Non-coal mine intelligent evaluation method

Abstract

The invention discloses an intelligent evaluation method for a non-coal mine, and belongs to the technical field of non-coal mines, and the method comprises the following steps: S1, carrying out the field investigation of all subsystems of the non-coal mine, each subsystem of the non-coal mine comprising a first-level index and a second-level index; s2, the second-level indexes are scored intelligently; s3, the first-level indexes are scored intelligently; s4, obtaining an evaluation vector and an ideal vector; s5, obtaining a first-level index weight value; s6, the distance between the evaluation vector and the ideal vector is obtained based on the evaluation vector, the ideal vector and the first-level index weight value, and S7, the intelligent level of the non-coal mine is evaluated; the method is specially designed for the characteristics of the non-coal mine, the intelligent degree of the non-coal mine can be effectively evaluated, meanwhile, the evaluation not only considers the intelligent construction content of the mine, but also considers the intelligent construction difficulty, the intelligent construction advancement and the overall adaptability of the mine, the consideration is comprehensive, and the evaluation is more accurate.

Description

Technical Field

[0001] The present invention belongs to the technical field of non-coal mines, and in particular relates to an intelligent evaluation method for non-coal mines. Background Art

[0002] Non-coal mines refer to mines and tailings ponds that mine metal ores, radioactive ores, and other non-metallic minerals other than coal as petrochemical raw materials, building materials, auxiliary raw materials, refractory materials, and other non-metallic minerals. They are an important pillar of the national economy, and their production efficiency, safety conditions, and resource utilization are directly related to the country's economic development and social stability.

[0003] The intelligent construction of non-coal mines can significantly improve the production efficiency, safety status and resource utilization of non-coal mines. However, at present, the coal mining industry group has only introduced an intelligent evaluation method for coal mines. There are significant differences between non-coal mines and coal mines. Non-coal mines cannot directly refer to the intelligent evaluation method of coal mines to analyze and evaluate the intelligence of non-coal mines. Therefore, it is impossible to accurately evaluate the results and degree of intelligent construction of non-coal mines, and thus it is impossible to scientifically guide the intelligent construction and improvement of mines.

[0004] In view of this, an intelligent evaluation method for non-coal mines is designed to solve the above problems. Summary of the invention

[0005] To solve the problems raised in the above background technology. The present invention provides a non-coal mine intelligent evaluation method, which is specially designed for the characteristics of non-coal mines and can effectively evaluate the degree of intelligence of non-coal mines. At the same time, the evaluation not only takes into account the content of intelligent construction of mines, but also takes into account the difficulty and advancement of intelligent construction and the adaptability to the overall mine. It is comprehensive and has the characteristics of more accurate evaluation.

[0006] To achieve the above object, the present invention provides the following technical solution: a non-coal mine intelligent evaluation method, comprising the following steps:

[0007] S1: Invite a number of experts to conduct field investigations on the subsystems of non-coal mines, where the subsystems of non-coal mines include primary indicators and secondary indicators;

[0008] S2: Multiple experts score all the secondary indicators of non-coal mines, and the average of the experts’ scores is taken as the final score of the secondary indicators;

[0009] S3: Based on the final scores of the intelligent secondary indicators of non-coal mines, the intelligent primary indicators of non-coal mines corresponding to the secondary indicators are scored;

[0010] S4: Based on the intelligent scoring of the primary indicators of non-coal mines, the intelligent evaluation vector and ideal vector of non-coal mines are obtained;

[0011] S5: Based on the preset weight criteria of the first-level indicators of non-coal mines, multiple experts derive the weight values ​​of all the first-level indicators of non-coal mines;

[0012] S6: Based on the non-coal mine intelligent evaluation vector, the ideal vector and the weight values ​​of all primary indicators, the distance between the non-coal mine intelligent evaluation vector and the ideal vector is obtained, and the expression is:

[0013]

[0014] Where: (W1, W2, ..., W n ) is expressed as the weight value of each first-level indicator, (a1, a2, ..., a n ) is represented as the intelligent evaluation vector of non-coal mines, It is represented as the ideal vector of non-coal mines;

[0015] S7: Evaluate the intelligence level of non-coal mines based on the distance between the intelligent evaluation vector of non-coal mines and the ideal vector.

