Deep sea operation performance evaluation method and equipment based on simulation deduction data

Abstract

The invention discloses a deep-sea operation performance evaluation method and device based on simulation deduction data, and relates to the technical field of ocean engineering and performance evaluation, and the method comprises the steps: deducing a deep-sea operation task completed by a deep-sea operation system based on a simulation deduction platform, and obtaining the simulation deduction data; obtaining an availability vector, a credibility vector and a capability vector evaluated before the deep sea operation system executes the operation task; obtaining a correction value based on the simulation deduction data; and based on the correction value and the operation performance evaluation formula, obtaining the operation performance output by the operation performance evaluation formula. The method is used for realizing accurate evaluation of the operation efficiency of the deep-sea operation system in the deep-sea characteristic operation scene.

Description

Technical Field

[0001] The present application relates to the field of marine engineering and performance evaluation technology, and in particular to a method and device for evaluating the performance of deep-sea operations based on simulation and deduction data. Background Art

[0002] Deep-sea special operations refer to special tasks carried out in the deep sea, such as laying oil pipelines in the deep sea, deep-sea exploration, target search, etc. Due to the extreme operating conditions of the deep-sea environment, such as high pressure, low temperature and high concentration of salt content, deep-sea special operations need to be completed using special deep-sea operation systems. Among them, a deep-sea operation system is composed of multiple devices, and multiple devices work together to complete deep-sea operation tasks.

[0003] In order to measure the system's deep-sea operation capability and improve the system, it is necessary to evaluate the system's operating performance. However, due to the particularity of the deep-sea environment, the industry currently has no solution for evaluating the performance of systems in deep-sea special operation scenarios. Summary of the invention

[0004] In response to the above-mentioned problems and technical needs, the applicant has proposed a deep-sea operation efficiency evaluation method and equipment based on simulation data, so as to achieve accurate evaluation of the operation efficiency of deep-sea operation systems in deep-sea characteristic operation scenarios.

[0005] The present application embodiment provides a deep-sea operation performance evaluation method based on simulation deduction data, the method comprising:

[0006] Based on the simulation deduction platform, the deep-sea operation tasks completed by the deep-sea operation system are deduced to obtain simulation deduction data, wherein the simulation deduction data includes: deep-sea environment data, multiple operation equipment corresponding to the deep-sea operation task, the equipment status corresponding to each operation equipment, and the operation task performed by each operation equipment;

[0007] Obtaining the availability vector, credibility vector and capability vector evaluated by the deep-sea operation system before performing the operation task, wherein the availability vector is used to characterize the probability that the operation equipment is in a fault-free state when starting to perform the operation task, the credibility vector is used to characterize the probability that the operation equipment is in a normal working state during the execution of the operation task, and the capability vector is used to characterize the probability that the operation equipment completes the operation task within a preset time and under preset conditions;

[0008] Based on the simulation data, the following performance evaluation process is performed on each operating equipment and each operating task:

[0009] Determine a first correction value based on the equipment status, determine a second correction value based on the deep-sea environment data, and determine a third correction value based on the operation task; use the first correction value to correct the availability vector to obtain a target availability vector, use the second correction value to correct the credibility vector to obtain a target credibility vector, and use the third correction value to correct the capability vector to obtain a target capability vector; input the target availability vector, the target credibility vector, and the target capability vector into a preset operation performance evaluation formula to obtain the operation performance output by the operation performance evaluation formula;

[0010] The operation performance evaluation formula is:

[0011] E = ADC;

[0012] Wherein, E represents the operation efficiency, A represents the target availability vector, D represents the target credibility vector, and C represents the target capability vector;

[0013] Among them, one operation task corresponds to at least one operation equipment.

[0014] According to a deep-sea operation performance evaluation method based on simulation deduction data according to an embodiment of the present application, determining a first correction value based on the equipment status includes:

[0015] Determining the degree of damage of the operating equipment based on the physical parameters in the equipment status;

[0016] Determine the equipment type of the operating equipment, obtain a plurality of preset damage ranges corresponding to the equipment type, and a correction value corresponding to each of the damage ranges;

[0017] The correction value corresponding to the damage range to which the damage degree belongs is determined as the first correction value.

