Detection method and device of adhesive tape machine, computer readable storage medium and adhesive tape machine

Abstract

The application provides a detection method and device of a tape machine, a computer readable storage medium and the tape machine. The method comprises: obtaining running data of the tape machine in a predetermined time period, the running data being collected by a target device, the target device being installed on one side of the tape machine, and the running data comprising vibration data and impact pulse data; determining a characteristic parameter according to at least the running data, the characteristic parameter at least comprising displacement of the running data; and determining whether the tape machine is abnormal according to the characteristic parameter. In the scheme, a unified standardized detection scheme is provided, and human factors do not affect the detection result because human evaluation is not required. In addition, the vibration data and the impact pulse data are combined to determine the characteristic parameter, and the state of the tape machine is detected by using the characteristic parameter. Therefore, the tape machine can be detected in various scenarios by using the scheme, and the efficiency of evaluating the health state of the tape machine is improved.

Description

Technical Field

[0001] This application relates to the field of tape machine testing, and more specifically, to a tape machine testing method, apparatus, computer-readable storage medium, and tape machine. Background Technology

[0002] Currently, the health status of mining conveyor belts is mainly assessed manually. Vibration or temperature data is used as the basis for manual judgment based on experience. However, manual assessment is affected by factors such as the operating conditions of the conveyor belt, the experience of the assessor, external interference, and load conditions. Therefore, a standardized assessment cannot be obtained, and the results depend heavily on the individual skill level of the assessor. Different assessors will yield different results. As a result, the efficiency of manual assessment of the health status of conveyor belts is currently low. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, computer-readable storage medium, and tape machine for testing tape machines, in order to solve the problem of low efficiency in the prior art for manually assessing the health status of tape machines.

[0004] According to one aspect of the present invention, a detection method for a conveyor belt machine is provided, comprising: acquiring operating data of the conveyor belt machine within a predetermined time period, the operating data being collected using a target device installed on one side of the conveyor belt machine, the operating data including vibration data and impact pulse data; determining characteristic parameters based at least on the operating data, the characteristic parameters including at least the displacement of the operating data; and determining whether the conveyor belt machine is abnormal based on the characteristic parameters.

[0005] Optionally, at least the characteristic parameter is determined based on the operating data, including: obtaining the shaft diameter of the bearing of the conveyor belt and the rotational speed of the bearing of the conveyor belt; constructing a relationship based on the shaft diameter of the bearing of the conveyor belt and the rotational speed of the bearing of the conveyor belt; using the relationship to determine the change value of the influencing factor, the change value of the influencing factor changing with the change of the shaft diameter of the bearing of the conveyor belt and / or the rotational speed of the bearing of the conveyor belt; obtaining the difference between the operating data and the change value of the influencing factor, and determining the difference as the characteristic parameter.

[0006] Optionally, determining the change value of the influencing factor using the relationship includes: using the relationship: Determine the change value of the influencing factor, wherein, This indicates the change value of the influencing factor. The rotational speed of the bearing in the conveyor belt machine is indicated. The diameter of the shaft of the bearing of the conveyor belt machine is indicated.

[0007] Optionally, there are multiple feature parameters. Determining whether the tape machine is abnormal based on the feature parameters includes: obtaining the maximum value among the multiple feature parameters; obtaining the average value of a predetermined number of feature parameters; selecting multiple target feature parameters whose difference from the average value is less than a difference threshold; and determining a preset quantity based on the multiple target feature parameters; determining the tape machine to a first state when both the maximum value and the preset quantity are within a first predetermined range, wherein the tape machine is in a normal state when it is in the first state; determining the tape machine to a second state when the maximum value and / or the preset quantity are within a second predetermined range, and neither the maximum value nor the preset quantity is within a third predetermined range, wherein the tape machine is in an abnormal state with an abnormality level of first level when it is in the second state; and determining the tape machine to a third state when the maximum value and / or the preset quantity are within the third predetermined range, wherein the tape machine is in an abnormal state with an abnormality level of second level, wherein the abnormality level corresponding to the second level is greater than the abnormality level corresponding to the first level.

[0008] Optionally, before determining the feature parameters based at least on the operating data, the method further includes: acquiring relevant parameters of the conveyor belt machine, the relevant parameters including at least one of the following: kurtosis, skewness, crest, velocity, acceleration; constructing a first matrix and a second matrix based on the relevant parameters; generating a first sequence based on the first matrix and a second sequence based on the second matrix, wherein the first sequence includes multiple reference operating data, the reference operating data being data when the conveyor belt machine is in a normal state, and the second sequence includes multiple operating data; comparing the reference operating data of the first sequence and the operating data of the second sequence at the same time to obtain multiple comparison results, and if the sum of the comparison results exceeds a predetermined sum range, initially determining that the conveyor belt machine is abnormal.

[0009] Optionally, after determining whether the tape machine is abnormal based on the characteristic parameters, the method further includes: in the case that the tape machine is in an abnormal state, identifying the abnormal components, wherein the tape machine includes multiple of the components.

[0010] Optionally, in the case that the conveyor belt machine is in an abnormal state, determining the abnormal component includes: acquiring the operating data of multiple components in the conveyor belt machine; generating spectrum data based on the operating data; acquiring standard spectrum data of multiple components in the conveyor belt machine; determining the component whose difference between the spectrum data and the standard spectrum data is greater than a difference threshold as the target component, and determining the target component as the abnormal component.

