Intelligent management system for tunnel engineering steel bar processing plant

Abstract

The invention discloses an intelligent management system for a tunnel engineering reinforcement processing factory, and relates to the technical field of reinforcement processing management, and the system comprises a fault model construction module which is used for constructing an equipment fault model of reinforcement processing equipment; the equipment matching analysis module is used for analyzing the equipment processing matching degree between the reinforcing steel bar processing equipment of the reinforcing steel bar processing factory and the reinforcing steel bars in the reinforcing steel bar production order data; the processing production line module is used for planning a processing production line of the reinforcing steel bars; the fault analysis module is used for performing fault analysis on the target reinforcing steel bar processing equipment to obtain abnormal target processing equipment; and the intelligent management module is used for evaluating different reinforcing steel bar processing devices in the reinforcing steel bar processing plant and the processing replacement degree of the abnormal target processing device, obtaining a replacement reinforcing steel bar processing device of the abnormal target processing device, adjusting the production and processing of reinforcing steel bars in the reinforcing steel bar processing plant in the current period, and intelligently managing the reinforcing steel bar processing plant.

Description

Technical Field

[0001] The invention relates to the technical field of steel bar processing management, and in particular to an intelligent management system for a tunnel engineering steel bar processing plant. Background Art

[0002] Steel bars are an indispensable part of tunnel engineering. They are mainly used to enhance the strength and toughness of concrete and ensure the stability and durability of tunnels. During the construction of tunnel engineering, a large number of different types of steel bars are required to be used for tunnel construction according to the load, geological conditions and construction technology of the tunnel. Therefore, the efficiency and quality of the steel bars produced by the steel bar processing plant have a great impact on the engineering efficiency and quality of the tunnel engineering, and even determine whether the tunnel process can be completed normally.

[0003] Precisely because of the tunnel project's requirements for the type and quantity of steel bars, the steel bar processing plant needs to produce different quantities and types of steel bars according to actual production needs. However, the steel bar processing equipment required for different types of steel bars during production and processing is not exactly the same, and during the processing, the steel bar processing equipment may also malfunction or age, thus affecting the steel bar production and processing. If the steel bar processing plant cannot manage the steel bar production and processing according to production needs and the equipment status, it will not only lead to a significant drop in the steel bar production and processing rate, but may also produce a large number of unqualified steel bars, causing huge damage. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent management system for a tunnel engineering steel bar processing plant to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions: an intelligent management system for a tunnel engineering steel bar processing plant, the management system comprising a fault model building module, an equipment matching analysis module, a processing production line module, a fault analysis module, and an intelligent management module; A fault model building module is used to obtain historical equipment operation records and historical fault records of the steel bar processing equipment of the steel bar processing plant, obtain historical equipment fault data from the historical fault records, and build an equipment fault model for the steel bar processing equipment; The equipment matching analysis module is used to obtain the steel bar production order data of the steel bar processing plant in the current cycle, obtain the equipment data of the steel bar processing equipment, analyze the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bars in the steel bar production order data, and obtain the target steel bar processing equipment; The processing line module is used to obtain the production plan time and total production plan of steel bars, obtain the location data of the target steel bar processing equipment, and plan the steel bar processing production line; The fault analysis module is used to produce and process the steel bars according to the steel bar processing production line, collect equipment operation data of the target steel bar processing equipment during the steel bar processing process, and use the equipment fault model to perform fault analysis on the target steel bar processing equipment to obtain abnormal target processing equipment; The intelligent management module is used to evaluate the different steel bar processing equipment in the steel bar processing plant, the degree of processing replacement of abnormal target processing equipment, obtain the alternative steel bar processing equipment for the abnormal target processing equipment, adjust the production and processing of steel bars in the steel bar processing plant in the current cycle, and intelligently manage the steel bar processing plant.

[0006] Further, the fault model construction module includes a historical data acquisition unit and a fault model construction unit; A historical data acquisition unit is used to acquire historical equipment operation records of steel bar processing equipment of the steel bar processing plant, extract historical equipment operation data from the historical equipment operation records, the historical equipment operation data includes data corresponding to various equipment operation parameters of the steel bar processing equipment, acquire historical fault records of the steel bar processing equipment, extract historical equipment fault data from the historical fault records, the historical equipment fault data includes data corresponding to various equipment operation parameters during the equipment fault process of the steel bar processing equipment; The fault model building unit is used to standardize various equipment operating parameters of the steel bar processing equipment, obtain standard values ​​of various equipment operating parameters, and build an equipment fault model based on historical equipment operation records and historical fault records of the steel bar processing equipment.

