Mine equipment operation safety evaluation system based on big data

Abstract

The invention discloses a mining equipment operation safety evaluation system based on big data, and relates to the technical field of equipment safety evaluation, and the system achieves the omnibearing monitoring and safety evaluation of the operation state of mining equipment through the big data technology, and achieves the safety evaluation from the real-time monitoring of power data, the fine analysis of abnormal power to the preliminary risk evaluation. A set of dynamic and accurate safety monitoring system is formed, the abnormal state of the equipment can be captured in time, the initial risk can be quantified, and a solid data support and a scientific basis are provided for the operation safety of the mining equipment; meanwhile, the system combines power frequent diagnosis and an automatic alarm mechanism, realizes real-time monitoring and timely response to accumulated risks of abnormal events, and effectively reduces the probability of occurrence of equipment faults and safety accidents; on the whole, the system not only improves the stability and safety of equipment operation, but also provides efficient early warning and emergency support for mine production management.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment safety assessment, and in particular to a mining equipment operation safety evaluation system based on big data. Background Art

[0002] Currently, mining equipment operates under high load, high vibration and harsh environment. The stability and safety of the equipment are directly related to the efficiency and safety of mine production.

[0003] Patent publication number CN115015623B discloses a big data-based mining equipment operation safety evaluation system, which involves safety monitoring technology and is used to solve the problem that existing mining equipment cannot analyze and warn its operating status through various parameters during operation. The system includes a safety evaluation platform, which is communicatively connected to a noise detection module, a power distribution detection module, a safety rating module, an environmental analysis module, and a storage module. The power distribution detection module is used to detect and analyze the output voltage of the distribution room, and determine whether the output voltage of the distribution room meets the requirements by comparing the voltage value DY, the voltage performance value DB, and the voltage threshold DYmin and the voltage performance threshold DBmax. The power distribution detection module detects and analyzes the output voltage of the distribution room, and when the voltage output is qualified, the voltage coefficient is used to provide feedback on the overall stability of the output voltage of the distribution room.

[0004] Traditional equipment safety assessment methods often rely on periodic manual inspections and simple monitoring indicators, making it difficult to promptly and accurately capture subtle anomalies that occur during equipment operation. Because parameters such as power, current, and voltage fluctuate complexly during actual operation, traditional methods tend to overlook the cumulative effects of short-term and continuous anomalies. This results in untimely fault warnings and ineffective control of safety hazards, leading to equipment damage or safety accidents, resulting in significant economic losses and safety risks. Summary of the Invention

[0005] In view of the deficiencies in the prior art, the present invention provides a mining equipment operation safety evaluation system based on big data, which solves the problems in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A mining equipment operation safety evaluation system based on big data, comprising:

[0007] The power monitoring module is used to monitor whether the operating power of the mining equipment exceeds the specified threshold range during its operation. If it exceeds the specified threshold range, the operating power is judged to be abnormal power or fault power. If it does not exceed the specified threshold range, the monitoring is continued;

[0008] Abnormal power analysis module, used to analyze the current / voltage data of abnormal power in time period T1 to determine the current fluctuation value and voltage fluctuation value;

[0009] A preliminary assessment module is used to preliminarily assess the safety risk of mining equipment based on the current fluctuation value and the voltage fluctuation value, and determine the initial mining equipment safety risk value;

[0010] The power frequent diagnosis module is used to further determine the safety risk value of mining equipment according to the frequency of abnormal power occurrence, and compare the determined safety risk value of mining equipment with the safety risk evaluation threshold of mining equipment to determine whether to issue an alarm message.

[0011] As a further solution of the present invention: in the power monitoring module, the operating power of the mining equipment is monitored to see whether it exceeds a specified threshold range. If it exceeds the specified threshold range, the operating power is determined to be abnormal power or fault power. If it does not exceed the specified threshold range, the specific method of continuing monitoring is as follows:

[0012] AS1: Real-time acquisition of the working power of mining equipment, denoted as P work ;

[0013] AS2: Set the working power P work Compare with the preset interval values ​​Q1 and Q2:

[0014] If P work Does not exceed the interval value Q1, and judges that the working power P work is the normal working power;

[0015] If P work If the operating power exceeds the interval value Q1 and is within the interval value Q2, the operating power is judged to be abnormal power;

[0016] If P work If the operating power exceeds the interval value Q2, it is determined that the operating power is fault power;

[0017] AS3: When the operating power is determined to be normal operating power, no processing is performed and monitoring is continued;

[0018] When the operating power is determined to be abnormal power, further detecting the cause of the abnormal power;

[0019] When the operating power is determined to be fault power, an alarm message is issued.

