Monitoring device, display method and program

Abstract

To provide a monitoring device capable of outputting the probability of damage or the like to a monitoring target.SOLUTION: A monitoring device comprises: a sensor information acquisition unit for acquiring sensor information measured by a sensor; a damage level / failure probability evaluation unit for calculating a failure probability and a damage level for each part or device constituting an evaluation target using the sensor information; and a display control unit for displaying the sensor information and the failure probability or the damage level for the part or the device.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a monitoring device, a display method, and a program. [Background technology]

[0002] Industrial machines are equipped with many sensors, which generate a large amount of diverse sensor information. Acquiring sensor information that represents the operating characteristics of the machines is particularly important, and it is common to update digital models of industrial machines constructed in cyberspace with sensor information and to monitor and analyze the industrial machines using data obtained from the digital models. Patent Document 1 discloses a system that acquires sensor information that represents the operating characteristics of machines installed in oil and gas production facilities and generates a digital model of the machines based on user input via a GUI (Graphical User Interface). Patent Document 2 discloses an interactive monitoring system that visually displays the output values ​​of a digital model of machines in oil and gas production facilities. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] U.S. Patent No. 10,884,402 [Patent Document 2] U.S. Patent No. 10,746,015 Summary of the Invention [Problem to be solved by the invention]

[0004] When monitoring industrial machinery, plants, etc., in addition to acquiring sensor information and observing the state of the target, information such as the probability of breakage or the degree of damage is also required. Patent Documents 1 and 2 do not disclose a function to analyze and output this information.

[0005] The present disclosure provides a monitoring device, a display method, and a program that can solve the above problems. [Means for solving the problem]

[0006] The monitoring device disclosed herein includes a sensor information acquisition unit that acquires sensor information measured by a sensor, a damage degree / damage probability evaluation unit that uses the sensor information to calculate the damage probability or the damage degree for each part or device that constitutes an evaluation object, and a display control unit that displays the sensor information and the damage probability or the damage degree for the part or device. The object to be evaluated is a ship, and the damage / failure probability evaluation unit calculates the wave load acting on the ship using the position and orientation of the object to be evaluated and the wave information at the position acquired by the sensor information acquisition unit, calculates the probability that the fatigue damage based on the calculated wave load will exceed a threshold value as the failure probability due to fatigue crack initiation, calculates the amount of corrosion corresponding to the elapsed time as the damage based on a corrosion amount prediction model that indicates the relationship between the elapsed time since the occurrence of corrosion and the amount of corrosion, extracts the statistical failure rate λ of equipment equipped on the ship from a failure rate database in which the statistical failure rate for each piece of equipment is registered, and calculates the failure probability of the equipment in a time interval t as λe -λt Calculate as follows.

[0007] The display method of the present disclosure includes: The computer acquiring sensor information measured by a sensor; The computer A step of calculating a damage probability or a damage degree for each part or device constituting the evaluation object using the sensor information; The computer and a step of displaying the sensor information and the damage probability or the damage degree of the part or the device. The object to be evaluated is a ship, and in the step of calculating the failure probability or damage degree, a wave load acting on the ship is calculated using the position and orientation of the object to be evaluated and the wave information at the position acquired in the step of acquiring, and the probability that the fatigue damage degree based on the calculated wave load will exceed a threshold is calculated as the failure probability due to fatigue crack initiation, the corrosion amount corresponding to the elapsed time is calculated as the damage degree based on a corrosion amount prediction model showing the relationship between the elapsed time since the occurrence of corrosion and the corrosion amount, and a statistical failure rate λ of equipment provided on the ship is extracted from a failure rate database in which the statistical failure rate for each equipment is registered, and the failure probability of the equipment in a time interval t is calculated as λe -λt Calculate as follows.

[0008] The program of the present disclosure includes the steps of: acquiring sensor information measured by a sensor; calculating a damage probability or a damage degree for each part or device constituting an evaluation object using the sensor information; and displaying the sensor information and the damage probability or the damage degree for the part or device. the object to be evaluated is a ship, and the method calculates a wave load acting on the ship using the position and orientation of the object to be evaluated and the wave information at the position acquired in the acquiring step, calculates the probability that the fatigue damage level based on the calculated wave load will exceed a threshold as a failure probability due to fatigue crack initiation, calculates the corrosion level according to the elapsed time as the damage level based on a corrosion level prediction model showing the relationship between the elapsed time since the occurrence of corrosion and the corrosion level, extracts a statistical failure rate λ of equipment provided on the ship from a failure rate database in which the statistical failure rate for each equipment is registered, and calculates the failure probability of the equipment in a time interval t as λe -λt The process of calculating Execute the following. [Effects of the Invention]

[0009] According to the above-described monitoring device, display method, and program, it is possible to calculate the probability of failure or the degree of damage, and output the calculated probability of failure or the degree of damage. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 illustrates an example of a monitoring device according to an embodiment. [Figure 2]FIG. 10 is a diagram illustrating an example of an operation of the monitoring device according to the embodiment. [Figure 3] FIG. 2 is a first diagram showing an example of driving countermeasure evaluation according to the embodiment. [Figure 4] FIG. 2 is a first diagram showing an example of a maintenance countermeasure evaluation according to the embodiment. [Figure 5] FIG. 10 is a second diagram showing an example of a maintenance countermeasure evaluation according to the embodiment. [Figure 6] FIG. 10 is a third diagram illustrating an example of a maintenance countermeasure evaluation according to the embodiment. [Figure 7] FIG. 4 is a fourth diagram showing an example of a maintenance countermeasure evaluation according to the embodiment. [Figure 8] FIG. 10 is a second diagram showing an example of driving countermeasure evaluation according to the embodiment. [Figure 9] FIG. 2 is a first diagram showing an example of a layout of a monitoring screen according to the embodiment. [Figure 10] FIG. 10 is a second diagram showing an example of the layout of the monitoring screen according to the embodiment. [Figure 11] FIG. 10 is a third diagram showing an example of the layout of the monitoring screen according to the embodiment. [Figure 12] FIG. 4 is a fourth diagram showing an example of a layout of a monitoring screen according to the embodiment. [Figure 13A] FIG. 10 is a first diagram showing an example of an insight screen according to the embodiment. [Figure 13B] FIG. 10 is a second diagram showing an example of an insight screen according to the embodiment. [Figure 13C] FIG. 10 is a third diagram showing an example of an insight screen according to the embodiment. [Figure 14A] FIG. 10 is a first diagram showing an example of a risk analysis screen (summary) according to the embodiment. [Figure 14B] FIG. 2 is a second diagram showing an example of a risk analysis screen (summary) according to the embodiment. [Figure 14C] FIG. 10 is a third diagram showing an example of a risk analysis screen (summary) according to the embodiment. [Figure 15A] FIG. 10 is a first diagram showing an example of a risk analysis screen (individual) according to the embodiment. [Figure 15B]FIG. 2 is a second diagram showing an example of a risk analysis screen (individual) according to the embodiment. [Figure 15C] FIG. 10 is a third diagram showing an example of a risk analysis screen (individual) according to the embodiment. [Figure 16] FIG. 10 is a diagram illustrating an example of a sensor information screen according to the embodiment. [Figure 17] FIG. 2 illustrates an example of a hardware configuration of a monitoring apparatus according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] First Embodiment A monitoring device 10 according to an embodiment of the present disclosure will be described below with reference to FIGS. (composition) FIG. 1 is a diagram illustrating an example of a monitoring device according to an embodiment. The monitoring device 10 acquires and accumulates measurement values ​​(referred to as sensor information) output by various sensors provided in machines and equipment to be monitored, and calculates and displays information such as the probability of damage to the machines and equipment, the impact of failures, and countermeasures for those damages. The machines and equipment to be monitored are not limited, and the monitoring device 10 can be used for monitoring and risk management of turbines, compressors, boilers, ships, aircraft, vehicles, power plants, chemical plants, and the like. The following description will be given taking a case where a ship 1 is the monitoring target as an example. The ship 1 is, for example, a marine structure such as a ship sailing on the ocean, an FPSO (Floating Production, Storage, and Offloading system), or an FSO (Floating Storage and Offloading system). The marine structure includes not only the main body but also mooring chains and piles for mooring the marine structure. As illustrated, the monitoring device 10 includes a sensor information acquisition unit 11, an input unit 12, a control unit 13, and a memory unit 19.

