Analysis device, analysis method, and computer-readable medium having a program recorded thereon

Abstract

The present application provides an analysis device, which aims to analyze the behavior of a unit with high accuracy. It is provided with: a variation model storage unit that stores a plurality of variation models representing the variation of the characteristics of a unit corresponding to the operating conditions of the unit; a model extraction unit that obtains configuration information representing a configuration model of an analysis target unit, and extracts a variation model corresponding to the configuration model; and an analysis unit that analyzes the analysis target unit based on the configuration model of the analysis target unit and the variation model extracted by the model extraction unit.

Description

Technical Field

[0001] This invention relates to a parsing apparatus, a parsing method, and a computer-readable medium containing a program. Background Technology

[0002] Previously, software such as simulators that analyze the behavior of generator units was known (see, for example, Patent Document 1).

[0003] Patent Document 1: Japanese Patent Application Publication No. 2019-121112

[0004] Patent Document 2: Japanese Patent Application Publication No. 2009-163507

[0005] Patent Document 3: Japanese Patent Application Publication No. 2013-109711 Summary of the Invention

[0006] The technical problem that the invention aims to solve

[0007] The characteristics of the machines within a generator set can change due to degradation and other factors. Therefore, analysis based on the initial characteristics of the machines may not be able to provide a high-precision analysis of the generator set's behavior.

[0008] Technical solutions for solving technical problems

[0009] The first aspect of the present invention provides a parsing apparatus. The parsing apparatus may include a variation model storage unit that stores multiple variation models representing variations in the characteristics of a unit corresponding to its operating conditions. The parsing apparatus may include a model extraction unit that obtains construction information representing a construction model of the unit to be parsed, thereby extracting a variation model corresponding to the construction model. The parsing apparatus may include a parsing unit that performs parsing on the unit to be parsed based on the construction model of the unit to be parsed and the variation model extracted by the model extraction unit.

[0010] A second aspect of the present invention provides a parsing method. In this parsing method, multiple variation models representing changes in the characteristics of the unit corresponding to its operating conditions can be stored. In this parsing method, construction information representing the structural model of the unit to be parsed can be obtained, thereby extracting the variation model corresponding to the structural model. In this parsing method, the unit to be parsed can be parsed based on its structural model and variation model.

[0011] A third aspect of the present invention provides a computer-readable medium containing a program for causing a computer to execute the parsing method of the second aspect.

[0012] It should be noted that the above description of the invention does not list all the essential features of the invention. Furthermore, sub-combinations of these feature groups can also constitute an invention. Attached Figure Description

[0013] Figure 1 This illustrates an example of the configuration of the analysis device 100 that analyzes the operation of the generator set.

[0014] Figure 2 This represents a configuration example of the parsing object unit 110.

[0015] Figure 3 This is a diagram representing an example of the information contained in the overall change model 120.

[0016] Figure 4 This is an example of the information stored in the variable model storage unit 20.

[0017] Figure 5 This is an example of the information stored in the model storage unit 30.

[0018] Figure 6 This refers to other configuration examples of the parsing object unit 110.

[0019] Figure 7 This is a diagram representing other examples of the information contained in the overall change model 120.

[0020] Figure 8 These are other examples of information stored in the variable model storage unit 20.

[0021] Figure 9 These are other examples of information stored in the model storage unit 30.

[0022] Figure 10 This represents other configuration examples of the analytical device 100.

[0023] Figure 11 This represents other configuration examples of the analytical device 100.

[0024] Figure 12 This is a diagram illustrating an example of a parsing method for a parsing object unit.

[0025] Figure 13 This describes a configuration example of a computer 1200 that can embody, in whole or in part, multiple embodiments of the present invention.

