CN115796610A - Comprehensive monitoring method and system for operation of branch pipe forming system and storage medium - Google Patents
Comprehensive monitoring method and system for operation of branch pipe forming system and storage medium Download PDFInfo
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Abstract
The invention discloses a comprehensive monitoring method, a comprehensive monitoring system and a storage medium for operation of a branch pipe forming system, which relate to the technical field of intelligent monitoring of equipment and comprise the following steps: acquiring all forming equipment information in a branch pipe forming system; establishing and training an operation state prediction model of the forming equipment; establishing a maintenance consumable material library; updating historical operating data of the molding equipment to obtain real-time historical operating data of the molding equipment; calculating and predicting the risk probability value of various faults of the molding equipment; judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value or not; judging whether the maintenance failure can be met in the maintenance consumable material library; and judging whether the risk probability value of the forming equipment with a certain fault is greater than a second preset value. The invention has the advantages that: the risk probability value of the fault of the forming equipment is calculated, so that the pre-pertinence response is carried out on the hidden risk in the operation of the branch pipe forming system, and the operation stability of the branch pipe forming system can be ensured.
Description
Technical Field
The invention relates to the technical field of intelligent monitoring of equipment, in particular to a comprehensive monitoring method and system for operation of a branch pipe forming system and a storage medium.
Background
The branch pipe is pulled out from the pipeline, the design for changing the direction of fluid is common in a pipeline system, for a thick-wall pipeline, a hot extrusion drawing method is generally used, in a hot extrusion drawing forming system, the branch pipe is formed and drawn by cooperation of a hydraulic system, a medium-frequency heating system and other systems, each system comprises a plurality of devices, and in order to ensure the stable operation of the branch pipe forming system, the branch pipe is important when each forming device stably operates.
However, in the prior art, a set of effective fault risk analysis and prediction aiming at each forming device in the branch pipe forming system is lacked, the maintenance and the repair are often performed aiming at the forming device when the forming device is in fault, the prediction capability aiming at the operation risk of the branch pipe forming system is lacked, the advance risk response cannot be performed aiming at the operation of the branch pipe forming system, a lot of time is consumed for line stop maintenance when the branch pipe forming system is in fault, and the support forming production is influenced.
Disclosure of Invention
In order to solve the technical problems, the technical scheme solves the problems that in the prior art, a set of effective fault risk analysis and prediction aiming at each forming device in a branch pipe forming system is lacked, maintenance is often carried out aiming at the forming device when the forming device breaks down, prediction capability aiming at the running risk of the branch pipe forming system is lacked, risk response can not be carried out aiming at the running of the branch pipe forming system in advance, and a lot of time is consumed for line stop maintenance when the branch pipe forming system breaks down, so that support forming production is influenced.
In order to achieve the purpose, the invention adopts the technical scheme that:
a comprehensive monitoring method for the operation of a branch pipe forming system comprises the following steps:
acquiring all forming equipment information in a branch pipe forming system, wherein the forming equipment information comprises historical operating data of forming equipment and historical fault information of the forming equipment;
establishing and training an operation state prediction model of the molding equipment according to historical operation data and historical fault information of the molding equipment, wherein the operation state prediction model of the molding equipment corresponds to the molding equipment in the branch pipe molding system one by one, and the operation state prediction model takes the operation data of the molding equipment as input and outputs risk probability values of various faults of the molding equipment;
determining the type and the quantity of maintenance consumables required by various fault states of the molding equipment, determining the type and the quantity of the existing maintenance consumables, and establishing a maintenance consumable library;
monitoring the operation data of all the molding equipment in the branch pipe molding system in real time, updating the historical operation data of the molding equipment, and acquiring the real-time historical operation data of the molding equipment;
inputting real-time historical operation data of the molding equipment into an operation state prediction model of the molding equipment, and calculating and predicting risk probability values of various faults of the molding equipment;
judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value, if so, judging that the molding equipment has an implicit risk of the fault, and if not, judging that the molding equipment does not have the risk of the fault;
for the fault with hidden risk, analyzing the type and quantity of maintenance consumables required for maintaining the fault state, and judging whether the maintenance consumables in a maintenance consumables library can meet the requirement for maintaining the fault, if so, not outputting, and if not, analyzing and outputting the type and quantity of the lacking maintenance consumables;
and judging whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value, if so, judging that the risk of the fault of the molding equipment is high, and outputting a molding equipment maintenance signal, otherwise, judging that the risk of the fault of the molding equipment is low, and not responding.