[0012] The sensor information acquisition unit 11 acquires sensor information measured by various sensors on the ship 1, such as an acceleration sensor, a strain sensor, a wave radar, a thickness measurement sensor, a GPS (Global Positioning System) or GNSS (Global Navigation Satellite System) receiver, a flow rate sensor, a pressure sensor, a temperature sensor, a rotation speed sensor installed in the engine room, and a mooring chain tilt sensor, and stores the information in the storage unit 19 in association with the measurement time. The sensor information acquisition unit 11 also acquires values ​​calculated using measurements from the various sensors and wave forecast information. The input unit 12 is configured using input devices such as a keyboard, a mouse, a touch panel, and buttons, and accepts input from a user using the input device. For example, the input unit 12 accepts operations such as pressing buttons on various monitoring screens (described later) and selecting display items.

[0013] The control unit 13 uses the damage / damage probability evaluation unit 14 to the display control unit 18, which will be described later, to calculate and control output processes for information such as evaluation of the probability of damage, evaluation of the impact of failure, and countermeasures for those. The control unit 13 includes the damage / damage probability evaluation unit 14, a failure impact evaluation unit 15, an operation countermeasure evaluation unit 16, a maintenance countermeasure evaluation unit 17, and a display control unit 18. The damage / damage probability evaluation unit 14 calculates the damage probability (damage indicates that equipment, etc., is broken due to crack propagation, corrosion, wear, etc.) or equipment failure probability (failure indicates a state in which equipment does not operate normally, equipment malfunctions, etc.) of each component and equipment constituting the ship 1, and the damage. The failure impact evaluation unit 15 calculates the impact when a component or equipment of the ship 1 is damaged or fails (hereinafter, this may be referred to as the impact of failure, but it includes not only failure but also damage). The failure impact assessment unit 15 can calculate the impact from the perspective of cost (e.g., repair costs), safety (e.g., the impact on people on board the ship 1), environmental impact (e.g., the impact if oil leaks into the ocean), and manufacturing / production (e.g., if the ship 1 is an FPSO, oil is produced on the FPSO, and the extent to which damage to parts or equipment of the ship 1 affects oil production). The operational measure assessment unit 16 calculates operational measures to reduce damage to the ship 1. For example, based on the damage probability and damage degree calculated by the damage degree / damage probability assessment unit 14 and the impact calculated by the failure impact assessment unit 15, the operational measure assessment unit 16 calculates an operation method of the ship 1 (an operation method is an example of an operation measure) that avoids damage or failure of parts with a high probability of damage or parts with a high impact in the event of a failure. The maintenance measure assessment unit 17 calculates maintenance measures for the ship 1. For example, the maintenance measure evaluation unit 17 calculates the timing and cycle of efficient maintenance (the timing and cycle of maintenance are examples of maintenance measures) for parts with a high probability of breakage or parts that will be greatly affected in the event of a breakdown. The control unit 13 performs a final evaluation based on the intermediate evaluation of the probability of breakage, the degree of damage, the degree of impact, operational measures, maintenance measures, etc.Then, the display control unit 18 outputs the final assessment (operational measures, maintenance measures, etc. according to the O&M (Operation and Maintenance) conditions) and the interim assessment (calculated failure probability, damage level, impact level, and data on the calculation process of the operational measures and maintenance measures) to a graph or the like. By displaying the operational measures and maintenance measures according to the O&M conditions along with the interim assessment, the basis for the final assessment can be presented to the user. Furthermore, the control unit 13 processes the sensor information acquired by the sensor information acquisition unit 11 and records the processed values ​​in the storage unit 19. For example, the control unit 13 may calculate the horizontal bending moment from the port and starboard measurement values ​​obtained by the strain sensors and record the calculated values ​​in the storage unit 19.

[0014] The display control unit 18 generates a monitoring screen (image) including information such as sensor information of the ship 1 (for example, the latest acquired sensor information), the trend of sensor information accumulated over a predetermined period, the degree of damage accumulated in each part of the ship 1 indicated by the sensor information, the probability of damage, the impact from various perspectives in the event of damage or failure, operational measures, maintenance measures, etc., and displays it on the display device 2.

[0015] The memory unit 19 stores failure statistical information 191, FMEA 192, test information 193, design information 194, manufacturing information 195, assembly / installation / construction information 196, analysis model 197, monitoring information 198, maintenance history information 199, maintenance cost and construction period information 19A, user information, etc. The failure statistical information 191 includes the failure history of the ship 1. The FMEA 192 includes information on the failure risk calculated by FMEA (Failure Mode and Effect Analysis) performed when the ship 1 was designed. The test information 193 includes information on various tests performed on the ship 1. The design information 194 includes design information of the ship 1. The manufacturing information 195 includes information indicating how the ship 1 was manufactured. The assembly / installation / construction information 196 includes assembly, installation, and construction information for each part and equipment of the ship 1. The analysis model 197 is a digital model of the structure of the ship 1 modeled using FEM (Finite Element Method) or the like. The monitoring information 198 includes sensor information acquired by the sensor information acquisition unit 11. The maintenance history information 199 includes the maintenance history of the ship 1. The maintenance cost / construction period information 19A includes information on the cost and construction period required for maintaining the ship 1. The user information includes information on the user's account and authority. In addition, the memory unit 19 stores information defining for each ship 1 which parts and equipment will be processed in the processing described below, and which failure modes will be analyzed for which parts and equipment, as well as a life assessment model and a corrosion prediction model. A failure mode refers to the type of damage, such as fatigue crack initiation, fatigue crack propagation, corrosion, or wear, and the nature of the damage or failure.

[0016] (operation) FIG. 2 is a diagram illustrating an example of the operation of the monitoring device 10 according to the embodiment. For example, when a user specifies a ship 1, the input unit 12 acquires identification information of the specified ship and outputs it to the control unit 13. The control unit 13 sets a part i (i = 1 to n) among the parts constituting the ship 1 to be subjected to risk evaluation processing (step S1). Here, the risk in the risk evaluation is a value obtained by multiplying the probability of damage by the impact of a failure. The parts to be processed may be predetermined or may be arbitrarily set by the user. The range of parts may be broadly classified, such as the bow, stern, bottom, port side, starboard side, and bridge, or may be a range obtained by subdividing each of these parts. Instead of or in addition to parts, equipment (pumps, engines, tanks, turbines, generators, propellers, etc.) provided on the ship 1 may be set as a single part. The control unit 13 sets the part i (i = 1 to n) to be subjected to calculation of the probability of damage, etc.

[0017] Next, the control unit 13 sets a failure mode j (j=1 to m) for each set portion i (step S2). The failure mode j includes fatigue crack initiation, fatigue crack propagation, corrosion, wear, creep, etc. The failure mode may be determined for each portion i, or the user may be able to arbitrarily set which failure mode the portion will be evaluated for.

[0018] Next, the control unit 13 evaluates the probability of occurrence of failure mode j (damage probability, failure probability) and / or the damage degree, impact of failure, operational measures, and maintenance measures for each failure mode j using the damage degree / failure probability evaluation unit 14, failure impact evaluation unit 15, operational measures evaluation unit 16, and maintenance measures evaluation unit 17. The control unit 13 also calculates the damage degree and risk of the current part i and failure mode j, and the damage degree and risk of the future part i and failure mode j according to the O&M (Operation and Maintenance) conditions (step S3). As described above, the risk is the value obtained by multiplying the damage probability by the impact of failure.

[0019] Below, the details of the evaluation process for each case will be explained using examples where failure mode j is "fatigue crack occurrence," "corrosion," and "equipment failure." In the following explanation, the damage / failure probability evaluation unit 14 performs a failure probability evaluation, the failure impact evaluation unit 15 performs a failure impact evaluation, the operational measure evaluation unit 16 performs an operational measure evaluation, and the maintenance measure evaluation unit 17 performs a maintenance measure evaluation.

[0020] (1) Fatigue crack initiation in any structural part (1-1) Breakage probability evaluation The damage / failure probability evaluation unit 14 calculates the stress response function Φ of the evaluation target part by using design information 194 such as the structural shape and dimensions of the evaluation target and design load conditions (statistical values ​​of natural loads such as wave loads, and oil loading conditions in the case of FPSO / FSO) and finite element analysis using an analysis model 197. R (ω) (Response Amplitude Operator; RAO) is derived. The stress response function is a function of the angular frequency ω, etc.