[0020] As a further solution of the present invention: in the abnormal power analysis module, the abnormal power analysis module includes an abnormal power current analysis unit and an abnormal power voltage analysis unit;

[0021] An abnormal power and current analysis unit is used to analyze the current data of the time period before the abnormal power moment and determine the current stable value;

[0022] The abnormal power and voltage analysis unit is used to analyze the voltage data before the abnormal power moment and determine the voltage stability value.

[0023] As a further solution of the present invention: in the abnormal power current analysis unit, the specific method of analyzing the current data at time T1 before the abnormal power moment to determine the current stable value is:

[0024] BS1: Get the current data detected in the T1 period before the abnormal power occurs;

[0025] BS2: Based on the current data of the T1 period, a plane rectangular coordinate system is established and the current data is marked in the first quadrant of the plane rectangular coordinate system, where the horizontal axis is time and the vertical axis is the specific current data, to generate a current change curve;

[0026] BS3: Establish two current floating limit horizontal lines in the current change curve, namely straight line y=C1 and straight line y=C2;

[0027] According to the connection points in the current change curve, the connection points beyond the middle section of the straight line y=C1 and the straight line y=C2 are determined, and the number of connection points is counted and marked as k1;

[0028] Among them, C2>C1;

[0029] BS4: Then, based on the current change curve, when the current change value of two adjacent current data exceeds the preset value b1 for more than two consecutive times, the number of times the two adjacent current data exceeds the preset value b1 in the continuous process is determined and marked as HI. The formula Hs=HI / 2 is used, where the calculation result is rounded down to determine the number of current jumps Hs in the continuous process. In this way, the overall number of current jumps in the current change curve is obtained and marked as k2;

[0030] BS5: Get k1 and k2, and use the weighted calculation formula to determine the fluctuation value I of the current data in the T1 period w .

[0031] As a further solution of the present invention: in the abnormal power and voltage analysis unit, the specific method of analyzing the voltage data before the abnormal power moment to determine the voltage stability value is:

[0032] CS1: Gets the voltage data detected in the T1 period before the abnormal power occurs;

[0033] CS2: Based on the voltage data of the T1 period, a plane rectangular coordinate system is established and the voltage data is marked in the first quadrant of the plane rectangular coordinate system, where the horizontal axis is time and the vertical axis is the specific voltage data, to generate a voltage change curve;

[0034] CS3: Establish two voltage floating limit horizontal lines in the voltage change curve, namely straight line y=C3 and straight line y=C4;

[0035] According to the connection points in the voltage change curve, the connection points beyond the middle section of the straight line y=C3 and the straight line y=C4 are determined, and the number of connection points is counted and marked as d1;

[0036] Among them, and C4>C3;

[0037] CS4: Then, according to the voltage change curve, when the voltage change value of two adjacent voltage data exceeds the preset value b2 for more than two consecutive times, determine the number of times the two adjacent voltage data exceeds the preset value b2 in the continuous process, and mark it HU. Use the formula Hc=HU / 2, where the calculation result is rounded down to determine the number of voltage jumps in the continuous process H c In this way, the overall voltage jump times in the voltage change curve are obtained and marked as d2;

[0038] CS5: Get d1 and d2, and determine the fluctuation value U of the voltage data in the T1 period through the weighted calculation formula w .

[0039] As a further solution of the present invention: in the preliminary evaluation module, the preliminary evaluation of the mining equipment safety risk value based on the current fluctuation value and the voltage fluctuation value, the specific method of determining the initial mining equipment safety risk value is: obtaining the initial current fluctuation value I w And voltage fluctuation value U w , preliminarily evaluate the safety risk of mining equipment through the preset preliminary evaluation formula model, and determine the initial mining equipment safety risk value FP x1 .

[0040] As a further solution of the present invention: in the power frequent diagnosis module, the specific method of further determining the safety risk value of mining equipment according to the frequent occurrence of abnormal power is:

[0041] DS1: Get the time point t1 when the abnormal power first appears during the operation of the mining equipment, and then get the initial mining equipment safety risk value FP x1 ; The initial mining equipment safety risk value FP x1 Compare with the set mining equipment safety risk assessment threshold:

[0042] If the initial mining equipment safety risk value FPx1 When the risk exceeds the safety risk assessment threshold of mining equipment, an alarm message will be issued;

[0043] If the initial mining equipment safety risk value FP x1 If the value is less than or equal to the mining equipment safety risk assessment threshold, no action will be taken;

[0044] DS2: If the abnormal power occurs again, determine the time point t2 and calculate whether the interval between time points t1 and t2 exceeds T1:

[0045] If the T1 time period is not exceeded, the current mining equipment safety risk value FP is determined by the preset cumulative assessment formula model. x :

[0046] If the T1 time period is exceeded, the current mining equipment safety risk value FP is determined by the preset cumulative evaluation formula model. x :

