Intelligent detection system and method for abnormity of sampling machine

Abstract

The invention discloses a sampling machine abnormity intelligent detection system and method, and relates to the technical field of electric power engineering, and the system comprises an acquisition module, a control module, and an alarm module. The acquisition modules are respectively arranged on the coal conveying belt, the sampling head, the divider and the hopper and are used for acquiring the coal conveying flow and the weight of coal in the hopper; the control module is used for receiving the data acquired by the acquisition module, processing and analyzing the data, sending the data to a user background, and judging whether the sampling machine is abnormal or not; the alarm module sends an alarm signal according to the abnormal condition of the sampling machine; by collecting and analyzing key data in the operation process of the sampling machine in real time, the operation state of the sampling machine can be accurately detected, abnormal conditions such as coal blockage and coal interruption can be found in time, early warning and quick response are achieved, equipment damage and production interruption are effectively avoided, the production efficiency is improved, the equipment maintenance cost and production loss are reduced, and the working efficiency is improved. Meanwhile, industrial safety standards are met, and integration and expansion are easy.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power engineering, and in particular to a system and method for intelligently detecting abnormalities of a sampling machine. Background Art

[0002] During the production, transportation, and processing of materials such as coal and ore, samplers are critical equipment used to collect representative samples from the material flow on conveyor belts for quality inspection and elemental analysis. The proper operation of samplers is crucial to ensuring the accuracy and reliability of material quality control. However, due to the harsh operating environment of samplers, long-term operation can easily lead to various anomalies, such as coal blockage and coal shortages. These anomalies not only affect the normal operation of the samplers but can also cause significant deviations in the calorific value of the coal samples, resulting in significant economic losses.

[0003] Traditional sampling machine anomaly detection methods mainly rely on manual inspections and simple mechanical protection devices. Manual inspections have problems such as poor real-time performance, strong subjectivity, and low efficiency, making it difficult to detect and handle abnormal situations in a timely manner. Although mechanical protection devices can protect equipment to a certain extent, their functions are single and they cannot accurately judge and warn of abnormal situations. With the development of industrial automation technology, although some sampling machines have begun to use simple sensors for status monitoring, these monitoring methods can often only detect a single parameter and lack the ability to comprehensively analyze and judge the overall operating status of the sampling machine, making it impossible to achieve early warning and precise positioning of abnormal situations.

[0004] Based on the above problems, we propose an intelligent detection system and method for sampling machine anomalies. Summary of the Invention

[0005] Therefore, the technical problem to be solved by the present invention is: how to collect and comprehensively analyze multiple key parameters during the operation of the sampler in real time, realize accurate detection and early warning of abnormal conditions of the sampler, and improve the operation reliability and production efficiency of the sampler.

[0006] The above technical problems are solved by the following technical solutions: acquisition module, control module, and alarm module; the acquisition modules are respectively arranged on the coal conveyor belt, sampling head, reducer and hopper, and are used to collect the actions of the sampling head and reducer, the coal flow rate and the weight of the coal in the hopper; the control module is used to receive the data collected by the acquisition module for processing and analysis and send it to the user background to determine whether the sampling machine has abnormal conditions such as coal blockage; the alarm module sends an alarm signal according to the abnormal conditions of the sampling machine.

[0007] In a preferred embodiment of the intelligent detection system for abnormalities of sampling machines of the present invention: the acquisition module includes weighing sensors arranged at the four corners of the hopper and action switches arranged on the coal conveyor belt, the sampling head and the reducer.

[0008] In a preferred embodiment of the intelligent detection system for abnormalities of sampling machines of the present invention: the weighing sensor is connected to the weighing instrument via a control cable, and the control module includes a sampling PLC, a coal conveying PLC, a small PLC and a management and control unit.

[0009] In a preferred embodiment of the intelligent detection system for abnormalities of a sampling machine of the present invention: the weighing sensor collects the weight of the hopper in real time and sends a signal to the sampling PLC.

[0010] In a preferred embodiment of the intelligent detection system for abnormalities of sampling machines of the present invention: the action switch signal is collected by a sampling PLC and the signal is sent to the control unit.

[0011] In a preferred embodiment of the sampling machine abnormality intelligent detection system of the present invention: the sampling PLC sends weight information to the control unit for data processing, and the coal conveying PLC sends operating status data of the coal conveyor belt to the control unit.

[0012] In a preferred embodiment of the intelligent detection system for abnormalities of sampling machines of the present invention: the small PLC receives information from the control unit and the coal conveying PLC, and sends an alarm signal to the coal conveying PLC.