[0021] During the assembly and installation stages of the actual machine, if assembly / welding or other work is performed that deviates from the design, or if measurements after assembly and installation reveal changes in the structural characteristics assumed at the time of design, the stress response of the evaluation portion may change. In such cases, the damage and failure probability evaluation unit 14 reflects the assembly / installation / construction information 196 in the analysis model 197 and the life evaluation model based on the assembly / installation / construction information.

[0022] The monitoring information 198 includes the position and orientation of the ship, acquired by GPS or GNSS, or wave information (wave height, wave direction, wave period) at the target location. The damage and failure probability evaluation unit 14 uses this information to calculate the wave spectrum S(ω) as the wave load acting on the marine structure (ship 1). The fatigue crack initiation life is defined as the state in which the fatigue damage level D exceeds 1. When fatigue evaluation is performed in the frequency domain, the fatigue damage level D accumulated over a certain evaluation period T can be evaluated, for example, using the following equation (1):

[0023]

number

[0024] where m R0 is the zeroth-order spectral moment of the stress response, and the stress response function Φ R (ω) and the wave spectrum S(ω) can be calculated using the following equation (2).

[0025]

number

[0026] Additionally, v0 is the average zero-crossing period. â and m are fatigue strength parameters set from design information such as literature values ​​and in-house test information 193. Fatigue strength has aleatoric uncertainty, generally represented by the fatigue strength parameter â. By evaluating the uncertainty of the fatigue strength parameter â using a probability distribution such as a log-normal distribution and calculating the probability distribution of the fatigue damage level D, the failure probability can be formulated as the probability p (D > 1) that D is 1 or greater. Furthermore, if maintenance history information 199, such as component inspection, reinforcement, and replacement history, is acquired on the actual machine, this maintenance history information 199 is reflected in the assessment of fatigue damage levels. For example, even if a structural part has a service life of 15 years, if the evaluation part i was replaced in the 12th year of service, the fatigue damage level assessment is performed using only the load history from the time of replacement in the 12th year of service. Furthermore, damage history data acquired through inspection can also be used to correct the fatigue assessment model. Furthermore, if the evaluation period T is set appropriately, the future fatigue damage level D (future damage level) can be predicted using equation (1).

[0027] (1-2) Failure impact assessment The failure impact of a failure of a target component is usually evaluated using FMEA 192 along with the failure frequency, failure detectability, and the like. The failure impact evaluation unit 15 calculates the impact based on FMEA 192. In this case, the impact is evaluated using multifaceted KPIs (Key Performance Indices), such as (A) safety (human impact), (B) environmental impact, (C) losses associated with the production and operation shutdown of related equipment, and (D) the amount of damage caused by the failure. In this case, the maintenance response costs and equipment downtime are evaluated with reference to the data on maintenance cost and construction period information 19A. For example, if the outer shell of an FPSO oil tank (an example of component i) is adjacent to the external environment (atmosphere, ocean), damage to the oil tank outer shell could lead to oil spillage into the ocean, and the environmental impact is determined to be high.

[0028] (1-3) Driving Measures Evaluation If the ship 1 is a moving vessel, the damage and failure probability evaluation unit 14 can combine the direction of travel and wave forecasts contained in the monitoring information 198 to evaluate the accumulation of fatigue damage according to the route and suggest a route that will mitigate fatigue accumulation. This is determined while taking into account trade-offs such as increases or decreases in sailing time and fuel consumption due to route changes. For an offshore structure moored at a certain location, such as an FPSO / FSO, the damage and failure probability evaluation unit 14 can predict the stress response and fatigue accumulation of each part according to the load capacity of each oil tank (an example of the monitoring information 198). This allows for improvements to be considered for the oil tank operation method and the mitigation of fatigue accumulation in the evaluated parts. The operational countermeasure evaluation unit 16 selects the route with the least accumulated fatigue damage from among multiple routes, and selects the operation method with the least fatigue accumulation from among multiple oil tank operation methods.

[0029] For example, the operational countermeasure evaluation unit 16 calculates the traveling direction (route) and speed of the ship 1 that can mitigate the accumulation of fatigue based on the relationship between the traveling direction of the ship 1 and the direction and strength of waves, or calculates the orientation and position of the ship 1 according to the load capacity of the oil tank. The display control unit 18 may display the operational countermeasures calculated by the operational countermeasure evaluation unit 16 as a diagram as shown in FIG. 3. For example, the operational countermeasure evaluation unit 16 calculates a critical operating range, a standard operating range, and an appropriate operating range for the traveling direction and speed that can reduce the load received from waves. For example, the operational countermeasure evaluation unit 16 calculates the appropriate operating range as ±X° centered on the north, the standard operating range as ±X1° centered on the north (X1>X), and the critical operating range as ±X2° centered on the north (X2>X1) for the traveling direction. Furthermore, the operational countermeasure evaluation unit 16 calculates the traveling speed as follows: ±Y1 (km / h) centered on Y as the appropriate operating range, ±Y2 (km / h) centered on Y (Y2>Y1) as the standard operating range, and ±Y3 (km / h) centered on Y (Y3>Y2) as the critical operating range. The display control unit 18 receives the two control parameters of the traveling direction and the traveling speed from the operational countermeasure evaluation unit 16, and, as shown in Fig. 3, may display a heat map of the magnitude of the benefit (in this case, the benefit is that the ship 1 receives less damage from waves) using the two selected control parameters as axes, and output a two-dimensional graph with borders that represent the critical operating range, the standard operating range, and the appropriate operating range.

[0030] (1-4) Maintenance measures evaluation While reinforcement or replacement of the target part can mitigate or repair the accumulated fatigue damage, implementing countermeasures incurs costs. Risk-based engineering considers the risk, defined as the product of the probability of failure and the impact of failure, by taking into account the cost of equipment restoration measures (construction costs, spare part holding costs, material costs, etc., assessed with reference to maintenance cost and construction period information 19A). Appropriate countermeasures are considered while considering the trade-off between the two. An example of the evaluation method is shown in Figures 4 and 5. The graph in Figure 4 shows a simulation of the amount of thinning, setting the uncertainty of the assumed worst-case to best-case progression of deterioration (amount of thinning) occurring in the target part i as a probability distribution. In the example in Figure 4, two replacements are performed at predetermined intervals during the service life. Furthermore, the probability Pf that the amount of thinning of the target part exceeds the failure limit at each replacement cycle represents the failure probability of the target part. For example, the maintenance measure evaluation unit 17 calculates the failure probability per replacement cycle and the number of maintenance operations for the target part i according to the replacement cycle, and then calculates the expected number of failures during the service life from the product. Figure 5 shows an example of the relationship between preventive maintenance costs, corrective maintenance costs, and total maintenance costs according to the replacement cycle. The maintenance measure evaluation unit 17 calculates the preventive maintenance costs for the target part and the expected value of corrective maintenance costs calculated from the expected number of times the target part breaks. The preventive maintenance costs are the costs required to replace the target part. The corrective maintenance costs are calculated as an expected value by multiplying the unit cost required for actual corrective maintenance (maintenance cost / work period information 19A) by the expected number of times the part breaks. The graph in Figure 5 shows an example of the relationship between the length of the replacement cycle of target part i and the preventive maintenance costs, corrective maintenance costs, and the total maintenance costs, which are the sum of these. The longer the replacement cycle, the smaller the preventive maintenance costs. On the other hand, the longer the replacement cycle of target part i, the higher the corrective maintenance costs. For example, the maintenance measure evaluation unit 17 sets the replacement cycle that minimizes the total maintenance costs, which are the sum of the preventive maintenance costs and corrective maintenance costs, as the optimal replacement cycle.

[0031] (2) Corrosion assessment of any structural part (2-1) Breakage probability evaluation The corrosion damage state of the target part is estimated from statistical information in literature, past failure statistical information191, and design information194 such as corrosion prediction formulas according to the operating environment (temperature, humidity, etc.). For example, the corrosion damage occurrence and progression model is divided into two stages: (a) a corrosion occurrence time model that predicts when corrosion will occur, and (b) a corrosion amount prediction model that predicts the progression of corrosion thinning after corrosion has occurred. Since corrosion damage is a phenomenon with a large variance, probability and statistical methods are generally used. When using past performance statistical information, the corrosion damage occurrence time T C can be estimated directly from a probability distribution, for example the log-normal distribution shown below.