Preferably, the operation state prediction model of the molding equipment comprises a fault prediction formula of a plurality of molding equipment, and the fault prediction formula of the molding equipment corresponds to a plurality of types of faults which may occur to the molding equipment one by one;
the fault prediction formula expression of the molding equipment is as follows:
wherein Y = i represents the occurrence of the ith fault, P represents the probability of the occurrence of the ith fault, and M 1 ，M 2 ，
，M k ，
M n An abnormality index representing operation data associated with the i-th fault, T represents the service time of the molding equipment, and alpha and beta 1 ，
，β k ，
β n And gamma are both formula coefficients.
Preferably, the method for predicting the operating state of the training forming equipment specifically comprises the following steps:
analyzing a plurality of possible fault states of the molding equipment according to historical fault information of the molding equipment;
analyzing operational data associated with each fault condition that may occur for the molding apparatus;
establishing fault prediction formulas of a plurality of molding devices in a one-to-one correspondence mode according to a plurality of possible fault states of the molding devices;
calculating the abnormal index of the historical operating data of the molding equipment according to the historical operating data of the molding equipment, and classifying the abnormal index of the historical operating data according to whether a certain fault occurs or not;
substituting a data classification result corresponding to a certain fault state of the molding equipment into a corresponding fault prediction formula of the molding equipment, and solving a formula coefficient by using a maximum likelihood method;
and judging whether the fault prediction formulas of all the molding equipment complete the solution of the formula coefficients, if so, completing the operation state prediction model training of the molding equipment, and if not, continuing to solve the formula coefficients of the fault prediction formulas of the molding equipment.
Preferably, the calculation method of the abnormality index is:
obtaining a rated value of the operation data of the molding equipment;
obtaining historical operating data of the molding equipment and/or operating data value and duration exceeding rated values of the operating data of the molding equipment in real-time historical operating data of the molding equipment;
substituting the running data value and the time length which exceed the rated value of the running data of the molding equipment into a calculation formula of the abnormal index to calculate the historical running data of the molding equipment and/or the abnormal index of the real-time historical running data of the molding equipment;
the calculation formula of the abnormality index is as follows:
wherein M is an abnormality index, U is an operation data value exceeding a rated value of operation data of the molding apparatus in the historical operation data of the molding apparatus and/or the real-time historical operation data of the molding apparatus, and U is a value of the operation data exceeding the rated value of the operation data of the molding apparatus 0 And t is the time length exceeding the rated value of the operation data of the molding equipment in the historical operation data of the molding equipment and/or the real-time historical operation data of the molding equipment.
Preferably, the step of judging whether the maintenance of the fault in the consumable supply library can be satisfied specifically comprises the following steps:
acquiring all maintenance consumable types owned by a maintenance consumable library, judging whether all maintenance consumable types owned by the maintenance consumable library include all maintenance consumable types required for maintaining the fault state, if so, judging that the maintenance consumable types are all included, otherwise, judging that the maintenance consumable types are absent, and outputting the absent maintenance consumable types and the required quantity corresponding to the maintenance consumable types;
acquire the consumptive material quantity of the maintenance consumptive material kind that maintenance consumptive material storehouse includes, judge whether the consumptive material quantity of the maintenance consumptive material kind that maintenance consumptive material storehouse includes is greater than the consumptive material quantity of the corresponding maintenance consumptive material kind that this fault condition of maintenance needs, if, then judge that maintenance consumptive material quantity is enough, if not, then judge that maintenance consumptive material quantity is not enough, the quantity that output maintenance consumptive material quantity is not enough maintenance consumptive material kind and lacks.
Further, a comprehensive monitoring system for the operation of the branch pipe forming system is provided, which is used for realizing the comprehensive monitoring method for the operation of the branch pipe forming system, and comprises the following steps:
the processor is used for establishing and training an operation state prediction model of the molding equipment, calculating and predicting the risk probability value of various faults of the molding equipment, judging whether the risk probability value of certain faults of the molding equipment is greater than a first preset value, judging whether the maintenance fault can be met in a maintenance consumable material library and judging whether the risk probability value of certain faults of the molding equipment is greater than a second preset value;
the consumable counting module is electrically connected with the processor and is used for determining the type and the quantity of the maintenance consumables owned at present and establishing a maintenance consumable library;
the data receiving module is electrically connected with the processor and used for receiving the operating data of the molding equipment and updating the historical operating data of the molding equipment;
the storage module is electrically connected with the processor, the consumable counting module and the data receiving module, and is used for storing an operation state prediction model of the molding equipment, a maintenance consumable library, historical operation data of the molding equipment and historical fault information of the molding equipment;
and the output module is used for outputting the types and the quantity of the lacking maintenance consumables and outputting maintenance signals of the forming equipment.
