Fault monitoring method and system for crushing and screening equipment

Abstract

The present application relates to the field of crusher operation monitoring technology, and specifically to a fault monitoring method and system for crushing and screening equipment, the method comprising: real-time collection of various operation monitoring data of a double-shaft crusher; when the rotation speed data exceeds a preset stable range, determining an operation fault of the double-shaft crusher, otherwise, the specific steps for determining whether the double-shaft crusher has an operation fault are: dividing the operation time range of the double-shaft crusher into various time intervals; determining the linear response deviation value of various operation monitoring data in each time interval; determining the asynchronous response value of the double-shaft crusher in each time interval based on the difference in the distribution range of various operation monitoring data between each time interval and all other time intervals, and the difference in the linear response deviation value; determining whether the double-shaft crusher has an operation fault based on the distribution of the asynchronous response value. The present application aims to improve the accuracy of monitoring the operation fault of a double-shaft crusher.

Description

Technical Field

[0001] The present application relates to the technical field of crusher operation monitoring, and in particular to a fault monitoring method and system for crushing and screening equipment. Background Art

[0002] With the widespread use of plastic products, the amount of plastic waste is also increasing day by day. Effective crushing and screening of plastic waste has become a hot topic of research. Commonly used crushing and screening equipment includes jaw crushers, hammer mills and double-shaft crushers. Among them, double-shaft crushers are widely used in waste recycling and can handle various types of waste, including domestic waste, industrial waste, large waste, etc. Double-shaft crushers break the waste into smaller blocks or particles, which is convenient for subsequent transportation, sorting and further processing.

[0003] In the process of using a double-shaft crusher to crush plastic waste, the load on the double-shaft crusher after feeding is in a state of frequent changes, given that the types of items mixed in the plastic waste are extremely complex. However, in the traditional double-shaft crusher operation monitoring process, the impact of the load change characteristics caused by the feeding difference on the double-shaft crusher operation status is usually not fully analyzed. For example, traditional monitoring only focuses on a single operating parameter, which makes it difficult to accurately judge the operation status and potential failure risks of the double-shaft crusher when facing complex feeding conditions. Summary of the invention

[0004] In view of the above, it is necessary to provide a fault monitoring method and system for crushing and screening equipment, which improves the accuracy of fault monitoring of double-shaft crusher operation compared with the traditional double-shaft crusher operation monitoring method:

[0005] In a first aspect, an embodiment of the present application provides a fault monitoring method for a crushing and screening device, the method comprising the following steps:

[0006] Real-time collection of various operating monitoring data of the double-shaft crusher, including speed data;

[0007] Determine whether the speed data exceeds the preset stable range. If so, determine that the double-shaft crusher has an operating fault. Otherwise, determine whether the double-shaft crusher has an operating fault based on all types of operating monitoring data. The specific steps are:

[0008] Based on the distribution of all types of operation monitoring data at all collection moments, the operation time range of the double-shaft crusher is divided into various time intervals;

[0009] Based on the collinearity between various operation monitoring data in each time interval and all other operation monitoring data, as well as the discreteness of various operation monitoring data, the linear response deviation value of various operation monitoring data in each time interval is determined;

[0010] Determine the asynchronous response value of the double-shaft crusher in each time interval based on the difference in the distribution range of various operation monitoring data between each time interval and all other time intervals, and the difference in the linear response deviation value;

[0011] Based on the distribution of the asynchronous response values, it is determined whether the double-shaft crusher has an operation fault.

[0012] In one embodiment, the operation monitoring data also includes torque data and vibration frequency data.

[0013] In one embodiment, the process of dividing the operating time range of the double-shaft crusher into time intervals is as follows:

[0014] The sum of the normalized data of all kinds of operation monitoring data at each collection moment is taken as the instantaneous comprehensive state data of the double-shaft crusher at each collection moment;

[0015] The data of each acquisition moment and its instantaneous comprehensive state are combined into two-dimensional data points, and the mutation point detection algorithm is used to obtain the mutation point in all data points;

[0016] The time corresponding to the mutation point is used as the division point of the operating time range of the double-shaft crusher, and the operating time range is divided into various time intervals.