[0007] Furthermore, the fault model building unit includes: The various equipment operating parameters of the steel bar processing equipment are standardized to obtain the standard values ​​of the equipment operating parameters. Among them, the standard value of the equipment operating parameter of the steel bar processing equipment item a is X´=(X a -X min ) / (X max -X min ), where X a is the value of the equipment operating parameter of the steel bar processing equipment, X min , X max They are the minimum and maximum values ​​of the equipment operating parameters of item a during the operation of the steel bar processing equipment; Construct an equipment failure model for steel bar processing equipment. The specific construction process of the equipment failure model is as follows: Obtain a preset time window for the equipment failure model, divide the standard values ​​of various equipment operation parameters of the steel bar processing equipment into time windows of fixed time lengths based on the historical equipment operation data and historical equipment failure data of the steel bar processing equipment, and use the standard values ​​of various equipment operation parameters of the steel bar processing equipment in each time window as input data for the equipment failure model; Define the input layer, hidden layer and output layer of the equipment failure model, preset the weight matrix and bias vector of the equipment failure model, construct the input vector based on the standard values ​​of various equipment operating parameters of the steel bar processing equipment within the time window, and obtain the output f of the forget gate of the hidden layer in the equipment failure model t : , Among them, the forget gate output f t The t in W represents the current time step; f is the weight matrix of the forget gate; h t-1 is the hidden state of the previous time step of the current time step; x t represents the input vector of the current time step; b f is the bias vector of the forget gate; σ is the activation function, σ(ζ)=1 / (1+e -ζ ); Get the output of the input gate at the current time step in the input layer: , Among them, W i is the weight matrix of the input gate; b i is the bias vector of the forget gate; Get the candidate state C´ of the unit in the hidden layer at the current time step t : , Among them, W c is the weight matrix of the unit candidate state; b c is the bias vector of the unit candidate state; Get the cell state C of the current time step in the hidden layer t : , Among them, C t-1 is the cell state at the previous time step; Get the output o of the output gate in the hidden layer at the current time step t : , Among them, W o is the weight matrix of the output gate; b ois the bias vector of the output gate; σ is σ (sigma) represents the sigmoid activation function; Get the hidden state h of the current time step in the hidden layer t : , The output layer of the equipment failure model uses an activation function to transform the hidden state h t , converted into the output of the equipment failure model, and the equipment failure model is trained and updated, and W in the equipment failure model is f , W i , W c , W o and b f 、b i 、b c 、b o Update to obtain equipment failure model; In the process of constructing the above equipment failure model, W f , W i , W c , W o These are the weight matrices of the equipment failure model, b f 、b i 、b c 、b o The bias vector of the equipment fault model is used. The updating of weights and biases is based on minimizing the loss function, which can reduce the error between the predicted output and the actual label, so that the model can extract useful information from the data, optimize the predicted output, enhance the ability to capture complex patterns, and improve the adaptability and generalization ability of the model.

[0008] Further, the device matching analysis module includes a data acquisition unit and a device matching analysis unit; A data acquisition unit is used to acquire the steel bar production order data of the steel bar processing plant in the current cycle, the steel bar production order data includes several steel bar models of the steel bar that the steel bar processing plant plans to produce in the current cycle, and the equipment data of each steel bar processing equipment of the steel bar processing plant in the current cycle, the equipment data includes data corresponding to several equipment technical parameters of the steel bar processing equipment, processing technology data of steel bars of several steel bar models, and processing technology data includes data corresponding to various processing technology indicators of the steel bars; The equipment matching analysis unit is used to analyze the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bar models of several steel bar models in the steel bar production order data according to the equipment data of each steel bar processing equipment, so as to obtain the target steel bar processing equipment.

[0009] Furthermore, the device matching analysis unit includes: Obtain steel bar processing equipment that processes several steel bar models, analyze the steel bar processing equipment of the steel bar processing plant, and the equipment processing matching degree between the steel bars of several steel bar models in the steel bar production order data, and obtain the target steel bar processing equipment. The specific process of analyzing the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bar of the αth steel bar model in the steel bar production order data is as follows: Obtaining several processes and processing industrial data of the αth steel bar model, and combining the equipment data of each steel bar processing equipment, obtaining steel bar processing equipment to be selected for several processes of the steel bar of the αth steel bar model, and recording the steel bar processing equipment as each steel bar processing equipment to be selected for several processes of the αth steel bar model, and obtaining the average steel bar processing rate and average processing qualification rate of each steel bar processing equipment to be selected; Calculate the equipment matching degree between the selected steel bar processing equipment and several processes of the steel bar of the αth steel bar model, among which the equipment matching degree value L between the βth selected steel bar processing equipment and the μth process of the steel bar of the αth steel bar model is β,μ : , Among them, p β is the average qualified processing rate of the βth selected steel bar processing equipment; v β is the average steel bar processing rate of the βth steel bar processing equipment to be selected; v α,max is the maximum value of the average steel bar processing rate of several steel bar processing equipment of the αth steel bar model; v α,min is the minimum value of the average steel bar processing rate of several steel bar processing equipment of the αth steel bar model; γ1 is the preset characteristic rate coefficient, γ2 is the preset characteristic qualification coefficient, γ1+γ2=1; When the device matching degree value L β,μ If the value is greater than the preset equipment matching threshold, the βth candidate steel bar processing equipment is recorded as the target steel bar processing equipment for the μth process of the steel bar of the αth steel bar model.