[0011] According to another aspect of the present invention, a detection device for a conveyor belt machine is also provided, comprising: a first acquisition unit, configured to acquire operating data of the conveyor belt machine within a predetermined time period, the operating data being collected using a target device installed on one side of the conveyor belt machine, the operating data including vibration data and impact pulse data; a first determination unit, configured to determine a characteristic parameter based at least on the operating data, the characteristic parameter including at least the displacement of the operating data; and a second determination unit, configured to determine whether the conveyor belt machine is abnormal based on the characteristic parameter.

[0012] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program executes any one of the methods described.

[0013] According to another aspect of the present invention, a tape machine is also provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including methods for performing any one of the methods described.

[0014] In this embodiment of the invention, the operating data of the conveyor belt machine within a predetermined time period is first acquired. Then, characteristic parameters are determined based on the operating data. Finally, the presence or absence of an abnormality in the conveyor belt machine is determined based on the characteristic parameters. This solution proposes a unified and standardized detection method that eliminates the need for human evaluation, thus preventing human factors from affecting the detection results. Furthermore, by combining vibration data and impact pulse data, characteristic parameters are determined, and these parameters are used to detect the condition of the conveyor belt machine. This method can be applied to detect conveyor belt machines in various scenarios, thereby improving the efficiency of assessing the health status of the conveyor belt machine. Attached Figure Description

[0015] 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. In the drawings:

[0016] Figure 1A schematic flowchart of a detection method for a tape machine according to an embodiment of this application is shown;

[0017] Figure 2 A schematic diagram of the characteristic parameters is shown;

[0018] Figure 3 A schematic diagram illustrating the classification of feature parameters is shown;

[0019] Figure 4 A flowchart illustrating the initial identification of a conveyor belt malfunction is shown.

[0020] Figure 5 A schematic diagram of the structure of a detection device for a tape machine according to an embodiment of this application is shown. Detailed Implementation

[0021] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] It should be understood that when an element (such as a layer, film, region, or substrate) is described as being "on" another element, the element may be directly on the other element, or there may be an intermediate element present. Furthermore, in the specification and claims, when an element is described as being "connected" to another element, the element may be "directly connected" to the other element, or "connected" to the other element via a third element.

[0025] In some solutions, vibration thresholds from vibration data are used as a preliminary standard to determine whether a conveyor belt is functioning properly. When the detected vibration data exceeds the threshold, the spectral data is then manually analyzed, and combined with human experience, the machine's malfunction and fault level are judged. Temperature changes are also considered as a reference indicator for the analysts. However, this approach has the following drawbacks: 1. Because human experience plays a crucial role, standardized results cannot be formed, and different analysts will obtain different results; 2. Existing solutions lack transmissibility. Due to personnel changes or the departure of experienced conveyor belt operators, new staff need to accumulate experience again to inspect the conveyor belt, leading to low efficiency in manually assessing the machine's health.

[0026] As mentioned in the background section, the efficiency of manually assessing the health status of tape machines in the prior art is low. In order to solve the above problems, in a typical embodiment of this application, a method, apparatus, computer-readable storage medium, and tape machine for detecting tape machines are provided.

[0027] According to an embodiment of this application, a testing method for a tape machine is provided.

[0028] Figure 1 This is a flowchart of a testing method for a tape machine according to an embodiment of this application. Figure 1 As shown, the method includes the following steps:

[0029] Step S101: Obtain the operating data of the conveyor belt within a predetermined time period. The operating data is collected using a target device installed on one side of the conveyor belt. The operating data includes vibration data and impact pulse data.

[0030] Specifically, the target device can be a miniature shock and vibration data logger, such as the MSR 165 model. Of course, it is not limited to the above-mentioned devices. Any other feasible devices can be used to collect vibration data and shock pulse data. The distance between the target device and the conveyor belt can be within 100 meters. By combining the vibration data and shock pulse data, the condition of the conveyor belt can be determined more accurately.

[0031] After collecting the operational data, to ensure its accuracy, preprocessing can be performed. Preprocessing includes at least one of the following: low-pass filtering, high-pass filtering, and band-pass filtering. Specifically, preprocessing can be low-pass filtering, high-pass filtering, band-pass filtering, low-pass and high-pass filtering, low-pass and band-pass filtering, high-pass and band-pass filtering, or a combination of all three. The specific settings can be configured according to the actual situation.

[0032] Step S102: Determine feature parameters based at least on the above-mentioned operating data, wherein the feature parameters include at least the displacement of the above-mentioned operating data;

[0033] The vibration data and impact pulse data generated by the collision of the conveyor belt are related to the relative velocity between the colliding objects. In order to more accurately determine the characteristic parameters and further improve the efficiency of assessing the health status of the conveyor belt, in one embodiment of this application, the characteristic parameters are determined at least based on the above-mentioned operating data, including: obtaining the shaft diameter of the bearing of the conveyor belt and the rotational speed of the bearing of the conveyor belt; constructing a relationship based on the shaft diameter of the bearing of the conveyor belt and the rotational speed of the bearing of the conveyor belt; determining the change value of the influencing factor using the above-mentioned relationship, wherein the change value of the influencing factor changes with the shaft diameter of the bearing of the conveyor belt and / or the rotational speed of the bearing of the conveyor belt; obtaining the difference between the above-mentioned operating data and the change value of the influencing factor, and determining the difference as the characteristic parameter.