Optionally, the processor is internally integrated with:
the model training unit is used for establishing and training an operation state prediction model of the molding equipment;
the calculation unit is used for calculating and predicting the risk probability value of various faults of the molding equipment;
the first judging unit is used for judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value or not;
the second judgment unit is used for judging whether the maintenance failure can be met in the maintenance consumable material library;
and the third judging unit is used for judging whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value.
Still further, a computer-readable storage medium is provided, on which a computer-readable program is stored, which, when invoked, performs the branch pipe forming system operation comprehensive monitoring method as described above.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a comprehensive monitoring scheme for the operation of a branch pipe forming system, which can realize the prediction of the operation risk of the branch pipe forming system by calculating the risk probability values of various faults of the forming equipment according to the operation data and service duration of all the forming equipment in the branch pipe forming system, can further carry out hidden trouble shooting on equipment with higher fault risk in the branch pipe forming system, can effectively avoid the abnormal operation of the branch pipe forming system caused by the fault of the forming equipment, and can effectively prevent the occurrence of forming and processing accidents.
According to the invention, by setting the first preset value, when the risk probability value of a certain fault of the forming equipment is greater than the first preset value, the forming equipment is determined to have hidden risk of the fault, and for the fault with hidden risk, maintenance consumables for dealing with the fault are prepared in advance in the scheme, so that the hidden risk in the operation of the branch pipe forming system is dealt with in advance in a targeted manner, sufficient maintenance consumables are ensured to be in an equipment troubleshooting warehouse, the condition that the maintenance consumables are insufficient when the equipment troubleshooting is carried out can be effectively prevented, the time consumed for carrying out the troubleshooting on the equipment can be effectively shortened, and the operation risk coping efficiency of the branch pipe forming system is improved.
Drawings
FIG. 1 is a block diagram of a comprehensive monitoring system for operation of a branch pipe forming system according to the present invention;
FIG. 2 is a flow chart of a comprehensive monitoring method for the operation of a branch pipe forming system in the present invention;
FIG. 3 is a flow chart of a method for training a model for predicting the operating condition of a molding apparatus according to the present invention;
FIG. 4 is a flow chart of a method of calculating an abnormality index in the present invention;
FIG. 5 is a flowchart of a method for determining whether a maintenance failure in a consumable supply library can be satisfied according to the present invention.
Detailed Description
The following description is provided to disclose the invention so as to enable any person skilled in the art to practice the invention. The preferred embodiments in the following description are given by way of example only, and other obvious variations will occur to those skilled in the art.
Referring to fig. 1, an integrated monitoring system for operation of a branch pipe forming system comprises:
the processor is used for establishing and training an operation state prediction model of the forming equipment, calculating and predicting the risk probability value of various faults of the forming equipment, judging whether the risk probability value of a certain fault of the forming equipment is greater than a first preset value, judging whether the maintenance fault can be met in a maintenance consumable material library and judging whether the risk probability value of the certain fault of the forming equipment is greater than a second preset value;
the consumable material counting module is electrically connected with the processor and is used for determining the type and the quantity of the maintenance consumable materials owned at present and establishing a maintenance consumable material library;
the data receiving module is electrically connected with the processor and used for receiving the operating data of the molding equipment and updating the historical operating data of the molding equipment;
the storage module is electrically connected with the processor, the consumable counting module and the data receiving module and is used for storing an operation state prediction model of the molding equipment, a maintenance consumable library, historical operation data of the molding equipment and historical fault information of the molding equipment;
and the output module is electrically connected with the processor and is used for outputting the types and the quantity of the lacking maintenance consumables and outputting maintenance signals of the molding equipment.
Wherein, the inside integration of treater has:
the model training unit is used for establishing and training an operation state prediction model of the molding equipment;
the calculating unit is used for calculating and predicting the risk probability value of various faults of the molding equipment;
the first judging unit is used for judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value or not;
the second judgment unit is used for judging whether the maintenance failure can be met in the maintenance consumable material library;
and the third judging unit is used for judging whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value.
