A method and system for operation monitoring and diagnosis of a multi-stage belt conveyor system

Abstract

The application provides a kind of operation monitoring and diagnosis method and system for multistage belt conveying system, comprising: obtaining the mass conversion coefficient and the no-load current of the first conveying unit and the second conveying unit;Real-time running current of the first conveying unit and the second conveying unit in two consecutive observation windows is collected, and the current change cumulative value is calculated;According to the current change cumulative value and the mass conversion coefficient, the mass estimation value of the first conveying unit and the second conveying unit is calculated;The mass estimation value of the first conveying unit between two observation windows and the mass estimation value of the second conveying unit in two observation windows are compared, and the diagnosis result of material conveying state is output.The application utilizes the self-comparison mechanism of the same conveying unit before and after window and the linkage imbalance characteristics between upstream and downstream, realizes effective distinction of normal working condition fluctuation and real fault, and can accurately locate the specific conveying unit where fault occurs.

Description

Technical Field

[0001] This invention belongs to the field of material conveying monitoring technology, and in particular relates to a method and system for operation monitoring and diagnosis of multi-stage belt conveyor systems. Background Technology

[0002] Multi-stage belt conveyor systems are widely used for the long-distance continuous transfer of bulk materials in industries such as mining, metallurgy, and power. Real-time monitoring of the conveyor system's operating status is crucial to ensuring production safety and operational efficiency.

[0003] In existing technologies, common monitoring methods include installing belt scales on individual conveyor belts for instantaneous flow monitoring, or setting thresholds for the drive motor current of individual belts to trigger over-limit alarms. However, these methods only reflect local load conditions and do not consider the characteristics of multi-stage conveyor systems, where similar equipment (such as belt conveyors, screw conveyors, chain conveyors, etc.) operate in series, making it impossible to synchronously capture the dynamic material transfer between upstream and downstream units. In actual operation, abnormal current fluctuations can be caused by various reasons: large pieces of material passing normally, operators actively adjusting the feed rate, material jamming leading to blockages, or large pieces of material adhering to the belt suddenly falling off. Existing single-threshold alarm methods cannot accurately distinguish these operating conditions, easily misjudging normal production load fluctuations as faults and triggering unnecessary shutdowns, or failing to report dangerous conditions such as jamming or falling off due to insignificant current changes.

[0004] Furthermore, when an anomaly is detected, existing technology cannot determine which specific belt the fault occurred on. Maintenance personnel can only rely on manual inspection along the conveyor line one by one, which leads to serious delays in fault handling and may even cause safety accidents such as equipment overload damage or belt tearing due to failure to remove blockages in time. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention aims to propose a method and system for operation monitoring and diagnosis of multi-stage belt conveyor systems. This solves the problem that the prior art cannot accurately distinguish between working conditions such as jamming faults, detachment of adhering materials and normal passage of large materials, and normal conveying volume adjustment, and cannot accurately locate the specific conveying unit where the fault occurs.

[0006] To achieve the above objectives, the technical solution of the present invention is implemented as follows: A method for operation monitoring and diagnosis of a multi-stage belt conveyor system, the method being applied to a multi-stage conveyor system comprising at least a first conveyor unit and a second conveyor unit connected in series, the method comprising the following steps: S1. Obtain the mass conversion factor and no-load current of the first and second conveying units; S2. Collect the real-time operating current of the first and second transmission units within two consecutive observation windows of equal duration, and calculate the cumulative current change of the first and second transmission units within the two observation windows based on the no-load current. S3. Calculate the estimated mass values ​​of the first and second transmission units within the two observation windows based on the corresponding cumulative current change value and mass conversion factor. S4. Compare the estimated mass values ​​of the first conveying unit between the two observation windows with the estimated mass values ​​of the second conveying unit within the two observation windows, and output the diagnostic results of the material conveying status.

[0007] Furthermore, the specific steps for calculating the mass conversion factor are as follows: Obtain the current increment when a standard material of known mass passes through the corresponding conveying unit, and use the ratio of the material mass to the current increment of the corresponding conveying unit as the mass conversion factor of the corresponding conveying unit.

[0008] Furthermore, in S2, the two consecutive observation windows are the first observation window and the second observation window, respectively; The length of the observation window is greater than or equal to the sum of the time it takes for the standard material to pass through the first conveying unit and the time it takes to pass through the second conveying unit.

[0009] Furthermore, in S2, the specific steps for calculating the cumulative value of current change are as follows: Within the first observation window, the real-time operating current I of the first transmission unit and the second transmission unit is acquired respectively. 11_inst(t) I 21_inst(t) Within the second observation window, the real-time operating current I of the first transmission unit and the second transmission unit is acquired respectively. 12_inst(t) I 22_inst(t) ; The cumulative current change ΔI of the first transmission unit within the first observation window 11 ΔI 11 =Σ{t∈Tobs}[I 11_inst(t) I 1_avg ]; The cumulative current change ΔI of the first transmission unit within the second observation window 12 ΔI 12 =Σ{t∈Tobs}[I 12_inst(t) I 1_avg ]; The cumulative current change ΔI of the second transmission unit within the first observation window 21 ΔI 21 =Σ{t∈Tobs}[I 21_inst(t) I 2_avg ]; The cumulative current change ΔI of the second transmission unit within the second observation window 22 ΔI 22 =Σ{t∈Tobs}[I 22_inst(t) I 2_avg ]; Where Tobs is the length of the observation window.

[0010] Furthermore, in S3, the specific steps for calculating the estimated quality value are as follows: Within the first observation window, the first estimated mass value Δm is calculated based on the mass conversion factor k1 of the first conveying unit. 11 , Δm 11 =k1·ΔI 11 The third estimated mass value Δm is calculated based on the mass conversion factor k2 of the second conveying unit. 21 , Δm 21 =k2·ΔI 21 ; Within the second observation window, the second estimated mass value Δm is calculated based on the mass conversion factor k1 of the first conveying unit. 12 , Δm 12 =k1·ΔI 12 The fourth estimated mass value Δm is calculated based on the mass conversion factor k2 of the second conveying unit. 22 , Δm 22 =k2·ΔI 22 .