[0026] Explanation of reference numerals in the attached figures

[0027] 10 Model Extraction Unit; 20 Variable Model Storage Unit; 30 Constructed Model Storage Unit; 40 Analysis Unit; 42 Analysis Module; 50 Model Generation Unit; 100 Analysis Device; 702 Input Unit; 704 Output Unit; 706 Valve; 712 First Heat Exchanger; 714 Second Heat Exchanger; 720 Reactor; 730 Tank; 740 Compressor; 708 Valve; 752 First Pump; 754 Second Pump; 760 Valve; 770 Block; 772 Block; 802-860 Sections Variation Model; 870 Partial Variation Model; 872 Partial Variation Model; 1200 Computer; 1201 DVD-ROM; 1210 Main Controller; 1212 CPU; 1214 RAM; 1216 Graphics Controller; 1218 Display Device; 1220 Input / Output Controller; 1222 Communication Interface; 1224 Hard Disk Drive; 1226 DVD-ROM Drive; 1230 ROM; 1240 Input / Output Chip; 1242 Keyboard. Detailed Implementation

[0028] The present invention will now be described through specific embodiments, but these embodiments are not intended to limit the invention as defined in the claims. Furthermore, not all combinations of the features described in the embodiments are necessarily necessary for the technical solution of the invention.

[0029] Figure 1 This describes an example of the configuration of an analysis device 100 for analyzing the operation of a generating unit. The analysis device 100 can analyze the operation of existing generating units as well as the operation of generating units to be constructed in the future. The generating unit is at least a part of facilities such as water treatment facilities, production facilities, power generation facilities, and storage facilities.

[0030] The analysis device 100 in this example is a computer that performs prescribed data processing. The computer can execute programs that enable it to function as various parts of the analysis device 100. In this example, the analysis device 100 obtains structural information representing the structure of the unit being analyzed. The structural information may be a piping and instrumentation diagram (P&ID) of the unit or CAD data representing the configuration of equipment such as machines and piping. In this specification, unless otherwise explicitly distinguished, equipment such as machines and piping will be simply referred to as machines. The analysis device 100 analyzes the operation of the unit based on the structural model and variation model corresponding to the structural information. Each model may be a set of data or a program used to simulate the operation of each machine in the unit. The set of data or the program may contain equations or determinants, etc.

[0031] The structural model of a generating unit is a model determined by the unit's structure and does not consider variations in the characteristics of individual machines. In the structural model, without altering any machines within the unit, the characteristics of each machine are assumed to remain unchanged compared to specified values, such as those defined during the unit's construction. If machines are altered, the structural model changes accordingly. The structural model can be generated from the unit's piping and instrumentation diagrams (P&ID) or CAD data representing the unit's configuration, including machines and piping. The structural model may contain the unit's P&ID or CAD data itself.

[0032] Furthermore, the construction model can be a portion of a model simulating the operation of the unit that is unaffected by variations in the characteristics of each machine. For example, the construction model can include a process control model representing the sequence in which each machine operates. The process control model can include information representing control information for each machine in time series, or information representing the internal temperature, internal pressure, and other states that each machine should exhibit in time series. For example, the control information can include control values ​​set for the rate at which a specific machine operates relative to its maximum performance. The construction model can also include time series data of these control values. The construction model can include a model represented by a process flow diagram (PFD). Within the information contained in the process flow diagram, the portion affected by variations in machine characteristics can also be used as a variation model.

[0033] A unit variation model is a model that simulates the variation of the characteristics of each machine in a unit. A variation model can be a model inferred from the structure of each machine, or a model generated from past actual operating data. A variation model can be generated from the changes in the characteristics of existing unit machines over time. A variation model can simulate the variation of the characteristics of each machine based on its load. Machine load includes control information for controlling the machine, ambient temperature, internal temperature, fluid flow rate through the machine, operating time, and operating rate (i.e., the ratio of operating time to downtime), among other indicators that may cause reversible or irreversible degradation of machine characteristics. Reversible degradation is, for example, degradation that can be recovered through cleaning processes, such as the accumulation of dirt or foreign matter. A variation model can be a model representing the actual variation of machine characteristics relative to the desired machine characteristics, under the condition of controlling the machine based on specified control information. A variation model can also be a model simulating the effects of degradation, dirt, and deposits in equipment such as machines or pipelines.

[0034] It should be noted that in this specification, the overall structural model of the unit may be referred to as the overall structural model, and the structural model of a part of the unit may be referred to as the partial structural model. Similarly, the overall variation model of the unit may be referred to as the overall variation model, and the variation model of a part of the unit may be referred to as the partial variation model.