The operation process of the comprehensive monitoring system for the operation of the branch pipe forming system is as follows:
the method comprises the following steps: the model training unit is used for establishing and training an operation state prediction model of the forming equipment, which corresponds to the forming equipment in the branch pipe forming system one by one, and storing the operation state prediction model of the forming equipment into the storage module;
step two: the consumable material counting module determines the type and the quantity of the current owned maintenance consumable materials and establishes a maintenance consumable material library;
step three: the data receiving module receives the operation data of the molding equipment, updates the historical operation data of the molding equipment, acquires the real-time historical operation data of the molding equipment, and stores the real-time historical operation data of the molding equipment to the storage module;
step four: the calculation unit calls an operation state prediction model of the molding equipment and real-time historical operation data of the molding equipment from the storage module, and calculates the risk probability values of various faults of the molding equipment;
step five: the first judging unit judges whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value;
step six: for the fault with the risk probability value larger than the first preset value, the second judging unit judges whether the maintenance fault can be met in the maintenance consumable material library or not, and the output module determines whether the type and the quantity of the lacking maintenance consumable materials are output or not according to the judgment result;
step seven: the third judging unit judges whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value or not, and the output module determines whether to output a molding equipment maintenance signal or not according to the judgment result.
Referring to fig. 2, further, in combination with the comprehensive monitoring system for branch pipe forming system operation, the present solution provides a comprehensive monitoring method for branch pipe forming system operation, including:
acquiring all forming equipment information in the branch pipe forming system, wherein the forming equipment information comprises historical operating data of the forming equipment and historical fault information of the forming equipment;
establishing and training an operation state prediction model of the molding equipment according to historical operation data and historical fault information of the molding equipment, wherein the operation state prediction model of the molding equipment corresponds to the molding equipment in the branch pipe molding system one by one, and the operation state prediction model takes the operation data of the molding equipment as input and outputs the risk probability value of various faults of the molding equipment;
determining the types and the number of maintenance consumables required by various fault states of the molding equipment, determining the types and the number of the maintenance consumables owned at present, and establishing a maintenance consumable library;
the method comprises the steps of monitoring the operation data of all the forming devices in a branch pipe forming system in real time, updating historical operation data of the forming devices, obtaining real-time historical operation data of the forming devices, carrying out real-time acquisition and updating on the operation data of the forming devices, and predicting the failure risk probability value of the forming devices more accurately according to the obtained real-time historical operation data of the forming devices;
inputting real-time historical operation data of the molding equipment into an operation state prediction model of the molding equipment, and calculating and predicting risk probability values of various faults of the molding equipment;
judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value, if so, judging that the molding equipment has an implicit risk of the fault, and if not, judging that the molding equipment does not have the risk of the fault;
for the fault with hidden risk, analyzing the type and quantity of maintenance consumables required for maintaining the fault state, and judging whether the maintenance consumables in a maintenance consumables library can meet the requirement for maintaining the fault, if so, not outputting, and if not, analyzing and outputting the type and quantity of the lacking maintenance consumables;
and judging whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value, if so, judging that the risk of the fault of the molding equipment is high, and outputting a molding equipment maintenance signal, otherwise, judging that the risk of the fault of the molding equipment is low, and not responding.
In the scheme, the first preset value is set to be 0.15, the value of the first preset value can be adjusted according to the actual state of the forming equipment, generally, the first preset value is not more than 0.2, when the risk probability value of the forming equipment with a certain fault is judged to be greater than the first preset value, the forming equipment is determined to have the hidden risk of the fault, and for the fault with the hidden risk, maintenance consumables for dealing with the fault are prepared in advance in the scheme, so that the purpose of pertinence dealing with the hidden risk in the operation of the branch pipe forming system in advance is realized;
in the scheme, the second preset value is set to be 0.45, the value of the second preset value can be adjusted according to the actual state of the forming equipment, generally, the second preset value is not more than 0.5, when the risk probability value of a certain fault of the forming equipment is greater than the second preset value, at the moment, the equipment is determined to have a higher risk of corresponding fault, and the forming equipment is coped with to perform corresponding fault risk troubleshooting.