[0017] In one embodiment, the linear response deviation value is determined as follows:

[0018] Calculate the variance inflation factors of various operational monitoring data in each time interval;

[0019] The objective weighting method is used to calculate the weight of each operation monitoring data;

[0020] The linear response deviation value is the product of the inverse of the variance inflation factor and the weight.

[0021] In one embodiment, the process of determining the asynchronous response value is as follows:

[0022] Determining the state response value of various operation monitoring data in each time interval based on the distribution range of various operation monitoring data in each time interval and the linear response deviation value;

[0023] The state response values ​​of all kinds of operation monitoring data in each time interval are combined into each state response sequence;

[0024] The asynchronous response value of the double-shaft crusher in each time interval is determined by combining the distribution of elements in the state response sequence of each time interval and the distance of the state response sequence between each time interval and all other time intervals.

[0025] In one embodiment, the state response value is a fusion result of the extreme difference of various operation monitoring data in each time interval and the linear response deviation value.

[0026] In one embodiment, the calculation relationship of the asynchronous response value is:

[0027] ; In the formula, Indicates that the double-shaft crusher is Asynchronous response value of a time interval; and Respectively represent and The state response sequence of a time interval; dis() represents the distance function; μ() represents the mean function; Indicates the number of time intervals.

[0028] In one embodiment, the process of judging whether the double-shaft crusher has an operation fault based on the distribution of the asynchronous response value is as follows:

[0029] Based on the distribution of the asynchronous response value, a fault judgment value of the double-shaft crusher is obtained;

[0030] When the fault judgment value is greater than or equal to the preset fault monitoring threshold, it is determined that the double-shaft crusher is operating faulty; otherwise, it is determined that the double-shaft crusher is operating normally.

[0031] In one embodiment, the fault judgment value is the average of normalized values ​​of asynchronous response values ​​of the double-shaft crusher in all time intervals.

[0032] In the second aspect, an embodiment of the present application also provides a fault monitoring system for crushing and screening equipment, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned fault monitoring methods for crushing and screening equipment are implemented.

[0033] This application has at least the following beneficial effects:

[0034] This application is aimed at the problem that traditional monitoring only focuses on a single operating parameter and does not comprehensively consider the impact mechanism of different load states on the key components of the double-shaft crusher, resulting in difficulty in accurately judging the operating status and potential failure risks of the double-shaft crusher when facing complex feeding conditions. This application is based on the frequent changes in load during the dynamic test of the double-shaft crusher, which causes the impact force, torque and other load parameters of the double-shaft crusher to show dynamic fluctuations, and there are asynchronous response characteristics to load changes in different time periods. Based on the moment of comprehensive deviation response of the tool working state during the dynamic test of the double-shaft crusher, the operating time range of the double-shaft crusher is divided, and the time intervals with different response states are accurately divided through the comprehensive influence of all the main shafts of the double-shaft crusher, which is convenient for subsequent accurate analysis of the response deviation of the double-shaft crusher during operation;

[0035] Furthermore, based on the time intervals divided by the comprehensive deviation response analysis, the collinearity characteristics of different types of operation monitoring data in local time periods during the dynamic test of the double-shaft crusher are analyzed to obtain the response deviation of each type of operation monitoring data. The response deviations of different time periods during the dynamic test of the double-shaft crusher and the significance characteristics of the response are combined to obtain the linear response deviation value, and further combined with the data response change range of each time interval during the dynamic test of the double-shaft crusher to obtain the asynchronous response value to determine whether the double-shaft crusher has an operating failure. The response deviations of different types of operation monitoring data when the operating state of the double-shaft crusher changes are fully considered to accurately determine the operating state and potential failure risks of the double-shaft crusher, thereby improving the accuracy of monitoring the operating failure of the double-shaft crusher. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 A flowchart of a method for fault monitoring of crushing and screening equipment provided in accordance with an embodiment of the present application;

[0038] Figure 2 This is a schematic diagram of the process of obtaining the time interval;

[0039] Figure 3 The figure is a flow chart of determining the asynchronous response value. DETAILED DESCRIPTION

[0040] In the description of the embodiments of the present application, words such as "exemplary", "or", "for example" and the like are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "or", "for example" and the like is intended to present related concepts in a concrete manner.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art in the present application. The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. It should be understood that, unless otherwise specified, " / " means or.

