Pre-class meeting intelligent management control method and system

Abstract

The invention relates to the technical field of mine field meeting before class, solves the technical problems that in the prior art, data analysis is low in accuracy and robustness, and the analysis process is tedious and difficult to learn, and particularly relates to a meeting before class intelligent management control method and system. Pre-processing the reference data Ck to obtain pre-processed data; s2, calculating an environment equipment personnel index Hsrh according to the preprocessed data; the optimal management control scheme is obtained through calculation of the cross experiment value, the process is simple and efficient, workers can rapidly obtain analysis results of the conference before class, the working efficiency of the conference before class is improved, the complexity can be reduced, rapid learning of the workers is facilitated, the global search ability is high, the convergence speed is high, and the method is suitable for popularization and application. And the accuracy of an analysis result and the working efficiency are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of pre-shift meetings in mines, and in particular to an intelligent management and control method and system for pre-shift meetings. Background Art

[0002] The pre-shift meeting at a drilling mine is a brief meeting held by the team leader or person in charge of all staff before the start of work each day. The main purpose of the meeting is to summarize the work of the previous day, arrange the tasks of the day, emphasize safety precautions, and ensure that all personnel have a clear understanding of the work content, risk points and emergency measures, and form a set of targeted management and control plans. The existing intelligent management and control methods for pre-shift meetings mainly conduct an overall analysis of the mine through electronic sign-in, virtual reality and data analysis. However, in the process of analyzing and obtaining management and control plans, it relies on multiple equipment systems to analyze different data, and uses intelligent algorithms to analyze nonlinear data, which has low accuracy and low robustness. In addition, due to the complexity of the data and the cumbersome process, the training of staff requires a lot of time and is very inefficient. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides an intelligent management and control method and system for pre-shift meetings, which solves the technical problems of low accuracy and low robustness of data analysis in the prior art, and complicated and difficult-to-learn analysis process, thereby achieving the purpose of greatly improving the accuracy and robustness of data analysis, simplifying the data analysis process and making it easy to learn.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for intelligent management and control of pre-shift meetings, the method comprising the following steps:

[0005] S1. Obtain reference data C of the drilling site k , and the reference data C k Performing preprocessing to obtain preprocessed data;

[0006] S2. Calculate the environmental equipment and personnel index Hsr based on the preprocessed data h , the pre-processed data includes basic equipment parameters;

[0007] S3, according to the environmental equipment personnel index Hsr h Calculate the mine risk factor Kf x ;

[0008] S4. Construct resource allocation index Zf based on basic equipment parameters y , and calculate the configuration function Pz u ;

[0009] S5. Configuration function Pz u and resource allocation index Zf yScreening is performed to obtain a set of management and control solutions that include multiple resource configuration solutions;

[0010] S6. Calculate the crossover experimental value Jc of any resource allocation scheme in the control scheme set s , and according to the crossover experimental value Jc s Select the best management and control solution Fa best .

[0011] Preferably, in step S1, the specific implementation steps are as follows:

[0012] S11. All reference data C k Arrange in ascending order to obtain the size sequence D x , according to the size sequence D x Calculate the first reference number C 1 and the second reference number C 2 , the calculation formula is:

[0013] C 1 =(D max +D min )×25%

[0014] C 2 =(D max +D min )×75%

[0015] Among them, D max and D min Represents the size sequence D x The maximum and minimum values ​​in ;

[0016] S12, according to the first reference number C 1 and the second reference number C 2 Calculate the distance value W z , the calculation formula is:

[0017] W z =C 2 -C 1

[0018] Among them, W z represents the zth distance value;

[0019] S13, according to the distance value W z Determine the reference data C k The upper boundary of the maximum and minimum values ​​of normal data in B up and the lower boundary B dn , the calculation formula is:

[0020] B up =C 2 +1.5×W z

[0021] B dn =C 1 -1.5×W z

[0022] Among them, the upper boundary B up and the lower boundary B dn Represents reference data C k The maximum and minimum values ​​of normal data in;

[0023] S14, according to the upper boundary B up and the lower boundary B dn For reference data C k The outliers are removed;

[0024] If C k ≤B dn or C k ≥B up , then the reference data C k is an outlier and is removed to obtain the removal bit T c ;

[0025] If B dn <C k up , then the reference data C k Normal value and keep it;

[0026] S15, calculate the removal position T c The processing value T b , the calculation formula is:

[0027]

[0028] Among them, T b Representation and elimination bit T c The corresponding processing value, T c-1 and T c+1 Respectively represent the removal bit T c Two adjacent reference data;

[0029] S16, process the value T b Fill to the removal position T c and obtain the preprocessed data.