[0047] Then the current mining equipment safety risk value FP x Compare with the set mining equipment safety risk assessment threshold:

[0048] If the current mine equipment safety risk value is greater than the mine equipment safety risk assessment threshold, an alarm message will be issued;

[0049] If the current mine equipment safety risk value is less than or equal to the mine equipment safety risk assessment threshold, no action will be taken;

[0050] DS3: For each abnormal power occurrence, the safety risk value of the mining equipment is accumulated or added up to determine the safety risk value of the mining equipment for each abnormal power occurrence:

[0051] When the time intervals between consecutive abnormal power events do not exceed T1, the mining equipment safety risk value determined by the first abnormal power event in the process and the number of abnormal power events are obtained. Each time an abnormal power event occurs, the mining equipment safety risk value for each abnormal power event in the process is determined using a preset cumulative evaluation formula model.

[0052] And compare each mining equipment safety risk value with the safety risk assessment threshold:

[0053] If the mine equipment safety risk value is greater than the mine equipment safety risk assessment threshold each time, it means that the mine equipment safety assessment risk is too high and an alarm message is issued.

[0054] If the mining equipment safety risk value is less than or equal to the mining equipment safety risk assessment threshold each time, no action will be taken;

[0055] When the consecutive adjacent abnormal power exceeds T1, the mining equipment safety risk value determined before the time period exceeding T1 is obtained, and the mining equipment safety risk value of each abnormal power occurrence after the time period exceeding T1 is determined at the same time. According to the cumulative result of the two mining equipment safety risk values, the cumulative result is judged and compared with the safety risk assessment threshold:

[0056] If the accumulated result is greater than the threshold value of the safety risk assessment of mining equipment, it means that the safety risk of mining equipment is too high and an alarm message is issued.

[0057] If the accumulated result is less than or equal to the mining equipment safety risk assessment threshold, no action will be taken;

[0058] This process is repeated in this way until the safety risk value of mining equipment determined by each abnormal power occurrence exceeds the safety risk assessment threshold, and an alarm is issued.

[0059] As a further solution of the present invention: also include:

[0060] The alarm module is used to receive the alarm information sent by the power frequent diagnosis module, issue an alarm, and notify the staff to handle or stop the operation of the mining equipment.

[0061] The present invention provides a mining equipment operation safety evaluation system based on big data. Compared with the existing technology, it has the following advantages:

[0062] This invention uses big data technology to achieve all-round monitoring and safety evaluation of the operating status of mining equipment. From real-time monitoring of power data, detailed analysis of abnormal power to preliminary risk assessment, it has formed a dynamic and accurate safety monitoring system that can timely capture abnormal equipment status and quantify initial risks, providing solid data support and scientific basis for the safe operation of mining equipment.

[0063] At the same time, the system combines frequent power diagnosis with an automatic alarm mechanism, enabling real-time monitoring and timely response to the cumulative risk of abnormal events, effectively reducing the probability of equipment failure and safety accidents. Overall, the system not only improves the stability and safety of equipment operation, but also provides efficient early warning and emergency support for mine production management. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The present invention will be further described below with reference to the accompanying drawings.

[0065] Figure 1 This is a structural framework diagram of a mining equipment operation safety evaluation system based on big data of the present invention;

[0066] Figure 2 This is a schematic diagram of current and voltage analysis of a big data-based mining equipment operation safety evaluation system of the present invention. DETAILED DESCRIPTION

[0067] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0068] Example 1

[0069] See also Figure 1-Figure 2 ,The present invention provides a mining equipment operation safety evaluation system based on big data, including a power monitoring module, an abnormal power analysis module, a preliminary evaluation module, a power frequent diagnosis module, and an alarm module;

[0070] The power monitoring module is used to monitor the working power of the mining equipment in real time during its operation, determine whether the working power of the mining equipment exceeds the specified threshold range, determine the working power status of the mining equipment based on the judgment result, and take corresponding measures;

[0071] The working power of the mining equipment includes normal working power, abnormal power and fault power;

[0072] The specific method of judging whether the working power of the mining equipment exceeds the prescribed threshold range, determining the working power of the mining equipment according to the judgment result, and making corresponding processing is as follows:

[0073] AS1: Real-time acquisition of the working power of mining equipment, denoted as P work ;

[0074] AS2: Set the working power P work Compare with the preset interval values ​​Q1 and Q2:

[0075] If P work Does not exceed the interval value Q1, and judges that the working power P work is the normal working power;

[0076] If P work If the operating power exceeds the interval value Q1 and is within the interval value Q2, the operating power is judged to be abnormal power;

[0077] If P work If the operating power exceeds the interval value Q2, it is determined that the operating power is fault power;