[0018] According to a deep-sea operation performance evaluation method based on simulation deduction data in one embodiment of the present application, the deep-sea environment data includes: the depth of the location of the operating equipment at time t, the salinity of the location of the operating equipment at time t, and the hydrological conditions of the location of the operating equipment at time t;

[0019] Determining a second correction value based on the deep sea environment data comprises:

[0020] Determine the equipment type of the operating equipment, obtain multiple correction tables corresponding to the equipment type, and in each correction table, a depth weight corresponding to the depth, a salinity weight corresponding to the salinity, and a hydrological condition weight corresponding to the hydrological condition;

[0021] Obtaining a target correction table matching the depth corresponding to time t, the salinity corresponding to time t, and the hydrological condition corresponding to time t from a plurality of correction tables;

[0022] The second correction value is obtained based on the target depth weight, target salinity weight and target hydrological condition weight in the target correction table.

[0023] According to a deep-sea operation performance evaluation method based on simulation deduction data according to an embodiment of the present application, determining a third correction value based on the operation task includes:

[0024] Determine the actual completion status of each indicator of the task, including: detection capability, communication capability, coordination capability and maintenance capability;

[0025] For each indicator, a correction value corresponding to the actual completion status and the target required completion status is obtained; and the obtained correction value is determined as the third correction value.

[0026] According to a deep-sea operation performance evaluation method based on simulation deduction data according to an embodiment of the present application, before a deep-sea operation system performs an operation task, an availability vector is evaluated, including:

[0027] Based on the mean time between failures and the mean time to repair of each operating device, an availability sub-vector of the operating device is obtained;

[0028] Determine the probability that the equipment status of all operating equipment is a fault-free state;

[0029] Combining the probability that the device states are all in a non-fault state and the availability sub-vector to obtain an availability vector;

[0030] The mean time between failures and the mean time to repair a failure are obtained by pre-calibrating the operating equipment.

[0031] According to a deep-sea operation performance evaluation method based on simulation deduction data according to an embodiment of the present application, before a deep-sea operation system performs an operation task, a credibility vector is evaluated, including:

[0032] Based on the reliability, durability, safety and survivability of the operating equipment, the credibility sub-vector of the operating equipment is obtained;

[0033] Combining the credibility sub-vectors to obtain the credibility vector;

[0034] The reliability, durability, safety and survivability are obtained by pre-calibrating the operating equipment.

[0035] According to a deep-sea operation performance evaluation method based on simulation deduction data according to an embodiment of the present application, before a deep-sea operation system performs an operation task, the capability vector is evaluated, including:

[0036] Based on the detection capability, communication capability, coordination capability and maintenance capability of the operating equipment during the operation task, the capability sub-vector is obtained;

[0037] Performing weighted summation on the capability sub-vectors of each indicator to obtain the capability vector;

[0038] Among them, the detection capability is based on the detection width, detection depth, recognition capability and command response speed of the operating equipment; the communication capability is based on the communication reliability, communication distance and communication delay of the operating equipment; the collaborative capability is based on the stability, accuracy and operating efficiency of the operating equipment during collaborative operation; the maintenance capability is based on the maintenance efficiency, economic cost, maintenance quality and environmental impact of the operating equipment during maintenance.

[0039] The embodiment of the present application also provides a deep-sea operation performance evaluation device based on simulation deduction data, comprising:

[0040] A first acquisition module is used to deduce the deep-sea operation tasks completed by the deep-sea operation system based on the simulation deduction platform to obtain simulation deduction data, wherein the simulation deduction data includes: deep-sea environment data, multiple operation equipment corresponding to the deep-sea operation task, the equipment status corresponding to each operation equipment, and the operation task performed by each operation equipment;

[0041] A second acquisition module is used to acquire the availability vector, credibility vector and capability vector evaluated by the deep-sea operation system before performing the operation task, wherein the availability vector is used to characterize the probability that the operation equipment is in a fault-free state when starting to perform the operation task, the credibility vector is used to characterize the probability that the operation equipment is in a normal working state during the execution of the operation task, and the capability vector is used to characterize the probability that the operation equipment completes the operation task within a preset time and under preset conditions;

[0042] The performance evaluation module is used to perform the following performance evaluation process on each operating equipment and each operating task based on the simulation deduction data:

[0043] Determine a first correction value based on the equipment status, determine a second correction value based on the deep-sea environment data, and determine a third correction value based on the operation task; use the first correction value to correct the availability vector to obtain a target availability vector, use the second correction value to correct the credibility vector to obtain a target credibility vector, and use the third correction value to correct the capability vector to obtain a target capability vector; input the target availability vector, the target credibility vector, and the target capability vector into a preset operation performance evaluation formula to obtain the operation performance output by the operation performance evaluation formula;

[0044] The operation performance evaluation formula is:

[0045] E = ADC;

[0046] Wherein, E represents the operation efficiency, A represents the target availability vector, D represents the target credibility vector, and C represents the target capability vector;

[0047] Among them, one operation task corresponds to at least one operation equipment.