[0030] Preferably, in step S2, the specific implementation steps are as follows:

[0031] S21. Calculate the environmental parameters H under normal operation of the drilling mine g , the calculation formula is:

[0032] ​

[0033] Among them, α, β and γ represent the ambient temperature hw d 、Ambient humidity hs a 、Ambient wind speed hf b The number of data, N represents the total number of α, β and γ;

[0034] S22. Calculate the equipment parameters S of the drilling mine under normal operation c , the calculation formula is:

[0035]

[0036] Among them, δ, ε and ∈ represent the vibration frequency of the equipment Sz respectively c , Equipment temperature Sw e and equipment power Sp s The number of data, M represents the total number of δ, ε and ∈, the basic parameters of the equipment include the equipment vibration frequency Sz c , Equipment temperature Sw e , Equipment power Sp s , the number of equipment M, the number of equipment in the drilling mine cost Cs b and the total number of uses Pc;

[0037] S23. Calculate the personnel safety parameter Aq of the drilling mine workers in the drilling mine r , the calculation formula is:

[0038]

[0039] Among them, θ, and μ represent the fatigue level of personnel Rp f , single disease frequency Rj p and personnel loss ratio Rs l The number of data, Q represents θ, and the total number of μ;

[0040] S24. Calculate the index weight Nq based on the total number of N, M and Q z ,Mq z and Qq z , the calculation formula is:

[0041]

[0042] Among them, the index weight Nq z ,Mq z and Qq z Respectively represent the environmental parameters H g 、Equipment parameters S c and personnel safety parameter Aq r The corresponding index weight;

[0043] S25, according to environmental parameters H g 、Equipment parameters S c and personnel safety parameter Aq r Calculation environment equipment personnel index Hsr h , the calculation formula is:

[0044] Hr h =Nq z ·H g +Mq z ·S c +Qq z ·Aq r

[0045] Among them, Hsr h Represents the hth environment equipment personnel index.

[0046] Preferably, in step S3, the specific implementation steps are as follows:

[0047] S31. Calculate the performance index OP used to evaluate the efficiency of drilling equipment i , the calculation formula is:

[0048]

[0049] Among them, OP i represents the i-th efficiency index, K represents the loss coefficient, T sj Indicates the actual working hours of the equipment in the drilling mine, T jh Represents the planned working hours of equipment in the drilling site;

[0050] S32. Calculate the operating factor G used to evaluate the energy consumption of drilling equipment k , the calculation formula is:

[0051]

[0052] Among them, G k Indicates the kth operating condition coefficient, SP k Indicates the instantaneous power of the equipment under normal working conditions, JP l Indicates the base power of a device operating normally;

[0053] S33. Calculate the mine risk factor Kf used to assess the risk of drilling mines x , the calculation formula is:

[0054]

[0055] Among them, Kf x represents the risk factor of the xth mine, b 1, b 2 and b 3 represents the risk weight, n, m and p represent the environment, equipment and personnel index Hsr h , performance index OP i and operating factor G k The amount of data.

[0056] Preferably, in step S4, the specific implementation steps are as follows:

[0057] S41, according to the vibration frequency Sz of the equipment c , Equipment temperature Sw e and equipment power Sp s Constructing the equipment capability matrix Sn rt , the expression is:

[0058]

[0059] Among them, Sn rt Indicates the tth capability value of the rth device;

[0060] S42, according to the environmental equipment personnel index Hsr h , performance index OP i and operating factor G k The measurement time constructs the time vector T v , the expression is:

[0061] T v ={t 1 t 2 … t v}

[0062] Among them, t v represents the vth measurement time;

[0063] S43, according to the equipment capability matrix Sn rt and the time vector T v Calculate the augmented value Zg p , the calculation formula is:

[0064] ZGar p =[Sn rt ||T v ]

[0065] Among them, Zg p represents the pth augmented value;

[0066] S44, according to the augmented value Zg p and mine risk factor Kf x Constructing the resource allocation index Zf y , the calculation formula is:

[0067] ZF y =Kf x ×[Sn rt ||T v ] T

[0068] Among them, Zf y represents the yth resource allocation index;

[0069] S45. Calculate the configuration function Pz for evaluating equipment cost u Configuration function Pz u , the calculation formula is:

[0070]

[0071] Among them, Pz u represents the u-th configuration function, Cs b represents the frequency cost of the bth device, and Pc represents the total number of times the device is used.

[0072] Preferably, in step S5, the specific implementation steps are as follows:

[0073] S51, according to the resource allocation index Zf y Equipment power Sp s Calculate the power consumption constraint Py s , the calculation formula is:

[0074]

[0075] Among them, Py s represents the power consumption constraint of the sth device;

[0076] S52, according to the configuration function Pz of multiple devices u , power consumption constraint Py s and mine risk factor Kf x Construct R resource allocation plans and calculate the screening coefficients H, I and J of the allocation plans;

[0077] S53, calculate the screening value Sx of each configuration scheme according to the screening coefficients H, I and J z , the calculation formula is:

[0078] Sx z =H·Pz u +I·Py s +J·Kf x

[0079] Among them, Sx z represents the screening value of the zth solution;

[0080] S54, according to the screening value Sxz Calculate the screening limit Jx s , the calculation formula is:

[0081]

[0082] Among them, R represents the screening value Sx z the number of

[0083] S55, according to the screening limit Jx s Screening R resource allocation plans;

[0084] If Sx z <Jx s , then the resource allocation plan is retained;

[0085] If Sx z ≥Jx s , then delete the resource configuration plan;

[0086] S56. The retained resource configuration schemes are grouped into a management and control scheme set.

[0087] Preferably, the calculation formula of the screening coefficients H, I and J of the configuration scheme is:

[0088]

[0089] Among them, H, I and J represent the configuration function Pz u , power consumption constraint Py s and mine risk factor Kf x The screening coefficient.