[0078] Among them, the interval value Q1 range is: [P b -D a ]∪[P b+D a ], P b is the rated power of the mining equipment during operation, D a is the allowable floating range power value, D a The specific value is set by professional and experienced staff;

[0079] The range of interval value Q2 is: [P b -D b ]∪[P b +D b ], D b is the allowable floating range power value, D b The specific value of D is set by professional and experienced staff, and b >D a ;

[0080] AS3: When the operating power is determined to be normal operating power, no processing is performed and monitoring is continued;

[0081] When the operating power is determined to be abnormal power, further detecting the cause of the abnormal power;

[0082] When the working power is judged to be fault power, an alarm message is issued;

[0083] This module collects the operating power data of mining equipment in real time and accurately compares it with two preset threshold ranges (Q1 and Q2), thereby dynamically monitoring and judging the working status of mining equipment. It can not only distinguish between normal operation, abnormal power and fault power, but also take corresponding measures for different statuses, such as continuing monitoring, in-depth analysis of the cause of the abnormality, or directly issuing an alarm, thereby effectively preventing failures caused by abnormal equipment power, ensuring that the equipment operates stably within a safe and reasonable working range, and reducing production risks and maintenance costs caused by power abnormalities.

[0084] Abnormal power analysis module, used to analyze the current / voltage data of abnormal power in time period T1 to determine the current fluctuation value and voltage fluctuation value;

[0085] The abnormal power analysis module includes an abnormal power current analysis unit and an abnormal power voltage analysis unit;

[0086] The abnormal power and current analysis unit is used to analyze the current data of the T1 period before the abnormal power moment and determine the current stability value; wherein, the T1 period is a preset value, which is specifically set by professional staff;

[0087] Abnormal power and voltage analysis unit, used to analyze the voltage data T1 time before the abnormal power moment and determine the voltage stability value;

[0088] The specific method of analyzing the current data at time T1 before the abnormal power moment to determine the current stable value is:

[0089] BS1: Get the current data detected in the T1 period before the abnormal power occurs;

[0090] BS2: Based on the current data of the T1 period, a plane rectangular coordinate system is established and the current data is marked in the first quadrant of the plane rectangular coordinate system, where the horizontal axis is time and the vertical axis is the specific current data, to generate a current change curve;

[0091] BS3: Establish two current floating limit horizontal lines in the current change curve, namely straight line y=C1 and straight line y=C2;

[0092] like Figure 2 As shown, according to the connection points (data points) in the current change curve, the connection points beyond the middle section of the straight line y=C1 and the straight line y=C2 are determined, and the number is counted and marked as k1;

[0093] The specific values ​​of C1 and C2 in the straight line y=C1 and the straight line y=C2 are determined by professional staff, and C2>C1;

[0094] BS4: Then, based on the current change curve, when the current change value of two adjacent current data exceeds the preset value b1 for more than two consecutive times, the number of times the two adjacent current data exceeds the preset value b1 in the continuous process is determined and marked as HI. The formula Hs=HI / 2 is used, where the calculation result is rounded down to determine the number of current jumps Hs in the continuous process. In this way, the overall number of current jumps in the current change curve is obtained and marked as k2;

[0095] The preset value b1 is determined by professional staff. In this embodiment,

[0096] Specifically, obtaining the overall current jump number in the current change curve is described by the following example:

[0097] If a set of current data is 5.2, 5.3, 5.8, 5.2, 5.7, 5.1, 5.6;

[0098] When the preset value b1 is 0.4, the difference between the first and second current data is 0.1, the difference between the second and third current data is 0.5, the difference between the third and fourth current data is 0.6, the difference between the fourth and fifth current data is 0.5, the difference between the fifth and sixth current data is 0.6, and the difference between the sixth and seventh current data is 0.5. In this set of current data, when the current changes of two adjacent current data exceed the preset value for five consecutive times, the formula Hs=H / 2 is used, where the calculation result is rounded down, and it is determined to be two current jumps;

[0099] If a set of current data is 5.2, 5.3, 5.4, 5.3, 5.8, 5.3, 5.6;

[0100] When the preset value b1 is 0.4, the current data exceeding 0.4 is when the difference between the fourth and fifth current data is 0.5, and the difference between the fourth and fifth current data is 0.5. In this set of current data, when the current change values ​​of two adjacent current data exceed the preset value for two consecutive times, the formula Hs=H / 2 is used, where the calculation result is rounded down, and it is determined to be a current jump;

[0101] BS5: Obtain k1 and k2, and use the following formula to determine the fluctuation value of the current data in time period T1:

[0102] I w =α1·k1+α2·k2

[0103] Where, I w is the fluctuation value of the current data, α1 and α2 are weight coefficients, which are determined by professional staff;

