Coal mine data acquisition and analysis method and system

Abstract

The invention provides a coal mine data acquisition and analysis method, which comprises the following steps of: acquiring operation data of grid-connected mining electrical equipment through a data acquisition terminal, and acquiring operation data of non-grid-connected mining electrical equipment through an edge data acquisition unit; the collected operation data of the grid-connected mining electrical equipment is transmitted to an OPC server, and the operation data of the non-grid-connected mining electrical equipment is transmitted to a data server; the OPC server and the data server respectively transmit acquired operation data of the grid-connected mining electrical equipment and operation data of the non-grid-connected mining electrical equipment to the monitoring terminal, and the operation data of the grid-connected mining electrical equipment and the operation data of the non-grid-connected mining electrical equipment form original data; and the monitoring terminal performs data preprocessing, state monitoring, alarming and visual display on the collected original data.

Description

Technical Field

[0001] The present invention relates to the technical field of motor equipment data collection, and in particular to a coal mine data collection and analysis method and a coal mine data collection and analysis system. Background Art

[0002] In the energy industry, coal mine production safety has always been a core concern in the field of industrial safety, among which the status monitoring of electrical equipment is particularly critical. The operating status of coal mine electrical equipment directly affects the safety and production efficiency of the mine area. Traditional monitoring methods rely on regular inspections and empirical judgments, which are not only inefficient, but also unable to detect potential faults in a timely manner, and have obvious limitations.

[0003] With the development of technology, the application of big data analysis in coal mine electrical equipment monitoring has gradually shown its great potential. By analyzing massive amounts of equipment operation data, big data technology can provide deeper insights and help monitoring personnel to identify and prevent potential equipment problems in a timely manner. However, the existing data collection method cannot provide accurate and comprehensive original data, which has a certain impact on the status prediction and fault alarm of mine electrical equipment. Based on this, the present invention proposes a coal mine data collection and analysis method and a coal mine data collection and analysis system. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for coal mine data collection and analysis.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for coal mine data collection and analysis comprises the following steps: collecting the operation data of the mine electrical equipment connected to the grid through a data collection terminal, and collecting the operation data of the mine electrical equipment not connected to the grid through an edge data collection device; transmitting the collected operation data of the mine electrical equipment connected to the grid to an OPC server, and transmitting the operation data of the mine electrical equipment not connected to the grid to a data server; the OPC server and the data server respectively transmit the collected operation data of the mine electrical equipment connected to the grid and the operation data of the mine electrical equipment not connected to the grid to a monitoring terminal, and the operation data of the mine electrical equipment connected to the grid and the operation data of the mine electrical equipment not connected to the grid constitute the original data; the monitoring terminal performs data preprocessing, status monitoring, alarm and visual display on the collected original data.

[0007] The data acquisition terminal is a sensor, which is electrically connected to the mining electrical equipment and is used to collect the operating data of the mining electrical equipment in real time.

[0008] The data preprocessing comprises the following steps:

[0009] Data cleaning:

[0010] Importing raw data into a data analysis environment;

[0011] Data evaluation;

[0012] Select a subset of data from the original data;

[0013] Check missing values, duplicate values, and outliers in the data set, fill in missing values, delete or merge duplicate values, and identify and remove outliers;

[0014] Data standardization: Classify and encode the cleaned raw data.

[0015] The state monitoring is performed by a state monitoring module, which includes a real-time monitor, an anomaly detection algorithm and a state evaluator. The real-time monitor is used to continuously collect the operating data of the mining electrical equipment. The real-time monitoring is represented by the following formula:

[0016] M(t)=monitor(P(t))

[0017] Wherein, M(t) represents the monitoring result at time point t, and P(t) represents the performance parameters of the mining electrical equipment at time point t;

[0018] The anomaly detection algorithm is used to analyze monitoring data and identify possible abnormal patterns and trends. The anomaly detection algorithm is expressed by the following formula:

[0019] R(t)=deterct(M(t),B)

[0020] In the formula, R(t) represents the anomaly detection result at time point t, and B represents the benchmark model established by historical data;

[0021] The state evaluator is used to evaluate the current state of the mining electrical equipment, which is expressed by the following formula:

[0022] S(t)=evaluate(R(t),M(t))

[0023] Where S(t) represents the evaluation result at time point t.