[0042] It should also be noted that the terms "first" and "second" in the present application are used to distinguish similar objects rather than to describe a specific order or sequence.

[0043] The specific scheme of the fault monitoring method and system for crushing and screening equipment provided by the present application is described in detail below with reference to the accompanying drawings.

[0044] See also Figure 1 , which shows a flowchart of a method for fault monitoring of crushing and screening equipment provided by an embodiment of the present application, the method comprising the following steps:

[0045] Step 1: collect various operation monitoring data of the double-shaft crusher in real time, including rotation speed data, and determine whether the rotation speed data exceeds a preset stable range. If so, determine that the double-shaft crusher has an operation failure.

[0046] In the process of garbage disposal and recycling, the present application utilizes a double-shaft crusher to crush the garbage, and further utilizes a vibrating screen to screen the crushed material. In the process of the double-shaft crusher crushing the garbage, sensors are used to collect real-time operation monitoring data of the dynamic test process of the double-shaft crusher, including torque data, speed data and vibration frequency data; specifically, the torque data and speed data of each main shaft in the double-shaft crusher are respectively collected through a torque sensor and a speed sensor, and the vibration frequency data of the double-shaft crusher is collected through a vibration sensor.

[0047] In this embodiment, when using sensors to collect operation monitoring data, the collection time interval is 3s. The value of the collection time interval can be set by the implementer, and this application does not impose any special restrictions.

[0048] All the collected torque data, speed data and vibration frequency data are arranged in ascending chronological order to form various operation monitoring data sequences of the dynamic test process of the double-shaft crusher, which are used to monitor whether there are any operation faults in the double-shaft crusher during the dynamic test process.

[0049] Since the environment of garbage crushing is relatively complex, environmental interference may cause noise in the collected data. Therefore, noise reduction processing is performed on each operation monitoring data sequence.

[0050] In this embodiment, a median filtering method is used to perform noise reduction processing on the operation monitoring data sequence. As other implementation methods, on the basis of being able to achieve noise reduction processing on the operation monitoring data sequence, the implementer may use other existing technologies to perform noise reduction processing on the operation monitoring data sequence, such as a Gaussian filtering method, a mean filtering method, etc., and this application does not impose any special restrictions.

[0051] It is determined whether the collected rotation speed data exceeds the preset stable range. If so, it is determined that the double-shaft crusher has an operation fault. Otherwise, it is determined whether the double-shaft crusher has an operation fault based on all the collected operation monitoring data.

[0052] In this embodiment, the preset stable range is set to 20-60r / min. For different types of double-shaft crushers, the range is artificially limited according to the actual rotation speed of the double-shaft crusher, and this application does not impose any special restrictions.

[0053] Step 2: If the rotation speed data does not exceed the preset stable range, determine whether the double-shaft crusher has an operating fault based on all types of operating monitoring data.

[0054] Normally, when a twin-shaft crusher is used to crush garbage, when the load on the main shaft changes, the corresponding main shaft speed and torque will also change accordingly, and the vibration frequency of the twin-shaft crusher will be stable; however, if the composition of the feed components during the crushing process is more complex, and the feed is attached to the cutter in different conditions, the response of different main shafts to load changes will be different during the actual processing process, causing the vibration of the twin-shaft crusher to be more disordered; and if some connection parts in the twin-shaft crusher are loose or the cutter is worn, it will also cause different main shafts to respond differently to load changes.