[0104] The specific method of analyzing the voltage data before the abnormal power moment to determine the voltage stability value is the same as the principle of analyzing the current data before the abnormal power moment to determine the voltage stability value. The specific method is as follows:

[0105] CS1: Gets the voltage data detected in the T1 period before the abnormal power occurs;

[0106] CS2: Based on the voltage data of the T1 period, a plane rectangular coordinate system is established and the voltage data is marked in the first quadrant of the plane rectangular coordinate system, where the horizontal axis is time and the vertical axis is the specific voltage data, to generate a voltage change curve;

[0107] CS3: Establish two voltage floating limit horizontal lines in the voltage change curve, namely straight line y=C3 and straight line y=C4;

[0108] According to the connection points (data points) in the voltage change curve, the connection points beyond the middle section of the straight line y=C3 and the straight line y=C4 are determined, and the number of them is counted and marked as d1;

[0109] The specific values ​​of C3 and C4 in the straight line y=C3 and the straight line y=C4 are determined by professional staff, and C4>C3;

[0110] CS4: Then, according to the voltage change curve, when the voltage change value of two adjacent voltage data exceeds the preset value b2 for more than two consecutive times, determine the number of times the two adjacent voltage data exceeds the preset value b2 in the continuous process, and mark it HU. Use the formula Hc=HU / 2, where the calculation result is rounded down to determine the number of voltage jumps in the continuous process H c In this way, the overall voltage jump times in the voltage change curve are obtained and marked as d2;

[0111] The preset value b2 is determined by professional staff. In this embodiment, b

[0112]

[0113] CS5: Obtain d1 and d2, and use the following formula to determine the fluctuation value of the voltage data during time period T1:

[0114] U w =β1·d1+β2·d2

[0115] Where U w is the fluctuation value of voltage data, β1 and β2 are weight coefficients, which are determined by professional staff;

[0116] This module focuses on in-depth analysis of current and voltage data in the period preceding the occurrence of abnormal power. By plotting data curves in a rectangular coordinate system and establishing two defined horizontal lines to detect data fluctuations and jumps, it quantitatively calculates the current and voltage fluctuation values ​​and the number of jumps. Utilizing this data mining and curve analysis method, the module accurately identifies the inherent characteristics and triggering factors of abnormal power generation, providing reliable, data-based parameter support for subsequent safety risk assessments, significantly improving the early warning capabilities and diagnostic accuracy of equipment abnormalities.

[0117] A preliminary assessment module is used to preliminarily assess the safety risk of mining equipment based on the current fluctuation value and the voltage fluctuation value, and determine the initial mining equipment safety risk value;

[0118] The specific method of preliminarily evaluating the safety risk value of mining equipment based on the current fluctuation value and the voltage fluctuation value and determining the initial safety risk value of mining equipment is as follows:

[0119] Get the initial current fluctuation value I w And voltage fluctuation value U w , preliminarily evaluate the safety risk of mining equipment through the preset preliminary evaluation formula model, and determine the initial mining equipment safety risk value FP x1 , the preset preliminary evaluation formula model is reflected by the following formula:

[0120] FP x1 =γ·(I w +U w ) n

[0121] Among them, γ is the evaluation factor, n is the impact index factor, and the specific values ​​of γ and n are set by professional staff;

[0122] Based on the current and voltage fluctuation data provided by the Abnormal Power Analysis Module, this module uses scientific and reasonable mathematical models and evaluation factors to quantitatively assess the initial safety risks of mining equipment. By combining the original fluctuation values ​​with the impact index factors, the module can quickly convert them into intuitive safety risk indicators, providing the first warning for the safety status of the equipment, helping operators to promptly identify potential risks and take necessary preventive measures before accidents occur, thereby improving the overall system's safety protection level and assessment accuracy.

[0123] The power frequency diagnosis module is used to further determine the safety risk value of mining equipment based on the frequency of abnormal power;

[0124] The specific method for further determining the safety risk value of mining equipment based on the frequent occurrence of abnormal power is as follows:

[0125] DS1: Get the time point t1 when the abnormal power first appears during the operation of the mining equipment, and then get the initial mining equipment safety risk value FP x1 ; The initial mining equipment safety risk value FP x1 Compare with the set mining equipment safety risk assessment threshold:

[0126] If the initial mining equipment safety risk value FP x1 When the risk exceeds the safety risk assessment threshold of mining equipment, an alarm message will be issued;

[0127] If the initial mining equipment safety risk value FP x1 If the value is less than or equal to the mining equipment safety risk assessment threshold, no action will be taken;

[0128] DS2: If the abnormal power occurs again, determine the time point t2 and calculate whether the interval between time points t1 and t2 exceeds T1:

[0129] If the T1 time period is not exceeded, the current mining equipment safety risk value FP is determined by the preset cumulative assessment formula model. x , the preset cumulative evaluation formula model is reflected by the following formula:

[0130] FP x =(1+v 2 )·FP x1

[0131] Where v represents the vth abnormal power order when the consecutive adjacent abnormal powers do not exceed T1, where v = 1;

[0132] If the T1 time period is exceeded, the current mining equipment safety risk value FP is determined by the preset cumulative evaluation formula model. x , the preset cumulative evaluation formula model is reflected by the following formula:

[0133] FP x =FP x1 +FP x2

[0134] Among them, FP x2 The mining equipment safety risk value determined for the second abnormal power;

[0135] Then the current mining equipment safety risk value FP x Compare with the set mining equipment safety risk assessment threshold:

[0136] If the current mine equipment safety risk value is greater than the mine equipment safety risk assessment threshold, an alarm message will be issued;

[0137] If the current mine equipment safety risk value is less than or equal to the mine equipment safety risk assessment threshold, no action will be taken;

[0138] DS3: Accumulate the safety risk value of mining equipment each time abnormal power occurs to determine the safety risk value of mining equipment each time abnormal power occurs;

[0139] Specifically, when the time intervals between consecutive abnormal power events do not exceed T1, the mining equipment safety risk value determined by the first abnormal power event in the process (initial mining equipment safety risk value) and the number of abnormal power events are obtained. Each time an abnormal power event occurs, the mining equipment safety risk value for each abnormal power event in the process is determined using the following formula:

[0140] FP x =(1+v 2 )·FP x1

[0141] Where v represents the vth abnormal power order when the consecutive abnormal powers do not exceed T1;

[0142] And compare each mining equipment safety risk value with the safety risk assessment threshold:

[0143] If the mine equipment safety risk value is greater than the mine equipment safety risk assessment threshold each time, it means that the mine equipment safety assessment risk is too high and an alarm message is issued.

[0144] If the mining equipment safety risk value is less than or equal to the mining equipment safety risk assessment threshold each time, no action will be taken;

[0145] When the consecutive adjacent abnormal power exceeds T1, the mining equipment safety risk value determined before the time period exceeding T1 is obtained, and the mining equipment safety risk value of each abnormal power occurrence after the time period exceeding T1 is determined at the same time. According to the cumulative result of the two mining equipment safety risk values, the cumulative result is judged and compared with the safety risk assessment threshold:

[0146] If the accumulated result is greater than the threshold value of the safety risk assessment of mining equipment, it means that the safety risk of mining equipment is too high and an alarm message is issued.

[0147] If the accumulated result is less than or equal to the mining equipment safety risk assessment threshold, no action will be taken;

[0148] This process is repeated until the safety risk value of mining equipment determined by each abnormal power exceeds the safety risk assessment threshold, and an alarm is issued;

[0149] This module dynamically diagnoses the frequent occurrence of abnormal power during the operation of mining equipment. By recording the time of the first abnormal power occurrence and calculating the time interval and cumulative risk value of subsequent abnormal events, it further refines and updates the safety risk assessment of mining equipment in real time. Using a risk accumulation formula and time interval judgment mechanism for continuous abnormal events, the module can capture subtle changes in the frequency of abnormalities during equipment operation. When the cumulative risk value exceeds the set threshold, it promptly reflects the deterioration trend of the equipment's operating status, providing a higher level of dynamic monitoring and preventive protection for system safety management.

[0150] The alarm module is used to receive the alarm information sent by the power frequent diagnosis module, issue an alarm, and notify the staff to handle or stop the operation of the mining equipment;

[0151] Example 2

[0152] In the specific implementation process, this embodiment is based on the first embodiment and differs from the first embodiment in that, in the power frequent diagnosis module, the safety risk value of the mining equipment is further determined according to the frequent occurrence of abnormal power, which is clearly explained through the following specific implementation methods:

[0153] If the current mining equipment has three abnormal power occurrences during operation, at 10:00, 10:05, and 10:15 respectively; if the set T1 time period is 6 minutes, and the first and second abnormal power occurrences do not exceed the set T1 time period:

[0154] Obtain the initial mining equipment safety risk value FP when the abnormal power first occurs at 10:00 x1 , then the second abnormal power mine equipment safety risk value that occurs at the time point 10:05 is calculated by the formula FP x =(1+v 2 )·FP x1 The calculated safety risk value FP of the mining equipment is x It is expressed as the overall result of the accumulation of the safety risk values ​​of mining equipment when abnormal power occurs for the first time and the second time, and the safety risk value of mining equipment FP is expressed as x The value is compared with the safety risk assessment threshold of mining equipment. If the comparison result is that no action is taken, the safety risk value of mining equipment for the third abnormal power is determined. Since the second and third abnormal powers exceed the set T1 time period, the initial safety risk value of mining equipment for the third abnormal power is recalculated and the previously determined safety risk value of mining equipment FP is used. x The value of the initial mining equipment safety risk value of the third abnormal power occurrence is added to the result, and the result is compared with the mining equipment safety risk assessment threshold. If the comparison result indicates that no action is taken, the abnormal power detection is continued:

[0155] This process is repeated in this way until the safety risk value of mining equipment determined by each abnormal power occurrence exceeds the safety risk assessment threshold, and an alarm is issued.