[0016] Furthermore, in step S1, the subsystems of non-coal mines include information control system S1, geological system S2, tunneling system S3, mining system S4, transportation system S5, ventilation system S6, power supply system S7, water supply and drainage system S8, mineral processing system S9, tailings treatment system S10, safety system S11 and environmental protection system S12, which are first-level indicators. The information control system S1 includes an integrated management and control platform C11, a transmission network C12 and other contents C13. The geological system S2 includes geological modeling C21, exploration equipment C22 and exploration technology C23. The tunneling system S3 includes tunneling equipment C31, tunneling control C32 and tunneling technology C33. The mining system S4 includes mining equipment C41, mining control C42 and mining technology C43. The transportation system S5 includes transportation equipment C5 1. Transport control C52 and transport technology C53, ventilation system S6 includes ventilation equipment C61, ventilation control C62 and ventilation technology C63, power supply system S7 includes power supply equipment C71 and power supply control C72, water supply and drainage system S8 includes water supply and drainage equipment C81 and water supply and drainage control C82, mineral processing system S9 includes mineral processing equipment C91, mineral processing control C92 and mineral processing technology C93, tailings treatment system S10 includes tailings treatment equipment C101, tailings treatment control C102 and tailings treatment technology C103, safety system S11 includes safety facilities and equipment C111, safety system control C112 and safety system technology C113, environmental protection system S12 includes environmental protection facilities and equipment C121, environmental protection system control C122 and environmental protection system technology C123. This is a secondary indicator.

[0017] Furthermore, in the step S3, the intelligent score of the first-level indicator of non-coal mines is calculated by the difficulty of intelligent construction, the results of intelligent construction, the advancement of intelligent construction and the adaptability to non-coal mines, wherein the difficulty of intelligent construction is represented by the difficulty coefficient of intelligent construction, the results of intelligent construction are represented by the weighted score of the final intelligent score of the second-level indicators of each first-level indicator, the advancement of intelligent construction and the adaptability to non-coal mines are represented by the coefficient corresponding to the expert evaluation, that is, the first-level indicator intelligent evaluation score = first-level indicator construction difficulty coefficient * first-level indicator weighted score * first-level indicator advancement coefficient.

[0018] Furthermore, in step S3, the method for determining the difficulty coefficient of the first-level indicator construction includes the following steps:

[0019] Set up evaluation and scoring tables for conditional indicators that affect the intelligent construction of first-level indicators. The conditional indicators include mining scale, mining area, ore body burial depth, ore body extension, engineering rock mass quality, hydrogeological conditions, engineering geological conditions, geological environment quality, ore dressing scale, ore dressing difficulty, tailings pond grade and tailings pond area;

[0020] Set the weight table of conditional indicators for the intelligent construction of first-level indicators;

[0021] Set up a corresponding table between the comprehensive score of the first-level indicator intelligent construction and the difficulty coefficient;

[0022] Based on the construction situation of non-coal mines, the evaluation and scoring table of conditional indicators affecting the intelligent construction of first-level indicators is set to obtain the scores of conditional indicators affecting the intelligent construction of first-level indicators;

[0023] Based on the scores of the conditional indicators that affect the intelligent construction of the first-level indicators and the set weight table of the conditional indicators for the intelligent construction of the first-level indicators, the weights of the conditional indicators for the intelligent construction of the first-level indicators are obtained;

[0024] The comprehensive score of the first-level indicator intelligent construction conditions is calculated by dividing the weighted score by the sum of the weights, that is, the comprehensive score of the first-level indicator construction conditions = (Σ(corresponding construction condition indicator score * indicator weight)) / (Σindicator weight);

[0025] Based on the comprehensive score of the first-level indicator intelligent construction conditions, the difficulty coefficient of the first-level indicator construction is obtained by comparing the relationship between the comprehensive score of the first-level indicator intelligent construction and the difficulty coefficient.

[0026] Furthermore, in step S3, the method for determining the weighted score of the primary indicator includes the following steps:

[0027] The weighted score of the first-level indicator is the weighted score of each second-level indicator under it, that is, the weighted score of the first-level indicator = Σ(the score of the second-level indicator under it * the weight of the second-level indicator), where the score of the second-level indicator is determined by the expert score, and the weight of the second-level indicator is determined by the preset weight criteria of the second-level indicator of non-coal mines;

[0028] The preset secondary indicator weight criteria are:

[0029] Principle 1:

[0030]

[0031] Where: i represents the first-level indicator, i = 1, 2, 3, ..., 12, j represents the first-level indicator, and m represents the number of second-level indicators of the first-level indicator;

[0032] Principle 2:

[0033] w 11 >w 12 >w 13 , w 21 >w 22 >w 23 , and w i1 ≈wi2>w i3 ; i = 2, 3, ..., 12

[0034] Where: w 11 It is expressed as the weight of the comprehensive management and control platform indicator, w 12 Denoted as the transmission network weight, w 13 Expressed as other content weights, w 21 Expressed as geological modeling weight, w 22 Expressed as the exploration equipment weight, w 23 Expressed as exploration technology weight, w i1 Expressed as device weight, w i2 Expressed as control weight, w i3 Expressed as technology weight.