The operation state prediction model of the molding equipment comprises a plurality of fault prediction formulas of the molding equipment, and the fault prediction formulas of the molding equipment correspond to a plurality of types of faults which may occur to the molding equipment one by one;
the fault prediction formula expression of the molding equipment is as follows:
wherein Y = i represents the occurrence of the ith fault, P represents the probability of the occurrence of the ith fault, and M 1 ，M 2 ，
，M k ，
M n An abnormality index representing operation data associated with the i-th fault, T represents the service time of the molding equipment, and alpha and beta 1 ，
，β k ，
β n And γ are formula coefficients.
Referring to fig. 3, the training of the operation state prediction model of the forming apparatus specifically includes the following steps:
analyzing a plurality of possible fault states of the molding equipment according to historical fault information of the molding equipment;
analyzing operational data associated with each fault condition that may occur for the molding apparatus;
establishing fault prediction formulas of a plurality of molding devices in a one-to-one correspondence mode according to a plurality of possible fault states of the molding devices;
calculating the abnormal index of the historical operating data of the molding equipment according to the historical operating data of the molding equipment, and classifying the abnormal index of the historical operating data according to whether a certain fault occurs or not;
substituting a data classification result corresponding to a certain fault state of the molding equipment into a corresponding fault prediction formula of the molding equipment, and solving a formula coefficient by using a maximum likelihood method;
and judging whether the fault prediction formulas of all the molding equipment complete the solution of the formula coefficients, if so, completing the operation state prediction model training of the molding equipment, and if not, continuing to solve the formula coefficients of the fault prediction formulas of the molding equipment.
The fault prediction formula of the forming equipment is established based on the Logistic regression model principle, and the Logistic regression model is a generalized linear regression analysis model and is commonly used in the fields of data mining, result prediction and the like;
the judgment basis for judging whether the forming equipment has a certain fault is the abnormal index of the running data related to the fault and the service duration of the forming equipment, the probability of the forming equipment having the certain fault can be calculated by substituting the abnormal index of the running data related to the fault and the service duration of the forming equipment into a regression prediction formula, and further the operation risk control of the branch pipe forming system is realized.
Referring to fig. 4, the method for calculating the abnormality index includes:
obtaining a rated value of the operation data of the molding equipment;
acquiring historical operating data of the molding equipment and/or operating data values and durations exceeding rated values of the operating data of the molding equipment in real-time historical operating data of the molding equipment;
substituting the running data value and the time length which exceed the rated value of the running data of the molding equipment into a calculation formula of the abnormal index to calculate the historical running data of the molding equipment and/or the abnormal index of the real-time historical running data of the molding equipment;
the anomaly index is calculated by the formula:
wherein M is an abnormality index, U is an operation data value exceeding a rating of operation data of the molding apparatus in the historical operation data of the molding apparatus and/or the real-time historical operation data of the molding apparatus, and U is a value of the operation data 0 And t is the time length exceeding the rated value of the operation data of the molding equipment in the historical operation data of the molding equipment and/or the real-time historical operation data of the molding equipment.
In the operation process of the molding equipment, when the operation data is abnormal, the larger the difference value of the operation data exceeding the rated value is, the longer the abnormal operation time is, the higher the risk of the fault is, therefore, the product of the excess amount of all the abnormal operation data and the abnormal operation time length in the historical operation process of the molding equipment is accumulated by the scheme to be used as the abnormal index of the molding equipment.
Referring to fig. 5, the step of determining whether the maintenance of the fault in the consumable supply library can be satisfied specifically includes the following steps:
acquiring all maintenance consumable types owned by a maintenance consumable library, judging whether all maintenance consumable types owned by the maintenance consumable library include all maintenance consumable types required for maintaining the fault state, if so, judging that the maintenance consumable types are all included, otherwise, judging that the maintenance consumable types are absent, and outputting the absent maintenance consumable types and the required quantity corresponding to the maintenance consumable types;
acquire the consumptive material quantity of the maintenance consumptive material kind that maintenance consumptive material storehouse includes, judge whether the consumptive material quantity of the maintenance consumptive material kind that maintenance consumptive material storehouse includes is greater than the consumptive material quantity of the corresponding maintenance consumptive material kind that this fault condition of maintenance needs, if, then judge that maintenance consumptive material quantity is enough, if not, then judge that maintenance consumptive material quantity is not enough, the quantity that output maintenance consumptive material quantity is not enough maintenance consumptive material kind and lacks.