[0048] An embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the deep-sea operation performance evaluation method based on simulation data as described in any one of the above items are implemented.

[0049] An embodiment of the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the deep-sea operation performance evaluation method based on simulation deduction data as described in any of the above items are implemented.

[0050] The deep-sea operation performance evaluation method and device based on simulation deduction data provided in the embodiment of the present application obtains simulation deduction data by deducing the deep-sea operation tasks completed by the deep-sea operation system based on the simulation deduction platform. The present application restores the deep-sea operation tasks through simulation operations, providing an accurate data basis for operation performance evaluation; based on the simulation deduction data, the following performance evaluation process is performed for each operation equipment and each operation task: a first correction value is determined based on the equipment status, a second correction value is determined based on the deep-sea environment data, and a third correction value is determined based on the operation task; the availability vector is corrected using the first correction value to obtain the target availability vector, and the credibility vector is corrected using the second correction value , obtain the target credibility vector, and the third correction value corrects the capability vector, obtains the target capability vector, and accurately corrects the availability vector, credibility vector and energy vector respectively through simulation deduction data; finally, inputs the target availability vector, target credibility vector and target capability vector into the preset operation efficiency evaluation formula, and obtains the operation efficiency output by the operation efficiency evaluation formula. It can be seen that this application quantifies the capability of each operation equipment in the operation task by analyzing the collaborative relationship between the operation equipment, thereby ensuring the credibility and accuracy of the operation efficiency analysis results, and realizing the accurate evaluation of the operation efficiency of the deep-sea operation system in the deep-sea characteristic operation scenario. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 It is a flowchart of a deep-sea operation efficiency evaluation method based on simulation deduction data provided in an embodiment of the present application;

[0053] Figure 2 It is a structural schematic diagram of a deep-sea operation efficiency evaluation device based on simulation deduction data provided in an embodiment of the present application;

[0054] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] The embodiment of the present application provides a deep-sea operation performance evaluation method based on simulation deduction data. The method can be applied to smart terminals and servers. Some other descriptions in the embodiments of the present application are for illustrative purposes only and are not intended to limit the scope of protection of the present application. They will not be described one by one. The specific implementation of the method is as follows Figure 1 As shown:

[0057] Step 101, based on the simulation platform, deduce the deep-sea operation tasks completed by the deep-sea operation system to obtain simulation data.

[0058] The simulation data include: deep-sea environment data, multiple operating equipment corresponding to deep-sea operating tasks, the equipment status corresponding to each operating equipment, and the operating tasks performed by each operating equipment.

[0059] Among them, one operation task corresponds to at least one operation equipment.

[0060] Step 102: Obtain the availability vector, credibility vector, and capability vector of the deep-sea operation system evaluated before executing the operation task.

[0061] Among them, the availability vector is used to characterize the probability that the operating equipment is in a fault-free state when it starts to perform the operating task, the credibility vector is used to characterize the probability that the operating equipment is in a normal working state during the execution of the operating task, and the capability vector is used to characterize the probability that the operating equipment completes the operating task within the preset time and under the preset conditions.

[0062] Step 103, based on the simulation data, the following performance evaluation process is performed on each operating equipment and each operating task:

[0063] A first correction value is determined based on the equipment status, a second correction value is determined based on the deep-sea environment data, and a third correction value is determined based on the operation task; the availability vector is corrected using the first correction value to obtain a target availability vector, the credibility vector is corrected using the second correction value to obtain a target credibility vector, and the capability vector is corrected using the third correction value to obtain a target capability vector; the target availability vector, the target credibility vector, and the target capability vector are input into a pre-set operation efficiency evaluation formula to obtain the operation efficiency output by the operation efficiency evaluation formula.

[0064] The operation performance evaluation formula is shown in formula (1):

[0065] E=ADC……………………………………………………(1)

[0066] Among them, E represents operational effectiveness, A represents the target availability vector, D represents the target credibility vector, and C represents the target capability vector.

