A water conservancy project operation supervision system and method based on digital twin technology

Abstract

The present invention relates to the technical field of water conservancy project operation supervision, specifically a water conservancy project operation supervision system and method based on digital twin technology, in which the risk topology area analysis module in the system is based on the connection relationship of each working equipment in the water conservancy project to be tested and the instruction call coordination equipment of each working equipment, combined with the failure time distribution relationship of each working equipment in the historical data, to build a risk equipment topology chain corresponding to each risk equipment, and generate a risk topology area corresponding to each risk equipment topology chain. The present invention realizes the locking of risk equipment machines and their corresponding risk equipment topology chains through an abnormal state dynamic association dictionary, and completes the mapping of the risk topology area corresponding to the risk equipment topology chain on the corresponding water conservancy project digital twin model; at the same time, according to the location distribution of the risk topology area, each risk topology area is fused and determined to obtain an inspection object set and an inspection object execution priority sequence.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project operation supervision, and specifically to a water conservancy project operation supervision system and method based on digital twin technology. Background Art

[0002] A digital twin is a virtual entity that integrates multi-source information such as physical models, sensor data, and operation history. In the field of water conservancy, digital twin technology can construct a holographic digital mirror of the water conservancy system, including but not limited to rivers, lakes, reservoirs, hydropower stations, etc., providing unprecedented visualization, quantification and intelligent support for water conservancy management.

[0003] In the existing water conservancy project operation supervision system based on digital twin technology, the sensors of the working equipment in the water conservancy project are often bound to the digital twin model of the water conservancy project through digital twin technology, and the sensor monitoring data is presented in real time on the visual interface of the digital twin model. When the sensor data is abnormal, the working equipment to which the abnormal sensor belongs is located and inspection tasks are arranged. This method has major defects and does not take into account the chain effect between the working equipment of the water conservancy project, as well as the problem of arranging inspection priorities when multiple fault points occur at the same time. Summary of the invention

[0004] The purpose of the present invention is to provide a water conservancy project operation supervision system and method based on digital twin technology to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a water conservancy project operation supervision method based on digital twin technology, the method comprising the following steps:

[0006] S1. Based on the architectural drawings of the water conservancy project, a spatial three-dimensional model of the water conservancy project to be tested is constructed; the distribution positions of various working equipment in the water conservancy project to be tested are obtained, and a mapping area of ​​the distribution positions of various working equipment in the spatial three-dimensional model of the water conservancy project to be tested is constructed, and the obtained mapping area is marked and the working equipment information is bound to generate a digital twin model of the water conservancy project to be tested;

[0007] S2. Based on the sensors built into each working equipment in the water conservancy project to be tested, the operating status of the corresponding working equipment is monitored in real time, and the monitoring results of each sensor in the water conservancy project to be tested are received in real time through the Internet of Things, and abnormal monitoring results are screened out, and a dynamic association dictionary of abnormal status is constructed, and the working equipment corresponding to each element in the dynamic association dictionary of abnormal status is regarded as a risk device;

[0008] S3. Based on the connection relationship of each working equipment in the water conservancy project to be tested and the instruction call coordination equipment of each working equipment, combined with the failure time distribution relationship of each working equipment in the historical data, a risk equipment topology chain corresponding to each risk equipment is constructed, and a risk topology area corresponding to each risk equipment topology chain is generated;

[0009] S4. Based on the location of the risk topology area, each risk topology area is fused and judged to generate an inspection object set; based on the data information of the risk topology area corresponding to each element in the inspection object set, an inspection object execution priority sequence is constructed, and the constructed inspection object execution priority sequence is fed back to the person in charge of the water conservancy project to be tested;

[0010] S5. During the inspection according to the inspection object execution priority, the abnormal state dynamic association dictionary, the inspection object set and the inspection object execution priority sequence are dynamically updated based on the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things.

[0011] Furthermore, the working equipment information includes the number of the corresponding working equipment and the numbers corresponding to each built-in sensor; the abnormal monitoring result is the sensor monitoring result where the corresponding data does not belong to the preset numerical range of the corresponding sensor; the abnormal state dynamic association dictionary includes multiple data mapping pairs, each data mapping pair corresponds to an abnormal monitoring result, the first parameter in the data mapping pair is the collection time corresponding to the corresponding abnormal monitoring result, and the second parameter in the data mapping pair is the working equipment number corresponding to the corresponding abnormal monitoring result.

[0012] Furthermore, the instruction calling collaborative device of the working device is all the working devices that need to call the historical working instructions of the corresponding working device or collect data with built-in sensors when generating the working instruction; the instruction calling collaborative device of the working device is obtained by querying the preset form of the database;

[0013] The method for constructing a risk device topology chain corresponding to each risk device in step S3 comprises the following steps:

[0014] S31, obtaining the connection relationship of each working device in the water conservancy project to be tested and the instruction calling collaborative device of each working device; constructing a device topology association set corresponding to each working device; the device topology association set includes the working devices connected to the corresponding working devices in the water conservancy project to be tested, and the instruction calling collaborative devices of the corresponding working devices;

[0015] S32, obtain the failure time distribution relationship of each working device in the historical data, and r Work equipment m The starting time of the fault is recorded as T（r，m） ; Get the first r Work equipment m The set of faulty coordinated devices corresponding to the fault is recorded as X （r，m） , X （r，m） Each element in corresponds to a fault start time, and X （r，m） The fault start time corresponding to each element in T （r，m） The interval between the two is less than or equal to the preset interval; r The union of the faulty coordination device sets corresponding to each fault of each working device is recorded as r Comprehensive coordination set of faults of working equipment;