[0010] Further, the processing line module includes a characteristic equipment total unit and a processing line unit; The characteristic equipment quantity unit is used to obtain the target steel bar processing equipment of several steel bar models in the current cycle, and obtain the characteristic equipment quantity of various processes of several steel bar models; The processing production line unit is used to reserve the target steel bar processing equipment of the total amount of characteristic equipment of several processes in several steel bar models according to the priority sorting, obtain the location data of the target steel bar processing equipment, and generate steel bar processing production lines of several steel bar models.

[0011] Furthermore, the characteristic equipment total quantity unit includes: Obtain target steel bar processing equipment for several steel bar models in the current cycle, and obtain the total amount of characteristic equipment for each process of several steel bar models. The process of obtaining the total amount of characteristic equipment for the δth process of the εth steel bar model is to obtain the production plan time and total amount of the steel bar for the εth steel bar model. The specific process of obtaining the equipment matching degree value of each target steel bar processing equipment in the δth process of the steel bar model of the εth steel bar is to prioritize each target steel bar processing equipment from large to small according to the size of the equipment matching degree value, and obtain the total amount of characteristic equipment in the δth process through the characteristic equipment total amount algorithm, wherein the characteristic equipment total amount algorithm is: , Among them, U ε,sum is the total planned production volume of the ε-th steel bar type; T ε is the production planning time of the εth steel bar model; v δ z is the average steel bar processing rate of the zth target steel bar processing equipment in the priority ranking of the δth process; n is the total number of target steel bar processing equipment when the total number of characteristic equipment algorithm is established; When the characteristic equipment quantity algorithm is established and n is the minimum value, the value of n being the minimum value is the characteristic equipment quantity of the δth process of the steel bar of the εth steel bar model.

[0012] Furthermore, the processing line unit includes: Based on the total amount of characteristic equipment of several processes in several steel bar models, the target steel bar processing equipment of the total amount of characteristic equipment is reserved according to the priority order; Obtaining the position data of the target steel bar processing equipment reserved for each process in the steel bars of several steel bar models, where the position data is the coordinates of the target steel bar processing equipment; According to the processing sequence of each process in the steel bars of several steel bar models and combined with the coordinates of the target steel bar processing equipment, the equipment distance between the target steel bar processing equipment of each process in the steel bars of several steel bar models is obtained, and based on the processing sequence, the two target steel bar processing equipment with the closest equipment distance are used as the target steel bar processing equipment in the same production line, and the processing production lines of the steel bars of several steel bar models are generated.

[0013] Further, the fault analysis module includes a fault analysis unit; The fault analysis unit is used to produce and process several types of steel bar models according to their processing production lines, collect equipment operation data of target steel bar processing equipment during the steel bar processing process, and use the equipment fault model to perform equipment fault analysis on the target steel bar processing equipment in the steel bar processing production line to obtain abnormal target processing equipment in the current cycle.

[0014] Further, the intelligent management module includes an intelligent management unit; The intelligent management unit is used to obtain various abnormal target processing equipment in the steel bar processing plant within the current cycle, obtain various target processing equipment with the same steel bar model and process as the steel bars processed by the abnormal target processing equipment, obtain the target processing equipment with the shortest equipment distance to the abnormal target processing equipment from various target processing equipment, use it as the replacement steel bar processing equipment for the abnormal target processing equipment, transport the steel bars to be processed by the abnormal target processing equipment to the replacement steel bar processing equipment for steel bar processing, adjust the production and processing of the steel bars in the steel bar processing plant within the current cycle, and intelligently manage the steel bar processing plant.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention realizes the intelligent management of the steel bar processing plant that supplies steel bars to the tunnel project, firstly, according to the historical equipment operation records and historical fault records of the steel bar processing plant, the equipment fault model of the steel bar processing equipment is constructed, and according to the steel bar production order and the equipment data of the steel bar processing equipment, the target steel bar processing equipment for processing the steel bar is obtained, and according to the position data of the target steel bar processing equipment, the steel bar processing production line is generated, and the constructed equipment fault model is used to perform fault analysis on the equipment on the steel bar processing production line, so as to timely adjust the steel bar processing production, which not only realizes the intelligent production of steel bar processing, but also greatly reduces the impact of equipment failure on steel bar processing production, and improves production efficiency and the qualified rate of steel bar processing production. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of a unit of an intelligent management system for a tunnel engineering steel bar processing plant of the present invention; Figure 2 It is a module schematic diagram of an intelligent management system for a tunnel engineering steel bar processing plant according to the present invention. DETAILED DESCRIPTION

[0017] 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.