[0035] The analysis device 100 can combine partial structural models and partial variable models corresponding to the machines included in the analysis target unit to construct an overall structural model and an overall variable model. Based on the overall or partial structural and variable models, the analysis device 100 analyzes the overall or partial operation of the unit at a future point in time. The analysis device 100 can analyze the connection relationships and initial values ​​of characteristics of each machine based on the structural model, and analyze the future characteristic values ​​of each machine based on the variable model, thereby analyzing the operation of the unit. In this example, the analysis device 100 includes a model extraction unit 10, an analysis unit 40, and a variable model storage unit 20. The analysis device 100 may also include a structural model storage unit 30.

[0036] The variation model storage unit 20 stores multiple variation models that represent changes in the characteristics of the unit corresponding to the unit's operating conditions. The variation model storage unit 20 can store overall variation models or partial variation models.

[0037] The operating conditions of a generator set are conditions that affect the characteristics of the machines contained within the generator set. As mentioned above, the operating conditions of a generator set can be conditions that represent the load on each machine. As an example, the operating conditions of a generator set are conditions that affect the deterioration of the characteristics of each machine. The operating conditions of a generator set can also be conditions extracted from the future operating plan of the generator set. For example, the operating conditions of a generator set include the operating time of the generator set at a future time, the operating rate of the generator set (i.e., the ratio of operating time to downtime), the cumulative output of the generator set's products, the cumulative input of materials into the generator set, and the cumulative consumption of resources such as electricity or water consumed by the generator set. Based on these indicators, the degree of deterioration of each machine in the generator set may change. Furthermore, based on these indicators, the degree of contamination or accumulation of foreign matter in each machine in the generator set may change. The variation model storage unit 20 can store variation models corresponding to the degree of deterioration of each machine and variation models corresponding to stains or accumulations in each machine as different types of models. The parsing unit 40 can generate a model that combines multiple variation models for a single machine.

[0038] Furthermore, operating conditions can include future control information for each machine. This control information can include control data input to each machine to control its operation. For example, control data might be data used to control the opening of a valve. Based on this control information, the future load on the machines can be analyzed, allowing for predictions of changes in machine characteristics.

[0039] Operating conditions can include conditions describing the surrounding environment of the unit or machine. The surrounding environment can include meteorological data such as temperature, humidity, and rainfall. Depending on the surrounding environment, such as in cold or warm regions, the degree of degradation of each machine will differ even when controlled in the same way.

[0040] Operating conditions may include indicators related to the operators who operate the various machines on the unit. Operating conditions may include indicators representing operator proficiency. Even if the unit's output and other operating plans are the same, the load on each machine may vary depending on the operator's proficiency, thus potentially affecting the degree of deterioration of each machine. Operator proficiency can be expressed as the time required from the start to the end of a prescribed operation.

[0041] Operating conditions may include the maintenance cycle for each machine in the unit and indicators related to the maintenance content. Depending on the maintenance cycle or maintenance content of each machine, even if the operating time of each machine is the same, the degree of deterioration of each machine will vary.

[0042] The variation model storage unit 20 can store variation models generated from the results of actual operations of existing units. The variation model can be generated from the relationship between the actual values ​​of existing units under the aforementioned operating conditions and the degree of degradation of each machine within the existing units. The degree of degradation of each machine can be, for example, the deviation between the actual value and the target value relative to the condition that the machine should control indicators such as flow rate to target values.

[0043] The model extraction unit 10 obtains construction information representing the structure of the target machine group. The construction information may include information representing the construction model. The model extraction unit 10 extracts the variant model corresponding to the construction information from the variant model storage unit 20. Thus, the model extraction unit 10 extracts the variant model corresponding to the construction model. In this example, the model extraction unit 10 extracts a corresponding partial variant model from each machine or block included in the target machine group based on the construction information. The construction information may include the construction model itself, or it may include information specifying any one or more construction models stored in the construction model storage unit 30.