[0067] The deep-sea operation performance evaluation method based on simulation deduction data provided in the embodiment of the present application obtains simulation deduction data by deducing the deep-sea operation tasks completed by the deep-sea operation system based on the simulation deduction platform. The present application restores the deep-sea operation tasks through simulation operations, providing an accurate data basis for operation performance evaluation; based on the simulation deduction data, the following performance evaluation process is performed for each operation equipment and each operation task: a first correction value is determined based on the equipment status, a second correction value is determined based on the deep-sea environment data, and a third correction value is determined based on the operation task; the availability vector is corrected using the first correction value to obtain the target availability vector, and the credibility vector is corrected using the second correction value, The target credibility vector and the third correction value corrected capability vector are obtained, and the target capability vector is obtained. The availability vector, the credibility vector and the energy vector are accurately corrected respectively through simulation deduction data. Finally, the target availability vector, the target credibility vector and the target capability vector are input into the preset operation efficiency evaluation formula to obtain the operation efficiency output by the operation efficiency evaluation formula. It can be seen that this application ensures the credibility and accuracy of the operation efficiency analysis results by analyzing the collaborative relationship between the various operation equipment and quantifying the capability of each operation equipment in the operation task, thereby realizing the accurate evaluation of the operation efficiency of the deep-sea operation system in the deep-sea characteristic operation scenario.

[0068] In a specific embodiment, the specific implementation of evaluating the availability vector before the deep-sea operation system performs the operation task includes:

[0069] Based on the mean time between failures and the mean time to repair each operating device, the availability sub-vector of the operating device is obtained; the probability that the device status of all operating devices is in a fault-free state is determined; and the availability vector is obtained by combining the probability that the device status is in a fault-free state and the availability sub-vector.

[0070] Among them, the mean time between failures and the mean time to repair failures are obtained by calibrating the operating equipment in advance.

[0071] Among them, the availability subvector

[0072] Among them, T bf represents the mean time between failures, T tr Indicates the mean time to repair a fault.

[0073] The availability vector is represented by A = [A0A1…A k …A n ].

[0074] Among them, A0 represents the probability that the equipment status of all operating equipment is in a fault-free state, A k represents the kth availability sub-vector, that is, the probability that the equipment status of the kth operating equipment is a fault-free state, and n represents the total number of operating equipment.

[0075] Where A0 = a n , a represents the reliability of the operating equipment, which is calculated by averaging all available sub-vectors.

[0076] In a specific embodiment, the specific implementation of determining the first correction value based on the device state includes:

[0077] Based on the physical parameters in the equipment status, determine the degree of damage of the operating equipment; determine the equipment type of the operating equipment, obtain multiple preset damage ranges corresponding to the equipment type, and the correction value corresponding to each damage range; determine the correction value corresponding to the damage range to which the damage degree belongs as the first correction value.

[0078] Among them, physical parameters are used to characterize the actual maintenance status of operating equipment.

[0079] Among them, different equipment types correspond to different correction values, and different degrees of damage correspond to different correction values ​​under the equipment type.

[0080] Specifically, when it is determined that the availability of the operating equipment is greater than a preset availability, the degree of damage of the operating equipment is determined based on the physical parameters in the equipment state.

[0081] For example, a certain device type corresponds to two damage ranges, that is, two correction values. When it is determined that the damage degree is greater than the damage threshold, the first correction value is 0.5; when it is determined that the damage degree is less than or equal to the damage threshold, the first correction value is 1.

[0082] In a specific embodiment, the availability vector is corrected using the first correction value to obtain a target availability vector, as shown in formula (2):

[0083] A m =k A *A…………………………………………(2)

[0084] Among them, A m represents the target availability vector, k A Indicates the first correction value.

[0085] Specifically, for the availability of operating equipment, there are only two states before the operation task is performed: available and unavailable. Therefore, the availability vector of the deep-sea operation system is A q =[A m , 1-A m ].

[0086] In a specific embodiment, the specific implementation of evaluating the credibility vector before the deep-sea operation system performs the operation task includes:

[0087] Based on the reliability, durability, safety and survivability of the operating equipment, the credibility sub-vector of the operating equipment is obtained; and the credibility vector is obtained by combining the credibility sub-vectors.

[0088] Among them, reliability, durability, safety and survivability are obtained by calibrating the operating equipment in advance.

[0089] Specifically, there are only normal working state and abnormal working state in the process of the operating equipment performing the operating task. Therefore, the credibility subvector can be obtained as

[0090] Among them, D k represents the kth credibility sub-vector, d 11 =d represents the probability that the operating equipment always maintains normal operation during the execution of the operating task, d 12 =1-d represents the probability that the operating equipment changes from a normal working state to an abnormal working state during the execution of the operating task, d 21 It represents the probability that the operating equipment always maintains an abnormal working state during the execution of the operating task, d 22 It indicates the probability that the operating equipment switches from an abnormal working state to a normal working state during the execution of the task.