[0032]

number

[0033] The time-series corrosion amount d(t) is estimated, for example, from the following exponential law (Equation (4)). d(t)=a(tT C ) b ···(4) where the logarithmic mean T C , logarithmic standard deviation σ TCThe power law parameters a and b related to the amount of corrosion are estimated from, for example, past damage data and statistical data (design information 194). If any corrosion protection treatment has been performed on the actual equipment being evaluated, the related assembly / installation / construction information 196 is reflected in the corrosion prediction model. Examples of monitoring information 198 include monitoring information 198 from ultrasonic wall thickness measurement sensors, which can be used for soundness assessment, including measurement errors. Furthermore, if explanatory variables such as temperature and humidity are used to predict corrosion damage and this monitoring information 198 is available, the damage / failure probability evaluation unit 14 reflects this information in the corrosion prediction model. Furthermore, if maintenance history information 199, such as the inspection, reinforcement, and replacement history of components, is acquired from the actual equipment, the damage / failure probability evaluation unit 14 reflects this information in the corrosion assessment. For example, even if a structure has been in service for 15 years, if the evaluation part was replaced in the 12th year of service, the corrosion assessment will be performed from the time of replacement in the 12th year of service onward. In addition, damage history data obtained through inspections can be used to correct the damage progression rate model. Note that the corrosion amount d(t) is an example of damage. Equation (4) can be used to predict the future corrosion amount d(t) (future damage).

[0034] (2-2) Failure impact assessment The failure impact assessment is the same as in the case of fatigue crack initiation (1-2).

[0035] (2-3) Evaluation of driving measures none

[0036] (2-4) Maintenance measures evaluation The evaluation of maintenance measures is the same as in the case of fatigue crack occurrence (1-4), except that corrosion prevention treatment is carried out instead of reinforcement work.

[0037] (3) Equipment failure on offshore structures Generally, various types of machinery and equipment are mounted on offshore structures. Floating offshore wind turbines are equipped with generators and gearboxes, while FPSOs are equipped with pumps, valves, generators, gas turbines, gas-liquid separators, etc. This section provides examples of equipment mounted on structures.

[0038] (3-1) Failure probability evaluation Equipment failures include not only obvious damage events such as crack initiation but also functional malfunctions such as valve malfunctions and reduced pump performance. Equipment failure prediction can be performed in two ways: (a) using an aging degradation model centered on design information for fatigue crack initiation and corrosion evaluation, or (b) using equipment failure statistics, primarily a random failure model. Regarding (a), as mentioned above, evaluation is performed using various information, including various design and manufacturing information. Regarding (b), failure statistics information 191 includes in-house databases compiled by analysts at their own institutions and public failure rate databases (such as the Offshore and Onshore Reliability Database (OREDA)). These databases are analyzed to extract the statistical failure rate λ of the target equipment. To match the equipment listed in the public failure rate database with the equipment being evaluated, information with high similarity is selected and used, referring to equipment design and manufacturing information 195. The statistical failure rate λ is the probability parameter of the exponential distribution f(t;λ) = λexp[-λt], which is a probabilistic model of the time interval between random failures.

[0039] (3-2) Failure impact assessment The failure impact assessment is the same as in the case of fatigue crack initiation (1-2).

[0040] (3-3) Evaluation of driving measures none

[0041] (3-4) Maintenance measures evaluation Because it is difficult to predict when random failures will occur, maintenance measures primarily focus on early recovery from failures by stocking spare parts. The probability mass of the number of random failures x occurring in a given evaluation period T can be evaluated using the Poisson distribution P(x│m=λT) in the following equation (5).

[0042]

number

[0043] The gain from avoiding prolonged outages due to failures corresponding to the number of spare parts held can be calculated probabilistically from the above-mentioned probability mass function P(x|m=λT) and an evaluation of the impact of each failure. Adding up the spare part holding costs (spare part holding costs, warehouse fees, taxes, etc.) corresponding to the number of spare parts held makes it possible to calculate the optimal number of spare parts held that maximizes the gain minus the costs. The evaluation of spare part holding costs and the impact of failures is set based on maintenance cost and construction period information and FMEA.

[0044] As a specific example of losses due to the impact of a failure resulting from the shutdown of production and operation of related facilities (C) above, for example, economic losses (such as lost production and power generation opportunities, labor costs, and costs for replacement machinery and fuel) occur when an FPSO production stoppage or an offshore wind turbine stops generating power. For example, the maintenance measure evaluation unit 17 calculates the number of spare parts to be held that minimizes the total value obtained by subtracting costs from profits by combining the prediction of the number of failures over the evaluation period T, the evaluation of the impact of failures, and the evaluation of the cost of holding spare parts. The graph in Figure 6 shows the relationship between the effectiveness of avoiding prolonged outages due to failures and the cost of holding spare parts, depending on the number of spare parts held. The vertical axis of Figure 6 represents the amount of money, and the horizontal axis represents the number of spare parts held. Graph L1 represents the effectiveness of holding spare parts in avoiding prolonged outages due to failures, graph L2 represents the cost of holding spare parts, and graph L3 represents the effectiveness of preventing prolonged outages due to failures relative to the cost of holding spare parts. The maintenance measure evaluation unit 17 calculates functions L1 to L3 in Figure 6 using the number of spare parts held as an evaluation index. 6, when the number of spare parts held is 12, the effect of preventing prolonged breakdowns relative to the cost of holding spare parts is maximized, so the maintenance measure evaluation unit 17 sets the optimal number of spare parts to be held to "12." Regarding the holding of spare parts, by optimizing the situation including the status of multiple systems that have common spare parts, rather than managing them in a single system, it becomes possible to reduce spare part costs.

[0045] Similarly to the process described with reference to FIG. 5, the timing of repairs and replacements that optimize preventive and corrective maintenance costs for each piece of equipment can be calculated based on the equipment failure probability and pre- and post-maintenance costs. For example, the maintenance measure evaluation unit 17 calculates the total preventive maintenance costs and the total post-maintenance costs required for maintenance of all parts and equipment of the ship 1, assuming that maintenance is performed at a certain interval. This is considered to be one maintenance menu. The maintenance measure evaluation unit 17 calculates the total preventive maintenance costs and the total post-maintenance costs for various maintenance menus when the maintenance interval is varied. FIG. 7 shows the preventive maintenance costs and post-maintenance costs for various maintenance menus. The display control unit 18 may output a graph, as shown in FIG. 7, plotting the total preventive maintenance costs and the total post-maintenance costs for each maintenance menu calculated by the maintenance measure evaluation unit 17. Referring to the graph in FIG. 7, the user can select a maintenance menu 71 that reduces both preventive and post-maintenance costs.

[0046] Furthermore, for example, the operational countermeasure evaluation unit 16 may calculate comparative information on economic efficiency based on the results of simulating the traveling speed of the ship 1 under the initial conditions and the optimized traveling speed. For example, the damage / damage probability evaluation unit 14 calculates the damage probability of a certain piece of equipment on the ship 1 based on a predetermined traveling speed and a wave forecast. The predetermined traveling speed is shown in the speed curve g1 of the graph 81 in the upper part of FIG. 8, and the change in the damage probability at that time is shown in the damage probability curve g3 of the graph 82 in the lower part of FIG. 8. The damage / damage probability evaluation unit 14 also calculates the damage probability of the corresponding part when the ship 1 is navigated at a speed calculated by the operational countermeasure evaluation unit 16 that reduces the impact of waves. The traveling speed when the operating method calculated by the operational countermeasure evaluation unit 16 is adopted is shown in the speed curve g2 of the graph 81, and the change in the calculated damage probability is shown in the damage probability curve g4 of the graph 82. The display control unit 18 may generate and display a graph such as the one shown in FIG. 8. In addition, the driving countermeasure evaluation unit 16 may calculate a value by subtracting the value obtained by multiplying the maintenance cost and the amount of damage when sailing at the speed indicated by g2 by the probability of damage of 20% from the value obtained by multiplying the maintenance cost and the amount of damage when sailing at the speed indicated by g1 by the probability of damage of 100%, to determine the potential lost revenue when the driving method calculated by the driving countermeasure evaluation unit 16 is adopted, and display this value on the display device 2 together with the graph of FIG. 8.