[0044] The construction model storage unit 30 stores multiple construction models. The construction model storage unit 30 can store the entire construction model or partial construction models. The construction model storage unit 30 can also database-store the construction models used when analyzing existing units.

[0045] In this example, the model extraction unit 10 extracts partial variable models corresponding to the machines or blocks included in the construction model from the variable model storage unit 20. The model extraction unit 10 combines the partial variable models corresponding to each machine or block based on the overall construction model to generate an overall variable model.

[0046] The analysis unit 40 analyzes the target unit based on its structural model and the variation model extracted by the model extraction unit 10. Condition information representing the operating conditions of the target unit is input to the analysis unit 40. The analysis unit 40 can output analysis results representing the future actions of the target unit. For example, the analysis unit 40 analyzes parameters such as the output, raw material and resource consumption, temperature, and flow rate of the target unit. The analysis unit 40 can combine the structural model and the variation model to output a simulation module that simulates the actions of the target unit. This module can output action results corresponding to the input condition information of the target unit. According to this example, the actions of the target unit can be analyzed with high precision considering the variation model.

[0047] Figure 2 This represents a configuration example of the parsed object unit 110. In Figure 2 In the example, the unit being analyzed includes an input unit 702, an output unit 704, a valve 706, a first heat exchanger 712, a second heat exchanger 714, a reactor 720, a tank 730, a compressor 740, a valve 708, a first pump 752, a second pump 754, a valve 760, and piping connecting these machines. The construction model storage unit 30 can store partial construction models corresponding to these machines and piping. The overall construction model 110 includes information such as the unit's piping and instrumentation diagram (P&ID), and the configuration and connection relationships of equipment such as machines and piping. Furthermore, Figure 2 The configuration shown can be part of the analysis object unit. Input unit 702 and output unit 704 represent the connection between this part and the upstream and downstream parts.

[0048] The construction model can contain characteristic information representing the properties of these machines and pipelines. As mentioned above, the characteristic information contained in the construction model can be values ​​that do not change over time. As an example, the characteristic information contained in the construction model can be the initial values ​​of the properties of each machine and pipeline.

[0049] Figure 3This diagram illustrates an example of the information contained in the overall variation model 120. In this example, the model extraction unit 10 extracts the corresponding variation model from the variation model storage unit 20 for each machine and pipeline included in the analysis object unit 110. The model extraction unit 10 can obtain attribute information such as the name, type, function, performance, and body of the machines and pipelines included in the analysis object unit 110 from the construction information. Based on this attribute information, the model extraction unit 10 extracts the variation model from the variation model storage unit 20. Preferably, the variation model storage unit 20 stores the attribute information of each variation model.

[0050] exist Figure 3 In the example, as the variation models corresponding to input 702, output 704, valve 706, first heat exchanger 712, second heat exchanger 714, reactor 720, tank 730, compressor 740, valve 708, first pump 752, second pump 754, and valve 760, some variation models 802, 804, 806, 812, 814, 820, 830, 840, 808, 852, 854, and 860 are extracted. For the variation model relative to the pipeline, in Figure 3 The reference numerals in the accompanying drawings are omitted. The model extraction unit 10 combines the individual variation models extracted for each machine and pipeline to construct an overall variation model 12.

[0051] It should be noted that there are cases where an ontology is described as a formal expression of knowledge as a set of relationships between concepts. For example, by defining a word as a relationship between multiple concepts, it is possible to distinguish whether the word is identified as another word, as a homonym, or as a word with the same meaning even if the word's expression is different, thereby enabling the word to be used effectively as knowledge. As an example, by associating the word "tube" with concepts such as "cylinder," "tubular," and "gas," it can be known that it means a tube used to allow liquids or gases to pass through, and it can be determined that it is not a "tube" used for smoking, wind instruments, or to represent the value of sending and receiving data in a program. The variable model storage unit 20 can store words that are expressed by the ontology for machines, etc., corresponding to the variable models of each part.

[0052] For example, when a partial variation model is associated with words such as "flow rate" and a machine is associated with words such as "pump," the model extraction unit 10 can determine from the relationship between these words that the partial variation model corresponds to that machine. In this way, by using the ontology, even when the attribute information is inconsistent, the partial variation model corresponding to each machine can be extracted.

