Intelligent mine belt conveyor unattended system based on automatic control technology

Abstract

The invention relates to the technical field of conveying equipment, in particular to an intelligent mine belt conveyor unattended system based on an automatic control technology. The system comprises a data acquisition module used for acquiring tension data and pressure data of each carrier roller; the local mutability acquisition module is used for acquiring the local difference of the pressure data acquired by each carrier roller and the local difference of the tension data acquired by each carrier roller; the confidence degree of local mutability of each carrier roller is obtained; according to the confidence degree of the local mutability of each carrier roller and the local difference between the tension data and the pressure data collected by each carrier roller, the local mutability of each carrier roller is obtained; the abnormal degree obtaining module is used for obtaining the abnormal degree of each carrier roller according to the local mutability of each carrier roller, and the abnormal early warning module is used for conducting abnormal judgment on each carrier roller according to the abnormal degree of each carrier roller.

Description

Technical Field

[0001] The present invention generally relates to the technical field of conveying equipment. More specifically, the present invention relates to an unattended system for intelligent mine belt conveyors based on automation control technology. Background Art

[0002] As an important material conveying equipment in mines, the stability of belt conveyors directly affects the production efficiency and safety of mines. However, traditional belt conveyor monitoring systems generally rely on manual attendance. Manual inspection not only increases labor costs but also is prone to human errors, failing to detect potential equipment faults in a timely manner, which may lead to safety accidents or production interruptions. Abnormal conditions of belt conveyors, such as excessive or too small belt tension, uneven idler load, belt deviation, material accumulation, etc., are often the main causes of belt conveyor failures. Traditional belt conveyor monitoring methods mainly rely on single mechanical detection devices, such as temperature sensors, vibration sensors, etc., and it is difficult to accurately identify various complex fault types. Therefore, there is an urgent need for a system that can collect multi-dimensional data in real time and perform intelligent analysis to comprehensively improve the operation monitoring ability of belt conveyors.

[0003] Traditional anomaly detection algorithms can only detect data with a high degree of outlier in the obtained data. During the normal operation of belt conveyors, due to the presence of ore on the belt conveyor, the collected data will change locally; if the belt conveyor has an anomaly (such as idler jamming), it will also cause local changes in the collected data. Therefore, traditional anomaly detection algorithms cannot effectively distinguish between the two, resulting in inaccurate anomaly monitoring results. Summary of the Invention

[0004] To solve the technical problem that traditional anomaly detection algorithms cannot effectively distinguish the local changes in the data collected when there is ore on the belt conveyor and the local changes in the data collected when the belt conveyor has an anomaly (such as idler jamming), resulting in inaccurate anomaly monitoring results, the present invention proposes an unattended system for intelligent mine belt conveyors based on automation control technology. The system includes the following modules: A data acquisition module for acquiring the tension data and pressure data of each idler. A local mutation acquisition module for obtaining the local differences in the pressure data collected by each idler and the local differences in the tension data collected by each idler; obtaining the confidence level of the local mutation of each idler according to the consistency of the pressure data and tension data collected by each idler; obtaining the local mutation of each idler based on the local differences and confidence levels. An anomaly degree acquisition module for obtaining the anomaly degree of each idler , represents the anomaly degree of the i-th idler; represents the local mutation of the i-th idler; represents the mean of the local mutability of all the surrounding idlers of the i-th idler; represents the standard deviation of the local mutability of all the surrounding idlers of the i-th idler; norm() represents the normalization function; exp() represents the exponential function with the natural constant as the base; Anomaly warning module, used to make an anomaly judgment on each idler according to the degree of anomaly of each idler.

[0005] Preferably, the obtaining of the local differences of the pressure data collected by each idler includes: Obtaining the neighboring idlers of each idler; ; In the formula, represents the local difference of the pressure data collected by the i-th idler; represents the number of neighboring idlers of the i-th idler; represents the value of the pressure data collected by the i-th idler; represents the value of the pressure data collected by the a-th neighboring idler of the i-th idler; || represents the absolute value symbol; norm() represents the normalization function; according to the obtaining method of the local difference of the pressure data collected by the i-th idler, obtain the local difference of the tension data collected by the i-th idler.

[0006] The greater the local differences of the pressure data and the tension data collected by each idler, the greater the local mutability of each idler.