[0055] Since the composition of the feed components is unevenly distributed in time, according to the characteristics of different load response changes caused by feed differences in different time periods during the process of the double-shaft crusher processing garbage, the dynamic test process of the double-shaft crusher is analyzed to obtain the fault monitoring results of the dynamic test of the double-shaft crusher. The specific analysis process is as follows:

[0056] Step 2.1, based on the distribution of all types of operation monitoring data at all collection moments, the operation time range of the double-shaft crusher is divided into various time intervals.

[0057] During the dynamic test of the double-shaft crusher, the garbage is mainly crushed by the rotation of the cutters on the two main shafts, and the different types of cutters selected will result in different degrees of crushing of the garbage after crushing. Due to the different compositions of the garbage fed into the double-shaft crusher, the load of the double-shaft crusher changes frequently during the processing, causing the impact force, torque and other load parameters of the double-shaft crusher to show dynamic fluctuations. If there are asynchronous response characteristics to load changes in different time periods, the operating state of the double-shaft crusher may change during the dynamic test.

[0058] In view of the above situation, the time interval in which the state of the double-shaft crusher may respond asynchronously due to load changes is obtained based on the operation monitoring data. The specific process is as follows:

[0059] Each operation monitoring data sequence obtained during the dynamic test of the double-shaft crusher is normalized separately;

[0060] In this embodiment, the Min-Max normalization method is used to normalize the operation monitoring data sequence. As other implementation methods, on the basis of being able to realize the normalization of the operation monitoring data sequence, the implementer may use other existing technologies to normalize the operation monitoring data sequence, such as the Z-Score normalization method, the decimal calibration normalization method, etc., and this application does not make any special restrictions.

[0061] In order to further analyze the comprehensive response state characteristics of the double-shaft crusher at each acquisition moment during the dynamic test, the sum of the normalized values ​​of all kinds of operation monitoring data at each acquisition moment during the dynamic test of the double-shaft crusher is used as the instantaneous comprehensive state data of the double-shaft crusher at each acquisition moment. Each acquisition moment and its instantaneous comprehensive state data are composed of two-dimensional data points. The mutation point detection algorithm is used to obtain the mutation point in all data points. The moment corresponding to the mutation point is used as the moment of the comprehensive deviation response of the tool working state during the dynamic test of the double-shaft crusher, thereby accurately dividing the time interval of the state asynchronous response during the dynamic test of the crusher.

[0062] In this embodiment, a Bayesian mutation point detection algorithm is used to obtain mutation points. As other implementation methods, based on the available mutation points, the implementer can use other existing technologies to obtain mutation points, such as the Pettitt point mutation detection algorithm, the Mann-Kendall mutation point detection algorithm, etc. This application does not impose any special restrictions.

[0063] Specifically, the time corresponding to the mutation point is used as the segmentation point of the operating time range of the double-shaft crusher, and the operating time range is segmented into various time intervals. As an example of segmentation of the operating time range, for example, if the operating time range of the double-shaft crusher is [1,50], and the time corresponding to the mutation point is 12 and 39, then the segmented time intervals are [1,12], [12,39] and [39,50]. The schematic diagram of the time interval acquisition process is shown in FIG. Figure 2 shown.

[0064] Step 2.2, based on the collinearity between various operation monitoring data in each time interval and all other operation monitoring data, and the degree of dispersion of various operation monitoring data, determine the linear response deviation value of various operation monitoring data in each time interval.

[0065] Through the time intervals divided based on the comprehensive deviation response analysis, the collinearity characteristics of different types of operation monitoring data in the local time period during the dynamic test of the double-shaft crusher are analyzed, that is, the more complex the state change response of the double-shaft crusher, the greater the possibility of its faulty operation, and the more likely the operation monitoring data is to deviate from the linear change relationship; therefore, for each time interval during the operation of the double-shaft crusher, any type of operation monitoring data in the time interval is used as the target data, and the remaining various operation monitoring data are used as various reference data. The target data and all kinds of reference data are used as input to calculate the variance expansion factor of the target data. The smaller the variance expansion factor, the weaker the collinearity between any one type of operation monitoring data and the remaining operation monitoring data, the more likely it is to deviate from the linear change relationship, and the more likely the response state of any one type of operation monitoring data in the dynamic test of the double-shaft crusher is to deviate. Among them, the calculation of the variance expansion factor is a well-known technology and will not be repeated in this application.