[0090] Preferably, in step S6, the specific implementation steps are as follows:

[0091] S61. Take the K resource allocation schemes in the control scheme set as the elements of the matrix to construct the initial group matrix C k , the expression is:

[0092] C k =[c 1 c 2 … c k ]

[0093] Among them, c k Denotes the initial group matrix C k The kth resource allocation scheme in ;

[0094] S62. Define the initial group matrix C k The best individual in the vth generation is Calculate the initial group matrix C k The random difference coefficient Sj x , the calculation formula is:

[0095]

[0096] in, and They represent the initial group matrix C in the vth generation respectively. k The μth individual and the πth individual are randomly selected;

[0097] S63, according to the random difference coefficient Sj x Calculate the progressive value Dy z , the calculation formula is:

[0098]

[0099] Among them, Dy z represents the zth progressive value, G represents the random coefficient;

[0100] S64, according to the progressive value Dy z Calculate the mutation value By q , the calculation formula is:

[0101]

[0102] Among them, By q represents the Qth mutation value;

[0103] S65, by mutation value q Calculate the crossover experimental value Jc s , the calculation formula is:

[0104]

[0105] Among them, CR represents the initial random number between 0.5-1, and rand(0,1) represents the random number between 0-1;

[0106] S66, filter value Sx z As the evolution function F(X), according to the crossover experimental value Jc s Calculate the evolutionary individuals of the v+1th generation The calculation formula is:

[0107]

[0108] in, represents the kth individual of the vth generation;

[0109] S67, according to the initial group matrix C k The number of iterations A is calculated using the formula:

[0110]

[0111] Among them, A represents the initial group matrix C k The corresponding number of iterations;

[0112] S68. Obtain the solution set Jh according to the number of iterations A f ;

[0113] If v < A, obtain the individual at the v-th iteration Return to step S62 and set v = v + 1;

[0114] If v = A, end the iteration and obtain a solution set Jh composed of multiple individuals ; f ;

[0115] S69. Substitute the elements in the solution set Jh f into the evolution function F(X), and take the solution corresponding to the minimum value of the evolution function F(X) as the optimal management control solution Fa best , and the expression is:

[0116] min[F(Jh f )] = Fa best

[0117] Among them, min[F(Jh f )] represents the minimum value of the evolution function F(X).

[0118] This technical solution also provides a system applied to the above management control method. The system includes:

[0119] A preprocessing module for obtaining reference data C of the drilling mine k , and preprocessing the reference data C k to obtain preprocessed data;

[0120] An analysis module for calculating the environmental equipment personnel index Hsr according to the preprocessed data h , and the preprocessed data includes equipment basic parameters;

[0121] A risk module for calculating the mine risk coefficient Kf according to the environmental equipment personnel index Hsr h ; x ;

[0122] A resource allocation module for constructing a resource allocation index Zf based on the equipment basic parameters y , and calculating a configuration function Pz u ;

[0123] A screening module for the configuration function Pz u and the resource allocation index Zf yScreening is performed to obtain a set of management and control solutions that include multiple resource configuration solutions;

[0124] The optimal module is used to calculate the cross-experimental value Jc of any resource allocation scheme in the control scheme set s , and according to the crossover experimental value Jc s Select the best management and control solution Fa best .

[0125] By means of the above technical solution, the present invention provides a method and system for intelligent management and control of pre-shift meetings, which has at least the following beneficial effects:

[0126] 1. The present invention can improve the accuracy of data through data preprocessing and quickly eliminate abnormal data in the data, which not only improves the accuracy of data but also improves the efficiency of data processing. Filling in the proposed data can make the data more reliable, and the analysis results are close to the real results, which greatly improves the analysis efficiency of subsequent steps.

[0127] 2. The present invention can conduct a comprehensive analysis of the drilling mine through risk analysis of the mine, which can not only ensure the safety of the working equipment, but also ensure the safety of the staff, and ensure the efficient work of the working equipment and staff. The calculation process is simple and efficient, which improves the work efficiency of the mine analysis.

[0128] 3. The present invention forms a variety of allocation matrices by combining the risk analysis results of the mine with various aspects of analysis, and obtains various combinations of configuration schemes based on the cost and power consumption of the equipment and the risk factor analysis. This method can not only efficiently obtain a variety of configuration schemes, but also avoid the problem of low accuracy in linear data analysis, thereby improving the accuracy of the analysis results.

[0129] 4. The present invention obtains the optimal management and control solution by calculating the cross-experimental values. The process is simple and efficient. It can not only enable the staff to quickly obtain the analysis results of the pre-shift meeting and improve the work efficiency of the pre-shift meeting, but also reduce the complexity and help the staff to learn quickly. It also has strong global search capabilities and fast convergence speed, which greatly improves the accuracy of the analysis results and work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0130] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0131] Figure 1 This is a flow chart of an intelligent management and control method for pre-shift meetings of the present invention;

[0132] Figure 2The present invention is a structural block diagram of an intelligent management and control system for pre-shift meetings. DETAILED DESCRIPTION

[0133] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods, so that the implementation process of how the present application uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0134] Due to the low accuracy and robustness of existing data analysis technologies, and the cumbersome and difficult-to-learn analysis process, please refer to Figure 1 This embodiment provides an intelligent management and control method for pre-shift meetings, which can greatly improve the accuracy and robustness of data analysis, simplify the data analysis process and make it easy to learn. The method includes the following steps:

[0135] S1. Obtain reference data of drilling sites C k , and the reference data C k Preprocessing is performed to obtain preprocessed data; since there is noise in the collected data in the original data, the abnormal data affected by the noise in the data needs to be preprocessed to obtain the hourly ambient temperature hw of the drilling mine. d 、Ambient humidity hs a 、Ambient wind speed hf b , the device vibration frequency Sz of each device c , Equipment temperature Sw e , Equipment power Sp s , each staff member's fatigue level Rp f , single disease frequency Rj p , Personnel loss ratio Rs l , the actual working hours of the mine T sj , Planned working hours T jh , the instantaneous power SP of the working condition k , reference power JP l The specific implementation steps are as follows:

[0136] S11. All reference data C k Arrange in ascending order to obtain the size sequence D x , according to the size sequence D x Calculate the first reference number C 1 and the second reference number C 2 , the calculation formula is:

[0137] C 1 =(D max +D min )×25%

[0138] C 2 =(D max +D min )×75%

[0139] Among them, D max and D min Represents the size sequence D x Get the maximum and minimum values ​​in the data sequence; get the data at different positions in the data sequence as reference data for calculation.

[0140] S12, according to the first reference number C 1 and the second reference number C 2 Calculate the distance value W z , the calculation formula is:

[0141] W z =C 2 -C 1

[0142] Among them, W z represents the zth distance value;

[0143] S13, according to the distance value W z Determine the reference data C k The upper boundary of the maximum and minimum values ​​of normal data in B up and the lower boundary B dn , the calculation formula is:

[0144] B up =C 2 +1.5×W z

[0145] B dn =C 1 -1.5×W z

[0146] Among them, the upper boundary B up and the lower boundary B dm Represents reference data C k The maximum and minimum values ​​of normal data; upper boundary B up and the lower boundary B dn It is equivalent to filtering out the range of abnormal data.

[0147] S14, according to the upper boundary B up and the lower boundary B dn For reference data C k The outliers are removed;

[0148] If C k ≤B dn or C k ≥B up , then the reference data Ck is an outlier and is removed to obtain the removal bit T c ;

[0149] If B dn <C k up , then the reference data C k Normal value and keep it;

[0150] S15, calculate the removal position T c The processing value T b , the calculation formula is:

[0151]

[0152] Among them, T b Representation and elimination bit T c The corresponding processing value, T c-1 and T c+1 Respectively represent the removal bit T c Two adjacent reference data; since the data position after elimination is missing data, it is necessary to eliminate the position T of the actual data c Fill in the data.

[0153] S16, process the value T b Fill to the removal position T c The data is preprocessed and the accuracy of the data is improved. The abnormal data is quickly eliminated, which not only improves the accuracy of the data but also improves the efficiency of data processing. Filling in the eliminated data can make the data more reliable and the analysis results close to the real results, which greatly improves the analysis efficiency of the subsequent steps.

[0154] S2. Calculate the environmental equipment and personnel index Hsr based on the preprocessed data h The pre-processed data includes basic equipment parameters; the pre-processed data contains a variety of data, including environmental data, equipment data, personnel data, and energy consumption data, etc. These data can be used to calculate the risk of the mine and complete the assessment of the risk factor. The specific implementation steps are as follows:

[0155] S21. Calculate the environmental parameters H under normal operation of the drilling mine g , the calculation formula is:

[0156]

[0157] Among them, α, β and γ represent the ambient temperature hw d 、Ambient humidity hf a 、Ambient wind speed hf b ​N represents the total number of data of α, β and γ; since environmental data, equipment data, personnel data and energy consumption data contain multiple data, such as the number of air particles, equipment update rate, equipment loss, etc., only three relatively characteristic data are listed here for calculation. In practice, more data can be substituted for more accurate analysis.

[0158] S22. Calculate the equipment parameters S of the drilling mine under normal operation c , the calculation formula is:

[0159]

[0160] Among them, δ, ε and ∈ represent the vibration frequency of the equipment Sz respectively c , Equipment temperature Sw e and equipment power Sp s The number of data, M represents the total number of δ, ε and ∈, and the basic parameters of the equipment include the vibration frequency Sz c , Equipment temperature Sw e , Equipment power Sp s , the number of equipment M, the number of equipment in the drilling mine cost Cs b and the total number of uses Pc;

[0161] S23. Calculate the personnel safety parameter Aq of the drilling mine workers in the drilling mine r , the calculation formula is:

[0162]

[0163] Among them, θ, and μ represent the fatigue level of personnel Rp f , single disease frequency Rj p and personnel loss ratio Rs l The number of data, Q represents θ, and the total number of μ;

[0164] S24. Calculate the index weight Nq based on the total number of N, M and Q z ,Mq z and Qq z , the calculation formula is:

[0165]

[0166] Among them, the index weight Nq z ,Mq z and Qq z Respectively represent the environmental parameters H g 、Equipment parameters S c and personnel safety parameter Aq rThe corresponding index weight;

[0167] S25, according to environmental parameters H g , Equipment parameters S c and personnel safety parameter Aq r Calculation environment equipment personnel index Hsr h , the calculation formula is:

[0168] HkD h =Nq z ·H g +Mq z ·S c +Qq z ·Aq r

[0169] Among them, Hsr h It represents the hth environment, equipment and personnel index. Through the risk analysis of the mine, a comprehensive analysis of the drilling mine can be carried out, which can not only ensure the safety of the working equipment, but also ensure the safety of the staff, and ensure the efficient work of the working equipment and staff. The calculation process is simple and efficient, which improves the work efficiency of the mine analysis.