[0024] The evaluation result S(t) is compared with the preset threshold to determine whether it exceeds the threshold. If so, an alarm is issued.

[0025] A coal mine data collection and analysis system comprises: an acquisition module, the acquisition module is used to collect the operation data of the mine electrical equipment connected to the grid through a data acquisition terminal, and collect the operation data of the mine electrical equipment not connected to the grid through edge data collection; a first transmission module, the first transmission module is used to transmit the collected operation data of the mine electrical equipment connected to the grid to an OPC server, and transmit the operation data of the mine electrical equipment not connected to the grid to a data server; a second transmission module, the second transmission module is used for the OPC server and the data server to transmit the collected operation data of the mine electrical equipment connected to the grid and the operation data of the mine electrical equipment not connected to the grid to a monitoring terminal, and the operation data of the mine electrical equipment connected to the grid and the operation data of the mine electrical equipment not connected to the grid constitute the original data; and a monitoring terminal, the monitoring terminal is used to perform data preprocessing, status monitoring, alarm and visual display on the collected original data.

[0026] The data acquisition terminal is a sensor, which is electrically connected to the mining electrical equipment and is used to collect the operating data of the mining electrical equipment in real time.

[0027] The data preprocessing comprises the following steps:

[0028] Data cleaning: importing raw data into the data analysis environment;

[0029] Data evaluation;

[0030] Select a subset of data from the original data;

[0031] Check missing values, duplicate values, and outliers in the data set, fill in missing values, delete or merge duplicate values, and identify and remove outliers;

[0032] Data standardization: classify and encode raw data.

[0033] The state monitoring is performed by a state monitoring module, which includes a real-time monitor, an anomaly detection algorithm and a state evaluator. The real-time monitor is used to continuously collect the operating data of the mining electrical equipment. The real-time monitoring is represented by the following formula:

[0034] M(t)=monitor(P(t))

[0035] Wherein, M(t) represents the monitoring result at time point t, and P(t) represents the performance parameters of the mining electrical equipment at time point t;

[0036] The anomaly detection algorithm is used to analyze monitoring data and identify possible abnormal patterns and trends. The anomaly detection algorithm is expressed by the following formula:

[0037] R(t)=deterct(M(t),B)

[0038] In the formula, R(t) represents the anomaly detection result at time point t, and B represents the benchmark model established by historical data;

[0039] The state evaluator is used to evaluate the current state of the mining electrical equipment, which is expressed by the following formula:

[0040] S(t)=evaluate(R(t),M(t))

[0041] Where S(t) represents the evaluation result at time point t.

[0042] The evaluation result S(t) is compared with the preset threshold to determine whether it exceeds the threshold. If so, an alarm is issued.

[0043] Beneficial effects of the present invention:

[0044] The coal mine data collection method and the coal mine data collection system of the present invention perform dual-channel real-time data collection through an OPC server and an edge data collection integrated machine. The OPC server module is used to process the data of existing mining electrical equipment that has been connected to the grid, and collects key data of the mining electrical equipment operation in real time through sensors. The edge data collection and transmission integrated machine communicates with the mining electrical equipment that is not connected to the grid and the data server, and the monitoring terminal processes the collected data, thereby realizing real-time and comprehensive collection and standardized processing of coal mine data, and improving the state prediction and fault alarm capabilities of mining electrical equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A flow chart of a method for collecting and analyzing coal mine data according to an embodiment of the present invention;

[0046] Figure 2 A block diagram of a coal mine data collection and analysis device according to an embodiment of the present invention;

[0047] Figure 3 The figure is a block diagram of the connection between an OPC server and an edge data acquisition integrated machine according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] like Figure 1As shown, a coal mine data collection and analysis method according to an embodiment of the present invention comprises the following steps:

[0050] S1: The operation data of the mining electrical equipment connected to the grid is collected through the data collection terminal, and the operation data of the mining electrical equipment not connected to the grid is collected through the edge data collection.