[0035] Furthermore, in step S3, the method for determining the first-level indicator advancement coefficient includes the following steps:

[0036] Set up a corresponding table of the relationship between the first-level indicator advancement and the comprehensive score, evaluation and coefficient of the overall adaptability of the mine;

[0037] Multiple experts scored the advancement of the first-level indicators and their adaptability to the mine as a whole, and the average of the scores of the experts was taken as the comprehensive score of the advancement of the first-level indicators and their adaptability to the mine as a whole, that is: the comprehensive score of the advancement of the first-level indicators and their adaptability to the mine as a whole = (Σthe scores of each expert on the advancement of the indicator and its adaptability to the mine as a whole) / number of experts;

[0038] Based on the comprehensive score of the first-level indicator's advancement and the overall adaptability of the mine, the first-level indicator's advancement coefficient is obtained by comparing the set first-level indicator's advancement and the comprehensive score of the mine's overall adaptability, the evaluation and the coefficient correspondence table.

[0039] Furthermore, in step S5, the preset first-level indicator weight criterion is:

[0040] Principle 1:

[0041]

[0042] Where: i represents the first-level indicator, n represents the number of first-level indicators, which is generally 12. However, when some first-level indicators are missing, n < 12, the same below;

[0043] Principle 2:

[0044] W1>(W3≈W4≈W5≈W9≈W 10 )>(W6≈W7≈W8≈W 11 )>(W2≈W 12 );

[0045] Where: W1 is the weight of the information control system, W3 is the weight of the tunneling system, W4 is the weight of the mining system, W5 is the weight of the transportation system, W9 is the weight of the ore dressing system, and W 10 is the weight of the tailings treatment system, W6 is the weight of the ventilation system, W7 is the weight of the power supply system, W8 is the weight of the water supply and drainage system, and W 11 is the safety system weight, W2 is the geological system weight, and W 12 It is the weight of environmental protection system.

[0046] Furthermore, the specific steps of step S7 include:

[0047] Set up a corresponding table of the relationship between the distance between the non-coal mine intelligent evaluation vector and the ideal vector and the non-coal mine intelligent grade;

[0048] Based on the distance between the intelligent evaluation vector of non-coal mines and the ideal vector, a corresponding table of the relationship between the distance between the intelligent evaluation vector of non-coal mines and the ideal vector and the intelligent grade of non-coal mines is set to obtain the intelligent grade evaluation of non-coal mines.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention first divides the non-coal mine system into primary indicators and secondary indicators, then scores the secondary indicators, then scores the primary indicators based on the secondary indicator scores, then obtains an evaluation vector and an ideal vector based on the primary indicator scores, then calculates the distance between the two based on the evaluation vector and the ideal vector, and finally obtains an evaluation of the intelligence of the non-coal mine based on the distance between the two. The present invention is specially designed for the characteristics of non-coal mines, and can effectively evaluate the intelligence level of non-coal mines. At the same time, the evaluation not only takes into account the content of the intelligent construction of the mine, but also takes into account the difficulty and advancement of the intelligent construction and the adaptability to the mine as a whole. The consideration is comprehensive and the evaluation is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The figure is a flow chart of the intelligent evaluation method for non-coal mines of the present invention. DETAILED DESCRIPTION

[0052] 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.

[0053] See also Figure 1 The present invention provides the following technical solution: a non-coal mine intelligent evaluation method, comprising the following steps:

[0054] S1: Invite a number of experts to conduct field investigations on the subsystems of non-coal mines, where the subsystems of non-coal mines include primary indicators and secondary indicators;

[0055] S2: Multiple experts score all the secondary indicators of non-coal mines, and the average of the experts’ scores is taken as the final score of the secondary indicators;

[0056] S3: Based on the final scores of the intelligent secondary indicators of non-coal mines, the intelligent primary indicators of non-coal mines corresponding to the secondary indicators are scored;

[0057] S4: Based on the intelligent scoring of the primary indicators of non-coal mines, the intelligent evaluation vector and ideal vector of non-coal mines are obtained;