[0034] In one specific embodiment of this application, determining the change value of the influencing factor using the above-mentioned relationship includes: using the above-mentioned relationship: Determine the changes in the above influencing factors, where, This indicates the change in the above-mentioned influencing factors. This refers to the aforementioned rotational speed of the bearing in the aforementioned conveyor belt machine. The above refers to the shaft diameter of the bearing of the aforementioned conveyor belt machine. In this embodiment, the constructed relationship allows for a more accurate determination of the influencing factor variation value, and consequently, a more accurate determination of the characteristic parameters.

[0035] Specifically, taking bearings as an example, relative to the raceway, the speed of the rolling elements depends on their diameter and the rotational speed of the shaft. In order to determine the characteristic parameters, an influencing factor variation value can be used. The influencing factor variation value is the unstandardized raw data. The raw data is greatly affected by the rotational speed and shaft diameter. The influencing factor variation value will increase with the increase of rotational speed (or shaft diameter) or decrease with the decrease of rotational speed (or shaft diameter).

[0036] In one embodiment, the above relational expression It can be 20. It can be 0.6. It can be 2150.

[0037] In another embodiment, the feature parameters can also be obtained through the following relationship: ,in, For running data, As a characteristic parameter, its calculation principle formula is as follows: It should be noted that, and The calculation results are the same.

[0038] Step S103: Determine whether the tape machine is abnormal based on the above characteristic parameters.

[0039] To more accurately determine whether a conveyor belt machine is malfunctioning based on characteristic parameters, thereby further improving the efficiency of assessing the health status of the conveyor belt machine, in another specific embodiment of this application, there are multiple characteristic parameters. Determining whether the conveyor belt machine is malfunctioning based on the characteristic parameters includes: obtaining the maximum value among the multiple characteristic parameters; obtaining the average value of a predetermined number of the characteristic parameters; selecting multiple target characteristic parameters whose difference from the average value is less than a difference threshold; and determining a preset quantity based on the multiple target characteristic parameters; when both the maximum value and the preset quantity are within a first predetermined range, determining the conveyor belt machine to be in a first state, wherein, when the conveyor belt machine is in the first state, the aforementioned... The tape machine is in a normal state. If the maximum value and / or the preset amount are within a second predetermined range, and neither the maximum value nor the preset amount is within a third predetermined range, the tape machine is determined to be in a second state. In this second state, the tape machine is in an abnormal state with an abnormality level of first grade. If the maximum value and / or the preset amount are within the third predetermined range, the tape machine is determined to be in a third state. In this third state, the tape machine is in an abnormal state with an abnormality level of second grade, where the degree of abnormality corresponding to the second grade is greater than the degree of abnormality corresponding to the first grade.

[0040] One way to obtain the preset value is to first obtain the average value of 10 feature parameters, then find multiple target feature parameters whose difference from the average value is less than 5 from the multiple feature parameters, and then calculate the average value of these 5 target feature parameters to obtain the preset value. Alternatively, the maximum value among these 5 target feature parameters can be used as the preset value.

[0041] Specifically, a predetermined range of level diagrams can be generated in advance to qualitatively assess the health status of the conveyor belt, which is divided into three levels: normal, warning, and alarm. The status of the conveyor belt is represented by three colors: green, yellow, and red, so that managers or maintenance personnel can understand the status of the conveyor belt at a glance.

[0042] Specifically, such as Figure 2 As shown, curve data for multiple feature parameters were obtained. Figure 2 In For running data, These are characteristic parameters, including the maximum value. and preset amount , It is the change value of the influencing factor. Figure 2 The bars in the chart represent three preset levels: 0-20 is normal (green), 21-34 is abnormal (level 1, yellow), and 35-60 is abnormal (level 2, red).

[0043] In one embodiment, whether the conveyor belt is malfunctioning can be determined solely based on vibration data or solely based on impact pulse data. Based on operating data and characteristic parameters, and in conjunction with relevant ISO 10816 standards, such as... Figure 3 As shown, when the characteristic parameter (maximum value and / or preset value) is 0-20, it is determined to be normal (green); when the characteristic parameter (maximum value and / or preset value) is 21-34, it is determined to be abnormal and an early warning is issued (yellow); when the characteristic parameter (maximum value and / or preset value) is 35-60, it is determined to be abnormal and a fault alarm is issued (green).

[0044] Since vibration data and impact pulse data are not in the same unit, two graphs are generated, and the data divisions are different in different graphs. For example, 21-34 in the vibration data corresponds to 5-10 in the impact pulse data.

[0045] In another embodiment, if it is determined that the tape machine is abnormal and the abnormality level is the first level, a first prompt message can be sent to provide an early warning. If it is determined that the tape machine is abnormal and the abnormality level is the second level, a second prompt message can be sent to provide an alarm. The first prompt message and the second prompt message are different, and the sound of the second prompt message can be louder than the sound of the first prompt message.

[0046] The method described above first acquires the operating data of the conveyor belt within a predetermined time period, then determines characteristic parameters based on the operating data, and finally determines whether the conveyor belt is malfunctioning based on the characteristic parameters. This proposed solution offers a unified and standardized detection method that eliminates the need for human evaluation, thus preventing human factors from affecting the detection results. Furthermore, it combines vibration data and impact pulse data to determine characteristic parameters, which are then used to detect the condition of the conveyor belt. This allows the solution to be applied to conveyor belt inspection in various scenarios, thereby improving the efficiency of assessing the health status of the conveyor belt.