[0047] As described above with some examples, the control unit 13 (damage degree / breakage probability evaluation unit 14, failure impact evaluation unit 15, operational countermeasure evaluation unit 16, maintenance countermeasure evaluation unit 17) calculates the current and future failure probability, damage degree, impact, risk (= failure probability × impact), operational countermeasure, maintenance countermeasure, etc. of the part i and failure mode j using a known calculation method appropriate for each part (step S4).

[0048] Next, the control unit 13 (display control unit 18) visualizes the information calculated up to that point (step S4). For example, the display control unit 18 generates monitoring screens exemplified in FIGS. 9 to 12 and outputs them to the display device 2. The monitoring screens include an insight screen 100, a risk analysis screen 200, and a sensor information screen 300. These screens can be switched and displayed by selecting them in the menu area 101 shown in FIG. 9 etc.

[0049] (Monitoring screen type) Figure 9 shows an example of the layout of the insight screen 100. The insight screen 100 is a screen that functions like a dashboard and displays an overall picture of the damage and risks accumulated on the ship 1, information of high urgency, information updated daily, processed sensor information, and information of interest to the user. The insight screen 100 includes a menu area 101, a header area 102, and an information display area 103. Buttons 101A to 101C are arranged in the menu area 101. When button 101A is selected, the display control unit 18 displays the insight screen 100. When button 101B is selected, the display control unit 18 displays the risk analysis screen 200. When button 101C is selected, the display control unit 18 displays the sensor information screen 300. The header area 102 displays the name of the screen (e.g., dashboard), identification information of the ship 1, a user ID, etc. The information display area 103 displays various information related to the damage status and risks of the ship 1. Information display area 103 is divided into areas 103A to 103G, for example, and different information is displayed in each area. An example of the display content will be described later. Note that the arrangement of areas 103A to 103G shown in Fig. 9 is one example. For example, area 103A and area 103B may be arranged adjacent to each other in the vertical direction.

[0050] Figure 10 shows an example of the layout of the risk analysis screen 200 (summary screen 200). The risk analysis screen 200 is a screen that displays in more detail the overall trends in damage and risks accumulated on the ship 1. The risk analysis screen 200 can be switched between a summary screen 200 (Figure 10) that displays the overall status of risks, etc., and an individual screen 200' (Figure 11) that displays detailed information for each individual failure mode. The summary screen 200 includes a menu area 201, a header area 202, a switching tab area 203, a KPI (Key Performance Indices) setting area 204, and an information display area 205. The menu area 201 is the same as that of the insight screen 100. The header area 102 displays the name of the screen (e.g., Risk Analysis (Summary)), identification information for the ship 1, a user ID, etc. The switching tab area 203 displays "Summary," "Fatigue Crack," "Corrosion," "Creep," and so on. When "Summary" is selected, a summary screen 200, as shown in FIG. 10, is displayed. When "Fatigue Crack" or "Corrosion" is selected, an individual screen 200' displaying information about "Fatigue Crack" or an individual screen 200' displaying information about "Corrosion" is displayed, respectively. In the KPI setting area 204, one or more of "Cost," "Safety," "Environment," and "Production" can be selected. These items relate to the impact of a failure. When "Cost" is selected, the amount of cost required in the event of a failure becomes an indicator. When "Safety" is selected, the amount of impact on safety becomes an indicator. When "Environment" is selected, the amount of impact on the environment becomes an indicator. For example, when the ship 1 is an FPSO, "Production" refers to oil, which is the product of the FPSO. The amount of oil that cannot be produced in the event of a failure and the amount of lost profits due to the inability to produce oil become an indicator. Furthermore, when multiple indicators are selected in the KPI setting area 204, the sum of the selected indicators becomes an indicator. The settings in the KPI setting area 204 are retained even if another item is selected in the switching tab area 203 and the individual screen 200' is displayed. The information display area 205 is divided into areas 205B to 205E, for example, and different information is displayed in each area. An example of the display content will be described later. The arrangement of the areas 205B to 205E shown in FIG. 10 is an example.For example, areas 205B and 205C may be arranged adjacent to each other in the vertical direction. Areas 205D and 205E may be the same size as area 205B. Furthermore, a switching list 205A is arranged in the information display area 205. The switching list 205A is valid for the entire summary screen 200, and individual failure modes such as fatigue crack, corrosion, and creep can be selected in the switching list 205A. When fatigue crack is selected in the switching list 205A, the summary screen 200 displays the risk for the probability of damage due to "fatigue crack." Unlike the KPI setting area 204, the content selected in the switching list 205A is not carried over to other screens (individual screens 200').

[0051] Figure 11 shows an example of the layout of a risk analysis screen 200' (individual screen 200'). The individual screen 200' is a screen that displays detailed information on the probability of failure, damage level, and risk for each failure mode. The individual screen 200' includes a menu area 201', a header area 202', a switching tab area 203', a KPI setting area 204', and an information display area 205'. The menu area 201' is similar to that of the insight screen 100. The header area 202' displays the name of the screen (e.g., risk analysis (fatigue crack)), identification information for the ship 1, a user ID, etc. The switching tab area 203' displays summary, fatigue crack, corrosion, creep, etc., and when "fatigue crack" is selected, the individual screen 200' for fatigue crack, as shown in Figure 11, is displayed. The KPI setting area 204' is similar to the KPI setting area 204 of the summary screen 200. The information display area 205' is divided into areas 205A' to 205B', for example, and different information is displayed in each area. An example of the display contents will be described later.

[0052] FIG. 12 shows an example of the layout of the sensor information screen 300. The sensor information screen 300 includes a menu area 301, a header area 302, a period designation area 303, a display item selection area 304, and an information display area 305. The menu area 301 is the same as that of the insight screen 100. The header area 302 displays the name of the screen (e.g., real-time monitoring), the identification information of the vessel 1, the user ID, and the like. The period designation area 303 includes a setting field 303a for the target period of the monitoring information (sensor information) and a scroll bar 303b. For example, if 2022 / 01 / 01 to 2022 / 01 / 31 are entered in the setting field 303a, the sensor information measured during this period will be displayed. Furthermore, by setting in this manner, the left end of the scroll bar 303b is set to 2022 / 01 / 01, and the right end is set to 2022 / 01 / 31. By moving the scroll bar 303b left or right, sensor information for any date and time between 2022 / 01 / 01 and 2022 / 01 / 31 can be displayed in the information display area 305. The display item selection area 304 is an area for selecting which sensor's measured information to display or which value calculated based on the measured information to display. For example, one or more items can be selected from the following: direction of travel, output, temperature, rotation speed, position information, wave information, strain information, acceleration, thickness, moment, fatigue damage level, crack length, and corrosion thinning amount. Note that while FIG. 12 shows selection from the display item selection area 304, items such as direction of travel and output may be arranged in tab format, allowing the user to select the monitoring information to display from among them. The information display area 305 is divided into areas 305A to 305D, for example, and different monitoring information is displayed in each area. An example of the display contents will be described later.

[0053] (Example of monitoring screen) Next, a specific example of the monitoring screen will be described.

[0054] (Insight screen) FIGS. 13A to 13C are first to third diagrams, respectively, illustrating an example of an insight screen according to an embodiment. FIG. 13A shows an example of the information display area 103 of the insight screen 100. FIGS. 13B and 13C show enlarged views. In FIG. 13B, a left area 103A1 of the area 103A displays a diagram showing the distribution of wave direction over a predetermined period, and a right area 103A2 displays a diagram showing the distribution of wave height and wave frequency over a predetermined period. The display control unit 18 displays the area 103A based on the wave information in the monitoring information 198. In area 103B, the daily damage level accumulated by the load from waves is displayed for each part. In area 103B, graphs for each of the five parts are displayed, with the vertical axis representing the damage level and the horizontal axis representing time (days). Each line in each graph represents the daily damage level, and FIG. 13B displays the progress of the daily damage level over the past month. The damage / failure probability evaluation unit 14 calculates the daily damage level for each of the five components, and the display control unit 18 displays the area 103B based on the calculation results. While the area 103B in FIG. 13B shows the daily damage level, the damage level may be displayed for a predetermined period, such as every hour or every half day. The threshold value 103B1 represents a damage level threshold. The user can compare the relationship between this threshold and the daily damage level to determine whether their daily operation was appropriate. Regarding the display of the areas 103A and 103B, the display control unit 18 may display an Integrity Operating Window (IOW) diagram, as shown in FIG. 3, on the insight screen 100. This allows the user to understand the damage level caused to each component by past wave information and past operation, and to understand what operation should be performed based on future wave forecasts to reduce the accumulation of damage to each component.