[0053] Figure 4This is an example of the information stored in the variable model storage unit 20. The variable model storage unit 20 stores multiple partial variable models (variable models A, B, etc.). Furthermore, the variable model storage unit 20 stores more than one attribute piece of information for each partial variable model. Figure 4 In the example, the attribute information includes at least one of the following: machine name, machine type, original unit, entity representation, and operating conditions. The machine name and machine type can be selected from a pre-defined list of machine names or a list of machine types. Furthermore, the original unit is information used to identify existing units based on measured data used in the formation of each variation model. The entity representation can be the entity representing the machine included in each variation model, the entity represented by the variation model, or the entity representing the original unit. The entity representing the variation model can include, for example, the main cause of the variation simulated by the variation model and the parameters of the variation, such as "change in flow rate caused by accumulation." As mentioned above, the way the characteristics of each machine change may vary depending on the operating conditions of the unit. The variation model storage unit 20 can store variation models for the operating conditions of each unit. However, the attribute information is not limited to these. The attribute information can be information that establishes a correspondence between a portion of the variation model and each machine or a portion of the structural model. And... Figure 4 In one example, the variable model storage unit 20 stores the same type of attribute information for each variable model, but in other examples, the variable model storage unit 20 may also store different types of attribute information for each variable model.

[0054] The model extraction unit 10 extracts variant models based on the attribute information of each machine included in the constructed model. The model extraction unit 10 can extract variant models with attribute information that has the highest similarity to the attribute information of the machines. The model extraction unit 10 can calculate the similarity between attribute information using a pre-set algorithm.

[0055] Furthermore, the model extraction unit 10 can prioritize selecting partial variation models of the same original unit relative to a single parsing target unit. When multiple candidates exist as partial variation models for each machine, the model extraction unit 10 can extract partial variation models for each machine in a manner that maximizes the number of partial variation models identical to the original unit in the overall variation model. The model extraction unit 10 can prioritize extracting variation models of the same original unit relative to multiple interconnected machines. For example, consider the case where type D and type E machines are connected. Figure 4 In the example, for machines of type D, models D and E are candidates for modified models. On the other hand, for machines of type E, model F is a candidate for modified models. In this case, for machines of type D, the model extraction unit 10 can select model E, which is the same as the original unit and model F.

[0056] Since the change model storage unit 20 stores multiple change models generated based on the actions of multiple existing units, it is possible to database a wide variety of change models. The parsing unit 40 can combine the change models generated from the action results of different existing units to parse the target unit. Therefore, it is possible to appropriately combine some change models suitable for the structure of the target unit to construct an overall change model for the entire unit. Thus, parsing change models becomes easier for various types of units.

[0057] Figure 5 This is an example of the information stored in the construction model storage unit 30. The construction model storage unit 30 stores multiple partial construction models (construction models A, B, etc.). Furthermore, the construction model storage unit 30 stores more than one attribute piece of information for each partial construction model. Figure 5 In the example, the attribute information includes at least one of the following: machine name, machine type, original machine group, and ontology representation. Furthermore... Figure 5 In one example, the construction model storage unit 30 stores the same type of attribute information for each part of the construction model. However, in other examples, the construction model storage unit 30 can record different types of attribute information for each part of the construction model. Furthermore, the construction model storage unit 30 can also record ontology representations for each part of the construction model.

[0058] When the construction information does not include the construction model itself, the model extraction unit 10 can extract the construction model from the construction model storage unit 30 based on the construction information. The construction information may include information specifying the construction model stored in the construction model storage unit 30. The model extraction unit 10 can also extract the corresponding construction model based on the attribute information included in the construction information, similar to the variable model. Each construction model may be a model pre-generated by the manufacturer of each machine or the designer of the unit. Each construction model may also be a model generated during the design of an existing unit. When the construction information includes the construction model itself, the construction model storage unit 30 may also register the construction model newly. In this case, it is preferable to establish a correspondence between the attribute information included in the construction information and the construction model and store them. The model extraction unit 10 can extract the construction model based on the ontology expression corresponding to each construction model. In this case, the construction information may include the ontology expression of the construction model. The model extraction unit 10 can extract multiple partial construction models based on the ontology information of the construction information, and generate an overall construction model of the unit to be analyzed by combining the multiple partial construction models.