[0091] Since the equipment cannot be repaired during the operation, 21 =0,d 22 =1.

[0092] The credibility vector is represented by D = [D1…D k …D n ].

[0093] In a specific embodiment, the deep-sea environment data includes: the depth of the location of the operating equipment at time t, the salinity of the location of the operating equipment at time t, and the hydrological conditions of the location of the operating equipment at time t.

[0094] Since the operating tasks of the deep-sea operating system are time-series, the deep-sea environmental data corresponding to the operating equipment is also changing, so it is necessary to deduce the deep-sea environmental data of the entire operating process.

[0095] The specific implementation of determining the second correction value based on deep sea environment data includes:

[0096] Determine the equipment type of the operating equipment, obtain multiple correction tables corresponding to the equipment type, and in each correction table, a depth weight corresponding to the depth, a salinity weight corresponding to the salinity, and a hydrological condition weight corresponding to the hydrological condition; obtain a target correction table matching the depth corresponding to time t, the salinity corresponding to time t, and the hydrological condition corresponding to time t from the multiple correction tables; and obtain a second correction value based on the target depth weight, target salinity weight, and target hydrological condition weight in the target correction table.

[0097] Among them, the depth, salinity and hydrological conditions of different correction tables are inconsistent.

[0098] In a specific embodiment, the credibility vector is corrected using the second correction value to obtain a target credibility vector, which can be specifically referred to in formula (3):

[0099] D m =k D D…………………………………………(3)

[0100] Among them, D m represents the target credibility, k D Indicates the second correction value.

[0101] In a specific embodiment, the specific implementation of evaluating the capability vector of the deep-sea operation system before executing the operation task includes:

[0102] Based on the detection capability, communication capability, coordination capability and maintenance capability of the operating equipment during the operating task, a capability sub-vector is obtained; and the capability vector is obtained by combining the capability sub-vectors.

[0103] Among them, the detection capability is based on the detection width, detection depth, recognition capability and command response speed of the operating equipment; the communication capability is based on the communication reliability, communication distance and communication delay of the operating equipment; the collaborative capability is based on the stability, accuracy and operating efficiency of the operating equipment during collaborative operation; the maintenance capability is based on the maintenance efficiency, economic cost, maintenance quality and environmental impact of the operating equipment during maintenance.

[0104] Specifically, there is a two-level indicator system for evaluating the capability of operating equipment. Detection capability, communication capability, coordination capability and maintenance capability belong to the first level; detection width, detection depth, recognition capability, command response speed, communication reliability, communication distance, communication delay, stability during collaborative operation, accuracy, operating efficiency, maintenance efficiency, economic cost, maintenance quality and environmental impact belong to the second level.

[0105] Based on the above, the capability vector can be obtained as

[0106] Among them, R k represents the kth capability subvector, l represents the number of the first level, j represents the number of the second level, and w lj Indicates the weight of the second-level indicators in the first-level indicators, R lj It represents the evaluation score of the second-level indicators, s represents the number of first-level indicators, and p represents the number of second-level indicators.

[0107] However, in actual deep-sea operations (or simulations), the operating performance of the operating equipment may not necessarily reach the evaluated capability vector. For example, there are five detection targets set in the detection capability, but only four targets are actually detected. Therefore, it is necessary to determine the third correction value based on the simulation data to correct the capability vector.

[0108] Among them, the third correction value of the present application only acts on the first-level indicators.

[0109] In a specific embodiment, the specific implementation of determining the third correction value based on the operation task includes:

[0110] Determine the actual completion status corresponding to each indicator of the task; for each indicator, obtain a correction value corresponding to the actual completion status and the target required completion status; and determine the obtained correction value as a third correction value.

[0111] Among them, the third correction coefficient of the hth first-level indicator is k ch , the target energy subvector corresponding to the hth first-level indicator is

[0112] Then, the target capability vector is obtained by weighted summation.

[0113] Among them, w i represents the weight corresponding to the i-th target energy sub-vector, and y represents the number of first-level indicators.

[0114] Due to the complexity of the deep-sea environment involved in deep-sea operation tasks, for example, conditions such as high pressure, low temperature, darkness and strong salinity will significantly affect the reliability and effectiveness of the operation equipment and operation tasks. Therefore, this application simulates the completed deep-sea operation tasks and evaluates the operation performance of the deep-sea operation system based on the obtained simulation data and the preset operation performance evaluation formula (ADC model).