[0058] S5: Based on the preset weight criteria of the first-level indicators of non-coal mines, multiple experts derive the weight values ​​of all the first-level indicators of non-coal mines;

[0059] S6: Based on the non-coal mine intelligent evaluation vector, the ideal vector and the weight values ​​of all primary indicators, the distance between the non-coal mine intelligent evaluation vector and the ideal vector is obtained, and the expression is:

[0060]

[0061] Where: (W1, W2, ..., W n ) is expressed as the weight value of each first-level indicator, (a1, a2, ..., a n ) is represented as the intelligent evaluation vector of non-coal mines, It is represented as the ideal vector of non-coal mines;

[0062] S7: Evaluate the intelligence level of non-coal mines based on the distance between the intelligent evaluation vector of non-coal mines and the ideal vector.

[0063] Specifically, in step S1, the subsystems of non-coal mines include information control system S1, geological system S2, tunneling system S3, mining system S4, transportation system S5, ventilation system S6, power supply system S7, water supply and drainage system S8, mineral processing system S9, tailings treatment system S10, safety system S11 and environmental protection system S12, which are first-level indicators. The information control system S1 includes an integrated management and control platform C11, a transmission network C12 and other contents C13, among which other contents C13 include data storage devices and data processing equipment, etc. The geological system S2 includes geological modeling C21, exploration equipment C22 and exploration technology C23. The tunneling system S3 includes tunneling equipment C31, tunneling control C32 and tunneling technology C33. The mining system S4 includes mining equipment C41, mining control C42 and mining technology C43. The transportation System S5 includes transportation equipment C51, transportation control C52 and transportation technology C53, the ventilation system S6 includes ventilation equipment C61, ventilation control C62 and ventilation technology C63, the power supply system S7 includes power supply equipment C71 and power supply control C72, the water supply and drainage system S8 includes water supply and drainage equipment C81 and water supply and drainage control C82, the mineral processing system S9 includes mineral processing equipment C91, mineral processing control C92 and mineral processing technology C93, the tailings treatment system S10 includes tailings treatment equipment C101, tailings treatment control C102 and tailings treatment technology C103, the safety system S11 includes safety facilities and equipment C111, safety system control C112 and safety system technology C113, the environmental protection system S12 includes environmental protection facilities and equipment C121, environmental protection system control C122 and environmental protection system technology C123. This is a secondary indicator.

[0064] Specifically, in step S3, the score of the first-level intelligent indicator of non-coal mines is calculated by the difficulty of intelligent construction, the results of intelligent construction, the advancement of intelligent construction and the adaptability to non-coal mines, among which, the difficulty of intelligent construction is represented by the difficulty coefficient of intelligent construction, the results of intelligent construction are represented by the weighted points of the final intelligent scores of the second-level indicators of each first-level indicator, the advancement of intelligent construction and the adaptability to non-coal mines are represented by the coefficients corresponding to the expert evaluation, that is, the first-level indicator intelligent evaluation score = first-level indicator construction difficulty coefficient * first-level indicator weighted score * first-level indicator advancement coefficient.

[0065] Specifically, in step S3, the method for determining the difficulty coefficient of the first-level indicator construction includes the following steps:

[0066] The evaluation and scoring table of conditional indicators that affect the intelligent construction of the first-level indicators are set. The conditional indicators include mining scale, mining area, ore body burial depth, ore body extension, engineering rock mass quality, hydrogeological conditions, engineering geological conditions, geological environment quality, ore dressing scale, ore dressing difficulty, tailings pond grade and tailings pond area, as shown in Table 1:

[0067] Table 1: Evaluation and scoring of non-coal mine intelligent construction condition indicators

[0068]

[0069]

[0070]

[0071] Note: In the interval range, the lower digit includes the number, while the upper digit does not include the number. The specific value is fitted by linear interpolation between the upper and lower intervals.