[0170] S3, according to the environmental equipment personnel index Hsr h Calculate the mine risk factor Kf x ; Get the environmental equipment and personnel index Hsr h Further calculation is needed to obtain the mine risk factor Kf x The specific implementation steps are as follows:

[0171] S31. Calculate the performance index OP used to evaluate the efficiency of drilling equipment i , the calculation formula is:

[0172]

[0173] Among them, OP i represents the i-th efficiency index, K represents the loss coefficient, T sj Indicates the actual working hours of the equipment in the drilling mine, T jh Represents the planned working hours of equipment in the drilling site;

[0174] S32. Calculate the operating factor G used to evaluate the energy consumption of drilling equipment k , the calculation formula is:

[0175]

[0176] Among them, G k Indicates the kth operating condition coefficient, SP k Indicates the instantaneous power of the equipment under normal working conditions, JPl Indicates the base power of a device that is operating normally; performance index OP i and operating factor G k It can reflect the working conditions of staff and equipment in the mine, which is conducive to the formation of management and control plans in subsequent steps.

[0177] S33. Calculate the mine risk factor Kf used to assess the risk of drilling mines x , the calculation formula is:

[0178]

[0179] Among them, Kf x represents the risk factor of the xth mine, b 1 , b 2 and b 3 represents the risk weight, n, m and p represent the environment, equipment and personnel index Hsr h , performance index OP i and operating factor G k With the large amount of data, through the risk analysis of the mine, a comprehensive analysis of the drilling mine can be carried out, which can not only ensure the safety of the working equipment, but also ensure the safety of the staff, ensure the efficient work of the working equipment and staff, and the calculation process is simple and efficient, which improves the work efficiency of the mine analysis.

[0180] S4. Construct resource allocation index Zf based on basic equipment parameters y , and calculate the configuration function Pz u ; Get the mine risk factor Kf x Finally, in order to obtain a more optimized management and control plan, it is necessary to complete the selection of the plan in a matrix manner. The specific implementation steps are as follows:

[0181] S41, according to the vibration frequency Sz of the equipment c , Equipment temperature Sw e and equipment power Sp s Constructing the equipment capability matrix Sn rt , the expression is:

[0182]

[0183] Among them, Sn rt Represents the tth capability value of the rth device; each element here represents the capability of each device, including the device vibration frequency Sz c , Equipment temperature Sw e and equipment power Sp s Multiple factors can make the selection of management and control solutions more efficient.

[0184] S42, according to the environmental equipment personnel index Hsr h , performance index OP i and operating factor G k The measurement time constructs the time vector T v , the expression is:

[0185] T v ={t 1 t 2 … t v}

[0186] Among them, t v represents the vth measurement time; adding the time vector makes it easier to compare the efficiency of different solutions.

[0187] S43, according to the equipment capability matrix Sn rt and the time vector T v Calculate the augmented value Zg p , the calculation formula is:

[0188] ZGar p =[Sn rt ||T v ]

[0189] Among them, Zg p Represents the pth augmented value; combining equipment capacity and effectiveness into augmented values ​​can improve the comprehensive analysis of the mine. Different matrices can also be added here according to actual conditions, such as adding a matrix reflecting the health status of the staff to improve the comprehensiveness of the analysis.

[0190] S44, according to the augmented value Zg p and mine risk factor Kf x Constructing the resource allocation index Zf y , the calculation formula is:

[0191] ZF y =Kf x ×[Sn rt ||T v ] T

[0192] Among them, Zf y Represents the yth resource allocation index; by adding the mine risk coefficient Kf x It can improve the comprehensive analytical nature of the plan and make the acquisition of management and control plans more accurate.

[0193] S45. Calculate the configuration function Pz for evaluating equipment cost u , the calculation formula is:

[0194]

[0195] Among them, Pz u represents the u-th configuration function, Cs b Pc represents the total number of times the b-th device is used. The present invention forms a variety of allocation matrices by combining the risk analysis results of the mine and various analyses. Various combinations of configuration schemes are obtained based on the cost, power consumption and risk coefficient analysis of the equipment. This method can not only efficiently obtain a variety of configuration schemes, but also avoid the problem of low accuracy in linear data analysis, thereby improving the accuracy of the analysis results.

[0196] S5. Configuration function Pz u and resource allocation index Zf y Screening is performed to obtain a set of control solutions that include multiple resource configuration solutions; in order to obtain the control solutions quickly and efficiently. The specific implementation steps are as follows:

[0197] S51, according to the resource allocation index Zf y Equipment power Sp s Calculate the power consumption constraint Py s , the calculation formula is:

[0198]

[0199] Among them, Py s Represents the power consumption constraint of the sth device; in this step, the power consumption of the device is added as a consideration.

[0200] S52, according to the configuration function Pz of multiple devices u , power consumption constraint Py s and mine risk factor Kf x Construct R resource allocation plans and calculate the screening coefficients H, I and J of the allocation plans. The calculation formula is:

[0201]

[0202] Among them, H, I and J represent the configuration function Pz u , power consumption constraint Py s and mine risk factor Kf x The screening coefficient

[0203] S53, calculate the screening value Sx of each configuration scheme according to the screening coefficients H, I and J z , the calculation formula is:

[0204] Sx z =H·Pz u +I·Py s +J·Kf x

[0205] Among them, Sx z Indicates the screening value of the zth solution; screening value Sx z It can comprehensively reflect the comprehensive situation of different control schemes, and the comprehensive situation reflects the configuration function Pz u , power consumption constraint Py s and mine risk factor Kf x The size of the control scheme provides a reference for the selection of the control scheme and also provides an objective function for the calculation of subsequent steps.