Through screening in advance and preparing to the maintenance consumptive material of trouble, can effectively guarantee that the maintenance consumptive material can all hidden risks of effectual reply branch pipe forming system operation in-process in the maintenance consumptive material storehouse, only carry out the maintenance consumptive material to hidden risk and prepare simultaneously, can realize the pertinence accurate preparation of maintenance consumptive material, reduce the reserve volume of maintenance consumptive material, reduce maintenance consumptive material cost.
Furthermore, the scheme also provides a computer readable storage medium, wherein a computer readable program is stored on the computer readable storage medium, and when the computer readable program is called, the comprehensive monitoring method for the operation of the branch pipe forming system is executed;
it is understood that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, a magnetic tape; optical media such as DVD; or semiconductor media such as solid state disk SolidStateDisk, SSD, etc.
In conclusion, the invention has the advantages that: by calculating the risk probability values of various faults of the forming equipment according to the operation data and service duration of all the forming equipment in the branch pipe forming system, the pre-pertinence response can be realized for hidden risks in the operation of the branch pipe forming system, and the operation stability of the branch pipe forming system is ensured.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the invention, but that various changes and modifications may be made without departing from the spirit and scope of the invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. A comprehensive monitoring method for operation of a branch pipe forming system is characterized by comprising the following steps:
acquiring all forming equipment information in a branch pipe forming system, wherein the forming equipment information comprises historical operating data of forming equipment and historical fault information of the forming equipment;
establishing and training an operation state prediction model of the molding equipment according to historical operation data and historical fault information of the molding equipment, wherein the operation state prediction model of the molding equipment corresponds to the molding equipment in the branch pipe molding system one by one, and the operation state prediction model takes the operation data of the molding equipment as input and outputs risk probability values of various faults of the molding equipment;
determining the types and the number of maintenance consumables required by various fault states of the molding equipment, determining the types and the number of the maintenance consumables owned at present, and establishing a maintenance consumable library;
monitoring the operation data of all the molding equipment in the branch pipe molding system in real time, updating the historical operation data of the molding equipment, and acquiring the real-time historical operation data of the molding equipment;
inputting real-time historical operation data of the molding equipment into an operation state prediction model of the molding equipment, and calculating and predicting risk probability values of various faults of the molding equipment;
judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value, if so, judging that the molding equipment has an implicit risk of the fault, and if not, judging that the molding equipment does not have the risk of the fault;
for the fault with hidden risk, analyzing the type and quantity of maintenance consumables required for maintaining the fault state, and judging whether the maintenance consumables in a maintenance consumables library can meet the requirement for maintaining the fault, if so, not outputting, and if not, analyzing and outputting the type and quantity of the lacking maintenance consumables;
and judging whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value, if so, judging that the risk of the fault of the molding equipment is high, and outputting a molding equipment maintenance signal, otherwise, judging that the risk of the fault of the molding equipment is low, and not responding.
2. The comprehensive monitoring method for the operation of the branch pipe forming system according to claim 1, wherein the operation state prediction model of the forming equipment comprises fault prediction formulas of a plurality of forming equipment, and the fault prediction formulas of the forming equipment correspond to a plurality of faults which may occur to the forming equipment one by one;
the fault prediction formula expression of the molding equipment is as follows:
in the formula (I), the compound is shown in the specification,
representing the occurrence of the ith fault, P representing the probability of the occurrence of the ith fault,
an anomaly index representing operational data associated with the ith fault,
represents the length of service time of the molding equipment,
are all formula coefficients.
3. The comprehensive monitoring method for the operation of the branch pipe forming system according to claim 2, wherein the step of training the operation state prediction model of the forming equipment specifically comprises the following steps:
analyzing a plurality of possible fault states of the molding equipment according to historical fault information of the molding equipment;
analyzing operational data associated with each fault condition that may occur for the molding apparatus;
establishing fault prediction formulas of a plurality of molding devices in one-to-one correspondence according to a plurality of possible fault states of the molding devices;
calculating the abnormal index of the historical operating data of the molding equipment according to the historical operating data of the molding equipment, and classifying the abnormal index of the historical operating data according to whether a certain fault occurs or not;
substituting a data classification result corresponding to a certain fault state of the molding equipment into a corresponding fault prediction formula of the molding equipment, and solving a formula coefficient by using a maximum likelihood method;
and judging whether the fault prediction formulas of all the molding equipment complete the solution of the formula coefficients, if so, completing the operation state prediction model training of the molding equipment, and if not, continuing to solve the formula coefficients of the fault prediction formulas of the molding equipment.