[0047] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0048] The detection of whether a conveyor belt machine is abnormal is not limited to the detection based on the characteristic parameters of the conveyor belt machine as described above. In order to further detect the conveyor belt machine, a preliminary detection can be performed, and then the abnormality of the conveyor belt machine can be determined based on the characteristic parameters. In this way, different methods can be used to detect the conveyor belt machine to further improve the efficiency of assessing the health status of the conveyor belt machine. In another embodiment of this application, before determining the characteristic parameters based on the above-mentioned operating data, the method further includes: obtaining the relevant parameters of the conveyor belt machine, the relevant parameters including at least one of the following: kurtosis, skewness, crest, velocity, acceleration; constructing a first matrix and a second matrix based on the relevant parameters; generating a first sequence based on the first matrix, generating a second sequence based on the second matrix, wherein the first sequence includes multiple reference operating data, the reference operating data being the data when the conveyor belt machine is in a normal state, and the second sequence including multiple of the above operating data; comparing the reference operating data of the first sequence and the operating data of the second sequence at the same time to obtain multiple comparison results, and if the sum of the comparison results exceeds a predetermined sum range, the abnormality of the conveyor belt machine is preliminarily determined.

[0049] Specifically, reference operating data of the conveyor belt machine can be obtained first. Using this reference data as a basis, calculations are performed on the actual operating data to make estimations. After obtaining the operating data, the correlation between the reference and actual operating data is determined. The correlation refers to the consistency between the reference and actual operating data. High consistency indicates the conveyor belt machine is operating normally, while low consistency suggests a possible malfunction. Based on the correlation, the operating data is estimated, and a weighted vector is used to determine the similarity between the actual and normal states (the weighted vector represents the proportion of similarity in the overall result). For example, if the similarity between the operating data and reference operating data is high or low, specifically, if the deviation between the actual impact pulse data in the operating data and the normal impact pulse data in the reference data is within 5%, the two sets of data are considered similar; similarly, if the deviation between the actual acceleration data in the operating data and the normal acceleration data in the reference data is within 12%, the two sets of data are considered similar. By comparing and analyzing the estimation results of the reference and actual operating data, the state of the conveyor belt machine can be preliminarily determined.

[0050] In one optional embodiment, when assessing bearing health, four relevant parameters of the actual state—impact pulse, acceleration, velocity, and displacement—can be compared with reference operating data under normal conditions. These four indicators have different weight vectors (i.e., different weight ratios): impact pulse accounts for 60% of the weight, acceleration for 20%, velocity for 10%, and displacement for 10%, with a total weight of 100%. We define a deviation of more than 10% between the operating data and the reference operating data as a condition where the equipment has reached an unhealthy stage. In this measurement, the impact pulse indicator itself has a deviation of 5%, with a weight ratio of 60%, resulting in a total deviation of 5% due to the impact pulse indicator. 60% = 3%; the acceleration itself has a deviation of 10%, with a weighting of 20%, so the acceleration index contributes 10% to the total deviation. 20% = 2%; Speed ​​deviation itself is 20%, weight is 10%, total deviation is 20%. 10% = 2%; displacement deviation itself is 5%, weight is 10%, total deviation is 0.5%, the sum of the total deviations caused by the four indicators is 3% + 2% + 2% + 0.5% = 7.5%, the overall deviation is not greater than 10%, so the equipment is currently normal.

[0051] Specifically, we can assume that the "relevant variable set" of the tape machine contains a total of There are several interrelated variables, which are the aforementioned operational data. The vibration data and impact pulse data within the operational data are parallel and do not interfere with each other. This time, only the vibration data is used for detection; next time, only the impact pulse data can be used. In the... Detected at all times The variables are denoted as the observation vector, i.e. The process of constructing the first and second matrices described above is the same. The following description focuses on the construction of the first matrix; the process for constructing the second matrix will not be repeated. In fact, this is the first step in modeling, which involves collecting data under different operating conditions during the process or when the conveyor belt is in normal operation. The first matrix, composed of historical observation vectors, is:

[0052] .

[0053] Each column of the historical observation vector in the first matrix represents a normal operating state of the conveyor belt machine. The first matrix, after careful selection... The subspace formed by historical observation vectors (using) The subspace represents the set of observation vectors, such as the kurtosis of the measurement point collected at 8 o'clock. Distortion Waiting for data, kurtosis was collected again at 9 o'clock. Distortion Another sample was collected at 10 o'clock. , The set of observation vectors formed by these collected data sets constitutes a subspace (which is actually the first matrix). This subspace can represent the process (the data state of the observation vectors during a time period when the conveyor belt is working normally) or the entire dynamics of the conveyor belt's normal operation. Therefore, the construction of the first matrix is ​​essentially a learning and memorization process of the process or the characteristics of the conveyor belt's normal operation.

[0054] Specifically, operational data can be stored in a database. The stored operational data can be used to predict future operational data for future time periods. For example, if the stored operational data is 25, 26, 27, 28, 30, 28, 39, 31, the future operational data can be predicted based on the trend of the operational data. Future operational data refers to operational data for future time periods. This allows for the prediction of future operational data in advance, achieving the purpose of early warning. Specifically, a model can be used for prediction. The model can be a neural network model or any other feasible model for predicting data.