[0115] Specifically, by evaluating the availability of the deep-sea operation system, the energy of the deep-sea operation system to operate normally under complex conditions can be determined; by evaluating the credibility of the deep-sea operation system, the stability and durability of the deep-sea operation system can be determined; by evaluating the capability of the deep-sea operation system, the task completion of the deep-sea operation system can be determined. This application can effectively and comprehensively consider the collaborative relationship between various operating equipment through the ADC model, introduce the capability vector, quantify the contribution of each operating equipment in the collaborative task, and evaluate the comprehensive effectiveness of the entire deep-sea operation system in completing the task.

[0116] Moreover, the capability vector is obtained by decomposing it layer by layer according to the actual needs of the task, constructing appropriate indicators at all levels and superior indicators, and subdividing the relationship between tasks. It can well meet the requirements of performance evaluation and improve the credibility, feasibility and accuracy of the performance evaluation method.

[0117] The present application also provides a deep-sea operation performance evaluation device based on simulation deduction data. The specific implementation of the device can refer to the description of the deep-sea operation performance evaluation method based on simulation deduction data, and the repeated parts will not be repeated. Figure 2 As shown, the device comprises:

[0118] The first acquisition module 201 is used to deduce the deep-sea operation tasks completed by the deep-sea operation system based on the simulation platform to obtain simulation data, wherein the simulation data includes: deep-sea environment data, multiple operation equipment corresponding to the deep-sea operation task, the equipment status corresponding to each operation equipment, and the operation task performed by each operation equipment.

[0119] The second acquisition module 202 is used to obtain the availability vector, credibility vector and capability vector evaluated by the deep-sea operation system before performing the operation task, wherein the availability vector is used to characterize the probability that the operation equipment is in a fault-free state when starting to perform the operation task, the credibility vector is used to characterize the probability that the operation equipment is in a normal working state during the execution of the operation task, and the capability vector is used to characterize the probability that the operation equipment completes the operation task within a preset time and under preset conditions.

[0120] The performance evaluation module 203 is used to perform the following performance evaluation process on each operation equipment and each operation task based on the simulation deduction data:

[0121] A first correction value is determined based on the equipment status, a second correction value is determined based on the deep-sea environment data, and a third correction value is determined based on the operation task; the availability vector is corrected using the first correction value to obtain a target availability vector, the credibility vector is corrected using the second correction value to obtain a target credibility vector, and the capability vector is corrected using the third correction value to obtain a target capability vector; the target availability vector, the target credibility vector, and the target capability vector are input into a pre-set operation efficiency evaluation formula to obtain the operation efficiency output by the operation efficiency evaluation formula.

[0122] The operational performance evaluation formula is:

[0123] E = ADC.

[0124] Among them, E represents operational effectiveness, A represents the target availability vector, D represents the target credibility vector, and C represents the target capability vector.

[0125] Among them, one operation task corresponds to at least one operation equipment.

[0126] In a specific embodiment, the performance evaluation module 203 is used to determine the degree of damage of the operating equipment based on the physical parameters in the equipment status;

[0127] Determine the equipment type of the operating equipment, obtain a plurality of preset damage ranges corresponding to the equipment type, and a correction value corresponding to each damage range;

[0128] The correction value corresponding to the damage range to which the damage degree belongs is determined as the first correction value.

[0129] In a specific embodiment, the deep-sea environmental data includes: the depth of the location of the operating equipment at time t, the salinity of the location of the operating equipment at time t, and the hydrological conditions of the location of the operating equipment at time t. The performance evaluation module 203 is used to determine the equipment type of the operating equipment, obtain multiple correction tables corresponding to the equipment type, and the depth weight corresponding to the depth, the salinity weight corresponding to the salinity, and the hydrological condition weight corresponding to the hydrological condition in each correction table; obtain a target correction table matching the depth corresponding to time t, the salinity corresponding to time t, and the hydrological condition corresponding to time t from the multiple correction tables; and obtain a second correction value based on the target depth weight, target salinity weight, and target hydrological condition weight in the target correction table.

[0130] In a specific embodiment, the performance evaluation module 203 is used to determine the actual completion status corresponding to each indicator of the work task, where the indicators include: detection capability, communication capability, coordination capability and maintenance capability; for each indicator, obtain a correction value corresponding to the actual completion status and the target required completion status; and determine the obtained correction value as the third correction value.