[0011] Furthermore, in S4, when comparing the first quality estimate, the second quality estimate, the third quality estimate, and the fourth quality estimate, an allowable upper deviation coefficient L1 and an allowable lower deviation coefficient L2 are preset.

[0012] Furthermore, the allowable upper deviation coefficient L1 ranges from 1.05 to 1.1, and the allowable lower deviation coefficient L2 ranges from 0.9 to 0.95.

[0013] Furthermore, in S4, the diagnostic results include jamming faults, specifically: When Δm is satisfied 11 ·L1<Δm 12 And Δm 22 <Δm 21 At L2, the diagnosis was that the first conveying unit was jammed; When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 21 ·L1<Δm 22 At that time, the diagnosis result was that the second conveying unit was stuck.

[0014] Furthermore, in S4, the diagnostic results include material shedding, specifically: When Δm is satisfied 12 <Δm 11 ·L2 and Δm 21 ·L1<Δm 22 At that time, the diagnosis was that large pieces of material adhering to the first conveying unit had fallen off; When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 22 <Δm 21 At L2, the diagnosis result was that large pieces of material adhering to the second conveying unit had fallen off.

[0015] Furthermore, in S4, the diagnostic results include normal operating conditions, specifically: When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 21 ·L2<Δm 22 <Δm 21 At L1, the diagnostic result indicates normal operation. When Δm is satisfied 12 <Δm 11 ·L2 and Δm 22 <Δm 21 At L2, the diagnosis was a normal adjustment due to a decrease in feed rate. When Δm is satisfied 11 ·L1<Δm 12 And Δm 21 ·L1<Δm 22 At that time, the diagnosis was that the increase in feed volume was a normal adjustment under operating conditions.

[0016] Furthermore, when the multi-stage conveying system includes multiple conveying units operating in series, and multiple fault diagnosis results exist at the same time, the handling priority is determined according to the degree of hazard. Conveying units that experience jamming faults are handled first, followed by conveying units that experience material spillage.

[0017] A system for monitoring and diagnosing the operation of a multi-stage belt conveyor system, comprising executing the aforementioned method for monitoring and diagnosing the operation of a multi-stage belt conveyor system, including: The parameter acquisition module is used to acquire the mass conversion factor and no-load current of the first and second conveying units; The data acquisition and calculation module is used to acquire the real-time operating current of the first and second transmission units within two consecutive observation windows, and to calculate the cumulative current change of the first and second transmission units within the two observation windows in combination with the no-load current. The quality estimation module is used to calculate the quality estimation values ​​of the first transmission unit and the second transmission unit within two observation windows based on the corresponding cumulative current change value and quality conversion factor. The diagnostic output module is used to compare the estimated mass values ​​of the first conveying unit and the estimated mass values ​​of the second conveying unit between two observation windows, and output the diagnostic results of the material conveying status.

[0018] Compared with existing technologies, the operation monitoring and diagnosis method and system for multi-stage belt conveyor systems described in this invention have the following advantages: This invention establishes a linear mapping relationship between current signals and material mass by acquiring the mass conversion coefficients and no-load current of the first and second conveying units; it transforms raw current data into quantifiable load characteristics by collecting real-time operating current within two consecutive observation windows and calculating the cumulative current change value; it calculates the estimated mass value of each window based on the cumulative current change value and the mass conversion coefficient, making the loads between different conveying units comparable; and it outputs diagnostic results by comparing the estimated mass values ​​of the same conveying unit between the two observation windows and the estimated mass values ​​of upstream and downstream conveying units. By utilizing the self-comparison mechanism of the front and rear windows of the same conveying unit and the linkage imbalance characteristics between upstream and downstream, it effectively distinguishes between normal operating condition fluctuations and actual faults, and can accurately locate the specific conveying unit where the fault occurred.

[0019] This invention can distinguish between jamming faults, adhering material falling off, and normal passage of large pieces of material and feed rate adjustment without the need for any additional hardware sensors, significantly reducing the false alarm rate and missed alarm rate. At the same time, it can accurately locate the fault location and provide clear guidance for subsequent maintenance.

[0020] This invention sets a priority order for handling multiple faults in a multi-level conveying system, which includes multiple conveying units operating in series and has multiple fault diagnosis results. The priority order is determined according to the severity of the fault. Conveyor units experiencing jamming faults are dealt with first, followed by conveyor units experiencing material spillage. This allows operators to arrange maintenance work according to the correct priority order when multiple faults occur simultaneously, avoiding delays in troubleshooting serious faults (such as jamming) due to prioritizing minor faults. This minimizes equipment damage and downtime losses, and improves system safety and maintenance efficiency. Attached Figure Description

[0021] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of the overall process provided for an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of Embodiment 1 provided in this invention.

[0022] Explanation of reference numerals in the attached figures: 1. First current sampling module; 2. First belt; 3. First belt discharge end; 4. Second current sampling module; 5. Second belt; 6. Second belt discharge end. Detailed Implementation

[0023] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0024] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are used only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0025] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0026] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0027] like Figures 1 to 2 As shown, a method for operation monitoring and diagnosis of a multi-stage belt conveyor system is disclosed. This method is applied to a multi-stage conveyor system, which includes at least a first conveyor unit and a second conveyor unit connected in series. The method includes the following steps: S1. Obtain the mass conversion factor and no-load current of the first and second conveying units; S2. Collect the real-time operating current of the first and second transmission units within two consecutive observation windows of equal duration, and calculate the cumulative current change of the first and second transmission units within the two observation windows in combination with the no-load current. S3. Calculate the estimated mass values ​​of the first and second transmission units within the two observation windows based on the corresponding cumulative current change value and mass conversion factor. S4. Compare the estimated mass values ​​of the first conveying unit between the two observation windows with the estimated mass values ​​of the second conveying unit within the two observation windows, and output the diagnostic results of the material conveying status.