[0055] When constructing the first matrix, second matrix, and predicted output using operational data from the database, due to the different dimensions of the relevant measuring points (a measuring point refers to a specific point on the conveyor belt; the first measuring point is horizontal, and the second is vertical) of a certain conveyor belt model, and the significant differences in the absolute values ​​of the operational data from different measuring points, it is necessary to ensure that the nonlinear operator is used to correctly measure the distance between different observation vectors (here, the operator represents the measured observation vector, obtained through monitoring equipment. The distance here refers to the same horizontal plane, because the observation vectors here do not increase or decrease linearly; for example, at a rotation speed of 40 rpm, the vertical acceleration of this measuring point is 2 mm / s², and the horizontal acceleration is...). At a rotational speed of 50 rpm, the vertical acceleration is 2.3 mm / s², and the horizontal acceleration is 3.6 mm / s². At a rotational speed of 60 rpm, the vertical acceleration is 2.7 mm / s², and the horizontal acceleration is 3.3 mm / s². It can be seen that this observed vector does not change linearly with the rotational speed; it is a nonlinear operator. For the three different rotational speeds, the absolute values ​​of this nonlinear operator are not on the same horizontal plane (or rather, not on the same horizontal baseline). Therefore, mapping the data to the range [0, 1] and normalizing it to bring them to the same horizontal plane allows for better measurement of each point. Each variable is normalized according to its own extreme value, mapping the running data to the range [0, 1] (assuming the measured value of a certain observation vector is...). The maximum value is The minimum value is The mapping method is .

[0056] The construction of the first matrix can make its internal observation vectors To cover the normal operating space of the conveyor belt machine as much as possible, each observation vector of the normal operating space of the conveyor belt machine is... The dataset consists of 100 variables, all of which have been normalized. For each variable, the interval [0,1] is divided into 100 equal parts, with a step size of 0.01 from the set. Several observation vectors are found and added to the matrix. In, with variables For example, to the matrix Methods for adding observation vectors include Figure 4 As shown, firstly, let Step distance It is 0.01 and The product of ,make ,Sure and Is the absolute value of the difference less than the predetermined value? If the absolute value is less than the predetermined value, an additional value will be added. To matrix In the case where the absolute value is greater than or equal to the predetermined value, determine Is it greater than ,exist Greater than In the case of, determine Is it greater than 100? If the number is greater than 100, the addition process ends. If the value is not less than or equal to 100, , Less than or equal to In this case, Specifically, matrix It consists of many observation vector data, for example, 500. These 500 observation vector data must cover the entire normal operating range of the conveyor belt (e.g., no-load, heavy-load, variable-load, etc.). These 500 observation vectors are selected from the observation vector set. For example, over three days, there are 5 observation vectors, each collecting 3000 data points, resulting in a set of 15000 data points. The 500 observation vector data are selected from these 15000 data points, and for each of the 5 observation vectors, 100 data points are selected from its 3000 data points, forming 500 data matrices. Let's take one of the five vectors as an example; its vector set... We have 3000 data points. We divide these 3000 data points into 100 equal parts, meaning each step consists of 30 data points. We then take one data point from each step and add it to the matrix as a sample. The same principle applies to other components. The matrix is ​​added to compare the health status with the current operating status data to assess whether the device is malfunctioning.

[0057] By conducting a preliminary inspection of the conveyor belt's condition, it can be preliminarily determined whether the conveyor belt is malfunctioning. However, the preliminary inspection does not represent an absolute result. The current operating functions, load, environment, and operating data of the conveyor belt may change. Therefore, when a preliminary malfunction is determined, further determination can be made based on characteristic parameters.

[0058] In order to determine the cause of the tape machine malfunction when it is already malfunctioning, so as to facilitate maintenance personnel to carry out maintenance, in another embodiment of this application, after determining whether the tape machine is malfunctioning based on the above-mentioned characteristic parameters, the method further includes: identifying the malfunctioning components when the tape machine is in an malfunctioning state, wherein the tape machine includes multiple of the above-mentioned components.

[0059] To further accurately identify abnormal components in the conveyor belt machine, in another embodiment of this application, when the conveyor belt machine is in an abnormal state, identifying the abnormal components includes: acquiring the operating data of multiple components in the conveyor belt machine; generating spectrum data based on the operating data; acquiring standard spectrum data of multiple components in the conveyor belt machine; identifying the component whose difference between the spectrum data and the standard spectrum data is greater than a difference threshold as a target component, and identifying the target component as the abnormal component.

[0060] This application also provides a testing device for a tape machine. It should be noted that the testing device for a tape machine in this application can be used to execute the testing method for tape machines provided in this application. The testing device for a tape machine provided in this application will be described below.

[0061] Figure 5 This is a schematic diagram of a detection device for a tape machine according to an embodiment of this application. Figure 5 As shown, the device includes:

[0062] The first acquisition unit 10 is used to acquire the operating data of the conveyor belt machine within a predetermined time period. The operating data is collected by a target device installed on one side of the conveyor belt machine. The operating data includes vibration data and impact pulse data.

[0063] The first determining unit 20 is used to determine characteristic parameters based at least on the above-mentioned operating data, wherein the characteristic parameters include at least the displacement of the above-mentioned operating data.