[0013] The present invention also proposes an intelligent detection method for abnormalities of a sampling machine, which includes collecting the instantaneous flow rate of the belt conveyor, the weight of the weighing hopper, the density of the coal type, the action signal of the sampling head, the number of times the divider operates, and calculating the upper and lower thresholds of the increase in the weight of the coal sample;

[0014] Cyclic monitoring of sampling head action;

[0015] After the sampling head is activated, a certain time is delayed to determine the added weight of the coal sample in the weighing hopper.

[0016] In a preferred embodiment of the method for intelligently detecting abnormalities in a sampling machine according to the present invention:

[0017] Determine whether the weight of the coal sample added to the weighing hopper is greater than an upper threshold or less than a lower threshold;

[0018] If the weight increment is greater than the upper threshold or less than the lower threshold, the count is increased by 1;

[0019] If not, continue to monitor the sampling head action.

[0020] In a preferred embodiment of the method for intelligently detecting abnormalities in a sampling machine according to the present invention: determining whether the number of times the weight of the coal sample in the weighing hopper is greater than an upper threshold or less than a lower threshold is greater than or equal to 2 times;

[0021] If the number of times is greater than or equal to 2, a coal blockage alarm signal is sent to the small PLC, and the small PLC forwards the alarm signal to the coal conveying PLC;

[0022] If not, continue to monitor the sampling head action.

[0023] The beneficial effects of the present invention are: by real-time collection and analysis of key data during the operation of the sampling machine, the operating status of the sampling machine can be accurately detected, abnormal situations such as coal blockage and coal shortage can be discovered in time, early warning and rapid response can be achieved, and equipment damage and production interruption can be effectively avoided. Production efficiency can be improved, equipment maintenance costs and production losses can be reduced, and at the same time, it complies with industrial safety standards, is easy to integrate and expand, and provides a powerful tool for the digital management and decision-making support of enterprises. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings of the embodiments of the present invention. Obviously, the drawings described below only relate to some embodiments of the present invention and are not intended to limit the present invention. Among them:

[0025] Figure 1 Shows the flow chart of the sampling machine abnormality intelligent detection control system;

[0026] Figure 2 Shows a schematic diagram of the sampling equipment connection;

[0027] Figure 3 The flow chart of the intelligent detection and control method for sampling machine abnormality is shown. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present invention, the present invention is further described in detail below with reference to specific embodiments and the accompanying drawings.

[0029] The terms used in the present invention are those commonly used in the art in view of the functions of the present invention, but these terms may vary according to the intentions of those skilled in the art, precedents, or new technologies in the art. In addition, specific terms may be selected by the applicant, and in such cases, their detailed meanings will be described in the detailed description of the present invention. Therefore, the terms used in the specification should not be understood as simple names, but rather as the meanings of the terms and the overall description of the present invention.

[0030] Reference Figures 1 to 3This embodiment provides an intelligent detection system for abnormalities of a sampling machine, including a collection module 1, a control module 2, and an alarm module 3; the collection module 1 is respectively arranged on the coal conveyor belt, the sampling head, the reducer, and the hopper, and is used to collect the actions of the sampling head and the reducer, the coal flow rate, and the weight of the coal in the hopper; the control module 2 is used to receive the data collected by the collection module 1, process and analyze it, and send it to the user background to determine whether the sampling machine has abnormal conditions such as coal blockage; the alarm module 3 sends an alarm signal according to the abnormal conditions of the sampling machine.

[0031] Acquisition module 1 collects data from multiple locations to ensure comprehensive monitoring of the sampler's operating status. Control module 2 receives signals from acquisition module 1 and, based on data such as coal density, instantaneous conveyor flow rate, and the number of times the splitter operates, determines whether the coal sample weight increment is within a set threshold, thereby detecting abnormal conditions such as coal blockage or coal shortage. When control module 2 detects an abnormality, alarm module 3 immediately issues an alarm signal to alert the operator. Simultaneously, the alarm information is recorded and transmitted to the user's backend for further analysis and processing.

[0032] As an optional embodiment, the collection module 1 includes weighing sensors 11 provided at the four corners of the hopper and action switches 12 provided on the coal conveyor belt, the sampling head, and the reducer.

[0033] A weighing sensor 11 is installed on each of the four corners of the hopper to monitor the weight of the coal in the hopper in real time; the action switch 12 on the coal conveyor belt is used to detect the state and flow of the coal flow to ensure the continuity and stability of the coal flow; the action switch 12 on the sampling head is used to trigger the switch and generate a signal every time the sampling head takes a sampling action to ensure the accuracy of the system sampling head action detection signal; the action switch 12 on the reducer monitors the action frequency and reduction ratio of the reducer to ensure the accuracy of the system reducer action detection signal.