[0066] Further, the significance of different types of operation monitoring data of the double-shaft crusher in each time interval relative to the state change response of the double-shaft crusher is compared and analyzed. The specific method is: taking all types of operation monitoring data in each time interval as input, and using the objective weighting method to calculate the weight of each type of operation monitoring data, the larger the weight of a certain type of operation monitoring data, the more significant the relative response of the change of this type of operation monitoring data to the operation state of the double-shaft crusher during the dynamic test of the double-shaft crusher, and the greater the accuracy of the collinearity analysis of this type of operation monitoring data for the analysis of the change of the operation state of the double-shaft crusher;

[0067] In this embodiment, the entropy weight method is used to calculate the weight of each operation monitoring data. As other implementation methods, on the basis of being able to calculate the weight of each operation monitoring data, the implementer can use other existing technologies to calculate the weight of each operation monitoring data, such as the standard deviation method, the CRITIC method, etc., and this application does not make any special restrictions.

[0068] Therefore, the variance expansion factors and weights of various operation monitoring data in each time interval during the dynamic test of the double-shaft crusher are combined to determine the linear response deviation value of various operation monitoring data in each time interval during the dynamic test of the double-shaft crusher. The specific calculation relationship is: ; In the formula, Indicates the first In the time interval The linear response deviation value of the operation monitoring data; and They represent the first In the time interval Variance inflation factors and weights of various operation monitoring data.

[0069] It should be noted that the larger the calculated linear response deviation value is, the more In the time interval The more significant the response characteristics of the operation monitoring data are when the load changes frequently.

[0070] Step 2.3, based on the difference in distribution range of various operation monitoring data between each time interval and all other time intervals, and the difference in the linear response deviation value, determine the asynchronous response value of the double-shaft crusher in each time interval.

[0071] Since different spindle cutters are affected by the feed and bear different loads during the dynamic test of the double-shaft crusher, the load of the double-shaft crusher changes frequently during the dynamic test, which may cause the operating state of the crusher to change and cause failures. After obtaining the analysis results reflecting the relative response deviation of different time intervals during the dynamic test of the double-shaft crusher; further combined with the data response change range of each time interval during the dynamic test of the double-shaft crusher, the asynchronous response characteristics of the double-shaft crusher are analyzed.

[0072] Specifically, the range of each type of operation monitoring data in each time interval during the dynamic test of the double-shaft crusher is calculated, and the fusion result of the range of each type of operation monitoring data in each time interval and the linear response deviation value is used as the state response value of each type of operation monitoring data in each time interval. The larger the state response value, the greater the response deviation of each type of operation monitoring data when the operation state of the double-shaft crusher changes, and the more significant the response characteristics;

[0073] It should be understood that fusion refers to combining multiple independent variables in a way that enhances the overall effect, such as an additive relationship, a multiplicative relationship, etc. The implementer may limit it according to the actual situation, and this application does not impose any special restrictions.

[0074] In this embodiment, the sum of the range and the linear response deviation value of each type of operation monitoring data in each time interval is used as the state response value of each type of operation monitoring data in each time interval.

[0075] In another embodiment, the product of the range of each type of operation monitoring data in each time interval and the linear response deviation value is used as the state response value of each type of operation monitoring data in each time interval.

[0076] The state response values ​​of all kinds of operation monitoring data in each time interval during the dynamic test of the double-shaft crusher are combined into each state response sequence. According to the distribution of elements in the state response sequence of each time interval during the dynamic test of the double-shaft crusher, and the distance between each time interval and the state response sequence of all other time intervals, the asynchronous response value of the double-shaft crusher in each time interval is determined. The specific calculation relationship is:

[0077] ; In the formula, Indicates that the double-shaft crusher is Asynchronous response value of a time interval; and Respectively represent and The state response sequence of a time interval; dis() represents the distance function; μ() represents the mean function; Indicates the number of time intervals.