[0131] In a specific embodiment, the device also includes: a prediction module, which is used to obtain an availability sub-vector of the operating equipment based on the average failure interval time and the average failure repair time of each operating equipment; determine the probability that the equipment status of all operating equipment is a fault-free state; combine the probability that the equipment status is a fault-free state and the availability sub-vector to obtain an availability vector; wherein the average failure interval time and the average failure repair time are pre-calibrated for the operating equipment.

[0132] In a specific embodiment, the prediction module is used to obtain a credibility sub-vector of the operating equipment based on the reliability, durability, safety and survivability of the operating equipment; and to combine the credibility sub-vectors to obtain a credibility vector; wherein the reliability, durability, safety and survivability are obtained by pre-calibrating the operating equipment.

[0133] In a specific embodiment, the prediction module is used to obtain a capability sub-vector based on the detection capability, communication capability, coordination capability and maintenance capability of the operating equipment during the operating task; and to obtain a capability vector by weighted summing up the capability sub-vectors of each indicator; wherein the detection capability is obtained based on the detection width, detection depth, recognition capability and command response speed of the operating equipment; the communication capability is obtained based on the communication reliability, communication distance and communication delay of the operating equipment; the coordination capability is obtained based on the stability, accuracy and operating efficiency of the operating equipment during collaborative operation; and the maintenance capability is obtained based on the maintenance efficiency, economic cost, maintenance quality and environmental impact of the operating equipment during maintenance.

[0134] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3As shown, the electronic device may include: a processor 301, a communications interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communications interface 302 and the memory 303 communicate with each other through the communication bus 304. The processor 301 may call the logic instructions in the memory 303 to execute the deep-sea operation performance evaluation method based on simulation deduction data.

[0135] In addition, the logic instructions in the above-mentioned memory 303 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0136] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the deep-sea operation efficiency evaluation method based on simulation deduction data provided by the above-mentioned methods.

[0137] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the deep-sea operation efficiency evaluation method based on simulation deduction data provided in the above-mentioned embodiments.

[0138] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0139] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0140] Finally, it should be noted that the above is only the preferred implementation of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and changes directly derived or associated by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the scope of protection of the present application.

Claims

1. A deep-sea operation performance evaluation method based on simulation data, characterized in that: The method comprises: Based on the simulation deduction platform, the deep-sea operation tasks completed by the deep-sea operation system are deduced to obtain simulation deduction data, wherein the simulation deduction data includes: deep-sea environment data, multiple operation equipment corresponding to the deep-sea operation task, the equipment status corresponding to each operation equipment, and the operation task performed by each operation equipment; Obtaining the availability vector, credibility vector and capability vector evaluated by the deep-sea operation system before performing the operation task, wherein the availability vector is used to characterize the probability that the operation equipment is in a fault-free state when starting to perform the operation task, the credibility vector is used to characterize the probability that the operation equipment is in a normal working state during the execution of the operation task, and the capability vector is used to characterize the probability that the operation equipment completes the operation task within a preset time and under preset conditions; Based on the simulation data, the following performance evaluation process is performed on each operating equipment and each operating task: Determine a first correction value based on the equipment status, determine a second correction value based on the deep-sea environment data, and determine a third correction value based on the operation task; use the first correction value to correct the availability vector to obtain a target availability vector, use the second correction value to correct the credibility vector to obtain a target credibility vector, and use the third correction value to correct the capability vector to obtain a target capability vector; input the target availability vector, the target credibility vector, and the target capability vector into a preset operation performance evaluation formula to obtain the operation performance output by the operation performance evaluation formula; The operation performance evaluation formula is: E = ADC; Wherein, E represents the operation efficiency, A represents the target availability vector, D represents the target credibility vector, and C represents the target capability vector; Among them, one operation task corresponds to at least one operation equipment.

2. The deep-sea operation efficiency evaluation method based on simulation data according to claim 1 is characterized in that: Determining a first correction value based on the device state includes: Determining the degree of damage of the operating equipment based on the physical parameters in the equipment status; Determine the equipment type of the operating equipment, obtain a plurality of preset damage ranges corresponding to the equipment type, and a correction value corresponding to each of the damage ranges; The correction value corresponding to the damage range to which the damage degree belongs is determined as the first correction value.

3. The deep-sea operation performance evaluation method based on simulation data according to claim 1 is characterized in that: The deep sea environment data includes: the depth of the location of the operating equipment at time t, the salinity of the location of the operating equipment at time t, and the hydrological conditions of the location of the operating equipment at time t; Determining a second correction value based on the deep sea environment data comprises: Determine the equipment type of the operating equipment, obtain multiple correction tables corresponding to the equipment type, and in each correction table, a depth weight corresponding to the depth, a salinity weight corresponding to the salinity, and a hydrological condition weight corresponding to the hydrological condition; Obtaining a target correction table matching the depth corresponding to time t, the salinity corresponding to time t, and the hydrological condition corresponding to time t from a plurality of correction tables; The second correction value is obtained based on the target depth weight, target salinity weight and target hydrological condition weight in the target correction table.