[0018] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution, an intelligent management system for a tunnel engineering steel bar processing plant, the management system includes a fault model building module, an equipment matching analysis module, a processing production line module, a fault analysis module, and an intelligent management module; A fault model building module is used to obtain historical equipment operation records and historical fault records of the steel bar processing equipment of the steel bar processing plant, obtain historical equipment fault data from the historical fault records, and build an equipment fault model for the steel bar processing equipment; The equipment matching analysis module is used to obtain the steel bar production order data of the steel bar processing plant in the current cycle, obtain the equipment data of the steel bar processing equipment, analyze the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bars in the steel bar production order data, and obtain the target steel bar processing equipment; The processing line module is used to obtain the production plan time and total production plan of steel bars, obtain the location data of the target steel bar processing equipment, and plan the steel bar processing production line; The fault analysis module is used to produce and process the steel bars according to the steel bar processing production line, collect equipment operation data of the target steel bar processing equipment during the steel bar processing process, and use the equipment fault model to perform fault analysis on the target steel bar processing equipment to obtain abnormal target processing equipment; The intelligent management module is used to evaluate the different steel bar processing equipment in the steel bar processing plant, the degree of processing replacement of abnormal target processing equipment, obtain the replacement steel bar processing equipment for the abnormal target processing equipment, adjust the production and processing of steel bars in the steel bar processing plant in the current cycle, and perform intelligent management of the steel bar processing plant; Among them, the fault model building module includes a historical data acquisition unit and a fault model building unit; A historical data acquisition unit is used to acquire historical equipment operation records of steel bar processing equipment of the steel bar processing plant, extract historical equipment operation data from the historical equipment operation records, the historical equipment operation data includes data corresponding to various equipment operation parameters of the steel bar processing equipment, acquire historical fault records of the steel bar processing equipment, extract historical equipment fault data from the historical fault records, the historical equipment fault data includes data corresponding to various equipment operation parameters during the equipment fault process of the steel bar processing equipment; For example, various equipment operating parameters include equipment voltage, equipment current, etc.; A fault model building unit is used to standardize various equipment operating parameters of the steel bar processing equipment to obtain standard values ​​of various equipment operating parameters, and to build an equipment fault model based on historical equipment operation records and historical fault records of the steel bar processing equipment; The fault model building unit includes: The various equipment operating parameters of the steel bar processing equipment are standardized to obtain the standard values ​​of the equipment operating parameters. Among them, the standard value of the equipment operating parameter of the steel bar processing equipment item a is X´=(X a -X min ) / (X max -X min ), where X a is the value of the equipment operating parameter of the steel bar processing equipment, X min , X max They are the minimum and maximum values ​​of the equipment operating parameters of item a during the operation of the steel bar processing equipment; Construct an equipment failure model for steel bar processing equipment. The specific construction process of the equipment failure model is as follows: Obtain a preset time window for the equipment failure model, divide the standard values ​​of various equipment operation parameters of the steel bar processing equipment into time windows of fixed time lengths based on the historical equipment operation data and historical equipment failure data of the steel bar processing equipment, and use the standard values ​​of various equipment operation parameters of the steel bar processing equipment in each time window as input data for the equipment failure model; Define the input layer, hidden layer and output layer of the equipment failure model, preset the weight matrix and bias vector of the equipment failure model, construct the input vector based on the standard values ​​of various equipment operating parameters of the steel bar processing equipment within the time window, and obtain the output f of the forget gate of the hidden layer in the equipment failure model t : , Among them, the forget gate output f t The t in W represents the current time step; f is the weight matrix of the forget gate; h t-1 is the hidden state of the previous time step of the current time step; x t represents the input vector of the current time step; b f is the bias vector of the forget gate; σ is the activation function, σ(ζ)=1 / (1+e -ζ ); Get the output of the input gate in the input layer for the current time step: , Among them, W i is the weight matrix of the input gate; b i is the bias vector of the forget gate; Get the candidate state C´ of the unit in the hidden layer at the current time step t : , Among them, W c is the weight matrix of the unit candidate state; b c is the bias vector of the unit candidate state; Get the cell state C of the current time step in the hidden layer t : , Among them, C t-1 is the cell state at the previous time step; Get the output o of the output gate in the hidden layer at the current time step t : , Among them, W o is the weight matrix of the output gate; b o is the bias vector of the output gate; Get the hidden state h of the current time step in the hidden layer t : , The output layer of the equipment failure model uses an activation function to transform the hidden state h t , converted into the output of the equipment failure model, and the equipment failure model is trained and updated, and W in the equipment failure model is f , W i , W c , W o and b f 、b i 、b c 、b o Update to obtain equipment failure model; Among them, the device matching analysis module includes a data acquisition unit and a device matching analysis unit; A data acquisition unit is used to acquire the steel bar production order data of the steel bar processing plant in the current cycle, the steel bar production order data includes several steel bar models of the steel bar that the steel bar processing plant plans to produce in the current cycle, and the equipment data of each steel bar processing equipment of the steel bar processing plant in the current cycle, the equipment data includes data corresponding to several equipment technical parameters of the steel bar processing equipment, processing technology data of steel bars of several steel bar models, and processing technology data includes data corresponding to various processing technology indicators of