[0028] This invention is applied to multi-stage series conveying systems, where the conveying units can be belt conveyors, chain conveyors, scraper conveyors, or other continuous conveying equipment. Material is transferred from the upstream conveying unit to the downstream conveying unit. Under normal circumstances, the mass passing through the upstream and downstream conveying units per unit time should maintain a dynamic balance. When a jamming fault occurs, material accumulation upstream of the fault point causes a sudden increase in the estimated mass value, while insufficient material supply downstream causes a sudden decrease in the estimated mass value. When adhering material detaches, the estimated mass value of the conveying unit where the detachment source is located suddenly decreases, while the estimated mass value of the downstream conveying unit suddenly increases. By establishing two continuous observation windows and comparing the upstream and downstream conveying units before and after their respective operations, these characteristic imbalance patterns can be extracted from the current signal, thereby accurately determining the operating condition. It should be further noted that this invention is only applicable to the paired use of similar conveying units; that is, the upstream and downstream conveying units should be of the same type with consistent structure and load response characteristics. This invention is not applicable to scenarios where different types of conveying equipment are mixed together, to ensure the accuracy and reliability of mass estimation and operating condition diagnosis.

[0029] Specifically, in S1, before performing online monitoring, it is necessary to first obtain the mass conversion factor of each conveying unit through calibration tests. The mass conversion factor reflects the linear mapping relationship between the mass of material carried by the conveying unit and the increment of its drive motor current. The no-load current refers to the stable operating current of the conveying unit when there is no material load and it only overcomes its own mechanical resistance and no-load loss. It can be obtained by collecting the average current over a period of time under no-load conditions.

[0030] The specific steps for calculating the mass conversion factor are as follows: Obtaining the mass conversion factor involves the current increment when a standard material of known mass passes through the corresponding conveying unit, and using the ratio of the material mass to the current increment of the corresponding conveying unit as the mass conversion factor of the corresponding conveying unit.

[0031] Specifically, before the system is put into operation, a standard material of known mass (such as a standard coal block, standard weight, etc.) is selected, and this standard material is passed through the first conveying unit alone. The increment ΔI of the first conveying unit relative to the no-load current during the passage of the standard material is recorded. Let the mass of the standard material be m0, then the mass conversion factor k1 of the first conveying unit is k1 = m0 / ΔI. Similarly, the same calibration operation is performed on the second conveying unit to obtain the mass conversion factor k2 of the first conveying unit.

[0032] Obtaining the quality conversion factor through calibration can eliminate the impact of differences in mechanical characteristics and motor efficiency between different conveying units, ensuring the traceability and consistency of quality estimation results. This method is simple and easy to implement, requires no complex theoretical calculations, and is suitable for rapid deployment in industrial settings.

[0033] In S2, two consecutive observation windows of equal duration refer to time intervals that are sequentially connected, non-overlapping, and of equal length. Within each observation window, the real-time operating current of each conveying unit is collected at a fixed sampling frequency (e.g., once every 0.1 seconds). The cumulative current change reflects the total additional current consumption of the conveying unit due to carrying materials within an observation window.

[0034] In S3, the cumulative value of current change calculated for each observation window is multiplied by the pre-calibrated mass conversion factor of the conveying unit to obtain the estimated value of the mass of the material passing through the conveying unit within the observation window.

[0035] In S4, by comparing the estimated mass values ​​of the same conveying unit in two consecutive observation windows, the trend of load change of the conveying unit can be determined; by comparing the change patterns of the estimated mass values ​​of upstream and downstream conveying units, abnormal working conditions such as material jamming or falling off during the transfer process can be identified, thereby outputting diagnostic conclusions.

[0036] This invention eliminates the need for additional hardware sensors, utilizing only the existing motor current signal from the conveying unit to achieve status diagnosis of a multi-stage conveying system. Through a dual-window self-comparison mechanism, it effectively distinguishes between normal production fluctuations (such as feed rate adjustments) and actual faults, avoiding the high false alarm rate problem of traditional single-threshold alarm methods. Furthermore, this invention can accurately locate the specific conveying unit where the fault occurred, providing a basis for subsequent precise maintenance.

[0037] In a preferred embodiment of the present invention, in S2, the two consecutive observation windows of equal duration are the first observation window and the second observation window, respectively. The length of the observation window is greater than or equal to the sum of the time it takes for the standard material to pass through the first conveying unit and the time it takes to pass through the second conveying unit.

[0038] Specifically, two observation windows with sequential timing and a duration of Tobs are set up, namely the first observation window and the second observation window; the length of a single observation window is not less than the sum of the standard material passage time T1_pass of the first conveying unit and the standard material passage time T2_pass of the second conveying unit; so that an observation window can completely cover the entire process of material from upstream to downstream, avoiding distortion of quality estimation values ​​due to window truncation.

[0039] In a preferred embodiment of the present invention, the specific steps for calculating the cumulative value of current change in step S2 are as follows: Obtain the no-load operating current I of the first transmission unit 1_avg Obtain the no-load operating current I of the second transmission unit. 2_avg ; The real-time operating current I of the first transmission unit and the second transmission unit is acquired within the first observation window. 11_inst(t) I 21_inst(t) Within the second observation window, the real-time operating current I of the first and second transmission units is acquired. 12_inst(t) I 22_inst(t) ; Obtain the cumulative current change ΔI of the first transmission unit within the first observation window. 11 ΔI 11 =Σ{t∈Tobs}[I 11_inst(t) I 1_avg The cumulative current change ΔI of the first transmission unit within the second observation window. 12 ΔI 12 =Σ{t∈Tobs}[I 12_inst(t) I 1_avg The cumulative value of the current change ΔI of the second transmission unit within the first observation window. 21 ΔI 21 =Σ{t∈Tobs}[I 21_inst(t) I 2_avg The cumulative current change ΔI of the second transmission unit within the second observation window. 22 ΔI 22 =Σ{t∈Tobs}[I 22_inst(t) I 2_avg ].