[0206] S54, according to the screening value Sx z Calculate the screening limit Jx s , the calculation formula is:

[0207]

[0208] Among them, R represents the screening value Sx z The number of; select the limit Jx s Equivalent to the range value for filtering multiple resource configuration schemes.

[0209] S55, according to the screening limit Jx s Screening R resource allocation plans;

[0210] If Sx z <Jx s , then the resource allocation plan is retained;

[0211] If Sx z ≥Jx s , then delete the resource configuration plan;

[0212] S56, the reserved resource allocation schemes are grouped into a control scheme set. By obtaining the control scheme set, a smaller range can be provided for the subsequent selection of the optimal control scheme, which can not only improve the efficiency of selecting the optimal control scheme, but also improve the accuracy of the selection, and simplify the complexity of sequentially analyzing multiple data in the existing technology, so that the difficulty of learning and mastering by the staff is greatly reduced.

[0213] S6. Calculate the crossover experimental value Jc of any resource allocation scheme in the control scheme set s , and according to the crossover experimental value Jc s Select the best management and control solution Fa best , in order to find the optimal management control solution Fa in the control solution set best The specific implementation steps are as follows:

[0214] S61. Take the K resource allocation schemes in the control scheme set as the elements of the matrix to construct the initial group matrix C k , the expression is:

[0215] C k =[c 1 c 2 … c k ]

[0216] Among them, c k Denotes the initial group matrix C k The kth resource allocation scheme in the above example; here, the resource allocation scheme is calculated as an element, and each element contains the configuration function Pz u , power consumption constraint Py s and mine risk factor Kf x And other information.

[0217] S62. Define the initial group matrix C k The best individual in the vth generation is Calculate the initial group matrix C k The random difference coefficient Sj x , the calculation formula is:

[0218]

[0219] in, and They represent the initial group matrix C in the vth generation respectively. k The μth individual and the πth individual are randomly selected;

[0220] S63, according to the random difference coefficient Sj x Calculate the progressive value Dy z , the calculation formula is:

[0221]

[0222] Among them, Dy z represents the zth progressive value, G represents the random coefficient;

[0223] S64, according to the progressive value Dy z Calculate the mutation value By q , the calculation formula is:

[0224]

[0225] Among them, By q represents the qth mutation value;

[0226] S65, by mutation value q Calculate the crossover experimental value Jc s , the calculation formula is:

[0227]

[0228] Among them, CR represents an initial random number between 0.5 and 1, and rand(0,1) represents a random number between 0 and 1; although the initial random number CR is a kind of random number here, in practice, in order to improve the convergence speed, it is generally set to a number greater than 0.8.

[0229] S66. Take the screening value Sx z as the evolution function F(X), and calculate the evolutionary individuals of the (A + 1)-th generation according to the cross-experiment value Jc s The calculation formula is: The calculation formula is:

[0230]

[0231] Among them, represents the k-th individual of the v-th generation; each individual will evolve once, and the optimal solution is selected by comparing the minimum values of the objective function.

[0232] S67. Calculate the number of iterations A according to the initial group matrix C k , and the calculation formula is:

[0233]

[0234] Among them, A represents the number of iterations corresponding to the initial group matrix C k ;

[0235] S68. Obtain the solution set Jh f according to the number of iterations A;

[0236] If v < A, obtain the individuals of the v-th iteration and return to step S62 and set v = v + 1;

[0237] If v = A, end the iteration and obtain the solution set Jh composed of multiple individuals f ;

[0238] S69. Substitute the elements in the solution set Jh f into the evolution function F(X), and take the solution corresponding to the minimum value of the evolution function F(X) as the optimal management control solution Fa best , and the expression is:

[0239] min[F(Jh f )] = Fa best

[0240] Among them, min[F(Jh f)] represents the minimum value of the evolution function F(X). The optimal management and control solution is obtained by calculating the cross-experimental value. The process is simple and efficient. It can not only enable the staff to quickly obtain the analysis results of the pre-shift meeting and improve the work efficiency of the pre-shift meeting, but also reduce the complexity and help the staff to learn quickly. It also has strong global search capabilities and fast convergence speed, which greatly improves the accuracy of the analysis results and work efficiency.

[0241] See also Figure 2 , which is a structural block diagram of the intelligent management and control system of the pre-shift meeting provided in this embodiment. The intelligent management and control system of the pre-shift meeting includes a pre-processing module, an analysis module, a risk module, a resource allocation module, a screening module, and a selection module.

[0242] Preprocessing module, used to obtain reference data C of drilling sites k , and the reference data C k Perform preprocessing to obtain preprocessed data; the analysis module is used to calculate the environmental equipment personnel index Hsr based on the preprocessed data h The pre-processed data includes basic equipment parameters; the risk module is used to calculate the risk of equipment according to the environment equipment personnel index Hsr h Calculate the mine risk factor Kf x ; Resource configuration module, used to build resource allocation index Zf based on basic equipment parameters y , and calculate the configuration function Pz u ; Screening module for configuring function Pz u and resource allocation index Zf y Screening is performed to obtain a set of control schemes containing multiple resource allocation schemes; the optimal selection module is used to calculate the crossover experimental value Jc of any resource allocation scheme in the control scheme set s , and according to the crossover experimental value Jc s Select the best management and control solution Fa best .