the steel bars; For example, several equipment technical parameters include the minimum processing steel bar diameter, minimum processing length, etc.; For example, various processing technology indicators include steel bar processing methods, processing accuracy, etc.; The equipment matching analysis unit is used to analyze the equipment matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bar of several steel bar models in the steel bar production order data according to the equipment data of each steel bar processing equipment, and obtain the target steel bar processing equipment; The device matching analysis unit includes: Obtain steel bar processing equipment that processes several steel bar models, analyze the steel bar processing equipment of the steel bar processing plant, and the equipment processing matching degree between the steel bars of several steel bar models in the steel bar production order data, and obtain the target steel bar processing equipment. The specific process of analyzing the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bar of the αth steel bar model in the steel bar production order data is as follows: Obtaining several processes and processing industrial data of the αth steel bar model, and combining the equipment data of each steel bar processing equipment, obtaining steel bar processing equipment to be selected for several processes of the steel bar of the αth steel bar model, and recording the steel bar processing equipment as each steel bar processing equipment to be selected for several processes of the αth steel bar model, and obtaining the average steel bar processing rate and average processing qualification rate of each steel bar processing equipment to be selected; For example, several processes include cutting, bending, welding, etc.; Calculate the equipment matching degree between the selected steel bar processing equipment and several processes of the steel bar of the αth steel bar model, among which the equipment matching degree value L between the βth selected steel bar processing equipment and the μth process of the steel bar of the αth steel bar model is β,μ : , Among them, p β is the average qualified processing rate of the βth selected steel bar processing equipment; v β is the average steel bar processing rate of the βth steel bar processing equipment to be selected; v α,max is the maximum value of the average steel bar processing rate of several steel bar processing equipment of the αth steel bar model; v α,min is the minimum value of the average steel bar processing rate of several steel bar processing equipment of the αth steel bar model; γ1 is the preset characteristic rate coefficient, γ2 is the preset characteristic qualification coefficient, γ1+γ2=1; For example, the average processing qualification rate p1 of the first candidate steel bar processing equipment is 0.95; the average steel bar processing rate v1 of the first candidate steel bar processing equipment is 50 / min; the average steel bar processing rate of the first candidate steel bar processing equipment; the maximum value v of the average steel bar processing rate of several steel bar processing equipment of the second steel bar model 2,max is 200 / min; the minimum value v of the average steel bar processing rate of several steel bar processing equipment of the second steel bar model 2,minis 20 / min; γ1 is 0.4; γ2 is 0.6; Calculate the equipment matching value L between the first candidate steel bar processing equipment and the third process of the steel bar of the second steel bar model 1,3 : , When the device matching degree value L β,μ If the value is greater than the preset equipment matching threshold, the βth candidate steel bar processing equipment is recorded as the target steel bar processing equipment for the μth process of the steel bar of the αth steel bar model; Among them, the processing production line module includes a characteristic equipment total unit and a processing production line unit; The characteristic equipment quantity unit is used to obtain the target steel bar processing equipment of several steel bar models in the current cycle, and obtain the characteristic equipment quantity of various processes of several steel bar models; The processing line unit is used to reserve the target steel bar processing equipment of the total amount of characteristic equipment according to the priority sorting according to the total amount of characteristic equipment of several processes in several steel bar models, obtain the position data of the target steel bar processing equipment, and generate the steel bar processing production line of several steel bar models; Among them, the characteristic equipment total quantity unit includes: Obtain target steel bar processing equipment for several steel bar models in the current cycle, and obtain the total amount of characteristic equipment for each process of several steel bar models. The process of obtaining the total amount of characteristic equipment for the δth process of the εth steel bar model is to obtain the production plan time and total amount of the steel bar for the εth steel bar model. The specific process of obtaining the equipment matching degree value of each target steel bar processing equipment in the δth process of the steel bar model of the εth steel bar is to prioritize each target steel bar processing equipment from large to small according to the size of the equipment matching degree value, and obtain the total amount of characteristic equipment in the δth process through the characteristic equipment total amount algorithm, wherein the characteristic equipment total amount algorithm is: , Among them, U ε,sum is the total planned production volume of the ε-th steel bar type; T ε is the production planning time of the εth steel bar model; v δ z is the average steel bar processing rate of the zth target steel bar processing equipment in the priority ranking of the δth process; n is the total number of target steel bar processing equipment when the total number of characteristic equipment algorithm is established; When the characteristic equipment quantity algorithm is established and n is the minimum value, the value of n being the minimum value is the characteristic equipment quantity of the δth process of the steel bar of the εth steel bar model; Among them, the processing production line unit includes: Based on the total amount of characteristic equipment of several processes in several steel bar models, the target steel bar processing equipment of the total amount of characteristic equipment is reserved according to the priority order; Obtaining the position data of the target steel bar processing equipment reserved for each process in the steel bars of several steel bar models, where the position data is the coordinates of the target steel bar processing equipment; According to the processing sequence of each process in the steel bars of several steel bar models and combined with the coordinates of the target steel bar processing equipment, the equipment distance between the target steel bar processing equipment of each process in the steel bars of several steel bar models is obtained, and based on the processing sequence, the two target steel bar processing equipment with the closest equipment distance are used as the target steel bar processing equipment in the same production line, and the processing production lines of the steel bars of several steel bar models are generated.