[0040] In a preferred embodiment of the present invention, in S3, the estimated quality value is equal to the product of the quality conversion factor of the corresponding transmission unit and the cumulative value of the current change within the corresponding observation window.

[0041] Specifically, the mass estimation values ​​of the first delivery unit within the first observation window and the second observation window are respectively the first mass estimation value Δm. 11 Second mass estimate Δm 12 ; The mass estimation values ​​of the second transport unit within the first and second observation windows are respectively the third mass estimation value Δm. 21 and the fourth mass estimate Δm 22 ; The first estimated mass value Δm is calculated based on the mass conversion factor k1 of the first conveying unit. 11 , Δm 11 =k1·ΔI 11 Second mass estimate Δm 12 , Δm 12 =k1·ΔI 12; The third estimated mass value Δm is calculated based on the mass conversion factor k2 of the second conveying unit. 21 , Δm 21 =k2·ΔI 21 The fourth mass estimate Δm 22 , Δm 22 =k2·ΔI 22 .

[0042] In a preferred embodiment of the present invention, in S4, the first mass estimation value Δm is... 11 Second mass estimate Δm 12 The third mass estimate Δm 21 and the fourth mass estimate Δm 22 When making comparisons, an upper allowable deviation coefficient L1 and an lower allowable deviation coefficient L2 are preset; and the upper allowable deviation coefficient L1 has a value range of 1.05 to 1.1, and the lower allowable deviation coefficient L2 has a value range of 0.9 to 0.95.

[0043] Specifically, the two coefficients define the permissible fluctuation range of the quality estimate under normal operating conditions. For example, when L1 = 1.08 and L2 = 0.92, then Δm is considered to be within a certain range. 12 Relative to Δm 11 Fluctuations between 0.92 and 1.08 times are considered normal production fluctuations (such as minor changes in feed amount or fluctuations in material moisture content), while fluctuations outside this range are considered significant changes.

[0044] By setting an adjustable deviation coefficient, this embodiment can adapt to the fluctuation range requirements under different working conditions, ensuring both sensitivity to real faults and maintaining stability during normal production, while reducing unnecessary alarms.

[0045] In a preferred embodiment of the present invention, in step S4, the diagnostic result includes a jamming fault, specifically: When Δm is satisfied 11 ·L1<Δm 12 And Δm 22 <Δm 21 At L2, the diagnosis was that the first conveying unit was jammed; When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 21 ·L1<Δm 22 At that time, the diagnosis result was that the second conveying unit was stuck.

[0046] Specifically, when the first conveying unit is jammed, the material accumulates on the first conveying unit and cannot be smoothly unloaded to the second conveying unit. As a result, the load on the first conveying unit increases significantly in the second observation window, while the load on the second conveying unit decreases significantly because it cannot receive any material.

[0047] When the second conveying unit is blocked, the material can be transferred normally from the first conveying unit to the second conveying unit, but cannot be discharged from the second conveying unit, resulting in a significant increase in the load of the second conveying unit, while the load of the first conveying unit remains within the normal fluctuation range.

[0048] This embodiment can accurately distinguish the specific location where the jamming occurs. Since jamming is a serious fault (which may lead to safety accidents such as equipment overload and belt tearing), this embodiment can output a jamming alarm and indicate the faulty unit in the first instance, which facilitates a quick response from maintenance personnel.

[0049] In a preferred embodiment of the present invention, in S4, the diagnostic result includes material shedding, specifically: When Δm is satisfied 12 <Δm 11 ·L2 and Δm 21 ·L1<Δm 22 At that time, the diagnosis was that large pieces of material adhering to the first conveying unit had fallen off; When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 22 <Δm 21 At L2, the diagnosis result was that large pieces of material adhering to the second conveying unit had fallen off.

[0050] Specifically, when large pieces of material adhering to the first conveyor unit (such as damp coal stuck to the belt) suddenly detach and fall onto the second conveyor unit during operation, the load on the first conveyor unit is suddenly reduced (Δm). 12 The load was significantly reduced, while the second conveying unit received additional large pieces of material that had fallen off, resulting in a sudden increase in load (Δm). 22 (Significant increase).

[0051] When large pieces of material adhering to the second conveying unit detach, the material falls from the second conveying unit to the ground or a collection device and no longer enters the downstream area. Therefore, the load on the second conveying unit is suddenly reduced (Δm). 22 (significantly reduced), while the load on the first conveying unit remained normal.

[0052] While the detachment of large pieces of material is not as urgent as a jamming fault, the detached material may damage downstream equipment or block the discharge port, posing a potential hazard. This embodiment can identify such anomalies and locate the conveyor unit where the detachment occurs, prompting maintenance personnel to clean it up and prevent secondary accidents.

[0053] In a preferred embodiment of the present invention, in step S4, the diagnostic result includes normal operating conditions, specifically: When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 21 ·L2<Δm 22 <Δm 21 At L1, the diagnostic result indicates normal operation. When Δm is satisfied 12 <Δm 11 ·L2 and Δm 22 <Δm 21 At L2, the diagnosis was a normal adjustment due to a decrease in feed rate. When Δm is satisfied 11 ·L1<Δm 12 And Δm 21 ·L1<Δm 22 At that time, the diagnosis was that the increase in feed volume was a normal adjustment under operating conditions.

[0054] Specifically, by observing the direction and magnitude of synchronous changes in upstream and downstream quality estimates, one can distinguish between genuine faults and normal feeding adjustments. Jamming or detachment faults will cause upstream and downstream quality changes to occur in opposite directions or only on one side, while feeding adjustments will cause changes on both sides in the same direction.