[0016] S33, obtain the r The intersection of the device topology association set and the fault comprehensive coordination set of the working devices is recorded as Ir ; Construct the r The working equipment is respectively Ir The device topology relationship between the various elements in the r Work equipment and Ir Middle a The device topology relationship between the elements is recorded as G Ar→A{Ir，a} ,in, Ar Indicates r The number of the working equipment; A {Ir, a} express Ir Middle a The working equipment number corresponding to each element;

[0017] S34, construct the abnormal state dynamic association dictionary n The risk device topology chain of the risk device corresponding to the element is recorded as Dn ; Dn The starting chain node in the abnormal state dynamic association dictionary is n The element corresponds to the number of the working equipment; the chain node with the smallest number of continuous chain nodes at the corresponding position in the risk equipment topology chain from the starting chain node position is recorded as b +1 level chain node, bIndicates the number of continuous chain nodes at which the number of continuous chain nodes at the corresponding position in the risk device topology chain is the smallest from the starting chain node position; the next-level chain node connected to each chain node in the risk device topology chain is a working device that has a device topology association relationship with the working device corresponding to the corresponding chain node; the link pointing relationship between two adjacent connected chain nodes in the risk device topology chain is the same as the arrow pointing relationship in the device topology association relationship formed by the corresponding devices of the corresponding chain nodes;

[0018] In the process of generating the risk topology area corresponding to each risk equipment topology chain, the distribution positions of the working equipment corresponding to each chain node in each risk equipment topology chain are obtained in the digital twin model of the water conservancy project to be tested, and the area with the largest area enclosed by connecting the distribution positions of each chain node is recorded as the risk topology area corresponding to the corresponding risk equipment topology chain.

[0019] When the present invention constructs the risk equipment topological chain corresponding to the risk equipment, the possible correlation influence of the monitoring data of different working equipment is taken into consideration (the damage of the working equipment may affect the working status of the working equipment connected to it. At the same time, for the remaining working equipment that needs to call the sensor monitoring data in the damaged working equipment, the deviation of the called data will cause the subsequent analysis results of the equipment that calls the data to also produce large errors. When subsequent inspections are required, the working equipment that calls the data also needs to be included in the inspection objects).

[0020] Furthermore, the method of generating the inspection object set in step S4 includes the following steps:

[0021] S401, obtaining a risk topology area of ​​a risk device corresponding to each element in the abnormal state dynamic association dictionary;

[0022] S402: record the risk topology area of ​​any risk device as RGC , get the value except RGC Other differences RGC The array of risk topological areas containing risky equipment in the intersection area is recorded as RGC The corresponding set of fusion candidate objects;

[0023] like RGC If the corresponding fusion candidate set is not an empty set, then RGC The corresponding fusion candidate objects are concentrated with RGC The element with the largest intersection area is RGC The fusion object will RGC The union area with the corresponding fusion object is used as a new risk topology area, and the two risk topology areas before the fusion of the new risk topology area are deleted, and the process jumps to S403; if RGCIf the corresponding fusion candidate object set is an empty set, jump to S403;

[0024] S403: If the fusion candidate object sets corresponding to the obtained risk topology areas are all empty sets, the set consisting of the obtained risk topology areas is used as the inspection object set, and each element in the inspection object set corresponds to a risk topology area;

[0025] If the fusion candidate object sets corresponding to the obtained risk topology regions are not empty sets, the sets consisting of the obtained risk topology regions are transmitted to S402 to repeat the corresponding operation steps.

[0026] When generating the inspection object set in the present invention, the risk topology area is fused and judged. This is to take into account the phenomenon that different risk topology areas may have overlapping areas. In this case, if no fusion is performed, during the inspection process, the inspection equipment or inspection personnel may need to repeatedly walk around in the same area, resulting in low inspection efficiency and poor timeliness of the inspection results.

[0027] Furthermore, the method of constructing the inspection object execution priority sequence in step S4 includes the following steps:

[0028] S411, obtaining the inspection object set and data information of the risk topology area corresponding to each element in the inspection object set;

[0029] S412, calculate the inspection object concentration k The calculation formula for the execution priority evaluation coefficient corresponding to each element is as follows:

[0030] P k =SA k ·[NR k / NC k +RP k ]

[0031] in, P k Indicates the inspection object concentration k The execution priority evaluation coefficient corresponding to each element; S k Indicates the inspection object concentration k The area of ​​the corresponding risk topology region in the data information of the risk topology region corresponding to each element; NR k Indicates the inspection object concentration k The total number of risky devices in the corresponding risky topology area in the data information of the risky topology area corresponding to each element; NCk Indicates the inspection object concentration k In the data information of the risk topology area corresponding to each element, the total number of chain nodes in the risk device topology chain corresponding to each risk device in the corresponding risk topology area; RP k Indicates the inspection object concentration k In the data information of the risk topology area corresponding to each element, the ratio of the maximum area enclosed by the risk devices connected to each other in the corresponding risk topology area to the area of ​​the corresponding risk topology area;

[0032] S413 , sorting the elements in the inspection object set in descending order of execution priority evaluation coefficients to obtain an inspection object execution priority sequence.