[0007] Preferably, the obtaining of the neighboring idlers of each idler includes: Preset the number N of adjacent idlers, and take the N idlers adjacent to the left of the i-th idler and the N idlers adjacent to the right of the i-th idler as the neighboring idlers of the i-th idler.

[0008] Facilitate subsequent analysis of the pressure data and the tension data collected by each idler and its neighboring idlers.

[0009] Preferably, the obtaining of the confidence level of the local mutability of each idler includes: ; In the formula, represents the confidence level of the local mutability of the i-th idler; represents the value of the pressure data collected by the i-th idler; represents the value of the tension data collected by the i-th idler; represents the standard deviation of the values of the pressure data collected by all idlers; represents the standard deviation of the values of the tension data collected by all idlers; || represents the absolute value symbol; exp() represents the exponential function with the natural constant as the base.

[0010] Preferably, obtaining the local mutation of each idler includes: ; In the formula, represents the local mutation of the i-th idler; represents the confidence level of the local mutation of the i-th idler; represents the local difference of the pressure data collected by the i-th idler; represents the local difference of the tension data collected by the idler.

[0011] The greater the local mutation of each idler, the greater the degree of abnormality.

[0012] Preferably, obtaining the surrounding idlers includes: Presetting the number of idlers M, and taking the M idlers adjacent to the left of the i-th idler and the M idlers adjacent to the right of the i-th idler as the surrounding idlers of the i-th idler.

[0013] Preferably, judging the abnormality of each idler according to the degree of abnormality of each idler includes: Presetting a warning threshold T1. If the degree of abnormality of any idler is greater than the abnormality degree threshold T1, notify the staff to repair the idler on the belt conveyor.

[0014] Make the warning result more accurate.

[0015] Preferably, collecting the tension data and pressure data of each idler includes: Install a pressure sensor near the bearing of any idler of the belt conveyor or on the idler support frame, arrange tension sensors at both ends where the idler contacts the belt, and at any moment during the operation of the belt conveyor, collect the pressure data and tension data of the idler to obtain the pressure data and tension data of each idler.

[0016] The present invention has the following technical effects: The present invention analyzes the local mutation difference between any idler and its surrounding idlers and the mean value of the local mutations of its surrounding idlers to obtain the degree of abnormality of the idler, effectively distinguishing the normal operation state and abnormal operation state of the belt conveyor, thereby making the warning result more accurate; further, analyzing the difference in tension data and pressure data collected by each idler and its neighboring idlers, obtaining the local difference in pressure data collected by each idler and the local difference in tension data collected by each idler, and analyzing the change of the pressure data and tension data of each idler to calculate the confidence level, and then obtaining the local mutation of each idler according to the mean value of the local differences of the pressure data and tension data collected by each idler and the confidence level, improving the accuracy of the local mutation, and further making the calculation result of the subsequent degree of abnormality more accurate. Brief Description of the Drawings

[0017] By referring to the following detailed description in conjunction with the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become readily understandable. In the drawings, several embodiments of the present invention are shown in an exemplary but non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein: Figure 1 FIG. is a system block diagram of an unattended system for a smart mine belt conveyor based on automation control technology according to an embodiment of the present invention. Detailed Embodiments

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0019] It should be understood that when terms such as "first" and "second" are used in the claims, specifications, and drawings of the present invention, they are only used to distinguish different objects and not to describe a specific order. The terms "including" and "comprising" used in the specifications and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0020] The present invention provides an unattended system for a smart mine belt conveyor based on automation control technology. As Figure 1 shown, an unattended system for a smart mine belt conveyor based on automation control technology includes Module 101 - Module 104, which will be specifically described below.

[0021] The data acquisition module 101 is used to acquire the tension data and pressure data of each idler.

[0022] It should be noted that the idler is a key component in the belt conveyor for supporting the conveyor belt and bears the weight of the belt and the material. During the operation of the belt conveyor, the idler is affected by various factors such as the material weight, conveying speed, and belt tension, and may experience uneven load changes, and even wear, damage, or jamming, which will affect the normal operation of the belt conveyor. The belt tension is also one of the key factors affecting the normal operation of the belt conveyor. Excessive belt tension will cause the belt to be overstretched and damaged, while too small tension may cause the belt to slip, unstable material conveying, and even belt deviation and belt dropping. Therefore, the present invention needs to perform abnormal monitoring on the idler pressure and belt tension of the belt conveyor.