[0055] This embodiment effectively avoids the pain point of frequent false alarms in traditional monitoring systems when production load fluctuates, enabling this method to truly adapt to the needs of continuous variable operating conditions in industrial sites, and significantly reducing the psychological burden on operators and the amount of ineffective confirmation work.

[0056] In a preferred embodiment of the present invention, when the multi-stage conveying system includes multiple conveying units operating in series and multiple fault diagnosis results exist at the same time, the handling priority is determined according to the degree of hazard. The conveying unit that experiences jamming fault is handled first, and the conveying unit that experiences material detachment is handled second.

[0057] Specifically, assuming a production line consisting of five conveyor units connected in series, the diagnostic system simultaneously outputs two alarms within the same observation period: "Third conveyor unit jammed" and "Material spillage in first conveyor unit." According to this priority rule, the system should prioritize outputting the emergency alarm "Third conveyor unit jammed" to the operator or automated control system and recommend immediate shutdown for handling; simultaneously, record "Material spillage in first conveyor unit" as a secondary alarm, to be handled after the jamming fault has been resolved.

[0058] Obstruction can directly lead to material blockage, equipment overload, and even serious accidents such as belt tearing or motor burnout, requiring emergency intervention. Adhesive material shedding mainly causes impact on downstream equipment and environmental pollution, with relatively delayed consequences. Therefore, prioritizing maintenance resources based on the degree of hazard allows for more rational allocation of resources.

[0059] When multiple faults occur simultaneously, this embodiment can help on-site personnel handle them according to the correct priorities, avoiding delays in troubleshooting major faults due to prioritizing minor issues, thereby minimizing accident losses.

[0060] A system for monitoring and diagnosing the operation of a multi-stage belt conveyor system, comprising executing the aforementioned method for monitoring and diagnosing the operation of a multi-stage belt conveyor system, including: The parameter acquisition module is used to acquire the mass conversion factor and no-load current of the first and second conveying units; The data acquisition and calculation module is used to acquire the real-time operating current of the first and second transmission units within two consecutive observation windows, and to calculate the cumulative current change of the first and second transmission units within the two observation windows in combination with the no-load current. The quality estimation module is used to calculate the quality estimation values ​​of the first transmission unit and the second transmission unit within two observation windows based on the corresponding cumulative current change value and quality conversion factor. The diagnostic output module is used to compare the estimated mass values ​​of the first conveying unit and the estimated mass values ​​of the second conveying unit between two observation windows, and output the diagnostic results of the material conveying status.

[0061] The parameter acquisition module includes a first current sampling module for acquiring the no-load current of the first transmission unit and a second current sampling module for acquiring the no-load current of the second transmission unit.

[0062] Example 1 To verify the invention's ability to synchronously determine and diagnose the status of large materials, such as whether they pass through, whether they are stuck, or whether they fall off, under continuous industrial operation conditions, a 72-hour continuous operation test was conducted on a multi-stage belt conveyor system consisting of a first belt 2 and a second belt 5 connected in series. The first belt 2 is equipped with a first current sampling module 1, and the material enters the second belt 5 from the first belt discharge end 3. The second belt 5 is equipped with a second current sampling module 4, and the material is discharged from the second belt discharge end 6.

[0063] The experimental conditions are as follows: System parameters: First belt bandwidth 1.2m, belt speed 2.5m / s; Second belt bandwidth 1.0m, belt speed 2.0m / s.

[0064] Standard material: Use standard coal blocks of known quality, each block weighing 50 kg.

[0065] Calibration process: Under standard operating conditions, a single standard coal block is passed through the first conveyor belt, and the current increment ΔI is recorded. The first mass conversion factor k1 = 50 / ΔI is calculated. Similarly, the mass conversion factor k2 for the second conveyor belt is obtained. (If standard materials of different masses are used, the mass values ​​are adjusted accordingly).

[0066] Normal passage time: Through multiple actual measurements, it was determined that the time required for a single standard material to pass through completely on the first belt is T1_pass=8s, and the passage time on the second belt is T2_pass=6s.

[0067] Observation window: Tobs = T1_pass + T2_pass = 14s.

[0068] Preset allowable deviation coefficients: L1=1.08, L2=0.92.

[0069] Data acquisition frequency: Current value is sampled once every 0.1 seconds.

[0070] The specific test results are as follows: (1) Stable and normal operation of materials Test data: First mass estimate Δm of the first belt in the first observation window 11 =490kg, the second estimated mass value Δm in the second observation window. 12 =500kg; the first estimated mass of the second belt in the first observation window Δm 21 =485kg, the second estimated mass value Δm in the second observation window. 22 =495kg.

[0071] Judgment process: satisfying Δm 11 ·L2<Δm 12 <Δm 11 ·L1, and Δm 21·L2<Δm 22 <Δm 21 • L1, the quality of the upstream and downstream belt windows is within the normal deviation range, with no abnormal quality imbalance.

[0072] Diagnostic conclusion: The material is being conveyed smoothly, the system is operating normally, and there are no fault alarms.

[0073] (2) Actively adjust the feeding rate. Test data (feed reduction): Δm 11 =500kg, Δm 12 =440kg; Δm 21 =490kg, Δm 22 =430kg. The quality of both upstream and downstream processes decreased slightly, meeting the characteristics of simultaneous reduction within a dual-window period.

[0074] Test data (feeding improvement): Δm 11 =440kg, Δm 12 =490kg; Δm 21 =430kg, Δm 22 =480kg. The quality of both upstream and downstream processes increased slightly, meeting the characteristics of simultaneous incremental increases within a dual-window period.

[0075] Diagnostic conclusion: All fluctuations were due to normal operating conditions caused by on-site adjustments to the feeding rate, not equipment failure, and the system did not issue any false alarms.