[0051] S2: The collected operation data of the mining electrical equipment connected to the grid is transmitted to the OPC server, and the operation data of the mining electrical equipment not connected to the grid is transmitted to the data server.

[0052] S3: The OPC server and the data server respectively collect the operating data of the mining electrical equipment connected to the grid and the operating data of the mining electrical equipment not connected to the grid and transmit them to the monitoring terminal. The operating data of the mining electrical equipment connected to the grid and the operating data of the mining electrical equipment not connected to the grid constitute the original data.

[0053] S4: The monitoring terminal performs data preprocessing, status monitoring, alarm and visualization on the collected raw data.

[0054] In one embodiment of the present invention, the data acquisition terminal is a sensor, which is electrically connected to the mining electrical equipment and is used to collect the operating data of the mining electrical equipment in real time. The OPC server sends a data acquisition instruction through its own serial port function, and the mining electrical equipment receives the instruction and the sensor performs data acquisition, and feeds back to the OPC server after the acquisition is completed.

[0055] In the present invention, the configuration software can be used as a monitoring terminal, KepServer can be used as an OPC server, the collected data is obtained through the data channel OPC server, and then the address of each data is added in the configuration software screen to display its actual data value.

[0056] In one embodiment of the present invention, the data preprocessing comprises the following steps:

[0057] S41: Data Cleansing

[0058] S411: Import the raw data into a data analysis environment, such as Python, R, or SQL database.

[0059] S412: Data evaluation, including checking the structure and data type of the data.

[0060] S413: Select a data subset from the original data.

[0061] S414: Check missing values, duplicate values, and outliers in the data set, fill in missing values, delete or merge duplicate values, and identify and remove outliers.

[0062] S42: Data Standardization

[0063] Data classification and coding are performed on the cleaned raw data.

[0064] Divide it into basic data, security data, production data and management data

[0065] In one embodiment of the present invention, the state monitoring is performed by a state monitoring module, which includes a real-time monitor, an anomaly detection algorithm and a state evaluator, wherein the real-time monitor is used to continuously collect operating data of mining electrical equipment, and the real-time monitoring is represented by the following formula:

[0066] M(t)=monitor(P(t))

[0067] Wherein, M(t) represents the monitoring result at time point t, and P(t) represents the performance parameters of the mining electrical equipment at time point t.

[0068] The anomaly detection algorithm is used to analyze monitoring data and identify possible abnormal patterns and trends. The anomaly detection algorithm is expressed by the following formula:

[0069] R(t)=deterct(M(t),B)

[0070] In the formula, R(t) represents the anomaly detection result at time point t, and B represents the benchmark model established based on historical data.

[0071] The state evaluator is used to evaluate the current state of the mining electrical equipment, which is expressed by the following formula:

[0072] S(t)=evaluate(R(t),M(t))

[0073] Where S(t) represents the evaluation result at time point t.

[0074] In one embodiment of the present invention, the evaluation result S(t) is compared with a preset threshold to determine whether it exceeds the threshold. If so, an alarm is issued.

[0075] like Figure 2 and Figure 3As shown, a coal mine data acquisition and analysis system of an embodiment of the present invention includes an acquisition module, a first transmission module, a second transmission module and a monitoring terminal, wherein the acquisition module is used to collect the operating data of the mining electrical equipment connected to the grid through the data acquisition terminal, and collect the operating data of the mining electrical equipment not connected to the grid through edge data acquisition; the first transmission module is used to transmit the collected operating data of the mining electrical equipment connected to the grid to the OPC server, and transmit the operating data of the mining electrical equipment not connected to the grid to the data server; the second transmission module is used for the OPC server and the data server to transmit the collected operating data of the mining electrical equipment connected to the grid and the operating data of the mining electrical equipment not connected to the grid to the monitoring terminal, and the operating data of the mining electrical equipment connected to the grid and the operating data of the mining electrical equipment not connected to the grid constitute the original data; the monitoring terminal is used to perform data preprocessing, status monitoring, alarm and visual display on the collected original data.