[0243] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, so the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0244] The above implementation methods have been described in detail. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. An intelligent management and control method for pre-shift meetings, characterized in that: The method comprises the following steps: S1. Obtain reference data C of the drilling site k , and the reference data C k Performing preprocessing to obtain preprocessed data; S2. Calculate the environmental equipment and personnel index Hsr based on the preprocessed data h , the pre-processed data includes basic equipment parameters; S3, according to the environmental equipment personnel index Hsr h Calculate the mine risk factor Kf x ; S4. Construct resource allocation index Zf based on basic equipment parameters y , and calculate the configuration function Pz u ; S5. Configuration function Pz u and resource allocation index Zf y Screening is performed to obtain a control plan set including multiple resource configuration plans; S6. Calculate the crossover experimental value Jc of any resource allocation scheme in the control scheme set s , and according to the crossover experimental value Jc s Select the best management and control solution Fa best .

2. The management and control method according to claim 1, characterized in that: In step S1, the specific implementation steps are as follows: S11. All reference data C k Arrange in ascending order to obtain the size sequence D x , according to the size sequence D x The first reference number C1 and the second reference number C2 are calculated using the following formula: C1=(D max +D min )×25% C2=(D max +D min )×75% Among them, D max and D min Represents the size sequence D x The maximum and minimum values ​​in ; S12, calculating the distance value W according to the first reference number C1 and the second reference number C2 z , the calculation formula is: IN z =C2-C1 Among them, W z represents the zth distance value; S13, according to the distance value W z Determine the reference data C k The upper boundary of the maximum and minimum values ​​of normal data in B up and the lower boundary B dn , the calculation formula is: B up =C2+1.5×W z B dn =C1-1.5×W z S14, according to the upper boundary B up and the lower boundary B dn For reference data C k The outliers are removed; If C k ≤B dn or C k ≥B up , then the reference data C k is an outlier and is removed to obtain the removal bit T c ; If B dn <C k up , then the reference data C k Normal value and keep it;​ S15, calculate the removal position T c The processing value T b , the calculation formula is: Among them, T b Representation and elimination bit T c The corresponding processing value, T c-1 and T c+1 Respectively represent the removal bit T c Two adjacent reference data; S16, process the value T b Fill to the removal position T c and obtain the preprocessed data.

3. The management and control method according to claim 1, characterized in that: In step S2, the specific implementation steps are as follows: S21. Calculate the environmental parameters H under normal operation of the drilling mine g , the calculation formula is: Among them, α, β and γ represent the ambient temperature hw d 、Ambient humidity hs a 、Ambient wind speed hf b The number of data, N represents the total number of α, β and γ; S22. Calculate the equipment parameters S of the drilling mine under normal operation c , the calculation formula is: Among them, δ, ε and ∈ represent the vibration frequency of the equipment Sz respectively c , Equipment temperature Sw e and equipment power Sp s The number of data, M represents the total number of δ, ε and ∈, the basic parameters of the equipment include the equipment vibration frequency Sz c , Equipment temperature Sw e 、Equipment power Sp s , the number of equipment M, the number of equipment in the drilling mine cost Cs b and the total number of uses Pc; S23. Calculate the personnel safety parameter Aq of the drilling mine workers in the drilling mine r , the calculation formula is: Among them, θ, and μ represent the fatigue level of personnel Rp f , single person disease frequency Rj p and personnel loss ratio Rs l The number of data, Q represents θ, and the total number of μ; S24. Calculate the index weight Nq based on the total number of N, M and Q z ,Mq z and Qq z , the calculation formula is: Among them, the index weight Nq z ,Mq z and Qq z Respectively represent the environmental parameters H g , Equipment parameters S c and personnel safety parameter Aq r The corresponding index weight; S25, according to environmental parameters H g , Equipment parameters S c and personnel safety parameter Aq r Calculation environment equipment personnel index Hsr h , the calculation formula is: Hsr h =Nq z ·H g +Mq z ·S c +Qq z ·Aq r Among them, Hsr h Represents the hth environment equipment personnel index.

4. The management and control method according to claim 1, characterized in that: In step S3, the specific implementation steps are as follows: S31. Calculate the performance index OP used to evaluate the efficiency of drilling equipment i , the calculation formula is: Among them, OP i represents the i-th efficiency index, K represents the loss coefficient, T sj Indicates the actual working hours of the equipment in the drilling mine, T jh Represents the planned working hours of equipment in the drilling site; S32. Calculate the operating factor G used to evaluate the energy consumption of drilling equipment k , the calculation formula is: Among them, G k Indicates the kth operating condition coefficient, SP k Indicates the instantaneous power of the equipment under normal working conditions, JP l Indicates the base power of a device operating normally; S33. Calculate the mine risk factor Kf used to assess the risk of drilling mines x , the calculation formula is: Among them, Kf x represents the risk coefficient of the xth mine, b1, b2 and b3 represent risk weights, n, m and p represent the environment, equipment and personnel index Hsr respectively h , performance index OP i and operating factor G k The amount of data.