[0055] Area 103C in Figure 13B is superimposed on a structural diagram of the hull, and shows which parts have accumulated damage from fatigue cracks (damage map). Parts 103C1 to 103C4 are parts where the damage level or probability of failure is above a threshold. In the example shown, damaged parts related to fatigue cracks are displayed, but a diagram showing damaged parts due to corrosion or cracks, or parts with a high probability of equipment failure, may also be displayed. The hull structure and damaged parts may also be displayed in 3D.

[0056] Area 103D in Figure 13C displays a pie chart showing the number of parts whose damage level due to fatigue or other factors exceeds the limit threshold (103D1), the number of parts whose damage level exceeds the warning threshold (103D2), the number of parts whose cracks or fractures occur (103D3), and the number of parts whose damage level has been affected by severe weather or other factors (103D4). Area 103E displays a bar chart showing the current and future (predetermined time period, e.g., the next maintenance inspection) damage levels for each part. Threshold 103E1 indicates the limit threshold, threshold 103E2 indicates the warning threshold, 103E3 indicates the current damage level for a given part, and 103E4 indicates the future increase in damage level for that part. In other words, 103E3 + 103E4 indicates the future damage level for that part. In the case of part 103E5, the predicted future damage level exceeds the limit threshold. In such cases, operational or maintenance measures are required at least before the limit threshold is exceeded.

[0057] Area 103F in FIG. 13C displays options for countermeasures. For example, area 103F displays the target part, the failure mode, options for countermeasures (effective operational countermeasures or maintenance countermeasures), and the cost required for the countermeasures. Regarding the display of this content, for example, the operation countermeasure evaluation unit 16 and the maintenance countermeasure evaluation unit 17 select components with high damage levels for the parts with high damage levels or high risks displayed in areas 103D, 103E, and 103G, calculate an operation method to reduce the load on the selected components, or calculate an optimal maintenance menu (e.g., low-cost or early implementation), and the display control unit 18 displays the calculated countermeasures in area 103F. However, automatic evaluation systems generally have defects in the early stages of system operation. Furthermore, automatic evaluation systems may suggest countermeasures that are incompatible with the user's convenience. Therefore, users who have knowledge about damage to each part are given approval authority, and the analysis results (e.g., 103E, 103G) of the damage probability and risk, and the operation and maintenance measures (e.g., 103F) calculated by the operation measure evaluation unit 16 and the maintenance measure evaluation unit 17 are displayed to the user after the approved user approves them. This makes it possible to prevent incorrect analysis results and operation and maintenance measures from being displayed by automatic processing.

[0058] Area 103G displays a Pareto chart. The top graph shows the current risk for each part from the perspectives of cost, safety, environment, and production. The bottom graph shows the future risk for the same content. The vertical axis of the top and bottom graphs represents the magnitude of risk, and the horizontal axis represents the part. As shown in the figure, a breakdown of the risks for cost, safety, environment, and production is displayed, allowing you to understand why a particular part is high risk, that is, which aspect is causing the overall risk to be high. In addition, by comparing this with the countermeasures displayed in area 103F, you can understand why such countermeasures are necessary. Note that curves 103G1 and 103G2 represent the sum of the risk values ​​for each part, and adding up all the risk values ​​for the five parts equals 100%.

[0059] (Risk analysis screen (summary screen)) 14A to 14C are first to third diagrams, respectively, illustrating an example of a risk analysis screen (summary) according to an embodiment. FIG. 14A illustrates an example of a switching tab area 203, a KPI setting area 204, and an information display area 205 of a summary screen 200. Because "Overview" (corresponding to "Summary" in FIG. 10) is selected in the switching tab area 203, the summary screen 200 is displayed. In the information display area 205, risk is calculated based on the indicators selected in the KPI setting area 204. Because the settings in the KPI setting area 204 are the same for the individual screens 200', by switching the display content in the switching tab area 203 without changing the settings in the KPI setting area 204, it is possible to move back and forth between the summary screen 200 and the individual screens 200' while performing risk assessment based on the same indicators.

[0060] 14B and 14C show enlarged views of the information display area 205. In area 205A, "fatigue damage" is selected. This means that the failure probability in the summary screen 200 is the probability of failure due to fatigue cracks. Area 205B displays a risk matrix 205B3. The vertical axis of the risk matrix 205B3 indicates the likelihood of damage (likelihood), and the horizontal axis indicates the impact of failure (consequence). The higher the vertical axis, the higher the likelihood of failure, and the further to the right the impact, the greater the impact. In this figure, the probability of occurrence is the probability of fatigue cracks, as selected in area 205A. The impact is the sum of the impacts of the indicators selected in the KPI setting area 204. For example, if cost and environmental impact are selected in the KPI setting area 204, the sum of the impact from a cost perspective and the magnitude of the impact on the environment in the event of a failure becomes the indicator on the horizontal axis. In risk matrix 205B3, areas with low probability of occurrence and low impact are colored green in the lower left; areas with relatively low probability of occurrence and impact, areas with high probability of occurrence but low impact, and areas with high impact but low probability of occurrence are colored yellow; areas with medium probability of occurrence and impact, areas with high probability of occurrence but relatively low impact, and areas with high impact but relatively low probability are colored orange; and areas with high probability of occurrence and impact in the upper right are colored red. If there is a part with a corresponding probability of occurrence and impact, it is displayed as a dot (e.g., point 205B4) in the corresponding area of ​​risk matrix 205B3. For example, hovering the mouse pointer over the dot displays details of the part, probability of occurrence, and impact indicated by the dot. Skewer displays 205B1 and 205B2 display the number of parts included in the green, yellow, orange, and red areas, respectively, from bottom to top. 205B1 displays the current number of parts, and 205B2 displays the future number of parts. This allows the user to know the number of parts of the vessel 1 that are in a dangerous state and the number of parts that are in a safe state.

[0061] Area 205C displays a diagram similar to the Pareto chart in area 103 described in Fig. 13C. However, by making a selection in KPI setting area 204, it is possible to change the indicators displayed, such as a Pareto chart focusing on four items (cost, safety, environment, and production), a Pareto chart focusing only on cost, or a Pareto chart focusing on cost and safety.

[0062] Area 205D in FIG. 14C is superimposed on a structural diagram of the hull, showing which parts have accumulated risk (risk map). Areas 205D1 to 205D4 are areas where the risk is above a threshold. The risk here is a value calculated by multiplying the impact based on the settings in KPI setting area 204 by the probability of occurrence of the failure mode selected in area 205A. For example, if four items (cost, safety, environment, and production) are selected, the display control unit 18 calculates the risk by multiplying these four impacts by the probability of occurrence of fatigue cracks, and highlights areas where this value is above a predetermined threshold. The hull structure and high-risk areas may be displayed as a three-dimensional model.

[0063] Area 205E in FIG. 14C displays the damage map exemplified in area 103C in FIG. 13B. Areas 205E1 to 205E4 are areas where the damage level or failure probability is above a threshold. In the example shown, by selecting area 205A, areas where the damage level or failure probability related to fatigue cracks is above a threshold are displayed. By displaying the risk map in area 205D and the damage map in area 205E side by side, it is possible to individually grasp areas where damage is accumulating and areas where risk is high (for example, even if the failure probability is low, if the impact is large, the risk value will be high).

