embodiment can realize the steps and processes of the conveyor belt fire hazard assessment method based on surface element analysis in any of the above embodiments, and achieve the same technical effect, which will not be described in detail here.

[0064] In the description of this embodiment, it should be understood that the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0065] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A conveyor belt fire hazard assessment method based on surface element analysis, characterized by, Comprising: By means of the content variation of surface constituent elements of the target conveyor belt at the wear time based on the constructed degradation degree index model: Degradation degree index of a target conveyor belt at a wear time ; wherein, a degradation weight coefficient of the target conveyor belt affected by the dechlorination reaction, and​​​​​ In response to an error between the predicted mass loss of the target conveyor belt and the actual mass loss of the target conveyor belt at the wear time being less than or equal to a preset mass threshold, determining a degradation degree index of the target conveyor belt at the wear time In response to an error between the predicted mass loss of the target conveyor belt and the actual mass loss of the target conveyor belt at the wear time being less than or equal to a preset mass threshold, determining a degradation degree index of the target conveyor belt at the wear time In response to an error between the predicted mass loss of the target conveyor belt and the actual mass loss of the target conveyor belt at the wear time being less than or equal to a preset mass threshold, determining a degradation degree index of the target conveyor belt at the wear time In response to an error between the predicted mass loss of the target conveyor belt and the actual mass loss of the target conveyor belt at the wear time being less than or equal to a preset mass Computing a fire risk index for a target conveyor belt at a wear time of the target conveyor belt; wherein the time to peak heat release rate when a fire occurs, the time to peak heat release rate when a fire occurs, the time to peak heat release rate when a fire occurs, the fire growth index when a fire occurs, the time to peak heat release rate when a fire occurs, the total heat release when a fire occurs; are fitting constants; the degradation index of the target conveyor belt at the time of wear, the degradation index of the target conveyor belt at the time of wear.

2. The method of claim 1, wherein, Through the target conveyor belt A degradation wear model of the target conveyor belt was constructed using wear samples with different wear gradients to predict the wear quality of the target conveyor belt; among them, It is a positive integer. ; and according to the predicted wear quality of the target conveyor belt and the mass loss of the target conveyor belt at the wear time , the degradation degree index of the target conveyor belt at the wear time is verified for reliability.

3. The method of claim 2, wherein, Acquiring target conveyor belt Wear samples of different wear gradients, and determining the element content of chlorine element, carbon element and oxygen element on the surface of the wear samples by an energy spectrometer Wear samples of different wear gradients, and determining the element content of chlorine element, carbon element and oxygen element on the surface of the wear samples by an energy spectrometer Degradation degree indexes of the wear samples under respective wear gradients right After normalizing the degradation degree index and corresponding mass loss of wear samples with different wear gradients, the degradation wear model of the target conveyor belt is obtained by fitting a linear function.

4. The method of claim 2, wherein, By degrading the wear model, the wear degree of the target conveyor belt at the wear time is predicted to obtain the predicted wear quality of the target conveyor belt.

5. A conveyor belt fire hazard assessment system based on surface element analysis, characterized by, The surface element analysis-based fire risk assessment method for a conveyor belt according to any one of claims 1-4 is used to predict the fire risk of a target conveyor belt, and the system comprises: an element degradation calculation unit configured to calculate a degradation degree index of the target conveyor belt at the abrasion time by a change in content of a surface constituent element of the target conveyor belt at the abrasion time of the target conveyor belt at the abrasion time​ A fire risk prediction unit configured to calculate a fire risk index of a target conveyor belt at a degradation time by a reliability verification through a degradation degree index of the target conveyor belt at the degradation time A fire risk prediction unit configured to calculate a fire risk index of a target conveyor belt at a degradation time by a reliability verification through a degradation degree index of the target conveyor belt at the degradation time A fire risk prediction unit configured to calculate a fire risk index of a target conveyor belt at a degradation time by a reliability verification through a degradation degree index of the target conveyor belt at the degradation time A fire risk prediction unit configured to calculate a fire risk index of a target conveyor belt at a degradation time by a reliability verification through a degradation degree index of the target conveyor belt at the degradation time

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