[0156] Example 3

[0157] The specific implementation process of this embodiment includes the entire implementation process of the above two groups of embodiments.

[0158] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0159] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A mining equipment operation safety evaluation system based on big data, characterized by: include: The power monitoring module is used to monitor whether the operating power of the mining equipment exceeds the specified threshold range during its operation. If it exceeds the specified threshold range, the operating power is judged to be abnormal power or fault power. If it does not exceed the specified threshold range, the monitoring is continued; Abnormal power analysis module, used to analyze the current / voltage data of abnormal power in time period T1 to determine the current fluctuation value and voltage fluctuation value; A preliminary assessment module is used to preliminarily assess the safety risk of mining equipment based on the current fluctuation value and the voltage fluctuation value, and determine the initial mining equipment safety risk value; The power frequent diagnosis module is used to further determine the safety risk value of mining equipment according to the frequency of abnormal power occurrence, and compare the determined safety risk value of mining equipment with the safety risk evaluation threshold of mining equipment to determine whether to issue an alarm message.

2. A mining equipment operation safety evaluation system based on big data according to claim 1, characterized in that: In the power monitoring module, the operating power of the mining equipment is monitored to see if it exceeds a specified threshold range. If it exceeds the specified threshold range, the operating power is determined to be abnormal power or fault power. If it does not exceed the specified threshold range, the specific method of continuing monitoring is as follows: AS1: Real-time acquisition of the working power of mining equipment, denoted as P work ; AS2: Set the working power P work Compare with the preset interval values ​​Q1 and Q2: If P work Does not exceed the interval value Q1, and judges that the working power P work is the normal working power; If P work If the operating power exceeds the interval value Q1 and is within the interval value Q2, the operating power is judged to be abnormal power; If P work If the operating power exceeds the interval value Q2, it is determined that the operating power is fault power; AS3: When the operating power is determined to be normal operating power, no processing is performed and monitoring is continued; When the operating power is determined to be abnormal power, further detecting the cause of the abnormal power; When the operating power is determined to be fault power, an alarm message is issued.

3. The mining equipment operation safety evaluation system based on big data according to claim 1 is characterized in that: In the abnormal power analysis module, the abnormal power analysis module includes an abnormal power current analysis unit and an abnormal power voltage analysis unit; An abnormal power and current analysis unit is used to analyze the current data of the time period before the abnormal power moment and determine the current stable value; The abnormal power and voltage analysis unit is used to analyze the voltage data before the abnormal power moment and determine the voltage stability value.

4. A mining equipment operation safety evaluation system based on big data according to claim 3, characterized in that: In the abnormal power and current analysis unit, the specific method of analyzing the current data at time T1 before the abnormal power moment to determine the current stable value is: BS1: Get the current data detected in the T1 period before the abnormal power occurs; BS2: Based on the current data of the T1 period, a plane rectangular coordinate system is established and the current data is marked in the first quadrant of the plane rectangular coordinate system, where the horizontal axis is time and the vertical axis is the specific current data, to generate a current change curve; BS3: Establish two current floating limit horizontal lines in the current change curve, namely straight line y=C1 and straight line y=C2; According to the connection points in the current change curve, the connection points beyond the middle section of the straight line y=C1 and the straight line y=C2 are determined, and the number of connection points is counted and marked as k1; Among them, C2>C1; BS4: Then, based on the current change curve, when the current change value of two adjacent current data exceeds the preset value b1 for more than two consecutive times, the number of times the two adjacent current data exceeds the preset value b1 in the continuous process is determined and marked as HI. The formula Hs=HI / 2 is used, where the calculation result is rounded down to determine the number of current jumps Hs in the continuous process. In this way, the overall number of current jumps in the current change curve is obtained and marked as k2; BS5: Get k1 and k2, and use the weighted calculation formula to determine the fluctuation value I of the current data in the T1 period w .