[0064] (Risk analysis screen (individual screen)) 15A and 15B are first and second diagrams, respectively, illustrating an example of a risk analysis screen (individual) according to an embodiment. FIG. 15A illustrates an example of a switching tab area 203′, a KPI setting area 204′, and an information display area 205′ of an individual screen 200′. Because “Fatigue” (corresponding to “Fatigue crack” in FIG. 11) is selected in the switching tab area 203′, an individual screen 200′ for risk analysis (fatigue crack) is displayed. In the information display area 205′, risk is calculated using the index selected in the KPI setting area 204′. The settings in the KPI setting area 204′ are the same for the individual screen 200′. In the area 205A, the part ID (column 205A1′), current risk (column 205A2′), future risk (column 205A3′), current damage level (column 205A4′), and a list of future damage levels (column 205A5′) are displayed. When the user selects a certain part, area 205B' displays operation and maintenance measures, a fatigue crack growth prediction for the selected part, and 2D and 3D diagrams of the part's location. For example, the rough location of the selected part is displayed in area 205B3' using a 2D diagram of ship 1, and the detailed location is displayed in area 205B4' using a 3D diagram. Area 205B5' also displays a 3D model diagram of the entire ship 1, with the damage status displayed in different colors.

[0065] Figure 15B shows an enlarged view of areas 205B1' and 205B2'. Area 205B1' displays operation and maintenance measures, the timing and scope of implementing the measures, and notes. Area 205B2' displays a diagram of predicted fatigue damage progression. The vertical axis of the graph in area 205B2' represents the fatigue damage level, and the horizontal axis represents time. The damage level / failure probability evaluation unit 14 performs a prediction calculation of the fatigue damage level taking into account variations in the material and load of the target area, resulting in a prediction with a width w as shown in the figure. In addition, by setting two types of thresholds, a caution threshold 205B6' and a warning threshold 205B7', it is possible to understand what level future fatigue damage will reach.

[0066] Figure 15C shows an enlarged view of the same positions (represented by areas 205B1" and 205B2") when corrosion is selected in the switching tab area 203'. Area 205B1" displays operation and maintenance measures, the timing and scope of the measures, and cautions. Area 205B2" displays a predicted corrosion progression diagram. The vertical axis of the graph in area 205B2" represents the amount of metal loss, and the horizontal axis represents time. The damage and failure probability evaluation unit 14 predicts the amount of metal loss using equation (4) above. As with the fatigue damage level, the prediction is given a range, and the upper and lower 99% limit intervals (curves u and l, respectively), the average value (curve m2), and the median value (curve m1) are displayed. The user can grasp the future trend of the amount of metal loss for the target area.

[0067] The individual screen 200' may also be provided with a function to display, for each part, FMEA 192, test information 193, design information 194, manufacturing information 195, analysis model 197, maintenance history information 199, photographs of the actual machine, and the like (for example, a call button for each piece of information). The individual screen 200' may also be provided with a function to display, for each part, the impact of a failure from the perspectives of cost, safety, environment, and production. The individual screen 200' may also be configured to display the graphs exemplified in FIGS. 4 to 8.

[0068] (Sensor information screen) Fig. 16 is a diagram showing an example of a sensor information screen according to the embodiment. Fig. 16 shows an example of a period specification area 303, a display item selection area 304, and an information display area 305 of a sensor information screen 300. When a period is specified in the setting field 303A and an item to be displayed is selected in the display item selection area 304, sensor information relating to the selected display item for the specified period is displayed in the information display area 305. In the example of Fig. 16, time-series information (information for the period specified in the setting field 303A) of the position information, heading direction, wave height, and wave direction of the ship 1 is displayed.

[0069] (effect) When monitoring machinery and equipment, it is desirable not only to observe sensor information and determine abnormalities, but also to perform risk management that takes into account the damage probability of the target equipment and the impact of failure. However, for example, damage probability assessment involves a variety of failure modes, such as fatigue, corrosion, wear, and creep, depending on the design and service environment. Therefore, the damage probability must be evaluated using failure assessment methods and models tailored to the failure mode, which creates complexity. Furthermore, risk assessments may use various metrics to measure the impact of failure, such as cost, safety (human damage), production loss, and environmental impact. In contrast, this embodiment can calculate the damage probability and damage level for failure modes specific to the component or equipment being evaluated. Furthermore, the impact levels can be calculated from the perspectives of cost, safety, the environment, and production. These can then be displayed along with the sensor information. Therefore, users can monitor the machinery and other equipment being monitored by referring to the damage and risk assessments. Furthermore, for each component and failure mode, (1) the damage probability and damage level, (2) the impact of failure, (3) operational measures, and (4) maintenance measures are evaluated, and a risk assessment is then performed as a final assessment. In addition, the transparency and consistency of the entire analysis can be ensured by displaying the calculation results, etc., performed in the evaluation process of intermediate evaluations, such as (1) failure probability and damage level, (2) failure impact level, (3) operational measures, and (4) maintenance measures, in various diagrams and graphs, and accessing and displaying design information, etc. (such as a function to call and display design information 194 from individual screen 200'). Also, by visualizing the intermediate evaluations and ensuring the transparency and consistency of the entire analysis, including the final evaluation, the user can deepen their understanding of the deterioration and damage of the machines and equipment being monitored, enabling flexible and appropriate measures.

[0070] 17 is a diagram showing an example of the hardware configuration of a monitoring device according to each embodiment. A computer 900 includes a CPU 901, a main storage device 902, an auxiliary storage device 903, an input / output interface 904, and a communication interface 905. The monitoring device 10 described above is implemented in the computer 900. The functions described above are stored in the auxiliary storage device 903 in the form of a program. The CPU 901 reads the program from the auxiliary storage device 903, loads it into the main storage device 902, and executes the above processing in accordance with the program. The CPU 901 also allocates a storage area in the main storage device 902 in accordance with the program. The CPU 901 also allocates a storage area in the auxiliary storage device 903 for storing data being processed in accordance with the program.

[0071] A program for implementing all or part of the functions of the monitoring device 10 may be recorded on a computer-readable recording medium, and the program may be loaded into a computer system and executed to perform processing by each functional unit. The term "computer system" as used herein includes hardware such as an OS and peripheral devices. Furthermore, if a WWW system is used, the term "computer system" also includes the homepage provision environment (or display environment). Furthermore, the term "computer-readable recording medium" refers to portable media such as CDs, DVDs, and USBs, as well as storage devices such as hard disks built into the computer system. Furthermore, if the program is distributed to the computer 900 via a communication line, the computer 900 that receives the program may load the program into the main storage device 902 and execute the above-described processing. Furthermore, the program may be for implementing part of the above-described functions, or may be capable of implementing the above-described functions in combination with a program already stored in the computer system.

[0072] As described above, several embodiments according to the present disclosure have been described, but all of these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope of the invention and its equivalents as defined in the claims, as well as in the scope and spirit of the invention.

[0073] <Additional Notes> The monitoring device, the display method, and the program described in each embodiment can be understood, for example, as follows.

[0074] (1) The monitoring device 10 according to the first aspect includes a sensor information acquisition unit 11 that acquires sensor information measured by a sensor, a damage / damage probability evaluation unit 14 that uses the sensor information to calculate the damage probability (damage probability includes damage probability and failure probability) or damage degree for each part constituting the monitored object (ship 1), and a display control unit 18 that displays the sensor information (area 103A in Figure 13A) and the damage probability or damage degree of the part (damage map in Figure 13A, etc.). This makes it possible to grasp not only the sensor information affecting the evaluation object, but also which parts of the evaluation object are damaged.

[0075] (2) The monitoring device 10 according to the second aspect is the monitoring device of (1), further comprising a failure impact evaluation unit 15 that calculates the impact if the part fails (damage includes damage and failure as explained in paragraph 0013), and the display control unit 18 displays the impact if the part fails or the risk obtained by multiplying the impact and the failure probability (risk map in Figure 14, Pareto chart of area 103G in Figure 13A). This makes it possible to evaluate not only the degree of damage to the object being evaluated, but also the impact and risk of failure.

[0076] (3) The monitoring device 10 according to the third aspect is the monitoring device of (2), wherein the display unit displays a risk matrix (205B3 in FIG. 14B) showing the correspondence between the damage probability and the impact degree for multiple parts. This allows parts to be classified by the probability of breakage and the degree of risk, making it possible to grasp the extent to which high-risk parts exist among all parts.