[0076] (3) Large pieces of material adhering to the second belt fall off. Test data: Δm 11 =480kg, Δm 12 =475kg; Δm 21 =490kg, Δm 22 =440kg.

[0077] Judgment process: satisfying Δm 11 ·L2<Δm 12 <Δm 11 • L1 (upstream quality is stable and without fluctuations), while simultaneously satisfying Δm 22 <Δm 21 • L2 (Sudden drop in downstream quality) is consistent with the quality imbalance characteristics of large pieces of material adhering to the second belt falling off.

[0078] Diagnostic conclusion: It was determined that the large pieces of material adhering to the second conveyor belt had fallen off, which is consistent with the actual working conditions.

[0079] (4) Second belt jamming fault Test data: Δm 11 =470kg, Δm 12 =468kg; Δm 21=460kg, Δm 22 =510kg.

[0080] Judgment process: satisfying Δm 11 ·L2<Δm 12 <Δm 11 • L1 (stable upstream material conveying), while simultaneously satisfying Δm 22 >Δm 21 • L1 (downstream material accumulation, sudden increase in quality) is consistent with the imbalance characteristics of material jamming on the second conveyor belt and inability to transfer normally.

[0081] Diagnostic conclusion: The problem was determined to be a jammed second belt, and the fault location was accurate.

[0082] (5) Large pieces of material adhering to the first conveyor belt fell off. Test data: Δm 11 =490kg, Δm 12 =430kg; Δm 21 =440kg, Δm 22 =495kg.

[0083] Judgment process: satisfying Δm 12 <Δm 11 • L2 (Sudden drop in upstream quality), while simultaneously satisfying Δm 22 >Δm 21 •L1 (Sudden surge in downstream material) is consistent with the working condition of large pieces of material adhering to the first belt falling off and material rushing into the downstream in an instant.

[0084] Diagnostic conclusion: It was determined that the large piece of material adhering to the first conveyor belt had fallen off; there were no misjudgments or omissions.

[0085] (6) First belt jamming fault Test data: Δm 11 =450kg, Δm 12 =500kg; Δm 21 =480kg, Δm 22 =435kg.

[0086] Judgment process: satisfying Δm 12 >Δm 11 • L1 (upstream material accumulation, sudden increase in mass), while simultaneously satisfying Δm 22 <Δm 21 •L2 (Insufficient downstream material supply and a sharp drop in quality) is consistent with the imbalance characteristics of the first belt being blocked and materials being unable to be transferred downstream.

[0087] Diagnostic conclusion: The first belt was found to be stuck, and the location of the fault was accurately identified.

[0088] During the aforementioned 72-hour continuous operation test, the invention's judgments for all operating conditions were consistent with the actual situation, with no missed or false alarms. The overall test results show that the invention can distinguish between normal feeding fluctuations, the smooth passage of large materials, and typical fault conditions; it can locate faulty conveyor belts; and it demonstrated strong diagnostic stability with no missed or false alarms during 72 hours of continuous operation.

[0089] Based on the physical transmission laws of multi-stage belt conveyor materials, this embodiment uses two sets of self-comparison logic to cover all operating conditions and complete classification and identification. The logic judgment principle is shown in Table 1.

[0090] Table 1 Principles of Logical Judgment

[0091] Comparative Example 1 The existing industrial monitoring solution is adopted: single-point belt scale instantaneous flow monitoring + single belt independent current threshold monitoring. There is no unified time sequence observation window, no upstream and downstream belt linkage verification, and no dual-window self-comparison judgment logic. Anomalies are judged only by a single current peak or instantaneous flow exceeding the standard.

[0092] Under the same 72-hour continuous operating condition test, the traditional solution has obvious shortcomings: (1) Unable to distinguish between normal working conditions and fault working conditions: When large pieces of material pass smoothly and the on-site feeding amount is adjusted, the current and flow rate will fluctuate normally. Traditional solutions are prone to misjudging as faults and triggering alarms. When large pieces of material that are stuck or adhered fall off, the peak fluctuations are not obvious and the alarms are easily missed.

[0093] (2) No fault location capability: It can only detect abnormal load fluctuations in the system, but cannot distinguish whether the fault location is on the first belt or the second belt, and relies entirely on manual on-site inspection for confirmation.

[0094] (3) No fault classification capability: All abnormalities trigger alarms in the same way, and it is impossible to distinguish between high-risk jamming faults and large pieces of material falling off, which can easily lead to delayed handling of high-risk faults and over-handling of minor faults.

[0095] The final test results are shown in Table 2. The traditional solution had 6 false alarms and 2 missed alarms during 72 hours of operation, which frequently caused unnecessary shutdowns. The accuracy of fault identification and location was extremely low, and it could not meet the requirements of continuous and stable industrial operation.

[0096] Table 2 Comparison of data between Example 1 and Comparative Example 1

[0097] In Example 1, this measure, in conjunction with the structure, achieves a complete path from signal acquisition to quality mapping and then to logical judgment, solving the problem of existing technologies that only provide local monitoring and cannot perform integrated diagnosis. Experimental data shows that this invention can accurately prevent large materials from passing through smoothly and accurately diagnose blockage locations. It features strong real-time monitoring, comprehensive diagnosis covering multiple anomalies, low false alarm rate, and adaptability to continuous operation in industrial settings, significantly improving the safety and maintenance efficiency of bulk material conveying systems.

[0098] Example 2 To further quantify and verify the accuracy of this invention in identifying various typical working conditions, the accuracy of fault location, and its anti-interference capability, a grouped comparative experiment was conducted using the controlled variable method. This experiment covered all typical working conditions of a multi-stage belt conveyor system, setting up an equal number of repeated test samples to compare the performance differences between this invention and traditional manual experience-based discrimination schemes.

[0099] All experimental conditions in this experiment were completely consistent with those in Example 1, and the duration of each test was no less than 10 minutes to ensure that the monitoring data were stable and effective.