5. The management and control method according to claim 1, characterized in that: In step S4, the specific implementation steps are as follows: S41, according to the vibration frequency Sz of the equipment c , Equipment temperature Sw e and equipment power Sp s Constructing the equipment capability matrix Sn rt , the expression is: Among them, Sn rt Indicates the tth capability value of the rth device; S42, according to the environmental equipment personnel index Hsr h , performance index OP i and operating factor G k The measurement time constructs the time vector T v , the expression is: T v ={t1 t2…t v Among them, t v represents the vth measurement time; S43, according to the equipment capability matrix Sn rt and the time vector T v Calculate the augmented value Zg p , the calculation formula is: Zg p =[Sn rt ||T v ] Among them, Zg p represents the pth augmented value; S44, according to the augmented value Zg p and mine risk factor Kf x Constructing the resource allocation index Zf y , the expression is: Among them, Zf y represents the yth resource allocation index; S45. Calculate the configuration function Pz for evaluating equipment cost u , the calculation formula is: Among them, Pz u represents the u-th configuration function, Cs b represents the frequency cost of the bth device, and Pc represents the total number of times the device is used.

6. The management and control method according to claim 1, characterized in that: In step S5, the specific implementation steps are as follows: S51, according to the resource allocation index Zf y Equipment power Sp s Calculate the power consumption constraint Py s , the calculation formula is: Among them, Py s represents the power consumption constraint of the sth device; S52, according to the configuration function Pz of multiple devices u , power consumption constraint Py s and mine risk factor Kf x Construct R resource allocation plans and calculate the screening coefficients H, I and J of the allocation plans; S53, calculate the screening value Sx of each configuration scheme according to the screening coefficients H, I and J z , the calculation formula is: Sx z =H·Pz u +I·Py s +J·Kf x Among them, Sx z represents the screening value of the zth solution; S54, according to the screening value Sx z Calculate the screening limit Jx s , the calculation formula is: Among them, R represents the screening value Sx z the number of S55, according to the screening limit Jx s Screening R resource allocation plans; If Sx z <Jx s , then the resource allocation plan is retained; If Sx z ≥Jx s , then delete the resource configuration plan; S56. The retained resource configuration schemes are grouped into a management and control scheme set.

7. The management and control method according to claim 1, characterized in that: The calculation formulas for the screening coefficients H, I and J of the configuration scheme are: Among them, H, I and J represent the configuration function Pz u , power consumption constraint Py s and mine risk factor Kf x The screening coefficient.

8. The management and control method according to claim 1, characterized in that: In step S6, the specific implementation steps are as follows: S61. Take the K resource allocation schemes in the control scheme set as the elements of the matrix to construct the initial group matrix C k , the expression is: C k =[c1 c2 … c k ] Among them, c k Denotes the initial group matrix C k The kth resource allocation scheme in ; S62. Define the initial group matrix C k The best individual in the vth generation is Calculate the initial group matrix C k The random difference coefficient Sj x , the calculation formula is: in, and They represent the initial group matrix C in the vth generation respectively. k The μth individual and the πth individual are randomly selected; S63, according to the random difference coefficient Sj x Calculate the progressive value Dy z , the calculation formula is: Among them, Dy z represents the zth progressive value, G represents the random coefficient; S64, according to the progressive value Dy z Calculate the mutation value By q , the calculation formula is: Among them, By q represents the qth mutation value; S65, by mutation value q Calculate the crossover experimental value Jc s , the calculation formula is: Among them, CR represents the initial random number between 0.5-1, and rand(0,1) represents the random number between 0-1; S66, filter value Sx z As the evolution function F(X), according to the crossover experimental value Jc s Calculate the evolutionary individuals of the v+1th generation The calculation formula is: in, represents the kth individual of the vth generation; S67, according to the initial group matrix C k The number of iterations A is calculated using the formula: Where A represents the initial group matrix C k The corresponding number of iterations; S68. Obtain solution set Jh according to the number of iterations A f ; If v < A, the individual of the v-th iteration is obtained Return to step S62 and set v = v + 1; If v = A, the iteration ends and multiple individuals are obtained. The solution set Jh f ; S69, set the scheme Jh f Substitute the elements in into the evolution function F(X), and take the solution corresponding to the minimum value of the evolution function F(X) as the optimal management and control solution Fa best , the expression is: <h2 style=";text-align:left;direction:ltr">min[F(Jh<h2 style=";text-align:left;direction:ltr"> f <h2 style=";text-align:left;direction:ltr"> )]=Fa<h2 style=";text-align:left;direction:ltr"> best Among them, min[F(Jh f )] represents the minimum value of the evolution function F(X).

9. A system applied to the management and control method according to any one of claims 1 to 8, characterized in that: The system includes: Preprocessing module, used to obtain reference data C of drilling sites k , and the reference data C k Performing preprocessing to obtain preprocessed data; Analysis module, used to calculate the environmental equipment personnel index Hsr based on preprocessed data h , the pre-processed data includes basic equipment parameters; Risk module, used to determine the risk of h Calculate the mine risk factor Kf x ; Resource configuration module, used to build resource allocation index Zf based on basic equipment parameters y , and calculate the configuration function Pz u ; Filter module for configuring the function Pz u and resource allocation index Zf y Screening is performed to obtain a control plan set including multiple resource configuration plans; The optimal module is used to calculate the cross-experimental value Jc of any resource allocation scheme in the control scheme set s , and according to the crossover experimental value Jc s Select the best management and control solution Fa best .

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