[0077] (4) The monitoring device 10 according to the fourth aspect is a monitoring device according to any one of (1) to (3), wherein the impact assessment unit calculates the impact for at least one of the impact on safety, the impact on the environment, the impact on production, and the impact on costs, and the display control unit displays the impact calculated by the impact assessment unit separately for each impact. This makes it possible to understand whether damage or failure of a particular part will affect costs, safety, the environment, or production.

[0078] (5) The monitoring device 10 according to the fifth aspect is a monitoring device according to any one of (1) to (4), wherein the damage level / failure probability evaluation unit calculates the future damage level of the part, and the display control unit displays the current damage level and the future damage level of the part. This makes it possible to predict the extent of damage that will occur in the future (for example, at the next maintenance inspection), and to consider carrying out maintenance before damage or failure occurs.

[0079] (6) The monitoring device 10 according to the sixth aspect is a monitoring device according to any one of (1) to (5), further comprising a countermeasure calculation unit (operation countermeasure evaluation unit 16, maintenance countermeasure evaluation unit 17) that calculates countermeasures for operation or maintenance of the object to be evaluated in response to damage to the part, and the display control unit displays the countermeasures for operation or maintenance calculated by the countermeasure calculation unit (e.g., area 103F in Figure 3 and Figure 13A). This makes it possible to understand what measures should be taken to deal with damage to parts and equipment.

[0080] (7) The monitoring device 10 according to the seventh aspect is a monitoring device according to any one of (1) to (6), wherein the object to be evaluated is a ship or a marine structure, the damage / failure probability evaluation unit calculates the damage level of the part due to the load received from waves for each predetermined period, and the display control unit displays the damage level of the part for each predetermined period. This allows daily observation of which areas are experiencing accumulated damage.

[0081] (8) The monitoring device 10 according to the eighth aspect is a monitoring device according to any one of (1) to (7), wherein the damage level / failure probability evaluation unit sets a failure mode indicating the type of damage for each of the parts or the equipment, and calculates the failure probability or damage level for each of the parts or the equipment for each of the failure modes. This allows for the evaluation of any type of damage that may occur in or that must be monitored for in each part or piece of equipment being evaluated, making it possible to perform a thorough evaluation.

[0082] (9) A display method according to a ninth aspect includes the steps of acquiring sensor information measured by a sensor, using the sensor information to calculate the probability of damage and the degree of damage for each part or piece of equipment that constitutes the object to be evaluated, and displaying the sensor information and the probability of damage or the degree of damage for the part or piece of equipment.

[0083] (10) A program according to the tenth aspect causes a computer to execute the steps of acquiring sensor information measured by a sensor, using the sensor information to calculate the probability of damage or the degree of damage for each part or piece of equipment that constitutes the object to be evaluated, and displaying the sensor information and the probability of damage or the degree of damage for the part or piece of equipment. [Explanation of symbols]

[0084] 10...Monitoring device 11. Sensor information acquisition unit 12 Input section 13 Control section 14. Damage and failure probability evaluation section 15. Failure Impact Assessment Section 16. Driving Measures Evaluation Department 17. Maintenance Measures Evaluation Department 18 Display control unit 19...Storage section 900···Computer 901 CPU 902...Main memory 903...Auxiliary storage device 904 Input / Output Interface 905···Communication Interface

Claims

1. a sensor information acquisition unit that acquires sensor information measured by the sensor; a damage / damage probability evaluation unit that uses the sensor information to calculate the damage probability or damage degree for each part or device that constitutes the evaluation object; a display control unit that displays the sensor information and the damage probability or the damage degree of the part or the device; Equipped with The evaluation object is a ship, The damage degree / breakage probability evaluation unit calculates the wave load acting on the ship using the position and orientation of the evaluation object and the wave information at the position acquired by the sensor information acquisition unit, and calculates the probability that the fatigue damage level based on the calculated wave load will exceed a threshold as the probability of failure due to fatigue crack initiation; calculating the amount of corrosion corresponding to the elapsed time as the damage level based on a corrosion amount prediction model showing the relationship between the elapsed time since the occurrence of corrosion and the amount of corrosion; The statistical failure rate λ of the equipment installed on the ship is extracted from a failure rate database in which the statistical failure rate for each of the equipment is registered, and the failure probability of the equipment in a time interval t is calculated as λe - λt. monitoring equipment.

2. The display control unit acquires a degree of impact that quantifies the magnitude of the impact when the part or the equipment fails or a value obtained by multiplying the degree of impact by the probability of failure, and displays the degree of impact or the value obtained by multiplying the degree of impact by the probability of failure. The monitoring device of claim 1 .

3. the display control unit displays a risk matrix indicating a correspondence between the damage probability and the impact degree for a plurality of the parts and the devices. The monitoring device according to claim 2 .

4. The display control unit acquires at least one of the following impact levels: the impact level on safety indicating the magnitude of the impact on people; the impact level indicating the magnitude of the impact on the environment; if the object being evaluated produces oil, the impact level indicating the magnitude of the impact on oil production; and the impact level on costs indicating the magnitude of repair costs in the event that the part or equipment breaks down, and displays them separately by impact level. The monitoring device according to claim 2 or 3.

5. the damage / failure probability evaluation unit calculates a future damage degree of the part or the equipment, the display control unit displays the current damage level of the part and the future damage level of the part. The monitoring device according to claim 1 or 2.

6. a countermeasure calculation unit that calculates a countermeasure for operation or maintenance of the evaluation object in response to damage to the portion; the display control unit displays the countermeasure related to the operation or the maintenance calculated by the countermeasure calculation unit; When the evaluation object is a ship, the countermeasure calculation unit calculates, as the countermeasure related to operation against fatigue crack occurrence, a route for the ship that can reduce the load that the ship receives from waves, based on the relationship between the traveling direction of the ship and the direction and strength of waves. The monitoring device according to claim 1 or 2.

7. The countermeasure calculation unit calculates the total preventive maintenance costs and the total corrective maintenance costs required for maintenance when maintenance is performed on all parts and equipment of the ship at a certain cycle, and further calculates the total preventive maintenance costs and the total corrective maintenance costs when the cycle is changed in various ways, the display control unit outputs a graph displaying the total of the preventive maintenance costs and the total of the corrective maintenance costs for each of the periods. The monitoring device according to claim 6.

8. the damage degree / failure probability evaluation unit sets a failure mode indicating a type of damage for each of the parts or the devices, and calculates the failure probability or the damage degree for each of the parts or the devices for each of the failure modes. The monitoring device according to claim 1 or 2.

9. A step in which a computer acquires sensor information measured by a sensor; a step in which the computer uses the sensor information to calculate a probability of breakage or a degree of damage for each part or piece of equipment constituting the evaluation object; a step in which the computer displays the sensor information and the damage probability or the damage degree of the part or the device; and The evaluation object is a ship, In the step of calculating the failure probability or damage degree, calculating a wave load acting on the ship using the position and orientation of the object to be evaluated and the wave information at the position acquired in the acquiring step, and calculating the probability that the degree of fatigue damage based on the calculated wave load will exceed a threshold as the probability of failure due to fatigue crack initiation; calculating the amount of corrosion corresponding to the elapsed time as the damage level based on a corrosion amount prediction model showing the relationship between the elapsed time since the occurrence of corrosion and the amount of corrosion; The statistical failure rate λ of the equipment installed on the ship is extracted from a failure rate database in which the statistical failure rate for each of the equipment is registered, and the failure probability of the equipment in a time interval t is calculated as λe - λt. Display method.

10. On the computer, acquiring sensor information measured by a sensor; A step of calculating a damage probability or a damage degree for each part or device constituting the evaluation object using the sensor information; displaying the sensor information and the damage probability or the damage degree of the part or the device; and The evaluation object is a ship, calculating a wave load acting on the ship using the position and orientation of the object to be evaluated and the wave information at the position acquired in the acquiring step, and calculating the probability that the degree of fatigue damage based on the calculated wave load will exceed a threshold as the probability of failure due to fatigue crack initiation; calculating the amount of corrosion corresponding to the elapsed time as the damage level based on a corrosion amount prediction model showing the relationship between the elapsed time since the occurrence of corrosion and the amount of corrosion; A process of extracting the statistical failure rate λ of the equipment installed on the ship from a failure rate database in which the statistical failure rate for each of the equipment is registered, and calculating the failure probability of the equipment in a time interval t as λe -λt; A program that executes the following.

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