[0064] The vibration data and impact pulse data generated by the collision of the conveyor belt are related to the relative velocity between the colliding objects. In order to more accurately determine the characteristic parameters and further improve the efficiency of assessing the health status of the conveyor belt, in one embodiment of this application, the first determining unit includes a first acquisition module, a construction module, a first determining module, and a second determining module. The first acquisition module is used to acquire the shaft diameter and the rotational speed of the bearing of the conveyor belt. The construction module is used to construct a relationship based on the shaft diameter and the rotational speed of the bearing of the conveyor belt. The first determining module is used to determine the change value of the influencing factor using the relationship. The change value of the influencing factor changes with the shaft diameter and / or the rotational speed of the bearing of the conveyor belt. The second determining module is used to acquire the difference between the operating data and the change value of the influencing factor, and determine the difference as the characteristic parameter.

[0065] In one specific embodiment of this application, the first determining module includes a determining submodule, which is used to employ the above-described relational expression: Determine the changes in the above influencing factors, where, This indicates the change in the above-mentioned influencing factors. This refers to the aforementioned rotational speed of the bearing in the aforementioned conveyor belt machine. The above refers to the shaft diameter of the bearing of the aforementioned conveyor belt machine. In this embodiment, the constructed relationship allows for a more accurate determination of the influencing factor variation value, and consequently, a more accurate determination of the characteristic parameters.

[0066] The second determining unit 30 is used to determine whether the tape machine is abnormal based on the above-mentioned characteristic parameters.

[0067] To more accurately determine whether a conveyor belt machine is malfunctioning based on characteristic parameters, thereby further improving the efficiency of assessing the health status of the conveyor belt machine, in another specific embodiment of this application, there are multiple characteristic parameters. The second determining unit includes a second acquisition module, a third acquisition module, a third determining module, a fourth determining module, and a fifth determining module. The second acquisition module is used to acquire the maximum value among the multiple characteristic parameters. The third acquisition module is used to acquire the average value of a predetermined number of the characteristic parameters, select multiple target characteristic parameters whose difference from the average value is less than a difference threshold, and determine a preset quantity based on the multiple target characteristic parameters. The third determining module is used to determine that the conveyor belt machine is in a first state when both the maximum value and the preset quantity are within a first predetermined range. In the first state described above, the tape machine is in a normal state; the fourth determining module is used to determine the tape machine as being in a second state when the maximum value and / or the preset amount are within a second predetermined range, and neither the maximum value nor the preset amount is within a third predetermined range, wherein when the tape machine is in the second state, the tape machine is in an abnormal state and the abnormality level is first level; the fifth determining module is used to determine the tape machine as being in a third state when the maximum value and / or the preset amount are within the third predetermined range, wherein when the tape machine is in the third state, the tape machine is in an abnormal state and the abnormality level is second level, wherein the degree of abnormality corresponding to the second level is greater than the degree of abnormality corresponding to the first level.

[0068] In the aforementioned device, the first acquisition unit acquires the operating data of the conveyor belt within a predetermined time period, the first determination unit determines at least the characteristic parameters based on the operating data, and the second determination unit determines whether the conveyor belt is abnormal based on the characteristic parameters. This solution proposes a unified and standardized detection scheme that eliminates the need for human evaluation, thus preventing human factors from affecting the detection results. Furthermore, it combines vibration data and impact pulse data to determine the characteristic parameters, which are then used to detect the condition of the conveyor belt. This allows the solution to be used to detect conveyor belts in various scenarios, thereby improving the efficiency of assessing the health status of the conveyor belt.

[0069] The detection of whether a tape machine is abnormal is not limited to the detection based on the characteristic parameters of the tape machine as described above. In order to further detect the tape machine, a preliminary detection can also be performed, and then the abnormality of the tape machine can be determined based on the characteristic parameters. In this way, different methods can be used to detect the tape machine, so as to further improve the efficiency of assessing the health status of the tape machine. In another embodiment of this application, the above-mentioned device further includes a second acquisition unit, a construction unit, a generation unit and a third determination unit. The second acquisition unit is used to acquire the relevant parameters of the tape machine. The relevant parameters include at least one of the following: kurtosis, skewness, crest, velocity, and acceleration. The construction unit is used to construct a first matrix and a second matrix based on the aforementioned relevant parameters; the generation unit is used to generate a first sequence based on the first matrix and a second sequence based on the second matrix, wherein the first sequence includes multiple reference operating data, which are data when the conveyor belt is in normal condition, and the second sequence includes multiple of the aforementioned operating data; the third determination unit is used to compare the reference operating data of the first sequence and the operating data of the second sequence at the same time to obtain multiple comparison results, and if the sum of the comparison results exceeds a predetermined sum range, it is preliminarily determined that the conveyor belt is abnormal.

[0070] In order to determine the cause of the tape machine malfunction when it is already malfunctioning, so as to facilitate maintenance personnel to carry out maintenance, in another embodiment of this application, the above-mentioned device further includes a fourth determining unit. The fourth determining unit is used to determine the abnormal component when the tape machine is in an abnormal state after determining whether the tape machine is abnormal based on the above-mentioned characteristic parameters, wherein the tape machine includes multiple of the above-mentioned components.