[0076] In one embodiment of the present invention, the data acquisition terminal is a sensor, and the sensor is electrically connected to the mining electrical equipment and is used to collect the operating data of the mining electrical equipment in real time.

[0077] In one embodiment of the present invention, the data preprocessing comprises the following steps:

[0078] S41: Data Cleansing

[0079] S411: Importing raw data into the data analysis environment;

[0080] S412: Data evaluation;

[0081] S413: Select a data subset from the original data;

[0082] S414: Check missing values, duplicate values, and outliers in the data set, fill in missing values, delete or merge duplicate values, and identify and remove outliers;

[0083] S42: Data Standardization

[0084] Data classification and coding are performed on the cleaned raw data.

[0085] In one embodiment of the present invention, the state monitoring is performed by a state monitoring module, which includes a real-time monitor, an anomaly detection algorithm and a state evaluator. The real-time monitor is used to continuously collect the operating data of the mining electrical equipment. The real-time monitoring is represented by the following formula:

[0086] M(t)=monitor(P(t))

[0087] Wherein, M(t) represents the monitoring result at time point t, and P(t) represents the performance parameters of the mining electrical equipment at time point t;

[0088] The anomaly detection algorithm is used to analyze monitoring data and identify possible abnormal patterns and trends. The anomaly detection algorithm is expressed by the following formula:

[0089] R(t)=deterct(M(t),B)

[0090] In the formula, R(t) represents the anomaly detection result at time point t, and B represents the benchmark model established by historical data;

[0091] The state evaluator is used to evaluate the current state of the mining electrical equipment, which is expressed by the following formula:

[0092] S(t)=evaluate(R(t),M(t))

[0093] Where S(t) represents the evaluation result at time point t.

[0094] In one embodiment of the present invention, the evaluation result S(t) is compared with a preset threshold to determine whether it exceeds the threshold. If so, an alarm is issued.

[0095] According to the coal mine data collection method and the coal mine data collection system of the embodiments of the present invention, dual-channel real-time data collection is performed through the OPC server and the edge data collection integrated machine. The OPC server module is used to process the data of the existing mining electrical equipment that has been connected to the grid, and the key data of the mining electrical equipment operation is collected in real time through sensors. The edge data collection and transmission integrated machine communicates with the mining electrical equipment that is not connected to the grid and the data server, and the monitoring terminal processes the collected data, thereby realizing real-time and comprehensive collection and standardized processing of coal mine data, and improving the status prediction and fault alarm capabilities of mining electrical equipment.

[0096] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0097] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0098] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0099] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0100] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0101] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0102] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0103] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0104] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0105] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for coal mine data collection and analysis, characterized in that: The following steps are involved: The operation data of the mining electrical equipment that has been connected to the grid is collected through the data collection terminal, and the operation data of the mining electrical equipment that is not connected to the grid is collected through the edge data collection. The collected operation data of the mining electrical equipment connected to the grid is transmitted to the OPC server, and the operation data of the mining electrical equipment not connected to the grid is transmitted to the data server; The OPC server and the data server respectively collect the operation data of the mining electrical equipment connected to the grid and the operation data of the mining electrical equipment not connected to the grid and transmit them to the monitoring terminal, and the operation data of the mining electrical equipment connected to the grid and the operation data of the mining electrical equipment not connected to the grid constitute the original data; The monitoring terminal performs data preprocessing, status monitoring, alarm and visual display on the collected raw data.

2. The coal mine data collection and analysis method according to claim 1, characterized in that: The data acquisition terminal is a sensor, which is electrically connected to the mining electrical equipment and is used to collect the operating data of the mining electrical equipment in real time.

3. The coal mine data collection and analysis method according to claim 2, characterized in that: The data preprocessing comprises the following steps: Data cleaning: Importing raw data into a data analysis environment; Conduct a preliminary assessment of the data; Select a subset of data from the original data; Check the missing values, duplicate values, and outliers in the data set, fill in the missing values, delete or merge the duplicate values, and identify and remove the outliers. Data Standardization: Data classification and coding are performed on the cleaned raw data.