[0072] The weight table of conditional indicators for the intelligent construction of the first-level indicators is set as shown in Table 2:

[0073] Table 2: Weights of intelligent construction condition indicators related to primary indicators

[0074]

[0075]

[0076] The relationship between the comprehensive score of the first-level indicator intelligent construction and the difficulty coefficient is set as shown in Table 3:

[0077] Table 3: Correspondence between the comprehensive score of the first-level indicator construction conditions and the difficulty coefficient

[0078]

[0079]

[0080] Note: In the interval range, the lower digit includes the number, while the upper digit does not include the number;

[0081] Based on the construction situation of non-coal mines, the evaluation and scoring table of conditional indicators affecting the intelligent construction of first-level indicators is set to obtain the scores of conditional indicators affecting the intelligent construction of first-level indicators;

[0082] Based on the scores of the conditional indicators that affect the intelligent construction of the first-level indicators and the set weight table of the conditional indicators for the intelligent construction of the first-level indicators, the weights of the conditional indicators for the intelligent construction of the first-level indicators are obtained;

[0083] The comprehensive score of the first-level indicator intelligent construction conditions is calculated by dividing the weighted score by the sum of the weights, that is, the comprehensive score of the first-level indicator construction conditions = (Σ(corresponding construction condition indicator score * indicator weight)) / (Σindicator weight);

[0084] Based on the comprehensive score of the first-level indicator intelligent construction conditions, the first-level indicator construction difficulty coefficient is obtained by comparing the relationship between the comprehensive score of the first-level indicator intelligent construction and the difficulty coefficient.

[0085] Specifically, in step S3, the method for determining the weighted score of the first-level indicator includes the following steps:

[0086] The weighted score of the first-level indicator is the weighted score of each second-level indicator under it, that is, the weighted score of the first-level indicator = Σ(the score of the second-level indicator under it * the weight of the second-level indicator), where the score of the second-level indicator is determined by the expert score, and the weight of the second-level indicator is determined by the preset weight criteria of the second-level indicator of non-coal mines;

[0087] The preset secondary indicator weight criteria are:

[0088] Principle 1:

[0089]

[0090] Where: i represents the first-level indicator, i = 1, 2, 3, ..., 12, j represents the first-level indicator, and m represents the number of second-level indicators of the first-level indicator;

[0091] Principle 2:

[0092] w 11 >w 12 >w 13 , w 21 >w 22 >w 23 , and w i1 ≈wi2>w i3 ; i = 2, 3, ..., 12

[0093] Where: w 11It is expressed as the weight of the comprehensive management and control platform indicator, w 12 Denoted as the transmission network weight, w 13 Expressed as other content weights, w 21 Expressed as geological modeling weight, w 22 Expressed as the exploration equipment weight, w 23 Expressed as exploration technology weight, w i1 Expressed as device weight, w i2 Expressed as control weight, w i3 Expressed as technology weight.

[0094] Specifically, in step S3, the method for determining the first-level indicator advancedness coefficient includes the following steps:

[0095] The relationship between the advancedness of the first-level indicators and the comprehensive score, evaluation and coefficient of the overall adaptability of the mine is set, as shown in Table 4:

[0096] Table 4: Evaluation and coefficients of advancement and adaptability to the mine as a whole

[0097]

[0098] Note: In the interval range, the lower digit includes the number, while the upper digit does not include the number;

[0099] Multiple experts scored the advancement of the first-level indicators and their adaptability to the mine as a whole, and the average of the scores of the experts was taken as the comprehensive score of the advancement of the first-level indicators and their adaptability to the mine as a whole, that is: the comprehensive score of the advancement of the first-level indicators and their adaptability to the mine as a whole = (Σthe scores of each expert on the advancement of the indicator and its adaptability to the mine as a whole) / number of experts;

[0100] Based on the comprehensive score of the first-level indicator's advancement and the overall adaptability of the mine, the first-level indicator's advancement coefficient is obtained by comparing the set first-level indicator's advancement and the comprehensive score of the mine's overall adaptability, the evaluation and the coefficient correspondence table.

[0101] Specifically, in step S5, the preset first-level indicator weight criterion is:

[0102] Principle 1:

[0103]

[0104] Where: i represents the first-level indicator, n represents the number of first-level indicators, which is generally 12. However, when some first-level indicators are missing, n < 12, the same below;

[0105] Principle 2:

[0106] W1>(W3≈W4≈W5≈W9≈W 10 )>(W6≈W7≈W8≈W11 )>(W2≈W 12 );

[0107] Where: W1 is the weight of the information control system, W3 is the weight of the tunneling system, W4 is the weight of the mining system, W5 is the weight of the transportation system, W9 is the weight of the ore dressing system, and W 10 is the weight of the tailings treatment system, W6 is the weight of the ventilation system, W7 is the weight of the power supply system, W8 is the weight of the water supply and drainage system, and W 11 is the safety system weight, W2 is the geological system weight, and W 12 It is the weight of environmental protection system.