5. The mining equipment operation safety evaluation system based on big data according to claim 3 is characterized in that: In the abnormal power and voltage analysis unit, the specific method of analyzing the voltage data before the abnormal power moment to determine the voltage stability value is: CS1: Gets the voltage data detected in the T1 period before the abnormal power occurs; CS2: Based on the voltage data of the T1 period, a plane rectangular coordinate system is established and the voltage data is marked in the first quadrant of the plane rectangular coordinate system, where the horizontal axis is time and the vertical axis is the specific voltage data, to generate a voltage change curve; CS3: Establish two voltage floating limit horizontal lines in the voltage change curve, namely straight line y=C3 and straight line y=C4; According to the connection points in the voltage change curve, the connection points beyond the middle section of the straight line y=C3 and the straight line y=C4 are determined, and the number of connection points is counted and marked as d1; Among them, and C4>C3; CS4: Next, based on the voltage change curve, when the voltage change values ​​of two adjacent voltage data exceed the preset value b2 for more than two consecutive times, the number of times the two adjacent voltage data exceed the preset value b2 in the continuous process is determined and marked as HU. The formula Hc = HU / 2 is used, where the calculated result is rounded down to determine the number of voltage jumps in the continuous process Hc. In this way, the overall number of voltage jumps in the voltage change curve is obtained and marked as d2. CS5: Get d1 and d2, and determine the fluctuation value U of the voltage data in the T1 period through the weighted calculation formula w .

6. A mining equipment operation safety evaluation system based on big data according to claim 5, characterized in that: In the preliminary assessment module, the preliminary assessment of the safety risk value of mining equipment is performed based on the current fluctuation value and the voltage fluctuation value. The specific method for determining the initial safety risk value of mining equipment is as follows: obtaining the initial current fluctuation value I w And voltage fluctuation value U w , preliminarily evaluate the safety risk of mining equipment through the preset preliminary evaluation formula model, and determine the initial mining equipment safety risk value FP x1 .

7. The mining equipment operation safety evaluation system based on big data according to claim 6 is characterized in that: In the power frequent diagnosis module, the specific method of further determining the safety risk value of mining equipment based on the frequent occurrence of abnormal power is as follows: DS1: Get the time point t1 when the abnormal power first appears during the operation of the mining equipment, and then get the initial mining equipment safety risk value FP x1 ; The initial mining equipment safety risk value FP x1 Compare with the set mining equipment safety risk assessment threshold: If the initial mining equipment safety risk value FP x1 When the risk exceeds the safety risk assessment threshold of mining equipment, an alarm message will be issued; If the initial mining equipment safety risk value FP x1 If the value is less than or equal to the mining equipment safety risk assessment threshold, no action will be taken; DS2: If the abnormal power occurs again, determine the time point t2 and calculate whether the interval between time points t1 and t2 exceeds T1: If the T1 time period is not exceeded, the current mining equipment safety risk value FP is determined by the preset cumulative assessment formula model. x : If the T1 time period is exceeded, the current mining equipment safety risk value FP is determined by the preset cumulative evaluation formula model. x : Then the current mining equipment safety risk value FP x Compare with the set mining equipment safety risk assessment threshold: If the current mine equipment safety risk value is greater than the mine equipment safety risk assessment threshold, an alarm message will be issued; If the current mine equipment safety risk value is less than or equal to the mine equipment safety risk assessment threshold, no action will be taken; DS3: For each abnormal power occurrence, the safety risk value of the mining equipment is accumulated or added up to determine the safety risk value of the mining equipment for each abnormal power occurrence: When the time intervals between consecutive abnormal power events do not exceed T1, the mining equipment safety risk value determined by the first abnormal power event in the process and the number of abnormal power events are obtained. Each time an abnormal power event occurs, the mining equipment safety risk value for each abnormal power event in the process is determined using a preset cumulative evaluation formula model. And compare each mining equipment safety risk value with the safety risk assessment threshold: If the mine equipment safety risk value is greater than the mine equipment safety risk assessment threshold each time, it means that the mine equipment safety assessment risk is too high and an alarm message is issued. If the mining equipment safety risk value is less than or equal to the mining equipment safety risk assessment threshold each time, no action will be taken; When the consecutive adjacent abnormal power exceeds T1, the mining equipment safety risk value determined before the time period exceeding T1 is obtained, and the mining equipment safety risk value of each abnormal power occurrence after the time period exceeding T1 is determined at the same time. According to the cumulative result of the two mining equipment safety risk values, the cumulative result is judged and compared with the safety risk assessment threshold: If the accumulated result is greater than the threshold value of the safety risk assessment of mining equipment, it means that the safety risk of mining equipment is too high and an alarm message is issued. If the accumulated result is less than or equal to the mining equipment safety risk assessment threshold, no action will be taken; This process is repeated in this way until the safety risk value of mining equipment determined by each abnormal power occurrence exceeds the safety risk assessment threshold, and an alarm is issued.

8. The mining equipment operation safety evaluation system based on big data according to claim 1 is characterized in that: Also includes: The alarm module is used to receive the alarm information sent by the power frequent diagnosis module, issue an alarm, and notify the staff to handle or stop the operation of the mining equipment.

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