[0033] Furthermore, in the process of dynamically updating the abnormal state dynamic association dictionary, the inspection object execution priority is executed during the inspection process, and the monitoring results of each sensor in the water conservancy project to be tested are received in real time through the Internet of Things, and the screened new abnormal monitoring results are added to the abnormal state dynamic association dictionary corresponding to the inspection object execution priority sequence executed at the current time; during the inspection process, the corresponding elements of the inspected risk equipment in the abnormal state dynamic association dictionary are deleted;

[0034] In the process of dynamically updating the inspection object set, a set of risk devices corresponding to the newly added elements in the abnormal state dynamic association dictionary is obtained, which is recorded as the updated device summary set; the risk topology area corresponding to each element in the updated device summary set is obtained; the set of unexecuted inspection objects corresponding to the inspection object execution priority sequence executed at the current time is obtained, which is recorded as the dynamic object summary set; based on the position of the risk topology area, each risk topology area in the union of the updated device summary set and the dynamic object summary set is fused and determined to generate a dynamically updated inspection object set;

[0035] In the process of dynamically updating the inspection object execution priority sequence, the inspection object execution priority sequence fragment that has not been executed at the current time is obtained; the mapping element of each inspection object in the inspection object set after dynamic update in the obtained inspection object execution priority sequence fragment is obtained; the intersection of the risk topology area corresponding to the inspection object and the risk topology area corresponding to the corresponding mapping object is equal to the risk topology area corresponding to the corresponding inspection object; each inspection object in the inspection object execution priority sequence fragment that has not been executed at the current time is replaced with the mapping element of the corresponding inspection object in the inspection object set after dynamic update to obtain the inspection object execution priority sequence after dynamic update; extract the set consisting of elements in the inspection object set after dynamic update that do not belong to the inspection object execution priority sequence fragment that has not been executed at the current time and record it as the inspection object set to be updated; after the inspection object set to be updated is executed as the inspection object execution priority sequence fragment that has not been executed at the current time, the analysis data when a new inspection object execution priority sequence is generated.

[0036] A water conservancy project operation supervision system based on digital twin technology, the system comprising: a twin model construction module, an abnormal dynamic association analysis module, a risk topology area analysis module, an operation supervision feedback module and a data dynamic update management module.

[0037] The twin model construction module builds a spatial three-dimensional model of the water conservancy project to be tested based on the architectural drawings of the water conservancy project; obtains the distribution positions of various working equipment in the water conservancy project to be tested, constructs a mapping area of ​​the distribution positions of various working equipment in the spatial three-dimensional model of the water conservancy project to be tested, and marks the obtained mapping area and binds the working equipment information to generate a digital twin model of the water conservancy project to be tested;

[0038] The abnormal dynamic association analysis module monitors the operating status of the corresponding working equipment in real time based on the sensors built into each working equipment in the water conservancy project to be tested, receives the monitoring results of each sensor in the water conservancy project to be tested in real time through the Internet of Things, and screens out the abnormal monitoring results, constructs an abnormal state dynamic association dictionary, and regards the working equipment corresponding to each element in the abnormal state dynamic association dictionary as a risk device;

[0039] The risk topology region analysis module constructs a risk device topology chain corresponding to each risk device based on the connection relationship of each working device in the water conservancy project to be tested and the instruction call coordination device of each working device, combined with the failure time distribution relationship of each working device in the historical data, and generates a risk topology region corresponding to each risk device topology chain;

[0040] The operation supervision feedback module performs fusion judgment on each risk topology area based on the location of the risk topology area to generate an inspection object set; constructs an inspection object execution priority sequence based on the data information of the risk topology area corresponding to each element in the inspection object set, and feeds back the constructed inspection object execution priority sequence to the person in charge of the water conservancy project to be tested;

[0041] The data dynamic update management module performs inspections according to the inspection object execution priority, and dynamically updates the abnormal state dynamic association dictionary, the inspection object set and the inspection object execution priority sequence based on the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things.

[0042] Furthermore, the data dynamic update management module includes an abnormal state dynamic association dictionary update unit, an inspection object set update unit and an inspection object execution priority sequence update unit.

[0043] The abnormal state dynamic association dictionary updating unit dynamically updates the abnormal state dynamic association dictionary in the process of performing inspection according to the inspection object execution priority, based on the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things;

[0044] The inspection object set updating unit dynamically updates the inspection object set in accordance with the inspection object execution priority during the inspection process, based on the monitoring results of each sensor in the water conservancy project to be tested and the update results of the abnormal state dynamic association dictionary received in real time by the Internet of Things;

[0045] The inspection object execution priority sequence update unit dynamically updates the inspection object execution priority sequence in the process of performing inspections according to the inspection object execution priority, based on the real-time reception of monitoring results of each sensor in the water conservancy project to be tested by the Internet of Things, the abnormal state dynamic association dictionary, and the update results of the inspection object set.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention locks the risk equipment and its corresponding risk equipment topology chain through the abnormal state dynamic association dictionary, and completes the mapping of the risk topology area corresponding to the risk equipment topology chain on the corresponding water conservancy project digital twin model; at the same time, according to the location distribution of the risk topology area, each risk topology area is fused and judged to obtain the inspection object set and the inspection object execution priority sequence, and during the inspection execution process, the abnormal state dynamic association dictionary, the inspection object set and the inspection object execution priority sequence are dynamically updated to achieve effective supervision of the operation of the water conservancy project. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 It is a structural schematic diagram of a water conservancy project operation supervision system based on digital twin technology of the present invention;

[0049] Figure 2 It is a flow chart of a method for supervising operation of a water conservancy project based on digital twin technology according to the present invention. DETAILED DESCRIPTION

[0050] 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.