4. The comprehensive monitoring method for the operation of the branch pipe forming system according to claim 3, wherein the abnormality index is calculated by the following method:
obtaining a rated value of the operation data of the molding equipment;
obtaining historical operating data of the molding equipment and/or operating data value and duration exceeding rated values of the operating data of the molding equipment in real-time historical operating data of the molding equipment;
substituting the running data value and the time length which exceed the rated value of the running data of the molding equipment into a calculation formula of the abnormal index to calculate the historical running data of the molding equipment and/or the abnormal index of the real-time historical running data of the molding equipment;
the calculation formula of the abnormality index is as follows:
in the formula (I), the compound is shown in the specification,
is the index of the abnormality,
for operating data values in the historical operating data of the molding machine and/or in the real-time historical operating data of the molding machine that exceed the rated values of the operating data of the molding machine,
for the nominal values of the operating data of the molding apparatus,
the time length of the historical operating data of the molding equipment and/or the real-time historical operating data of the molding equipment exceeding the rated value of the operating data of the molding equipment is obtained.
5. The method for comprehensively monitoring the operation of the branch pipe forming system according to claim 1, wherein the step of judging whether the maintenance of the fault in the maintenance consumable library can be met specifically comprises the following steps:
acquiring all maintenance consumable types owned by a maintenance consumable library, judging whether all maintenance consumable types owned by the maintenance consumable library include all maintenance consumable types required for maintaining the fault state, if so, judging that the maintenance consumable types are all included, otherwise, judging that the maintenance consumable types are absent, and outputting the absent maintenance consumable types and the required quantity corresponding to the maintenance consumable types;
acquire the consumptive material quantity of the maintenance consumptive material kind that maintenance consumptive material storehouse includes, judge whether the consumptive material quantity of the maintenance consumptive material kind that maintenance consumptive material storehouse includes is greater than the consumptive material quantity of the corresponding maintenance consumptive material kind that this fault condition of maintenance needs, if, then judge that maintenance consumptive material quantity is enough, if not, then judge that maintenance consumptive material quantity is not enough, the quantity that output maintenance consumptive material quantity is not enough maintenance consumptive material kind and lacks.
6. An integrated monitoring system for branch pipe forming system operation, which is used for realizing the integrated monitoring method for branch pipe forming system operation as claimed in any one of claims 1-5, and is characterized by comprising the following steps:
the processor is used for establishing and training an operation state prediction model of the molding equipment, calculating and predicting the risk probability value of various faults of the molding equipment, judging whether the risk probability value of certain faults of the molding equipment is greater than a first preset value, judging whether the maintenance fault can be met in a maintenance consumable material library and judging whether the risk probability value of certain faults of the molding equipment is greater than a second preset value;
the consumable counting module is electrically connected with the processor and is used for determining the type and the quantity of the maintenance consumables owned at present and establishing a maintenance consumable library;
the data receiving module is electrically connected with the processor and used for receiving the operating data of the molding equipment and updating the historical operating data of the molding equipment;
the storage module is electrically connected with the processor, the consumable counting module and the data receiving module, and is used for storing an operation state prediction model of the molding equipment, a maintenance consumable library, historical operation data of the molding equipment and historical fault information of the molding equipment;
and the output module is used for outputting the types and the quantity of the lacking maintenance consumables and outputting maintenance signals of the forming equipment.
7. The comprehensive branch pipe forming system operation monitoring system according to claim 6, wherein the processor is integrated with:
the model training unit is used for establishing and training an operation state prediction model of the molding equipment;
the calculation unit is used for calculating and predicting the risk probability value of various faults of the molding equipment;
the first judging unit is used for judging whether the risk probability value of a certain fault of the molding equipment is greater than a first preset value or not;
the second judgment unit is used for judging whether the maintenance failure can be met in the maintenance consumable material library;
and the third judging unit is used for judging whether the risk probability value of a certain fault of the molding equipment is greater than a second preset value.
8. A computer-readable storage medium having a computer-readable program stored thereon, wherein the computer-readable program, when invoked, performs a method of integrated monitoring of the operation of a pipe branch forming system according to any one of claims 1-5.
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