[0023] During the operation of the belt conveyor, the idler rolls bear the weight of the belt and the material. Therefore, the pressure sensor can sense the pressure borne by the idler rolls. When the belt conveyor operates unevenly or abnormally, the pressure data collected by the sensor will change; the tension sensor can obtain the tension data of the belt by measuring the elongation, deformation or tension borne by the belt, and the tension data of the belt changes with the different forces on the belt.

[0024] In the embodiment of the present invention, a pressure sensor is installed near any idler roll bearing of the belt conveyor or on the idler roll support frame, and tension sensors are arranged at both ends where the idler roll contacts the belt. At any moment during the operation of the belt conveyor, the pressure data and tension data of the idler roll are collected. Similarly, the pressure data and tension data of each idler roll are collected.

[0025] It should be noted that a tension sensor and a pressure sensor are arranged on each idler roll of the belt conveyor.

[0026] The local mutation acquisition module 102 is used to obtain the local differences of the pressure data collected by each idler roll and the local differences of the tension data collected by each idler roll; obtain the confidence level of the local mutation of each idler roll according to the consistency of the pressure data and tension data collected by each idler roll; obtain the local mutation of each idler roll according to the confidence level of the local mutation of each idler roll and the local differences of the tension data and pressure data collected by each idler roll.

[0027] It should be noted that traditional anomaly detection algorithms can only detect data with a high degree of outlier in the obtained data. During the normal operation of the belt conveyor, due to the presence of ore on the belt conveyor, the collected data will change locally; if the belt conveyor has an anomaly (such as idler roll jamming), it will also cause local changes in the collected data. Therefore, traditional anomaly detection algorithms cannot effectively distinguish between the two, resulting in inaccurate anomaly monitoring results; it is known that during the operation of the belt conveyor, the pressure borne by the idler roll and the belt tension are key factors affecting the stability of the belt conveyor, and the change in the size of the ore material carried on the belt conveyor or the reason for idler roll jamming will cause local changes in the pressure data and tension data collected by the idler roll. Therefore, the present invention first combines the differences in the pressure data collected by each idler roll and its neighboring idler rolls to obtain the local differences of the pressure data collected by each idler roll; similarly, obtain the local differences of the tension data collected by each idler roll.

[0028] In the embodiment of the present invention, obtain the local differences of the pressure data collected by each idler roll: The N rollers adjacent to the left of the ith roller and the N rollers adjacent to the right of the ith roller are taken as the neighborhood rollers of the ith roller; in the embodiments of the present invention, the preset number N of adjacent rollers is 2, and in other embodiments, the implementer can preset the value of N according to the specific implementation situation; ; wherein, represents the local difference of the pressure data collected by the ith roller; represents the number of neighborhood rollers of the ith roller; represents the pressure data value collected by the ith roller; represents the pressure data value collected by the ath neighborhood roller of the ith roller; || represents the absolute value symbol; norm() represents the normalization function; if the difference between the pressure data values collected by the ith roller and its neighborhood rollers is smaller, the local difference of the pressure data collected by the ith roller is smaller, and at this time, the local mutability of the ith roller is smaller.

[0029] According to the method for obtaining the local difference of the pressure data collected by the ith roller, obtain the local difference of the tension data collected by the ith roller.

[0030] It should be noted that, it is known that the local differences of the pressure data collected by each roller and the local differences of the tension data collected by each roller are obtained. If the average value of the local differences of the pressure data and the tension data collected by any roller is larger, it indicates that the local mutability of this roller is larger. However, there may be noise effects in the pressure data and the tension data collected by using the pressure sensor and the tension sensor. Therefore, in order to reduce the influence of noise data, the present invention analyzes the consistency between the pressure data value and the tension data value collected by each roller, obtains the confidence level of the local mutability of each roller, and further optimizes the accuracy of the local mutability of each roller.