[0108] Specifically, the specific steps of step S7 include:

[0109] The relationship between the distance between the non-coal mine intelligent evaluation vector and the ideal vector and the non-coal mine intelligent level is set in a corresponding table, as shown in Table 5:

[0110] Table 5: Evaluation criteria for intelligent mining

[0111] Mine intelligence level Distance from the ideal vector Intelligent evaluation Ⅰ ＜15 better Ⅱ 15～30 medium Ⅲ ≥30 generally

[0112] Note: In the interval range, the lower digit includes the number, while the upper digit does not include the number;

[0113] Based on the distance between the intelligent evaluation vector of non-coal mines and the ideal vector, a corresponding table of the relationship between the distance between the intelligent evaluation vector of non-coal mines and the ideal vector and the intelligent grade of non-coal mines is set to obtain the intelligent grade evaluation of non-coal mines. Specific embodiments

[0115] According to the above method, the intelligent evaluation of non-coal mines is carried out, wherein: in step S2, the final score of the intelligentization of each secondary indicator is shown in Table 6:

[0116] Table 6: Scores of each secondary indicator

[0117]

[0118]

[0119] In step S3, the statistical results and scores of the non-coal mine construction condition indicators to be evaluated are shown in Table 7:

[0120] Table 7: Statistical results and scores of construction condition indicators of non-coal mines to be evaluated

[0121]

[0122]

[0123] In step S3, the difficulty coefficients corresponding to the first-level indicators are shown in Table 8:

[0124] Table 8: First-level indicator construction condition scores and difficulty coefficients

[0125]

[0126]

[0127] In step S3, the difficulty coefficients corresponding to the first-level indicators are shown in Table 9:

[0128] Table 9: Weighted scores of primary indicators

[0129]

[0130]

[0131]

[0132] In step S3, the advancement of the primary indicator subsystem and its adaptability coefficient with the overall mine are shown in Table 10:

[0133] Table 10: Evaluation and coefficients of the advancement of the first-level indicator subsystem and its adaptability to the overall mine

[0134]

[0135]

[0136] In step S3, the intelligent evaluation scores of the first-level indicators are shown in Table 11:

[0137] Table 11: Smart evaluation scores for first-level indicators

[0138] First level indicator Intelligent evaluation score First level indicator Intelligent evaluation score Information control system S1 79 Power supply system S7 84 Geological System S2 74 Water supply and drainage system S8 82 Tunneling System S3 86 Ore dressing system S9 83 Mining System S4 75 Tailings treatment system S10 69 Transport system S5 87 Safety System S11 74 Ventilation System S6 73 Environmental protection system S12 77

[0139] In step S4, the non-coal mine intelligent evaluation vector A is A=(79, 74, 86, 75, 87, 73, 84, 82, 83, 69, 74, 77). Since the scores of the non-coal mine intelligent indicators are all positive scores, which is 100 points, the ideal vector A0 of the non-coal mine intelligent evaluation is A0=(100, 100, 100, 100, 100, 100, 100, 100, 100, 100, 100);

[0140] In step S5, the weights of each primary indicator are shown in Table 12:

[0141] Table 12: Weights of primary indicators

[0142] First level indicator Weight Weight value Information control system S1 <![CDATA[W1]]> 0.16 Geological System S2 <![CDATA[W2]]> 0.04 Tunneling System S3 <![CDATA[W3]]> 0.10 Mining System S4 <![CDATA[W4]]> 0.09 Transport system S5 <![CDATA[W5]]> 0.11 Ventilation System S6 <![CDATA[W6]]> 0.07 Power supply system S7 <![CDATA[W7]]> 0.06 Water supply and drainage system S8 <![CDATA[W8]]> 0.06 Ore dressing system S9 <![CDATA[W9]]> 0.09 Tailings treatment system S10 <![CDATA[W 10 ]]> 0.10 Safety System S11 <![CDATA[W 11 ]]> 0.07 Environmental protection system S12 <![CDATA[W 12 ]]> 0.05

[0143] In step S6, the distance D=22 between the intelligent evaluation vector A of the non-coal mine to be evaluated and the ideal vector A0 of the intelligent evaluation is obtained. Based on Table 5, it can be seen that the intelligent level of the non-coal mine is level II, and the intelligent construction effect is medium;

[0144] According to the intelligent evaluation scores of each first-level indicator, the intelligent scores of geological system S2, ventilation system S6, tailings treatment system S10 and safety system S11 are relatively low. In the future, these systems can be improved and upgraded to improve the intelligence level of non-coal mines, thereby improving the effectiveness of intelligent construction of mines.