4. The deep-sea operation efficiency evaluation method based on simulation data according to claim 1 is characterized in that: Determining a third correction value based on the work task includes: Determine the actual completion status of each indicator of the task, including: detection capability, communication capability, coordination capability and maintenance capability; For each indicator, a correction value corresponding to the actual completion status and the target required completion status is obtained; and the obtained correction value is determined as the third correction value.

5. The deep-sea operation efficiency evaluation method based on simulation data according to any one of claims 1 to 4, characterized in that: Before executing the operation task, the deep-sea operation system evaluates the availability vector, including: Based on the mean time between failures and the mean time to repair of each operating device, an availability sub-vector of the operating device is obtained; Determine the probability that the equipment status of all operating equipment is a fault-free state; Combining the probability that the device states are all in a non-fault state and the availability sub-vector to obtain an availability vector; The mean time between failures and the mean time to repair a failure are obtained by pre-calibrating the operating equipment.

6. The deep-sea operation efficiency evaluation method based on simulation data according to any one of claims 1 to 4, characterized in that: Before deep-sea operating systems perform their tasks, they evaluate the credibility vectors, including: Based on the reliability, durability, safety and survivability of the operating equipment, the credibility sub-vector of the operating equipment is obtained; Combining the credibility sub-vectors to obtain the credibility vector; The reliability, durability, safety and survivability are obtained by pre-calibrating the operating equipment.

7. The deep-sea operation efficiency evaluation method based on simulation data according to any one of claims 1 to 4, characterized in that: Before executing the operation task, the deep-sea operation system evaluates the capability vector, including: Based on the detection capability, communication capability, coordination capability and maintenance capability of the operating equipment during the operation task, the capability sub-vector is obtained; Performing weighted summation on the capability sub-vectors of each indicator to obtain the capability vector; Among them, the detection capability is based on the detection width, detection depth, recognition capability and command response speed of the operating equipment; the communication capability is based on the communication reliability, communication distance and communication delay of the operating equipment; the collaborative capability is based on the stability, accuracy and operating efficiency of the operating equipment during collaborative operation; the maintenance capability is based on the maintenance efficiency, economic cost, maintenance quality and environmental impact of the operating equipment during maintenance.

8. A method and device for evaluating the effectiveness of deep-sea operations based on simulation data, characterized in that: The device comprises: A first acquisition module is used to deduce the deep-sea operation tasks completed by the deep-sea operation system based on the simulation deduction platform to obtain simulation deduction data, wherein the simulation deduction data includes: deep-sea environment data, multiple operation equipment corresponding to the deep-sea operation task, the equipment status corresponding to each operation equipment, and the operation task performed by each operation equipment; A second acquisition module is used to acquire the availability vector, credibility vector and capability vector evaluated by the deep-sea operation system before performing the operation task, wherein the availability vector is used to characterize the probability that the operation equipment is in a fault-free state when starting to perform the operation task, the credibility vector is used to characterize the probability that the operation equipment is in a normal working state during the execution of the operation task, and the capability vector is used to characterize the probability that the operation equipment completes the operation task within a preset time and under preset conditions; The performance evaluation module is used to perform the following performance evaluation process on each operating equipment and each operating task based on the simulation deduction data: Determine a first correction value based on the equipment status, determine a second correction value based on the deep-sea environment data, and determine a third correction value based on the operation task; use the first correction value to correct the availability vector to obtain a target availability vector, use the second correction value to correct the credibility vector to obtain a target credibility vector, and use the third correction value to correct the capability vector to obtain a target capability vector; input the target availability vector, the target credibility vector, and the target capability vector into a preset operation performance evaluation formula to obtain the operation performance output by the operation performance evaluation formula; The operation performance evaluation formula is: E = ADC; Wherein, E represents the operation efficiency, A represents the target availability vector, D represents the target credibility vector, and C represents the target capability vector; Among them, one operation task corresponds to at least one operation equipment.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the deep-sea operation performance evaluation method based on simulation data as described in any one of claims 1 to 7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the deep-sea operation performance evaluation method based on simulation deduction data as described in any one of claims 1 to 7 are implemented.

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