[0051] See also Figure 1 The present invention provides a technical solution: a water conservancy project operation supervision system based on digital twin technology, the system comprising: a twin model construction module, an abnormal dynamic association analysis module, a risk topology area analysis module, an operation supervision feedback module and a data dynamic update management module,

[0052] The twin model construction module builds a spatial three-dimensional model of the water conservancy project to be tested based on the architectural drawings of the water conservancy project; obtains the distribution positions of various working equipment in the water conservancy project to be tested, constructs a mapping area of ​​the distribution positions of various working equipment in the spatial three-dimensional model of the water conservancy project to be tested, and marks the obtained mapping area and binds the working equipment information to generate a digital twin model of the water conservancy project to be tested;

[0053] The abnormal dynamic association analysis module monitors the operating status of the corresponding working equipment in real time based on the sensors built into each working equipment in the water conservancy project to be tested, receives the monitoring results of each sensor in the water conservancy project to be tested in real time through the Internet of Things, and screens out the abnormal monitoring results, constructs an abnormal state dynamic association dictionary, and regards the working equipment corresponding to each element in the abnormal state dynamic association dictionary as a risk device;

[0054] The risk topology region analysis module constructs a risk device topology chain corresponding to each risk device based on the connection relationship of each working device in the water conservancy project to be tested and the instruction call coordination device of each working device, combined with the failure time distribution relationship of each working device in the historical data, and generates a risk topology region corresponding to each risk device topology chain;

[0055] The operation supervision feedback module performs fusion judgment on each risk topology area based on the location of the risk topology area to generate an inspection object set; constructs an inspection object execution priority sequence based on the data information of the risk topology area corresponding to each element in the inspection object set, and feeds back the constructed inspection object execution priority sequence to the person in charge of the water conservancy project to be tested;

[0056] The data dynamic update management module includes an abnormal state dynamic association dictionary update unit, an inspection object set update unit and an inspection object execution priority sequence update unit.

[0057] The abnormal state dynamic association dictionary updating unit dynamically updates the abnormal state dynamic association dictionary in the process of performing inspection according to the inspection object execution priority, based on the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things;

[0058] The inspection object set updating unit dynamically updates the inspection object set in accordance with the inspection object execution priority during the inspection process, based on the monitoring results of each sensor in the water conservancy project to be tested and the update results of the abnormal state dynamic association dictionary received in real time by the Internet of Things;

[0059] The inspection object execution priority sequence update unit dynamically updates the inspection object execution priority sequence in the process of performing inspections according to the inspection object execution priority, based on the Internet of Things receiving in real time the monitoring results of each sensor in the water conservancy project to be tested, the abnormal state dynamic association dictionary, and the update results of the inspection object set.

[0060] like Figure 2 As shown, a water conservancy project operation supervision method based on digital twin technology includes the following steps:

[0061] S1. Based on the architectural drawings of the water conservancy project, a spatial three-dimensional model of the water conservancy project to be tested is constructed; the distribution positions of various working equipment in the water conservancy project to be tested are obtained, and a mapping area of ​​the distribution positions of various working equipment in the spatial three-dimensional model of the water conservancy project to be tested is constructed, and the obtained mapping area is marked and the working equipment information is bound to generate a digital twin model of the water conservancy project to be tested;

[0062] The working equipment information includes the serial number of the corresponding working equipment and serial numbers corresponding to each built-in sensor.

[0063] S2. Based on the sensors built into each working equipment in the water conservancy project to be tested, the operating status of the corresponding working equipment is monitored in real time, and the monitoring results of each sensor in the water conservancy project to be tested are received in real time through the Internet of Things, and abnormal monitoring results are screened out, and a dynamic association dictionary of abnormal status is constructed, and the working equipment corresponding to each element in the dynamic association dictionary of abnormal status is regarded as a risk device;

[0064] The abnormal monitoring result is a sensor monitoring result whose corresponding data does not belong to the preset numerical range of the corresponding sensor; the abnormal state dynamic association dictionary includes multiple data mapping pairs, each data mapping pair corresponds to an abnormal monitoring result, the first parameter in the data mapping pair is the collection time corresponding to the corresponding abnormal monitoring result, and the second parameter in the data mapping pair is the working equipment number corresponding to the corresponding abnormal monitoring result.

[0065] S3. Based on the connection relationship of each working equipment in the water conservancy project to be tested and the instruction call coordination equipment of each working equipment, combined with the failure time distribution relationship of each working equipment in the historical data, a risk equipment topology chain corresponding to each risk equipment is constructed, and a risk topology area corresponding to each risk equipment topology chain is generated;

[0066] The instruction calling collaborative device of the working device is all the working devices that need to call the historical working instructions of the corresponding working device or collect data with built-in sensors when generating the working instructions; the instruction calling collaborative device of the working device is obtained by querying the preset form of the database;

[0067] The method for constructing a risk device topology chain corresponding to each risk device in step S3 comprises the following steps:

[0068] S31, obtaining the connection relationship of each working device in the water conservancy project to be tested and the instruction calling collaborative device of each working device; constructing a device topology association set corresponding to each working device; the device topology association set includes the working devices connected to the corresponding working devices in the water conservancy project to be tested, and the instruction calling collaborative devices of the corresponding working devices;