[0145] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A non-coal mine intelligent evaluation method, characterized in that: The following steps are involved: S1: Invite a number of experts to conduct field investigations on the subsystems of non-coal mines, where the subsystems of non-coal mines include primary indicators and secondary indicators; S2: Multiple experts score all the secondary indicators of non-coal mines, and the average of the experts’ scores is taken as the final score of the secondary indicators; S3: Based on the final scores of the intelligent secondary indicators of non-coal mines, the intelligent primary indicators of non-coal mines corresponding to the secondary indicators are scored; S4: Based on the intelligent scoring of the primary indicators of non-coal mines, the intelligent evaluation vector and ideal vector of non-coal mines are obtained; S5: Based on the preset weight criteria of the first-level indicators of non-coal mines, multiple experts derive the weight values ​​of all the first-level indicators of non-coal mines; S6: Based on the non-coal mine intelligent evaluation vector, the ideal vector and the weight values ​​of all primary indicators, the distance between the non-coal mine intelligent evaluation vector and the ideal vector is obtained, and the expression is: Where: (W1, W2, ..., W n ) is expressed as the weight value of each first-level indicator, (a1, a2, ..., a n ) is represented as the intelligent evaluation vector of non-coal mines, It is expressed as the ideal vector of non-coal mines; S7: Evaluate the intelligence level of non-coal mines based on the distance between the intelligent evaluation vector of non-coal mines and the ideal vector.

2. The non-coal mine intelligent evaluation method according to claim 1 is characterized by: In the step S1, the subsystems of non-coal mines include information control system S1, geological system S2, tunneling system S3, mining system S4, transportation system S5, ventilation system S6, power supply system S7, water supply and drainage system S8, ore dressing system S9, tailings treatment system S10, safety system S11 and environmental protection system S12, which are first-level indicators. The information control system S1 includes an integrated management and control platform C11, a transmission network C12 and other content C13. The geological system S2 includes geological modeling C21, exploration equipment C22 and exploration technology C23. The tunneling system S3 includes tunneling equipment C31, tunneling control C32 and tunneling technology C33. The mining system S4 includes mining equipment C41, mining control C42 and mining technology C43. The transportation system S5 includes transportation equipment C51, Transport control C52 and transport technology C53, ventilation system S6 including ventilation equipment C61, ventilation control C62 and ventilation technology C63, power supply system S7 including power supply equipment C71 and power supply control C72, water supply and drainage system S8 including water supply and drainage equipment C81 and water supply and drainage control C82, mineral processing system S9 including mineral processing equipment C91, mineral processing control C92 and mineral processing technology C93, tailings treatment system S10 including tailings treatment equipment C101, tailings treatment control C102 and tailings treatment technology C103, safety system S11 including safety facilities and equipment C111, safety system control C112 and safety system technology C113, environmental protection system S12 including environmental protection facilities and equipment C121, environmental protection system control C122 and environmental protection system technology C123. These are secondary indicators.

3. The non-coal mine intelligent evaluation method according to claim 1 is characterized by: In the step S3, the intelligent score of the first-level indicator of non-coal mines is calculated by the difficulty of intelligent construction, the results of intelligent construction, the advancement of intelligent construction and the adaptability to non-coal mines, wherein the difficulty of intelligent construction is represented by the difficulty coefficient of intelligent construction, the results of intelligent construction are represented by the weighted score of the final intelligent score of the second-level indicators of each first-level indicator, the advancement of intelligent construction and the adaptability to non-coal mines are represented by the coefficient corresponding to the expert evaluation, that is, the intelligent evaluation score of the first-level indicator = the difficulty coefficient of the first-level indicator construction * the weighted score of the first-level indicator * the advancement coefficient of the first-level indicator.

4. The non-coal mine intelligent evaluation method according to claim 3 is characterized by: In step S3, the method for determining the difficulty coefficient of the first-level indicator construction includes the following steps: Set up evaluation and scoring tables for conditional indicators that affect the intelligent construction of first-level indicators. The conditional indicators include mining scale, mining area, ore body burial depth, ore body extension, engineering rock mass quality, hydrogeological conditions, engineering geological conditions, geological environment quality, ore dressing scale, ore dressing difficulty, tailings pond grade and tailings pond area; Set the weight table of conditional indicators for the intelligent construction of first-level indicators; Set up a corresponding table between the comprehensive score of the first-level indicator intelligent construction and the difficulty coefficient; Based on the construction situation of non-coal mines, the evaluation and scoring table of conditional indicators affecting the intelligent construction of first-level indicators is set to obtain the scores of conditional indicators affecting the intelligent construction of first-level indicators; Based on the scores of the conditional indicators that affect the intelligent construction of the first-level indicators and the set weight table of the conditional indicators for the intelligent construction of the first-level indicators, the weights of the conditional indicators for the intelligent construction of the first-level indicators are obtained; The comprehensive score of the first-level indicator intelligent construction conditions is calculated by dividing the weighted score by the sum of the weights, that is, the comprehensive score of the first-level indicator construction conditions = (Σ(corresponding construction condition indicator score * indicator weight)) / (Σindicator weight); Based on the comprehensive score of the first-level indicator intelligent construction conditions, the difficulty coefficient of the first-level indicator construction is obtained by comparing the relationship between the comprehensive score of the first-level indicator intelligent construction and the difficulty coefficient.