[0031] In the embodiments of the present invention, obtain the confidence level of the local mutability of the ith roller: ; wherein, represents the confidence level of the local mutability of the ith roller; represents the pressure data value collected by the ith roller; represents the tension data value collected by the ith roller; represents the standard deviation of the pressure data values collected by all rollers; represents the standard deviation of the tension data values collected by all rollers; || represents the absolute value symbol; exp() represents the exponential function with the natural constant as the base; The smaller the difference of, the more consistent the performance of the ith roller in terms of pressure data and tension data, and the higher the confidence level of the local mutation degree of this roller; It should be noted that the reason for obtaining the ratio of the tension data value collected by the i-th idler to the standard deviation of the tension data values collected by all idlers and the ratio of the pressure data value collected by the i-th idler to the standard deviation of the pressure data values collected by all idlers is to eliminate the influence of the different dimensions of the pressure data and the tension data on the calculation results, so as to make the calculation result of the difference between the two more accurate, and further make the confidence level of the local mutation of the i-th idler more accurate.

[0032] Obtain the local mutation of the i-th idler: ; In the formula, represents the local mutation of the i-th idler; represents the confidence level of the local mutation of the i-th idler; represents the local difference of the pressure data collected by the i-th idler; represents the -th local difference of the tension data collected by the idler; if the mean value of the local differences between the pressure data and the tension data collected by this idler is larger, and the performance of the i-th idler in terms of pressure data and tension data is more consistent, that is, the confidence level of the local mutation of the i-th idler is larger, then the local mutation of this idler is higher.

[0033] The abnormality degree acquisition module 103 is used to obtain the abnormality degree of each idler according to the local mutation of each idler.

[0034] It should be noted that when any idler has a jamming phenomenon, due to the sudden change of the tension data and the pressure data collected by itself, the local mutation of this idler is relatively high, but the surrounding idlers are not directly affected, so the local mutation of the surrounding idlers will not increase. At this time, if the difference in the local mutation of this idler compared with that of its surrounding idlers is large, and the mean value of the mutations of the surrounding idlers of this idler is small, it indicates that the abnormality is caused by the abnormal situation of this idler itself, so the abnormality degree of this idler is large; During the normal transportation of ore by the belt conveyor, if the ore distribution is too small, it will cause changes in the pressure data and the tension data of any idler, that is, the local mutation of this idler becomes larger. In this case, the surrounding idlers will also be affected similarly, resulting in a corresponding increase in the local mutation. Therefore, if the difference in the local mutation between this idler and its surrounding idlers is small, and the mean value of the mutations of the surrounding idlers of this idler is large, it means that this may be a normal and small-scale fluctuation, rather than a serious failure of a single idler alone, so the abnormality degree of this idler is small.

[0035] In the embodiment of the present invention, the surrounding rollers of each roller are obtained: a preset number of rollers M. The M rollers adjacent to the left of the i-th roller and the M rollers adjacent to the right of the i-th roller are used as the surrounding rollers of the i-th roller. In the embodiment of the present invention, the preset number of rollers M = 10. In other embodiments, the implementer can preset the value of M according to the specific implementation.

[0036] Obtain the abnormality degree of the i-th roller: ; In the formula, represents the abnormality degree of the i-th roller; represents the local mutability of the i-th roller; represents the mean value of the local mutabilities of all the surrounding rollers of the i-th roller; represents the standard deviation of the local mutabilities of all the surrounding rollers of the i-th roller; norm() represents the normalization function; exp() represents the exponential function with the natural constant as the base; represents the difference between the local mutability of the i-th roller and the mean value of the local mutabilities of all its surrounding rollers. The larger its value, the higher the mutability of the pressure data and tension data collected by the i-th roller, and the higher the abnormality degree of the i-th roller; The smaller the value of is, it indicates that the fluctuation of the local mutabilities of all the surrounding rollers of the i-th roller is small. At this time,

[0037] is more accurate. If the local mutability of the i-th roller is relatively large compared to its surrounding rollers, and the mean value of the mutabilities of all its surrounding rollers is relatively small, it indicates that an abnormal situation (such as roller jamming) may occur at the i-th roller at this time;

[0038] The abnormality warning module 104 is used to perform abnormality judgment on each roller according to the abnormality degree of each roller.

[0039] In the embodiment of the present invention, a preset warning threshold T1 is set. If the abnormality degree of any roller is greater than the abnormality degree threshold T1, at this time, the system gives a warning to the staff, and it is necessary to repair the roller on the belt conveyor. In the embodiment of the present invention, the preset warning threshold T1 = 0.75. In other embodiments, the implementer can preset the value of the warning threshold T1 according to the specific implementation situation.

[0040] Although this specification has shown and described multiple embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will envision many changes, alterations, and alternative ways without departing from the spirit and scope of the present invention. It should be understood that various alternatives of the embodiments of the present invention described herein may be employed in practicing the present invention.