[0034] As an optional embodiment, the weighing sensor 11 is connected to the weighing instrument via a control cable, and the control module 2 includes a sampling PLC 21 , a coal conveying PLC 22 , a small PLC 23 and a management and control unit 24 .

[0035] The weighing sensor 11 is connected to a weighing instrument via a control cable, and the weighing instrument sends an analog signal such as 4-20mA or 0-10V to the sampling PLC 21 .

[0036] As an optional embodiment, the weighing sensor 11 collects the weight of the hopper in real time and sends a signal to the sampling PLC 21.

[0037] The sampling PLC21 receives the signals from the weighing sensor 11 and the action switch 12, performs preliminary processing and conversion, converts the analog signal of the weighing sensor 11 into a digital signal, and processes the digital signal of the action switch 12. The processed data will be sent to the management and control unit 24.

[0038] As an optional embodiment, the signal of the action switch 12 is collected by the sampling PLC 21 and the signal is sent to the control unit 24 .

[0039] Receive the signal of the action switch 12 sent by the coal conveying PLC 22, monitor the operating status of the coal conveying conveyor belt, and send the operating status data of the coal conveying conveyor belt to the management and control unit 24.

[0040] As an optional embodiment, the sampling PLC 21 sends the weight information to the control unit 24 for data processing, and the coal conveying PLC 22 sends the operating status data of the coal conveyor belt to the control unit 24 .

[0041] The sampling PLC sends the processed weight information to the control unit 24 through the network or serial communication interface. The data sent by the coal conveying PLC includes the operating status of the coal conveyor belt. The data sent by the sampling PLC includes the action status of the sampling head, the number of actions of the reducer and other information.

[0042] As an optional embodiment, the small PLC 23 receives information from the control unit 24 and the coal transport PLC 22 , and sends an alarm signal to the coal transport PLC 22 .

[0043] The alarm module 3 receives the instruction from the control unit 24, generates an alarm signal and sends it to the small PLC 23, and sends the alarm signal to the coal conveying PLC 22 through electrical hard wiring.

[0044] In summary, through the coordinated work of sampling PLC21 and coal conveying PLC22, real-time monitoring and data transmission of the operating status of the sampling machine are realized. Sampling PLC21 is responsible for collecting and processing the weight information of the weighing sensor 11 and the operating status data of the sampling head and reducer action switch 12. Coal conveying PLC22 is responsible for collecting and processing the operating status data of the coal flow action switch 12 of the coal conveyor belt. These data are sent to the management and control unit 24 through the network or serial communication interface for comprehensive analysis and abnormality judgment to ensure the normal operation of the sampler.

[0045] Reference Figures 1 to 3 ,This embodiment provides a method for intelligent detection of sampling machine anomalies, including collecting the instantaneous flow rate of the belt conveyor, the weight of the weighing hopper, the density of the coal type, the action signal of the sampling head, the number of times the divider operates, and calculating the upper and lower thresholds of the increase in the weight of the coal sample;

[0046] Cyclic monitoring of sampling head action;

[0047] After the sampling head is activated, a certain time is delayed to determine the added weight of the coal sample in the weighing hopper.

[0048] The system is connected to the weighing instrument, sampling machine PLC, coal conveying system PLC, and third-party fuel management system; it collects data such as the instantaneous flow rate of the belt conveyor, the weight of the weighing hopper, the density of the coal type, the action signal of the sampling head, and the number of times the reducer acts; based on the data such as the instantaneous flow rate of the belt conveyor, the density of the coal type, and the number of times the reducer acts, it calculates the upper and lower thresholds of the increase in the weight of the coal sample. The sampling head action interval time and the reducer action interval time are set by the power plant fuel management personnel in the sampling machine PLC through the sampling machine host computer operation screen, and are executed in a timer countdown manner. The sampling head delay setting avoids weight judgment when the coal sample has not completely entered the weighing hopper, ensuring the accuracy of the judgment and ensuring that the coal sample has completely entered the weighing hopper.

[0049] As an optional embodiment,

[0050] Determine whether the weight of the coal sample added to the weighing hopper is greater than an upper threshold or less than a lower threshold;

[0051] If the weight increment is greater than the upper threshold or less than the lower threshold, the count is increased by 1;

[0052] If not, continue to monitor the sampling head action.

[0053] After the delay time ends, the system determines whether the weight of the coal sample added to the weighing hopper is within the set upper and lower limit thresholds; if the weight increase exceeds the threshold, the count is increased by 1; if not, the system continues to monitor in a loop to ensure the normal operation of the sampler.