[0071] To further accurately identify abnormal components in the conveyor belt machine, in another embodiment of this application, the fourth determining unit includes a third acquiring module, a generating module, a fourth acquiring module, and a sixth determining module. The third acquiring module is used to acquire the operating data of the plurality of components in the conveyor belt machine; the generating module is used to generate spectrum data based on the operating data; the fourth acquiring module is used to acquire standard spectrum data of the plurality of components in the conveyor belt machine; and the sixth determining module is used to determine that the component whose difference between the spectrum data and the standard spectrum data is greater than a difference threshold is a target component, and to determine that the target component is an abnormal component.

[0072] The detection device of the tape machine includes a processor and a memory. The first acquisition unit, the first determination unit, and the second determination unit are all stored in the memory as program units. The processor executes the program units stored in the memory to realize the corresponding functions.

[0073] The processor contains a kernel, which retrieves the corresponding program unit from memory. One or more kernels can be configured, and adjusting kernel parameters can address the low efficiency of manual assessment of the health status of conveyor belt machines in existing technologies.

[0074] The memory may include non-permanent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0075] This invention provides a computer-readable storage medium storing a program thereon, which, when executed by a processor, implements the aforementioned detection method for a tape machine.

[0076] This invention provides a processor for running a program, wherein the program executes the detection method of the tape machine.

[0077] This application also provides a tape machine, including one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include methods for performing any of the above-described methods.

[0078] The aforementioned conveyor belt machine, including any of the methods described above, first acquires the machine's operating data over a predetermined time period, then determines characteristic parameters based on the operating data, and finally determines whether the conveyor belt machine is malfunctioning based on the characteristic parameters. This solution proposes a unified and standardized detection scheme that eliminates the need for human evaluation, thus preventing human factors from affecting the detection results. Furthermore, it combines vibration data and impact pulse data to determine characteristic parameters, which are then used to detect the conveyor belt machine's condition. This allows the solution to be used for conveyor belt machine detection in various scenarios, thereby improving the efficiency of assessing the machine's health status.

[0079] This invention provides a device including a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs at least the following steps:

[0080] Step S101: Obtain the operating data of the conveyor belt within a predetermined time period. The operating data is collected using a target device installed on one side of the conveyor belt. The operating data includes vibration data and impact pulse data.

[0081] Step S102: Determine feature parameters based at least on the above-mentioned operating data, wherein the feature parameters include at least the displacement of the above-mentioned operating data;

[0082] Step S103: Determine whether the tape machine is abnormal based on the above characteristic parameters.

[0083] The devices mentioned in this article can be servers, PCs, tablets, mobile phones, etc.

[0084] This application also provides a computer program product, which, when executed on a data processing device, is suitable for executing an initialization program having at least the following method steps:

[0085] Step S101: Obtain the operating data of the conveyor belt within a predetermined time period. The operating data is collected using a target device installed on one side of the conveyor belt. The operating data includes vibration data and impact pulse data.

[0086] Step S102: Determine feature parameters based at least on the above-mentioned operating data, wherein the feature parameters include at least the displacement of the above-mentioned operating data;

[0087] Step S103: Determine whether the tape machine is abnormal based on the above characteristic parameters.

[0088] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0089] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units described above can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0090] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0091] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0092] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0093] As can be seen from the above description, the embodiments of this application achieve the following technical effects:

[0094] 1) The conveyor belt machine detection method of this application first acquires the operating data of the conveyor belt machine within a predetermined time period, then determines characteristic parameters based on the operating data, and finally determines whether the conveyor belt machine is abnormal based on the characteristic parameters. This scheme proposes a unified and standardized detection method that does not require human evaluation; therefore, human factors will not affect the detection results. Furthermore, it combines vibration data and impact pulse data to determine characteristic parameters, which are then used to detect the condition of the conveyor belt machine. This method can be used to detect conveyor belt machines in various scenarios, thereby improving the efficiency of assessing the health status of the conveyor belt machine.

[0095] 2) The conveyor belt machine detection device of this application comprises a first acquisition unit acquiring operating data of the conveyor belt machine within a predetermined time period, a first determination unit determining characteristic parameters based at least on the operating data, and a second determination unit determining whether the conveyor belt machine is abnormal based on the characteristic parameters. This solution proposes a unified and standardized detection scheme that eliminates the need for human evaluation, thus preventing human factors from affecting the detection results. Furthermore, it combines vibration data and impact pulse data to determine characteristic parameters, which are then used to detect the condition of the conveyor belt machine. This allows the solution to be used to detect conveyor belt machines in various scenarios, thereby improving the efficiency of assessing the health status of the conveyor belt machine.