[0069] S32, obtain the failure time distribution relationship of each working device in the historical data, and r Work equipment m The starting time of the fault is recorded as T （r，m） ; Get the first r Work equipment m The set of faulty coordinated devices corresponding to the fault is recorded as X （r，m） , X （r，m） Each element in corresponds to a fault start time, and X （r，m） The fault start time corresponding to each element in T （r，m） The interval between the two is less than or equal to the preset interval; r The union of the faulty coordination device sets corresponding to each fault of each working device is recorded as rComprehensive coordination set of faults of working equipment;

[0070] S33, obtain the r The intersection of the device topology association set and the fault comprehensive coordination set of the working devices is recorded as Ir ; Construct the r The working equipment is respectively Ir The device topology relationship between the various elements in the r Work equipment and Ir Middle a The device topology relationship between the elements is recorded as G Ar→A{Ir，a} ,in, Ar Indicates r The number of the working equipment; A {Ir, a} express Ir Middle a The working equipment number corresponding to each element;

[0071] S34, construct the abnormal state dynamic association dictionary n The risk device topology chain of the risk device corresponding to the element is recorded as Dn ; Dn The starting chain node in the abnormal state dynamic association dictionary is n The element corresponds to the number of the working equipment; the chain node with the smallest number of continuous chain nodes at the corresponding position in the risk equipment topology chain from the starting chain node position is recorded as b +1 level chain node, b Indicates the number of continuous chain nodes at which the number of continuous chain nodes at the corresponding position in the risk device topology chain is the smallest from the starting chain node position; the next-level chain node connected to each chain node in the risk device topology chain is a working device that has a device topology association relationship with the working device corresponding to the corresponding chain node; the link pointing relationship between two adjacent connected chain nodes in the risk device topology chain is the same as the arrow pointing relationship in the device topology association relationship formed by the corresponding devices of the corresponding chain nodes;

[0072] In this embodiment, the next-level chain node connected to each chain node in the risk device topology chain may be one or more, or may not exist;

[0073] In this embodiment, since the link pointing relationship between two adjacent connected chain nodes in the risk device topology chain is the same as the arrow pointing relationship in the device topology association relationship formed by the corresponding devices of the corresponding chain nodes, if the device topology association relationship between the two working devices A and B includes two arrow pointing relationships at the same time and the arrow pointing relationship in the device topology association relationship between the two working devices A and B in the two device topology association relationships is opposite, then the link pointing relationship between the two chain nodes A and B in the constructed risk device topology chain is bidirectional (bidirectional arrow);

[0074] If the device topology association relationship between two working devices A and B includes one at the same time, the link direction between the two chain nodes A and B in the constructed risk device topology chain is unidirectional (possibly "→" or "←").

[0075] Since there may be multiple elements in the intersection Ir of the device topology association set of the rth working device and the comprehensive fault coordination set, there may be multiple branches in the constructed risk device topology chain, and the same chain node where multiple branches intersect may have multiple situations based on the distances from each branch to the initial chain node position. Therefore, the chain node with the smallest number of continuous chain nodes at the corresponding position from the starting chain node position in the risk device topology chain is used as the reference basis for chain node classification, so that each chain node can be accurately located.

[0076] In the process of generating the risk topology area corresponding to each risk equipment topology chain, the distribution positions of the working equipment corresponding to each chain node in each risk equipment topology chain are obtained in the digital twin model of the water conservancy project to be tested, and the area with the largest area enclosed by connecting the distribution positions of each chain node is recorded as the risk topology area corresponding to the corresponding risk equipment topology chain.

[0077] S4. Based on the location of the risk topology area, each risk topology area is fused and judged to generate an inspection object set; based on the data information of the risk topology area corresponding to each element in the inspection object set, an inspection object execution priority sequence is constructed, and the constructed inspection object execution priority sequence is fed back to the person in charge of the water conservancy project to be tested;

[0078] The method for generating the inspection object set in step S4 comprises the following steps:

[0079] S401, obtaining a risk topology area of ​​a risk device corresponding to each element in the abnormal state dynamic association dictionary;

[0080] S402: record the risk topology area of ​​any risk device as RGC , get the value except RGC Other differences RGC The array of risk topological areas containing risky equipment in the intersection area is recorded as RGC The corresponding set of fusion candidate objects;

[0081] like RGC If the corresponding fusion candidate set is not an empty set, then RGC The corresponding fusion candidate objects are concentrated with RGC The element with the largest intersection area is RGC The fusion object will RGC The union area with the corresponding fusion object is used as a new risk topology area, and the two risk topology areas before the fusion of the new risk topology area are deleted, and the process jumps to S403; if RGC If the corresponding fusion candidate object set is an empty set, jump to S403;

[0082] S403: If the fusion candidate object sets corresponding to the obtained risk topology areas are all empty sets, the set consisting of the obtained risk topology areas is used as the inspection object set, and each element in the inspection object set corresponds to a risk topology area;

[0083] If the fusion candidate object sets corresponding to the obtained risk topology regions are not empty sets, the sets consisting of the obtained risk topology regions are transmitted to S402 to repeat the corresponding operation steps.