[0054] As an optional embodiment,

[0055] Determine whether the number of times the weight of the coal sample in the weighing hopper is greater than the upper threshold or less than the lower threshold is greater than or equal to 2 times;

[0056] If the number of times is greater than or equal to 2, a coal blockage alarm signal is sent to the small PLC, and the small PLC forwards the alarm signal to the coal conveying PLC;

[0057] If not, continue to monitor the sampling head action.

[0058] The system determines whether the weight of the coal sample in the weighing hopper is greater than the upper threshold or less than the lower threshold for more than or equal to 2 times; if the number is greater than or equal to 2 times, the system will issue a coal blockage alarm signal; the alarm signal is sent to the alarm module through the small PLC to alert the operator.

[0059] In summary, by real-time collection and processing of data such as the instantaneous flow rate of the belt conveyor, the weight of the weighing hopper, the density of the coal type, the action signal of the sampling head, the number of times the divider acts, etc., the upper and lower limit thresholds of the increase in the weight of the coal sample are calculated, and by cyclically monitoring the action of the sampling head and delaying the increase in the weight of the coal sample in the weighing hopper, real-time monitoring of the operating status of the sampler and abnormal early warning are achieved; abnormal situations such as coal blockage and coal shortage can be discovered in time, thus ensuring the normal operation of the sampler, improving production efficiency, and reducing equipment maintenance costs and production losses.

[0060] Finally, it should be pointed out that the methods and devices described in detail above are merely embodiments, and those skilled in the art can modify these embodiments in different ways without departing from the scope of the present invention.

Claims

1. An intelligent sampling machine abnormality detection system, characterized by: include, Acquisition module (1), control module (2), alarm module (3); The collection modules (1) are respectively arranged on the coal conveyor belt, the sampling head, the reducer and the hopper, and are used to collect the movements of the sampling head and the reducer, the coal flow rate and the weight of the coal in the hopper; The control module (2) is used to receive the data collected by the collection module (1), process and analyze the data, and send it to the user's backend to determine whether the sampling machine has abnormal conditions such as coal blockage or interruption; The alarm module (3) sends an alarm signal according to an abnormal situation of the sampling machine.

2. The intelligent sampling machine abnormality detection system according to claim 1 is characterized in that: The collection module (1) comprises weighing sensors (11) arranged at the four corners of the hopper and action switches (12) arranged on the coal conveyor belt, the sampling head and the reducer.

3. The intelligent sampling machine abnormality detection system according to claim 2 is characterized in that: The weighing sensor (11) is connected to a weighing instrument via a control cable, and the control module (2) comprises a sampling PLC (21), a coal conveying PLC (22), a small PLC (23) and a control unit (24).

4. The intelligent sampling machine abnormality detection system according to claim 3 is characterized in that: The weighing sensor (11) collects the weight of the hopper in real time and sends a signal to the sampling PLC (21).

5. The intelligent sampling machine abnormality detection system according to claim 4 is characterized in that: The action switch (12) signal is collected by a sampling PLC (21) and the signal is sent to the control unit (24).

6. The intelligent sampling machine abnormality detection system according to claim 5 is characterized in that: The sampling PLC (21) sends the weight information to the control unit (24) for data processing, and the coal conveying PLC (22) sends the operating status data of the coal conveying conveyor belt to the control unit (24).

7. The intelligent sampling machine abnormality detection system according to claim 6, characterized in that: The small PLC (23) receives information from the control unit (24) and the coal conveying PLC (22), and sends an alarm signal to the coal conveying PLC (22).

8. A method for intelligent detection of sampling machine anomalies, characterized by: The intelligent detection system for abnormality of a sampling machine according to any one of claims 1 to 7 further comprises: Collect the instantaneous flow rate of the belt conveyor, the weight of the weighing hopper, the density of the coal type, the action signal of the sampling head, the number of times the divider operates, and calculate the upper and lower thresholds of the coal sample weight increase; Cyclic monitoring of sampling head action; After the sampling head is activated, a certain time is delayed to determine the added weight of the coal sample in the weighing hopper.

9. The method for intelligent detection of sampling machine anomalies according to claim 8, characterized in that: Determine whether the weight of the coal sample added to the weighing hopper is greater than an upper threshold or less than a lower threshold; If the weight increment is greater than the upper threshold or less than the lower threshold, the count is increased by 1; If not, continue to monitor the sampling head action.

10. The method for intelligent detection of sampling machine anomalies according to claim 9, characterized in that: Determine whether the number of times the weight of the coal sample in the weighing hopper is greater than the upper threshold or less than the lower threshold is greater than or equal to 2 times; If the number of times is greater than or equal to 2, a coal blockage alarm signal is sent to the small PLC, and the small PLC forwards the alarm signal to the coal conveying PLC; If not, continue to monitor the sampling head action.

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