[0096] 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 method for testing a tape machine, characterized in that, include: The operation data of the conveyor belt machine is acquired within a predetermined time period. The operation data is collected using a target device installed on one side of the conveyor belt machine. The operation data includes vibration data and impact pulse data. The feature parameters are determined based on at least the operational data, and the feature parameters include at least the displacement of the operational data; Determine whether the tape machine is malfunctioning based on the aforementioned characteristic parameters; The determination of feature parameters based at least on the operational data includes: Obtain the shaft diameter of the bearing of the conveyor belt machine and the rotational speed of the bearing of the conveyor belt machine; Based on the shaft diameter of the bearing of the conveyor belt machine and the rotational speed of the bearing of the conveyor belt machine, construct the relationship; The relationship is used to determine the change value of the influencing factor, which varies with the shaft diameter of the bearing of the conveyor belt and / or the rotational speed of the bearing of the conveyor belt. Obtain the difference between the running data and the change value of the influencing factor, and determine the difference as the feature parameter; The process of determining the change value of the influencing factor using the aforementioned relationship includes: Using the aforementioned relation: Determine the change value of the influencing factor, wherein, This indicates the change value of the influencing factor. The rotational speed of the bearing in the conveyor belt machine is indicated. The shaft diameter of the bearing of the conveyor belt machine is indicated; Prior to determining the feature parameters based at least on the operational data, the method further includes: Obtain relevant parameters of the tape machine, wherein the relevant parameters include at least one of the following: kurtosis, skewness, crest, speed, and acceleration; Construct a first matrix and a second matrix based on the relevant parameters; A first sequence is generated based on the first matrix, and a second sequence is generated based on the second matrix. The first sequence includes multiple reference operating data, which are data when the conveyor belt machine is in normal operation. The second sequence includes multiple sets of the operating data. By comparing the reference operating data of the first sequence and the operating data of the second sequence at the same time, multiple comparison results are obtained. If the sum of the comparison results exceeds a predetermined sum range, the conveyor belt machine is preliminarily determined to be abnormal.

2. The method according to claim 1, characterized in that, There are multiple characteristic parameters, and determining whether the tape machine is malfunctioning based on these characteristic parameters includes: Obtain the maximum value among the multiple feature parameters; Obtain the average value of a predetermined number of the feature parameters, select multiple target feature parameters whose difference from the average value is less than a difference threshold, and determine a preset quantity based on the multiple target feature parameters; When both the maximum value and the preset amount are within a first predetermined range, the tape machine is determined to be in a first state, wherein when the tape machine is in the first state, the tape machine is in a normal state; If the maximum value and / or the preset amount are within a second predetermined range, and neither the maximum value nor the preset amount are within a third predetermined range, the tape machine is determined to be in a second state. In this case, if the tape machine is in the second state, the tape machine is in an abnormal state and the abnormality level is the first level. When the maximum value and / or the preset amount are within the third predetermined range, the tape machine is determined to be in a third state. When the tape machine is in the third state, the tape machine is in an abnormal state and the abnormality level is the second level, wherein the degree of abnormality corresponding to the second level is greater than the degree of abnormality corresponding to the first level.

3. The method according to claim 1 or 2, characterized in that, After determining whether the tape machine is malfunctioning based on the characteristic parameters, the method further includes: In the event that the tape conveyor is in an abnormal state, the abnormal component is identified, wherein the tape conveyor includes multiple such components.

4. The method according to claim 3, characterized in that, In the event that the conveyor belt machine is in an abnormal state, the abnormal components are identified, including: Obtain the operating data of multiple components in the tape machine; Generate spectrum data based on the operational data; Obtain standard spectral data of multiple components in the tape machine; The component whose difference between the spectrum data and the standard spectrum data is greater than the difference threshold is identified as the target component, and the target component is identified as the abnormal component.

5. A testing device for a tape machine, characterized in that, include: The first acquisition unit is used to acquire the operating data of the conveyor belt machine within a predetermined time period. The operating data is collected by a target device installed on one side of the conveyor belt machine. The operating data includes vibration data and impact pulse data. The first determining unit is configured to determine feature parameters based at least on the running data, wherein the feature parameters include at least the displacement of the running data; The second determining unit is used to determine whether the tape machine is abnormal based on the characteristic parameters; The first determining unit includes: The first acquisition module is used to acquire the shaft diameter of the bearing of the conveyor belt machine and the rotational speed of the bearing of the conveyor belt machine. The construction module is used to construct a relation based on the shaft diameter of the bearing of the conveyor belt machine and the rotational speed of the bearing of the conveyor belt machine; The first determining module is used to determine the change value of the influencing factor using the relationship, the change value of the influencing factor changing with the shaft diameter of the bearing of the conveyor belt machine and / or the rotational speed of the bearing of the conveyor belt machine; The second determining module is used to obtain the difference between the running data and the change value of the influencing factor, and determine the difference as the feature parameter; The first determining module includes: The submodule is used to employ the relation: Determine the change value of the influencing factor, wherein, This indicates the change value of the influencing factor. The rotational speed of the bearing in the conveyor belt machine is indicated. The shaft diameter of the bearing of the conveyor belt machine is indicated; The device further includes: The second acquisition unit is used to acquire relevant parameters of the tape machine before determining the feature parameters based at least on the operating data. The relevant parameters include at least one of the following: kurtosis, skewness, crest, speed, and acceleration. The generation unit is used to construct a first matrix and a second matrix based on the relevant parameters; The generation unit is used to generate a first sequence based on the first matrix and a second sequence based on the second matrix, wherein the first sequence includes multiple reference operating data, the reference operating data being the data when the conveyor belt is in normal state, and the second sequence includes multiple operating data; The third determining unit is used to compare the reference operating data of the first sequence and the operating data of the second sequence at the same time to obtain multiple comparison results. If the sum of the comparison results exceeds a predetermined sum range, the tape machine is preliminarily determined to be abnormal.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program performs the method according to any one of claims 1 to 4.

7. A tape-making machine, characterized in that, include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs comprising methods for performing any one of claims 1 to 4.

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