[0100] Each working condition was tested independently 10 times, for a total of 6 testing conditions: normal and stable operation 10 times, active increase / decrease in feeding 10 times, first belt jamming 10 times, large pieces of material adhering to the first belt falling off 10 times, second belt jamming 10 times, and large pieces of material adhering to the second belt falling off 10 times.

[0101] (I) Definition of core evaluation indicators of this invention and traditional manual experience-based discrimination schemes: (1) Accuracy rate of normal operating condition identification: Number of times normal non-fault operating conditions were correctly identified / Total number of tests for normal operating conditions × 100%; (2) Accuracy rate of jamming fault identification: Number of times jamming faults were correctly identified / Total number of tests for jamming conditions × 100%; (3) Accuracy rate of jamming fault location: Number of times the belt jamming was correctly identified / Number of times the jamming condition was correctly identified × 100%; (4) Accuracy of identifying large pieces of adhered material falling off: Number of times large pieces of adhered material falling off were correctly identified / Total number of tests for large pieces of adhered material falling off × 100%; (5) Accuracy of positioning large pieces of adhered material falling off: Number of times the belt correctly identified large pieces of adhered material falling off / Number of times the large pieces of adhered material falling off correctly identified × 100%.

[0102] (II) Comparison of experimental results and data between the present invention and traditional manual experience-based discrimination schemes (1) Normal operating condition identification performance: The present invention can distinguish 100% of all normal operating conditions such as stable material conveying and active increase or decrease of feeding amount. There were no alarms or misjudgments in all 10 normal operating conditions and 10 feeding adjustment conditions. The traditional manual identification scheme can only identify basic stable conveying. In 20 normal operating conditions, it misjudged large pieces of material as passing smoothly in 6 cases and small fluctuations in feeding as equipment abnormalities in 4 cases. The accuracy of normal operating condition identification is only 50%.

[0103] (2) Performance of jamming fault diagnosis: The present invention can identify all jamming in 10 tests of the first belt and the second belt. The jamming position can be distinguished by the asymmetric imbalance of upstream and downstream mass. The identification accuracy and positioning accuracy are both 100%. The traditional manual solution relies only on the sudden change of current peak to judge. In 20 jamming conditions, there were 3 missed judgments and 2 wrong judgments. The overall identification accuracy is only 75%. There were also 4 errors in judging the position of the jamming belt. The positioning accuracy is only 73.3%.

[0104] (3) Material shedding diagnosis performance: The present invention can identify all large pieces of material that have fallen off the first belt and the second belt in 10 tests each. It can distinguish faulty belts based on the unique imbalance characteristics of upstream decline and downstream rise, and upstream stability and downstream decline. The identification accuracy and positioning accuracy are both 100%. The traditional manual method cannot distinguish the characteristics of upstream and downstream shedding. In 20 shedding conditions, there were 2 missed judgments and 3 misjudgments. The overall identification accuracy is 75%. There were 5 faulty belt positioning errors. The positioning accuracy is only 66.7%.

[0105] (4) Overall operational stability: The invention has no missed reports or false reports in 60 tests throughout the process. The working condition judgment logic is stable and is not affected by normal production fluctuations. The traditional manual solution has accumulated 15 false reports and 5 missed reports, which can easily lead to production problems such as accidental shutdown and delayed fault handling.

[0106] Table 3 shows a comparison of the data between the present invention and the traditional manual experience-based discrimination scheme.

[0107] Table 3. Comparison of data between the present invention and traditional human experience-based discrimination schemes.

[0108] (III) Experimental Analysis and Verification of Beneficial Effects This embodiment fully verifies the superiority of the core innovative mechanism of this invention through equal-volume group control experiments. This invention employs synchronous sampling with dual-time-series observation windows, self-comparison of quality before and after a single conveyor belt, and a dual-layer self-comparison deviation discrimination logic to distinguish between jamming faults, large material detachment, and normal passage of large materials or normal conveying volume adjustments, thus avoiding false alarms. Simultaneously, combined with a tiered handling logic that prioritizes jamming faults and secondarily addresses large material detachment, it effectively solves the industry pain points of chaotic fault identification, inaccurate location, and delayed handling of high-risk faults in traditional operation and maintenance.

[0109] Comparative test data show that, compared with traditional manual judgment methods, the present invention improves the ability to identify working conditions, the accuracy of fault identification, the accuracy of fault location, and the stability of operation. It reduces manual intervention and reliance on operation and maintenance experience, and can be adapted to the monitoring and diagnosis needs of industrial sites for automation, high precision, and low false alarms. It has strong engineering applicability and promotion value.

[0110] This invention provides a cross-diagnosis method for adjacent conveyor equipment, which can be directly applied to multi-stage, non-adjacent belt-connected conveyor production lines of any number of levels. Specifically, the method involves pairing two belts in the entire production line into independent diagnostic units. Each diagnostic unit independently runs the diagnostic method described in this invention, enabling systematic status monitoring and fault location of the entire production line. Furthermore, the diagnostic units can corroborate each other, improving diagnostic reliability.

[0111] For example, in an upstream diagnostic unit, this method may diagnose that the downstream belt is stuck; and the downstream belt is also the upstream belt in the downstream diagnostic unit. Therefore, two adjacent diagnostic units can simultaneously determine that the equipment is abnormal. Through this alternating verification mechanism, the location of the faulty equipment can be further locked, effectively reducing the false alarm probability of single-unit diagnosis and improving the overall reliability of the diagnostic results.

[0112] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for operation monitoring and diagnosis of a multi-stage belt conveyor system, the method being applied to the multi-stage conveyor system, wherein the multi-stage conveyor system comprises at least a first conveyor unit and a second conveyor unit connected in series, characterized in that, The method includes the following steps: S1. Obtain the mass conversion factor and no-load current of the first and second conveying units; S2. Collect the real-time operating current of the first and second transmission units within two consecutive observation windows of equal duration, and calculate the cumulative current change of the first and second transmission units within the two observation windows based on the no-load current. S3. Calculate the estimated mass values ​​of the first and second transmission units within the two observation windows based on the corresponding cumulative current change value and mass conversion factor. S4. Compare the estimated mass values ​​of the first conveying unit between the two observation windows with the estimated mass values ​​of the second conveying unit within the two observation windows, and output the diagnostic results of the material conveying status.

2. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 1, characterized in that, The specific steps for calculating the mass conversion factor are as follows: Obtain the current increment when a standard material of known mass passes through the corresponding conveying unit, and use the ratio of the material mass to the current increment of the corresponding conveying unit as the mass conversion factor of the corresponding conveying unit.

3. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 1, characterized in that: In S2, the two consecutive observation windows are the first observation window and the second observation window, respectively. The length of the observation window is greater than or equal to the sum of the time it takes for the standard material to pass through the first conveying unit and the time it takes to pass through the second conveying unit.

4. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 3, characterized in that, In S2, the specific steps for calculating the cumulative value of current change are as follows: Within the first observation window, the real-time operating current I of the first transmission unit and the second transmission unit is acquired respectively. 11_inst(t) I 21_inst(t) Within the second observation window, the real-time operating current I of the first transmission unit and the second transmission unit is acquired respectively. 12_inst(t) I 22_inst(t) ; The cumulative current change ΔI of the first transmission unit within the first observation window 11 ΔI 11 =Σ{t∈Tobs}[I 11_inst(t) I 1_avg ]; The cumulative current change ΔI of the first transmission unit within the second observation window 12 ΔI 12 =Σ{t∈Tobs}[I 12_inst(t) I 1_avg ]; The cumulative current change ΔI of the second transmission unit within the first observation window 21 ΔI 21 =Σ{t∈Tobs}[I 21_inst(t) I 2_avg ]; The cumulative current change ΔI of the second transmission unit within the second observation window 22 ΔI 22 =Σ{t∈Tobs}[I 22_inst(t) I 2_avg ]; Where Tobs is the length of the observation window.

5. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 4, characterized in that, In S3, the specific steps for calculating the estimated mass value are as follows: Within the first observation window, the first estimated mass value Δm is calculated based on the mass conversion factor k1 of the first conveying unit. 11 , Δm 11 =k1·ΔI 11 The third estimated mass value Δm is calculated based on the mass conversion factor k2 of the second conveying unit. 21 , Δm 21 =k2·ΔI 21 ; Within the second observation window, the second estimated mass value Δm is calculated based on the mass conversion factor k1 of the first conveying unit. 12 , Δm 12 =k1·ΔI 12 The fourth estimated mass value Δm is calculated based on the mass conversion factor k2 of the second conveying unit. 22 , Δm 22 =k2·ΔI 22 .

6. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 5, characterized in that: In S4, when comparing the first quality estimate, the second quality estimate, the third quality estimate, and the fourth quality estimate, an allowable upper deviation coefficient L1 and an allowable lower deviation coefficient L2 are preset.

7. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 6, characterized in that: The allowable upper deviation coefficient L1 ranges from 1.05 to 1.1, and the allowable lower deviation coefficient L2 ranges from 0.9 to 0.

95.

8. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 6, characterized in that: In S4, the diagnostic results include jamming faults, specifically: When Δm is satisfied 11 ·L1<Δm 12 And Δm 22 <Δm 21 At L2, the diagnosis was that the first conveying unit was jammed; When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 21 ·L1<Δm 22 At that time, the diagnosis result was that the second conveying unit was stuck.

9. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 6, characterized in that: In S4, the diagnostic results include material detachment, specifically: When Δm is satisfied 12 <Δm 11 ·L2 and Δm 21 ·L1<Δm 22 At that time, the diagnosis was that large pieces of material adhering to the first conveying unit had fallen off; When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 22 <Δm 21 At L2, the diagnosis result was that large pieces of material adhering to the second conveying unit had fallen off.

10. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 6, characterized in that, In S4, the diagnostic results include normal operating conditions, specifically: When Δm is satisfied 11 ·L2<Δm 12 <Δm 11 ·L1 and Δm 21 ·L2<Δm 22 <Δm 21 At L1, the diagnostic result indicates normal operation. When Δm is satisfied 12 <Δm 11 ·L2 and Δm 22 <Δm 21 At L2, the diagnosis was a normal adjustment due to a decrease in feed rate. When Δm is satisfied 11 ·L1<Δm 12 And Δm 21 ·L1<Δm 22 At that time, the diagnosis was that the increase in feed volume was a normal adjustment under operating conditions.

11. The method for operation monitoring and diagnosis of a multi-stage belt conveyor system according to claim 1, characterized in that, When the multi-level conveying system includes multiple conveying units operating in series, and multiple fault diagnosis results exist at the same time, the handling priority is determined according to the degree of hazard. Conveying units that experience jamming faults are handled first, followed by conveying units that experience material spillage.

12. A system for monitoring and diagnosing the operation of a multi-stage belt conveyor system, used to execute the method for monitoring and diagnosing the operation of a multi-stage belt conveyor system as described in any one of claims 1 to 11, characterized in that, include: The parameter acquisition module is used to acquire the mass conversion factor and no-load current of the first and second conveying units; The data acquisition and calculation module is used to acquire the real-time operating current of the first transmission unit and the second transmission unit within two consecutive observation windows, and to calculate the cumulative current change value of the first transmission unit and the second transmission unit within the two observation windows in combination with the no-load current. The quality estimation module is used to calculate the quality estimation values ​​of the first transmission unit and the second transmission unit within two observation windows based on the corresponding cumulative current change value and quality conversion factor. The diagnostic output module is used to compare the estimated mass values ​​of the first conveying unit and the estimated mass values ​​of the second conveying unit between two observation windows, and output the diagnostic results of the material conveying status.

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