[0019] Wherein, the fault analysis module includes a fault analysis unit; A fault analysis unit is used to produce and process several types of steel bars according to the processing production lines of several types of steel bars, collect equipment operation data of target steel bar processing equipment during the steel bar processing process, and use the equipment fault model to perform equipment fault analysis on the target steel bar processing equipment in the steel bar processing production line to obtain abnormal target processing equipment in the current cycle; Wherein, the intelligent management module includes an intelligent management unit; The intelligent management unit is used to obtain various abnormal target processing equipment in the steel bar processing plant within the current cycle, obtain various target processing equipment with the same steel bar model and process as the steel bars processed by the abnormal target processing equipment, obtain the target processing equipment with the shortest equipment distance to the abnormal target processing equipment from various target processing equipment, use it as the replacement steel bar processing equipment for the abnormal target processing equipment, transport the steel bars to be processed by the abnormal target processing equipment to the replacement steel bar processing equipment for steel bar processing, adjust the production and processing of the steel bars in the steel bar processing plant within the current cycle, and intelligently manage the steel bar processing plant.

[0020] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An intelligent management system for a tunnel engineering steel bar processing plant, characterized in that: The management system includes a fault model building module, an equipment matching analysis module, a processing production line module, a fault analysis module, and an intelligent management module; The fault model building module is used to obtain historical equipment operation records and historical fault records of the steel bar processing equipment of the steel bar processing plant, obtain historical equipment fault data from the historical fault records, and build an equipment fault model for the steel bar processing equipment; The equipment matching analysis module is used to obtain the steel bar production order data of the steel bar processing plant in the current cycle, obtain the equipment data of the steel bar processing equipment, analyze the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bars in the steel bar production order data, and obtain the target steel bar processing equipment; The processing production line module is used to obtain the production plan time and the total production plan of the steel bars, obtain the location data of the target steel bar processing equipment of the steel bars, and plan the processing production line of the steel bars; The fault analysis module is used to produce and process the steel bars according to the steel bar processing production line, collect equipment operation data of the target steel bar processing equipment during the steel bar processing, and use the equipment fault model to perform fault analysis on the target steel bar processing equipment to obtain abnormal target processing equipment; The intelligent management module is used to evaluate the different steel bar processing equipment in the steel bar processing plant, the degree of processing replacement of the abnormal target processing equipment, obtain the alternative steel bar processing equipment of the abnormal target processing equipment, adjust the production and processing of the steel bars in the steel bar processing plant in the current cycle, and intelligently manage the steel bar processing plant.

2. According to claim 1, the intelligent management system for a tunnel engineering steel bar processing plant is characterized in that: The fault model building module includes a historical data acquisition unit and a fault model building unit; The historical data acquisition unit is used to acquire historical equipment operation records of the steel bar processing equipment of the steel bar processing plant, extract historical equipment operation data from the historical equipment operation records, the historical equipment operation data including data corresponding to various equipment operation parameters of the steel bar processing equipment, acquire historical fault records of the steel bar processing equipment, extract historical equipment fault data from the historical fault records, the historical equipment fault data including data corresponding to various equipment operation parameters during the equipment fault process of the steel bar processing equipment; The fault model building unit is used to standardize various equipment operating parameters of the steel bar processing equipment to obtain standard values ​​of the various equipment operating parameters, and to build an equipment fault model based on historical equipment operation records and historical fault records of the steel bar processing equipment.

3. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 2 is characterized in that: The fault model building unit comprises: The various equipment operating parameters of the steel bar processing equipment are standardized to obtain the standard values ​​of the various equipment operating parameters, wherein the standard value of the a-th equipment operating parameter of the steel bar processing equipment is X´=(X a -X min ) / (X max -X min ), where X a is the value of the equipment operating parameter of item a of the steel bar processing equipment, X min , X max are respectively the minimum and maximum values ​​of the equipment operating parameters of item a during the operation of the steel bar processing equipment; Constructing an equipment failure model of the steel bar processing equipment, wherein the specific construction process of the equipment failure model is as follows: Obtaining a preset time window of the equipment fault model, dividing the standard values ​​of the equipment operating parameters of the steel bar processing equipment into time windows of fixed time lengths based on the historical equipment operating data and historical equipment fault data of the steel bar processing equipment, and using the standard values ​​of the equipment operating parameters of the steel bar processing equipment in each time window as input data of the equipment fault model; The input layer, hidden layer and output layer of the equipment fault model are defined, the weight matrix and bias vector of the equipment fault model are preset, the input vector is constructed based on the standard values ​​of the equipment operating parameters of the steel bar processing equipment within the time window, and the output f of the forget gate of the hidden layer in the equipment fault model is obtained. t : ， Among them, the forget gate output f t The t in W represents the current time step; f is the weight matrix of the forget gate; t-1 is the hidden state of the previous time step of the current time step; x t represents the input vector of the current time step; b f is the bias vector of the forget gate; σ is the activation function, σ(ζ)=1 / (1+e -ζ ); Get the output of the input gate at the current time step in the input layer: ， Among them, W i is the weight matrix of the input gate; b i is the bias vector of the forget gate; Get the unit candidate state C' of the current time step in the hidden layer t : ， Among them, W c is the weight matrix of the candidate state of the unit; b c is the bias vector of the candidate state of the unit; Get the unit state C of the current time step in the hidden layer t : ， Among them, C t-1 is the cell state at the previous time step; Get the output o of the output gate in the hidden layer at the current time step t : ， Among them, W o is the weight matrix of the output gate; b o is the bias vector of the output gate; Get the hidden state h of the current time step in the hidden layer t : ， The output layer of the equipment failure model uses an activation function to transform the hidden state h t , converted into the output of the equipment failure model, and the equipment failure model is trained and updated, and W in the equipment failure model is updated. f , W i , W c , W o and b f 、b i 、b c 、b o Update and obtain the equipment failure model.

4. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 1 is characterized in that: The device matching analysis module includes a data acquisition unit and a device matching analysis unit; The data acquisition unit is used to acquire the steel bar production order data of the steel bar processing plant in the current cycle, the steel bar production order data including several steel bar models of the steel bars that the steel bar processing plant plans to produce in the current cycle, and the equipment data of each steel bar processing equipment of the steel bar processing plant in the current cycle, the equipment data including data corresponding to several equipment technical parameters of the steel bar processing equipment, and processing technology data of the steel bars of the several steel bar models, the processing technology data including data corresponding to various processing technology indicators of the steel bars; The equipment matching analysis unit is used to analyze the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bars of the several steel bar models in the steel bar production order data according to the equipment data of each steel bar processing equipment, so as to obtain the target steel bar processing equipment.

5. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 4 is characterized in that: The device matching analysis unit comprises: Obtain steel bar processing equipment that processes the several steel bar models, analyze the steel bar processing equipment of the steel bar processing plant, and the equipment processing matching degree between the steel bars of the several steel bar models in the steel bar production order data, and obtain the target steel bar processing equipment, wherein the specific process of analyzing the equipment processing matching degree between the steel bar processing equipment of the steel bar processing plant and the steel bar of the αth steel bar model in the steel bar production order data is: Acquire several processes and processing industrial data of the αth steel bar model, and in combination with the equipment data of each steel bar processing equipment, acquire steel bar processing equipment to be selected for several processes of the steel bar of the αth steel bar model, record the steel bar processing equipment as each steel bar processing equipment to be selected for the several processes of the αth steel bar model, and acquire the average steel bar processing rate and average processing qualification rate of each steel bar processing equipment to be selected; Calculate the equipment matching degree value between the selected steel bar processing equipment and the several processes of the steel bar of the αth steel bar model, where the equipment matching degree value L between the βth selected steel bar processing equipment and the μth process of the steel bar of the αth steel bar model is β,μ : ， Among them, p β is the average processing qualification rate of the βth steel bar processing equipment to be selected; v β is the average steel bar processing rate of the βth steel bar processing equipment to be selected; v α,max is the maximum value of the average steel bar processing rate of several steel bar processing equipment of the αth steel bar model; α,min is the minimum value of the average steel bar processing rate of several steel bar processing equipment of the αth steel bar model; γ1 is the preset characteristic rate coefficient, γ2 is the preset characteristic qualification coefficient, γ1+γ2=1; When the device matching degree value L β,μ If the value is greater than a preset equipment matching threshold, the βth selected steel bar processing equipment is recorded as the target steel bar processing equipment for the μth process of the steel bar of the αth steel bar model.

6. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 5 is characterized in that: The processing line module includes a characteristic equipment total unit and a processing line unit; The characteristic equipment quantity unit is used to obtain target steel bar processing equipment of several steel bar models in the current cycle, and obtain the characteristic equipment quantity of various processes of several steel bar models; The processing production line unit is used to reserve the target steel bar processing equipment of the total amount of characteristic equipment according to the total amount of characteristic equipment of several processes in the several steel bar models, sort them according to priority, obtain the location data of the target steel bar processing equipment, and generate a processing production line for the steel bars of the several steel bar models.

7. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 6 is characterized in that: The characteristic equipment total amount unit includes: Obtain target steel bar processing equipment for several steel bar models in the current cycle, and obtain the total amount of characteristic equipment for each process of the steel bar models, wherein the total amount of characteristic equipment for the δth process of the steel bar model of the εth steel bar is obtained by obtaining the production plan time and total amount of production plan for the steel bar model of the εth steel bar; The specific process of obtaining the equipment matching degree value of each target steel bar processing equipment of the δth process in the steel bar of the εth steel bar model is to prioritize each target steel bar processing equipment from large to small according to the size of the equipment matching degree value, and obtain the total amount of characteristic equipment of the δth process through the characteristic equipment total amount algorithm, wherein the characteristic equipment total amount algorithm is: ， Among them, U ε,sum is the planned total production volume of the steel bar type of the εth steel bar; T ε is the production planning time of the εth steel bar model; δ z is the average steel bar processing rate of the zth target steel bar processing equipment in the priority ranking of the δth process; n is the total number of target steel bar processing equipment when the total number algorithm of the characteristic equipment is established; When the characteristic equipment quantity algorithm is established and n is the minimum value, the value of n being the minimum value at this time is the characteristic equipment quantity of the δth process of the steel bar of the εth steel bar model.

8. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 6 is characterized in that: The processing production line unit comprises: Based on the total amount of characteristic equipment of several processes in the several steel bar models, target steel bar processing equipment of the total amount of characteristic equipment is reserved according to priority; Obtaining the position data of the target steel bar processing equipment reserved for each process in the steel bars of several steel bar models, wherein the position data is the coordinates of the target steel bar processing equipment; According to the processing sequence of each process of the steel bars of the several steel bar models and combined with the coordinates of the target steel bar processing equipment, the equipment distance between the target steel bar processing equipment of each process of the steel bars of the several steel bar models is obtained, and based on the processing sequence, the two target steel bar processing equipment with the closest equipment distance are used as the target steel bar processing equipment in the same production line, and the processing production lines of the steel bars of the several steel bar models are generated.

9. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 6, characterized in that: The fault analysis module includes a fault analysis unit; The fault analysis unit is used to produce and process several types of steel bar models according to the processing production lines of the several types of steel bar models, collect equipment operation data of the target steel bar processing equipment during the steel bar processing process, and use the equipment fault model to perform equipment fault analysis on the target steel bar processing equipment in the steel bar processing production line to obtain abnormal target processing equipment in the current cycle.

10. The intelligent management system for a tunnel engineering steel bar processing plant according to claim 9, characterized in that: The intelligent management module includes an intelligent management unit; The intelligent management unit is used to obtain various abnormal target processing equipment of the steel bar processing plant in the current cycle, obtain various target processing equipment with the same steel bar model and process as the steel bars processed by the abnormal target processing equipment, obtain the target processing equipment with the shortest equipment distance to the abnormal target processing equipment from the various target processing equipment, and use it as the replacement steel bar processing equipment for the abnormal target processing equipment, transport the steel bars to be processed by the abnormal target processing equipment to the replacement steel bar processing equipment for steel bar processing, adjust the production and processing of the steel bars of the steel bar processing plant in the current cycle, and intelligently manage the steel bar processing plant.

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