[0084] The method of constructing the inspection object execution priority sequence in step S4 comprises the following steps:

[0085] S411, obtaining the inspection object set and data information of the risk topology area corresponding to each element in the inspection object set;

[0086] S412, calculate the inspection object concentration k The calculation formula for the execution priority evaluation coefficient corresponding to each element is as follows:

[0087] P k =SA k ·[NR k / NC k +RP k ]

[0088] in, P k Indicates the inspection object concentration k The execution priority evaluation coefficient corresponding to each element; S k Indicates the inspection object concentration k The area of ​​the corresponding risk topology region in the data information of the risk topology region corresponding to each element; NR k Indicates the inspection object concentration k The total number of risky devices in the corresponding risky topology area in the data information of the risky topology area corresponding to each element; NC k Indicates the inspection object concentration k In the data information of the risk topology area corresponding to each element, the total number of chain nodes in the risk device topology chain corresponding to each risk device in the corresponding risk topology area; RP k Indicates the inspection object concentration k In the data information of the risk topology area corresponding to each element, the ratio of the maximum area enclosed by the risk devices connected to each other in the corresponding risk topology area to the area of ​​the corresponding risk topology area;

[0089] S413 , sorting the elements in the inspection object set in descending order of execution priority evaluation coefficients to obtain an inspection object execution priority sequence.

[0090] S5. In the process of performing inspection according to the inspection object execution priority, the abnormal state dynamic association dictionary, the inspection object set and the inspection object execution priority sequence are dynamically updated according to the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things;

[0091] During the dynamic update of the abnormal state dynamic association dictionary, the inspection object execution priority is executed during the inspection process, and the monitoring results of each sensor in the water conservancy project to be tested are received in real time through the Internet of Things, and the screened new abnormal monitoring results are added to the abnormal state dynamic association dictionary corresponding to the inspection object execution priority sequence executed at the current time; during the inspection process, the corresponding elements of the inspected risk equipment in the abnormal state dynamic association dictionary are deleted;

[0092] In the process of dynamically updating the inspection object set, a set of risk devices corresponding to the newly added elements in the abnormal state dynamic association dictionary is obtained, which is recorded as the updated device summary set; the risk topology area corresponding to each element in the updated device summary set is obtained; the set of unexecuted inspection objects corresponding to the inspection object execution priority sequence executed at the current time is obtained, which is recorded as the dynamic object summary set; based on the position of the risk topology area, each risk topology area in the union of the updated device summary set and the dynamic object summary set is fused and determined to generate a dynamically updated inspection object set;

[0093] In the process of dynamically updating the inspection object execution priority sequence, the inspection object execution priority sequence fragment that has not been executed at the current time is obtained; the mapping element of each inspection object in the inspection object set after dynamic update in the obtained inspection object execution priority sequence fragment is obtained; the intersection of the risk topology area corresponding to the inspection object and the risk topology area corresponding to the corresponding mapping object is equal to the risk topology area corresponding to the corresponding inspection object; each inspection object in the inspection object execution priority sequence fragment that has not been executed at the current time is replaced with the mapping element of the corresponding inspection object in the inspection object set after dynamic update to obtain the inspection object execution priority sequence after dynamic update; extract the set consisting of elements in the inspection object set after dynamic update that do not belong to the inspection object execution priority sequence fragment that has not been executed at the current time and record it as the inspection object set to be updated; after the inspection object set to be updated is executed as the inspection object execution priority sequence fragment that has not been executed at the current time, the analysis data when a new inspection object execution priority sequence is generated.