[0041] The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention shall be covered within the protection scope of the present invention.

Claims

1. An unattended system for a smart mine belt conveyor based on automation control technology, characterized in that, It includes the following modules: A data acquisition module, which is used to acquire the tension data and pressure data of each idler roller; A local mutation acquisition module, which is used to obtain the local differences of the pressure data collected by each idler roller and the local differences of the tension data collected by each idler roller; according to the consistency of the pressure data and tension data collected by each idler roller, obtain the confidence level of the local mutation of each idler roller; based on the local differences and the confidence level, obtain the local mutation of each idler roller; Anomaly degree acquisition module, used to acquire the anomaly degree of each idler , represents the anomaly degree of the i-th idler; represents the local mutability of the i-th idler; represents the mean value of the local mutabilities of all the surrounding idlers of the i-th idler; represents the standard deviation of the local mutabilities of all the surrounding idlers of the i-th idler; norm() represents the normalization function; exp() represents the exponential function with the natural constant as the base; An abnormal warning module, which is used to perform abnormal judgment on each idler roller according to the abnormal degree of each idler roller.

2. The unattended system for a smart mine belt conveyor based on automation control technology according to claim 1, characterized in that, The obtaining of the local differences of the pressure data collected by each idler roller includes: Obtaining the neighboring idler rollers of each idler roller; ； In the formula, represents the local difference of the pressure data collected by the i-th idler; represents the number of neighboring idlers of the i-th idler; represents the pressure data value collected by the i-th idler; represents the pressure data value collected by the a-th neighboring idler of the i-th idler; || represents the absolute value symbol; norm() represents the normalization function; according to the method for obtaining the local difference of the pressure data collected by the i-th idler, obtain the local difference of the tension data collected by the i-th idler.

3. The unattended system for the intelligent mine belt conveyor based on the automatic control technology according to claim 2, characterized in that, The obtaining of the neighboring idler rollers of each idler roller includes: Presetting the number N of adjacent idler rollers, and taking the N idler rollers adjacent to the left of the i-th idler roller and the N idler rollers adjacent to the right of the i-th idler roller as the neighboring idler rollers of the i-th idler roller.

4. The unattended system for the intelligent mine belt conveyor based on the automatic control technology according to claim 1, wherein The obtaining of the confidence level of the local mutation of each idler roller includes: ； Wherein, represents the confidence level of the local mutation of the i-th idler; represents the pressure data value collected by the i-th idler; represents the tension data value collected by the i-th idler; represents the standard deviation of the pressure data values collected by all idlers; represents the standard deviation of the tension data values collected by all idlers; || represents the absolute value symbol; exp() represents the exponential function with the natural constant as the base.

5. The unattended system for a smart mine belt conveyor based on automation control technology according to claim 1, wherein, The obtaining of the local mutation of each idler roller includes: ； In the formula, represents the local mutation of the i-th idler; represents the confidence level of the local mutation of the i-th idler; represents the local difference of the pressure data collected by the i-th idler; represents the local difference of the tension data collected by the idler.

6. The unattended system for a smart mine belt conveyor based on automation control technology according to claim 1, wherein The obtaining of the surrounding idler rollers includes: Presetting the number M of idler rollers, and taking the M idler rollers adjacent to the left of the i-th idler roller and the M idler rollers adjacent to the right of the i-th idler roller as the surrounding idler rollers of the i-th idler roller.

7. The unattended system for a smart mine belt conveyor based on automation control technology according to claim 1 or 5, characterized in that, The performing of abnormal judgment on each idler roller according to the abnormal degree of each idler roller includes: Presetting a warning threshold T1. If the abnormal degree of any idler roller is greater than the abnormal degree threshold T1, notify the staff to repair the idler roller on the belt conveyor.

8. The unattended system for a smart mine belt conveyor based on automation control technology according to claim 1, characterized in that, The acquisition of the tension data and pressure data of each idler roller includes: Installing a pressure sensor near the bearing of any idler roller on the belt conveyor or on the idler roller support frame, arranging tension sensors at both ends where the idler roller contacts the belt, and at any moment during the operation of the belt conveyor, acquiring the pressure data and tension data of the idler roller to obtain the pressure data and tension data of each idler roller.

Images