4. The coal mine data collection and analysis method according to claim 3, characterized in that: The state monitoring is performed by a state monitoring module, which includes a real-time monitor, an anomaly detection algorithm and a state evaluator. The real-time monitor is used to continuously collect the operating data of the mining electrical equipment. The real-time monitoring is represented by the following formula: M(t)=monitor(P(t)) Wherein, M(t) represents the monitoring result at time point t, and P(t) represents the performance parameters of the mining electrical equipment at time point t; The anomaly detection algorithm is used to analyze monitoring data and identify possible abnormal patterns and trends. The anomaly detection algorithm is expressed by the following formula: R(t)=deterct(M(t),B) In the formula, R(t) represents the anomaly detection result at time point t, and B represents the benchmark model established by historical data; The state evaluator is used to evaluate the current state of the mining electrical equipment, which is expressed by the following formula: S(t)=evaluate(R(t),M(t)) Where S(t) represents the evaluation result at time point t.

5. The method for coal mine data collection and analysis according to claim 4, characterized in that: The evaluation result S(t) is compared with the preset threshold to determine whether it exceeds the threshold. If so, an alarm is issued.

6. A coal mine data collection and analysis system, characterized in that: include: A collection module, the collection module is used to collect the operation data of the mining electrical equipment that has been connected to the grid through the data collection terminal, and to collect the operation data of the mining electrical equipment that is not connected to the grid through the edge data collection; A first transmission module, the first transmission module is used to transmit the collected operation data of the mining electrical equipment that has been connected to the grid to the OPC server, and transmit the operation data of the mining electrical equipment that is not connected to the grid to the data server; A second transmission module, wherein the second transmission module is used for the OPC server and the data server to collect the operation data of the mining electrical equipment connected to the grid and the operation data of the mining electrical equipment not connected to the grid and transmit them to the monitoring terminal, and the operation data of the mining electrical equipment connected to the grid and the operation data of the mining electrical equipment not connected to the grid constitute the original data; The monitoring terminal is used to perform data preprocessing, status monitoring, alarm and visual display on the collected raw data.

7. The coal mine data acquisition and analysis system according to claim 6, characterized in that: The data acquisition terminal is a sensor, which is electrically connected to the mining electrical equipment and is used to collect the operating data of the mining electrical equipment in real time.

8. The coal mine data acquisition and analysis system according to claim 7, characterized in that: The data preprocessing comprises the following steps: Data cleaning: Importing raw data into a data analysis environment; Data evaluation; Select a subset of data from the original data; Check missing values, duplicate values, and outliers in the data set, fill in missing values, delete or merge duplicate values, and identify and remove outliers; Data standardization: classify and encode raw data.

9. The coal mine data collection and analysis system according to claim 8, characterized in that: The state monitoring is performed by a state monitoring module, which includes a real-time monitor, an anomaly detection algorithm and a state evaluator. The real-time monitor is used to continuously collect the operating data of the mining electrical equipment. The real-time monitoring is represented by the following formula: M(t)=monitor(P(t)) Wherein, M(t) represents the monitoring result at time point t, and P(t) represents the performance parameters of the mining electrical equipment at time point t; The anomaly detection algorithm is used to analyze monitoring data and identify possible abnormal patterns and trends. The anomaly detection algorithm is expressed by the following formula: R(t)=deterct(M(t),B) In the formula, R(t) represents the anomaly detection result at time point t, and B represents the benchmark model established by historical data; The state evaluator is used to evaluate the current state of the mining electrical equipment, which is expressed by the following formula: S(t)=evaluate(R(t),M(t)) Where S(t) represents the evaluation result at time point t.

10. The coal mine data collection and analysis system according to claim 9, characterized in that: The evaluation result S(t) is compared with the preset threshold to determine whether it exceeds the threshold. If so, an alarm is issued.

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