[0094] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0095] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A water conservancy project operation supervision method based on digital twin technology, characterized in that: The method comprises the following steps: S1. Based on the architectural drawings of the water conservancy project, a spatial three-dimensional model of the water conservancy project to be tested is constructed; the distribution positions of various working equipment in the water conservancy project to be tested are obtained, and a mapping area of ​​the distribution positions of various working equipment in the spatial three-dimensional model of the water conservancy project to be tested is constructed, and the obtained mapping area is marked and the working equipment information is bound to generate a digital twin model of the water conservancy project to be tested; S2. Based on the sensors built into each working equipment in the water conservancy project to be tested, the operating status of the corresponding working equipment is monitored in real time, and the monitoring results of each sensor in the water conservancy project to be tested are received in real time through the Internet of Things, and abnormal monitoring results are screened out, and a dynamic association dictionary of abnormal status is constructed, and the working equipment corresponding to each element in the dynamic association dictionary of abnormal status is regarded as a risk device; S3. Based on the connection relationship of each working equipment in the water conservancy project to be tested and the instruction call coordination equipment of each working equipment, combined with the failure time distribution relationship of each working equipment in the historical data, a risk equipment topology chain corresponding to each risk equipment is constructed, and a risk topology area corresponding to each risk equipment topology chain is generated; S4. Based on the location of the risk topology area, each risk topology area is fused and judged to generate an inspection object set; based on the data information of the risk topology area corresponding to each element in the inspection object set, an inspection object execution priority sequence is constructed, and the constructed inspection object execution priority sequence is fed back to the person in charge of the water conservancy project to be tested; S5. In the process of performing inspection according to the inspection object execution priority, the abnormal state dynamic association dictionary, the inspection object set and the inspection object execution priority sequence are dynamically updated according to the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things; The instruction calling collaborative device of the working device is all the working devices that need to call the historical working instructions of the corresponding working device or collect data with built-in sensors when generating the working instructions; the instruction calling collaborative device of the working device is obtained by querying the preset form of the database; The method for constructing a risk device topology chain corresponding to each risk device in step S3 comprises the following steps: S31, obtaining the connection relationship of each working device in the water conservancy project to be tested and the instruction calling collaborative device of each working device; constructing a device topology association set corresponding to each working device; the device topology association set includes the working devices connected to the corresponding working devices in the water conservancy project to be tested, and the instruction calling collaborative devices of the corresponding working devices; S32, obtain the failure time distribution relationship of each working device in the historical data, and r Work equipment m The starting time of the fault is recorded as T （r，m） ; Get the first r Work equipment m The set of faulty coordinated devices corresponding to the fault is recorded as X （r，m） , X （r，m） Each element in corresponds to a fault start time, and X （r，m） The fault start time corresponding to each element in T （r，m） The interval between the two is less than or equal to the preset interval; r The union of the faulty coordination device sets corresponding to each fault of each working device is recorded as r Comprehensive coordination set of faults of working equipment; S33, obtain the r The intersection of the device topology association set and the fault comprehensive coordination set of the working devices is recorded as Ir ; Construct the r The working equipment is respectively Ir The device topology relationship between the various elements in the r Work equipment and Ir Middle a The device topology relationship between the elements is recorded as G Ar→A{Ir，a} ,in, Ar Indicates r The number of the working equipment; A{Ir, a} express Ir Middle a The working equipment number corresponding to each element; S34, construct the abnormal state dynamic association dictionary n The risk device topology chain of the risk device corresponding to the element is recorded as Dn ; Dn The starting chain node in the abnormal state dynamic association dictionary is n The element corresponds to the number of the working equipment; the chain node with the smallest number of continuous chain nodes at the corresponding position in the risk equipment topology chain from the starting chain node position is recorded as b +1 level chain node, b Indicates the number of continuous chain nodes at which the number of continuous chain nodes at the corresponding position in the risk device topology chain is the smallest from the starting chain node position; the next-level chain node connected to each chain node in the risk device topology chain is a working device that has a device topology association relationship with the working device corresponding to the corresponding chain node; the link pointing relationship between two adjacent connected chain nodes in the risk device topology chain is the same as the arrow pointing relationship in the device topology association relationship formed by the corresponding devices of the corresponding chain nodes; In the process of generating the risk topology area corresponding to each risk equipment topology chain, the distribution positions of the working equipment corresponding to each chain node in each risk equipment topology chain are obtained in the digital twin model of the water conservancy project to be tested, and the area with the largest area enclosed by connecting the distribution positions of each chain node is recorded as the risk topology area corresponding to the corresponding risk equipment topology chain.

2. According to claim 1, a water conservancy project operation supervision method based on digital twin technology is characterized in that: The working equipment information includes the number of the corresponding working equipment and the numbers corresponding to each built-in sensor; the abnormal monitoring result is the sensor monitoring result where the corresponding data does not belong to the preset numerical range of the corresponding sensor; the abnormal state dynamic association dictionary includes multiple data mapping pairs, each data mapping pair corresponds to an abnormal monitoring result, the first parameter in the data mapping pair is the collection time corresponding to the corresponding abnormal monitoring result, and the second parameter in the data mapping pair is the working equipment number corresponding to the corresponding abnormal monitoring result.

3. According to a method for monitoring water conservancy project operation based on digital twin technology according to claim 1, it is characterized by: The method for generating the inspection object set in step S4 comprises the following steps: S401, obtaining a risk topology area of ​​a risk device corresponding to each element in the abnormal state dynamic association dictionary; S402: record the risk topology area of ​​any risk device as RGC , get the value except RGC Other differences RGC The array of risk topological areas containing risky equipment in the intersection area is recorded as RGC The corresponding set of fusion candidate objects; like RGC If the corresponding fusion candidate set is not an empty set, then RGC The corresponding fusion candidate objects are concentrated with RGC The element with the largest intersection area is RGC The fusion object will RGC The union area with the corresponding fusion object is used as a new risk topology area, and the two risk topology areas before the fusion of the new risk topology area are deleted, and the process jumps to S403; if RGC If the corresponding fusion candidate object set is an empty set, jump to S403; S403: If the fusion candidate object sets corresponding to the obtained risk topology areas are all empty sets, the set consisting of the obtained risk topology areas is used as the inspection object set, and each element in the inspection object set corresponds to a risk topology area; If the fusion candidate object sets corresponding to the obtained risk topology regions are not empty sets, the sets consisting of the obtained risk topology regions are transmitted to S402 to repeat the corresponding operation steps.

4. According to claim 3, a water conservancy project operation supervision method based on digital twin technology is characterized in that: The method of constructing the inspection object execution priority sequence in step S4 comprises the following steps: S411, obtaining the inspection object set and data information of the risk topology area corresponding to each element in the inspection object set; S412, calculate the inspection object concentration k The calculation formula for the execution priority evaluation coefficient corresponding to each element is as follows: P k =SA k ·[NR k / NC k +RP k ] in, P k Indicates the inspection object concentration k The execution priority evaluation coefficient corresponding to each element; SA k Indicates the inspection object concentration k The area of ​​the corresponding risk topology region in the data information of the risk topology region corresponding to each element; NR k Indicates the inspection object concentration k The total number of risky devices in the corresponding risky topology area in the data information of the risky topology area corresponding to each element; NC k Indicates the inspection object concentration k In the data information of the risk topology area corresponding to each element, the total number of chain nodes in the risk device topology chain corresponding to each risk device in the corresponding risk topology area; RP k Indicates the inspection object concentration k In the data information of the risk topology area corresponding to each element, the ratio of the maximum area enclosed by the risk devices connected to each other in the corresponding risk topology area to the area of ​​the corresponding risk topology area; S413 , sorting the elements in the inspection object set in descending order of execution priority evaluation coefficients to obtain an inspection object execution priority sequence.