[0078] In this embodiment, the distance between the state response sequences is the DTW distance. As other implementation methods, on the basis of being able to measure the distance between the state response sequences, the implementer may adopt other existing technologies to measure the distance between the state response sequences, such as Euclidean distance, Manhattan distance, etc., and this application does not impose any special restrictions.

[0079] It should be noted that the larger the calculated asynchronous response value is, the greater the possibility that the coordinated working state of different spindle tools will change due to the change of running state during the dynamic test of the double-shaft crusher, and the greater the possibility that the double-shaft crusher will vibrate abnormally. The greater the probability of an operation failure in a time interval, the greater the probability of an operation failure. Figure 3 shown.

[0080] Step 2.4: judging whether the double-shaft crusher has an operation fault based on the distribution of the asynchronous response value.

[0081] The average of the normalized values ​​of the asynchronous response values ​​of the double-shaft crusher in all time intervals is used as the fault judgment value of the double-shaft crusher. The larger the fault judgment value, the greater the possibility of a fault in the double-shaft crusher during operation. When the operating state of the double-shaft crusher is stable, the response changes of different types of operating monitoring data of the double-shaft crusher are stable. If the long-term frequent load switching during the operation of the double-shaft crusher causes a large change in the operating state of the double-shaft crusher's cutter after feeding, or the connecting parts of the double-shaft crusher are loose and the cutter is worn, it will cause a large deviation in the response of the double-shaft crusher in different time periods, and an operating fault may occur.

[0082] In this embodiment, the Min-Max normalization method is used to obtain the normalized value of the asynchronous response value. As other implementation methods, on the basis of being able to obtain the normalized value of the asynchronous response value, the implementer may use other existing technologies to obtain the normalized value of the asynchronous response value, such as the Z-Score normalization method, the decimal calibration normalization method, etc., and this application does not impose any special restrictions.

[0083] Furthermore, a fault monitoring threshold is set. When the fault judgment value is greater than or equal to the fault monitoring threshold, it is determined that there is an operating fault during the dynamic test of the double-shaft crusher, and an early warning is issued; when the fault judgment value is less than the fault monitoring threshold, it is determined that the double-shaft crusher operates normally during the dynamic test.

[0084] In this embodiment, the value of the fault monitoring threshold is 0.3. The value of the fault monitoring threshold is preset manually and can be set by the implementer. This application does not impose any special restrictions.

[0085] Based on the same inventive concept as the above method, an embodiment of the present application also provides a fault monitoring system for crushing and screening equipment, including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, the steps of any one of the above-mentioned fault monitoring methods for crushing and screening equipment are implemented.

[0086] In summary, this application focuses on a single operating parameter in traditional monitoring, and does not comprehensively consider the impact mechanism of different load states on the key components of the double-shaft crusher, which makes it difficult to accurately judge the operating status and potential failure risks of the double-shaft crusher when facing complex feeding conditions. This application is based on the frequent changes in load during the dynamic test of the double-shaft crusher, which makes the impact force, torque and other load parameters of the double-shaft crusher show dynamic fluctuations, and there are asynchronous response characteristics to load changes in different time periods. Based on the moment of the comprehensive deviation response of the tool working state during the dynamic test of the double-shaft crusher, the operating time range of the double-shaft crusher is divided, and the time intervals with different response states are accurately divided through the comprehensive influence of all the main shafts of the double-shaft crusher, which is convenient for the subsequent accurate analysis of the response deviation of the double-shaft crusher during operation;

[0087] Furthermore, based on the time intervals divided by the comprehensive deviation response analysis, the collinearity characteristics of different types of operation monitoring data in local time periods during the dynamic test of the double-shaft crusher are analyzed to obtain the response deviation of each type of operation monitoring data. The response deviations of different time periods during the dynamic test of the double-shaft crusher and the significance characteristics of the response are combined to obtain the linear response deviation value, and further combined with the data response change range of each time interval during the dynamic test of the double-shaft crusher to obtain the asynchronous response value to determine whether the double-shaft crusher has an operating failure. The response deviations of different types of operation monitoring data when the operating state of the double-shaft crusher changes are fully considered to accurately determine the operating state and potential failure risks of the double-shaft crusher, thereby improving the accuracy of monitoring the operating failure of the double-shaft crusher.