5. The non-coal mine intelligent evaluation method according to claim 3 is characterized by: In step S3, the method for determining the weighted score of the primary indicator includes the following steps: The weighted score of the first-level indicator is the weighted score of each second-level indicator under it, that is, the weighted score of the first-level indicator = Σ(the score of the second-level indicator under it * the weight of the second-level indicator), where the score of the second-level indicator is determined by the expert score, and the weight of the second-level indicator is determined by the preset weight criteria of the second-level indicator of non-coal mines; The preset secondary indicator weight criteria are: Principle 1: Where: i represents the first-level indicator, i = 1, 2, 3, ..., 12, j represents the first-level indicator, and m represents the number of second-level indicators of the first-level indicator; Principle 2: w 11 > w 12 > w 13 , w 21 > w 22 > w 23 , and w i1 ≈ wi2 > w i3 ; i = 2, 3,..., 12 Where: w 11 It is expressed as the weight of the comprehensive management and control platform indicator, w 12 Denoted as the transmission network weight, w 13 Expressed as other content weights, w 21 Expressed as geological modeling weight, w 22 Expressed as the exploration equipment weight, w 23 Expressed as exploration technology weight, w i1 Expressed as device weight, w i2 Expressed as control weight, w i3 Expressed as technology weight.

6. The non-coal mine intelligent evaluation method according to claim 3 is characterized by: In step S3, the method for determining the first-level indicator advancement coefficient includes the following steps: Set up a corresponding table of the relationship between the first-level indicator advancement and the comprehensive score, evaluation and coefficient of the overall adaptability of the mine; Multiple experts scored the advancement of the first-level indicators and their adaptability to the mine as a whole, and the average of the scores of the experts was taken as the comprehensive score of the advancement of the first-level indicators and their adaptability to the mine as a whole, that is: the comprehensive score of the advancement of the first-level indicators and their adaptability to the mine as a whole = (Σthe scores of each expert on the advancement of the indicator and its adaptability to the mine as a whole) / number of experts; Based on the comprehensive score of the first-level indicator's advancement and the overall adaptability of the mine, the first-level indicator's advancement coefficient is obtained by comparing the set first-level indicator's advancement and the comprehensive score of the mine's overall adaptability, the evaluation and the coefficient correspondence table.

7. The non-coal mine intelligent evaluation method according to claim 1 is characterized by: In step S5, the preset first-level index weight criteria are: Principle 1: Where: i represents the first-level indicator, n represents the number of first-level indicators, which is generally 12. However, when some first-level indicators are missing, n < 12, the same below; Principle 2: W1>(W3≈W4≈W5≈W9≈W 10 )>(W6≈W7≈W8≈W 11 )>(W2≈W 12 ); Where: W1 is the weight of the information control system, W3 is the weight of the tunneling system, W4 is the weight of the mining system, W5 is the weight of the transportation system, W9 is the weight of the ore dressing system, and W 10 is the weight of the tailings treatment system, W6 is the weight of the ventilation system, W7 is the weight of the power supply system, W8 is the weight of the water supply and drainage system, and W 11 is the safety system weight, W2 is the geological system weight, and W 12 It is the weight of environmental protection system.

8. The non-coal mine intelligent evaluation method according to claim 1 is characterized by: The specific steps of step S7 include: Set up a corresponding table of the relationship between the distance between the non-coal mine intelligent evaluation vector and the ideal vector and the non-coal mine intelligent grade; Based on the distance between the intelligent evaluation vector of non-coal mines and the ideal vector, a corresponding table of the relationship between the distance between the intelligent evaluation vector of non-coal mines and the ideal vector and the intelligent grade of non-coal mines is set to obtain the intelligent grade evaluation of non-coal mines.

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