5. A water conservancy project operation supervision method based on digital twin technology according to claim 4, characterized in that: During the dynamic update of the abnormal state dynamic association dictionary, the inspection object execution priority is executed during the inspection process, and the monitoring results of each sensor in the water conservancy project to be tested are received in real time through the Internet of Things, and the screened new abnormal monitoring results are added to the abnormal state dynamic association dictionary corresponding to the inspection object execution priority sequence executed at the current time; During the inspection process, the corresponding elements in the abnormal state dynamic association dictionary of the inspected risk equipment are deleted; In the process of dynamically updating the inspection object set, a set of risk devices corresponding to the newly added elements in the abnormal state dynamic association dictionary is obtained, which is recorded as the updated device summary set; and the risk topology area corresponding to each element in the updated device summary set is obtained; Obtain the set of inspection objects that have not been executed corresponding to the execution priority sequence of the inspection objects executed at the current time, and record it as a dynamic object summary set; Based on the location of the risk topology area, each risk topology area in the union of the updated device summary set and the dynamic object summary set is fused and determined to generate a dynamically updated inspection object set; In the process of dynamically updating the inspection object execution priority sequence, a fragment of the inspection object execution priority sequence that has not been executed at the current time is obtained; Obtaining a mapping element of each inspection object in the inspection object set after dynamic update in the obtained inspection object execution priority sequence fragment; The intersection of the risk topology area corresponding to the inspection object and the risk topology area corresponding to the corresponding mapping object is equal to the risk topology area corresponding to the corresponding inspection object; each inspection object in the inspection object execution priority sequence fragment that has not been executed at the current time is replaced with the mapping element of the corresponding inspection object in the dynamically updated inspection object set to obtain the dynamically updated inspection object execution priority sequence; extract the set consisting of elements in the dynamically updated inspection object set that do not belong to the inspection object execution priority sequence fragment that has not been executed at the current time and record it as the inspection object set to be updated; after the inspection object set to be updated is executed as the inspection object execution priority sequence fragment that has not been executed at the current time, generate analysis data for a new inspection object execution priority sequence.

6. A water conservancy project operation supervision system based on digital twin technology, applying a water conservancy project operation supervision method based on digital twin technology as described in any one of claims 1 to 5, characterized in that: The system includes: a twin model construction module, an abnormal dynamic association analysis module, a risk topology area analysis module, an operation supervision feedback module and a data dynamic update management module. The twin model construction module builds a spatial three-dimensional model of the water conservancy project to be tested based on the architectural drawings of the water conservancy project; obtains the distribution positions of various working equipment in the water conservancy project to be tested, constructs a mapping area of ​​the distribution positions of various working equipment in the spatial three-dimensional model of the water conservancy project to be tested, and marks the obtained mapping area and binds the working equipment information to generate a digital twin model of the water conservancy project to be tested; The abnormal dynamic association analysis module monitors the operating status of the corresponding working equipment in real time based on the sensors built into each working equipment in the water conservancy project to be tested, receives the monitoring results of each sensor in the water conservancy project to be tested in real time through the Internet of Things, and screens out the abnormal monitoring results, constructs an abnormal state dynamic association dictionary, and regards the working equipment corresponding to each element in the abnormal state dynamic association dictionary as a risk device; The risk topology region analysis module constructs a risk device topology chain corresponding to each risk device based on the connection relationship of each working device in the water conservancy project to be tested and the instruction call coordination device of each working device, combined with the failure time distribution relationship of each working device in the historical data, and generates a risk topology region corresponding to each risk device topology chain; The operation supervision feedback module performs fusion judgment on each risk topology area based on the location of the risk topology area to generate an inspection object set; constructs an inspection object execution priority sequence based on the data information of the risk topology area corresponding to each element in the inspection object set, and feeds back the constructed inspection object execution priority sequence to the person in charge of the water conservancy project to be tested; The data dynamic update management module performs inspections according to the inspection object execution priority, and dynamically updates the abnormal state dynamic association dictionary, the inspection object set and the inspection object execution priority sequence based on the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things.

7. The water conservancy project operation supervision system based on digital twin technology according to claim 6 is characterized by: The data dynamic update management module includes an abnormal state dynamic association dictionary update unit, an inspection object set update unit and an inspection object execution priority sequence update unit. The abnormal state dynamic association dictionary updating unit dynamically updates the abnormal state dynamic association dictionary in the process of performing inspection according to the inspection object execution priority, based on the monitoring results of each sensor in the water conservancy project to be tested received in real time by the Internet of Things; The inspection object set updating unit dynamically updates the inspection object set in accordance with the inspection object execution priority during the inspection process, based on the monitoring results of each sensor in the water conservancy project to be tested and the update results of the abnormal state dynamic association dictionary received in real time by the Internet of Things; The inspection object execution priority sequence update unit dynamically updates the inspection object execution priority sequence in the process of performing inspections according to the inspection object execution priority, based on the real-time reception of monitoring results of each sensor in the water conservancy project to be tested by the Internet of Things, the abnormal state dynamic association dictionary, and the update results of the inspection object set.

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