[0088] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

[0089] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the basic features of the present application. Therefore, no matter from which point of view, the above embodiments of the present application should be regarded as exemplary and non-restrictive.

Claims

1. A fault monitoring method for crushing and screening equipment, characterized in that: The method comprises the following steps: Real-time collection of various operating monitoring data of the double-shaft crusher, including speed data; Determine whether the speed data exceeds the preset stable range. If so, determine that the double-shaft crusher has an operating fault. Otherwise, determine whether the double-shaft crusher has an operating fault based on all types of operating monitoring data. The specific steps are: Based on the distribution of all types of operation monitoring data at all collection moments, the operation time range of the double-shaft crusher is divided into various time intervals; Based on the collinearity between various operation monitoring data in each time interval and all other operation monitoring data, as well as the discreteness of various operation monitoring data, the linear response deviation value of various operation monitoring data in each time interval is determined; Determine the asynchronous response value of the double-shaft crusher in each time interval based on the difference in the distribution range of various operation monitoring data between each time interval and all other time intervals, and the difference in the linear response deviation value; Based on the distribution of the asynchronous response values, it is determined whether the double-shaft crusher has an operation fault; The operation monitoring data also includes torque data and vibration frequency data; The process of determining the linear response deviation value is as follows: Calculate the variance inflation factors of various operational monitoring data in each time interval; The objective weighting method is used to calculate the weight of each operation monitoring data; The linear response deviation value is the product of the inverse of the variance inflation factor and the weight; The process of determining the asynchronous response value is as follows: Determining the state response value of various operation monitoring data in each time interval based on the distribution range of various operation monitoring data in each time interval and the linear response deviation value; The state response values ​​of all kinds of operation monitoring data in each time interval are combined into each state response sequence; Combined with the distribution of elements in the state response sequence of each time interval and the distance between the state response sequence of each time interval and all other time intervals, the asynchronous response value of the double-shaft crusher in each time interval is determined; The state response value is a fusion result of the range of various operation monitoring data in each time interval and the linear response deviation value; The calculation formula of the asynchronous response value is: ; In the formula, Indicates that the double-shaft crusher is Asynchronous response value of a time interval; and Respectively represent and The state response sequence of a time interval; dis() represents the distance function; μ() represents the mean function; Indicates the number of time intervals.

2. The fault monitoring method for crushing and screening equipment according to claim 1, characterized in that: The process of dividing the operating time range of the double-shaft crusher into various time intervals is as follows: The sum of the normalized data of all kinds of operation monitoring data at each collection moment is taken as the instantaneous comprehensive state data of the double-shaft crusher at each collection moment; The data of each acquisition moment and its instantaneous comprehensive state are combined into two-dimensional data points, and the mutation point detection algorithm is used to obtain the mutation point in all data points; The time corresponding to the mutation point is used as the division point of the operating time range of the double-shaft crusher, and the operating time range is divided into various time intervals.

3. The fault monitoring method for crushing and screening equipment according to claim 1, characterized in that: The process of judging whether the double-shaft crusher has an operation fault based on the distribution of the asynchronous response value is as follows: Based on the distribution of the asynchronous response value, a fault judgment value of the double-shaft crusher is obtained; When the fault judgment value is greater than or equal to the preset fault monitoring threshold, it is determined that the double-shaft crusher is operating faulty; otherwise, it is determined that the double-shaft crusher is operating normally.

4. The fault monitoring method for crushing and screening equipment according to claim 3, characterized in that: The fault judgment value is the average of the normalized values ​​of the asynchronous response values ​​of the double-shaft crusher in all time intervals.

5. A fault monitoring system for crushing and screening equipment, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the fault monitoring method for crushing and screening equipment as described in any one of claims 1 to 4 are implemented.

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