[0059] The model extraction unit 10 can construct an overall structural model by combining the extracted partial structural models. The partial variable models extracted by the model extraction unit 10 may or may not correspond one-to-one with the partial structural models. The model extraction unit 10 can independently extract the structural models and variable models based on structural information. In other examples, after constructing the overall structural model of the target unit, the model extraction unit 10 can extract partial variable models corresponding to the machines included in the overall structural model. In this case, the model extraction unit 10 can extract the corresponding partial variable models based on the attribute information of the partial structural models.

[0060] Figure 6 This describes another configuration example of the object resolution group 110. In this example, the object resolution group 110 has more than one block (block 770 and block 772), which is consistent with... Figure 2 The examples differ. Other aspects are different from... Figure 2 The examples are the same.

[0061] Each block contains multiple machines. A block is a conceptual scope defined by the user of the parsing device 100, the designer of the unit, or the model extraction unit 10, rather than representing a physical frame or other object. A block can contain multiple machines that cooperate to achieve a specified function. Within each block, attribute information, including the included machines, the function of the block, or the expression of its entity, can be assigned.

[0062] The model extraction unit 10 can obtain the construction model corresponding to block 770 and block 772. The construction model storage unit 30 can store a portion of the construction model of the block unit.

[0063] Figure 7 This is a diagram illustrating other examples of the information contained in the overall variation model 120. This example of the overall variation model 120 has partial variation models 870 and 872 at block units, at this point... Figure 3 The examples differ. Other aspects are different from... Figure 3 The examples are the same. Partial variation model 870 is the variation model corresponding to block 770, and partial variation model 872 is the variation model corresponding to block 772. That is, partial variation models 870 and 872 are variation models of block units that include one or more machines. Variation model storage unit 20 can store variation models of block units. Similarly, construction model storage unit 30 can store construction models of block units.

[0064] The model extraction unit 10 can extract the variant model corresponding to the object blocks (e.g., blocks 770 and 772) contained in the construction model of the parsing object unit 110 from the variant model storage unit 20. By extracting the variant model on a block-by-block basis, a more suitable variant model can be extracted.

[0065] Figure 8 This is another example of the information stored in the variable model storage unit 20. In this example, the variable model storage unit 20 stores variable models in block units. Figure 4 Similarly, the variable model storage unit 20 can also store variable models for each machine.

[0066] In addition to the variable model storage unit 20 Figure 4 In addition to the attribute information in the example, the variable model attribute information, which serves as the block unit, can be stored for the block's structure and function. The block's structure can include the configuration of the machines contained within the block and the connection relationships between the machines. The block's function can be, for example, the type of processing of the material flowing within the unit, such as stirring, heating, or storage. Furthermore, the variable model storage unit 20 can store variable models for each operating condition relative to blocks of the same structure. Figure 8 In the example, the variation model storage unit 20 stores variation models A, B, and C corresponding to operating conditions A, B, and C for blocks of the same structure (machines A, B, ...). For example, in block 772, the degree of degradation of pumps 752 and 754 may change depending on the balance of the opening degrees of valves 708 and 760. The variation model storage unit 20 can store variation models corresponding to the operating conditions of each machine in the block.

[0067] The model extraction unit 10 extracts the variant model corresponding to the object block based on the similarity between the construction of the object block (e.g., block 770 and block 772) and the construction of their respective variant models. The similarity of the construction can be calculated based on the consistency of the constituent machines. A preset coefficient can be set for each machine. If the name or type of a machine with a higher coefficient is the same, an algorithm can be set for the model extraction unit 10 to increase the similarity of the construction. Furthermore, the similarity of the construction can also be calculated based on the consistency of the connection relationships between the constituent machines. A preset coefficient can be set for each machine. If the connection relationships between machines with a higher coefficient are the same, an algorithm can be set for the model extraction unit 10 to increase the similarity of the construction. This makes it easier to extract variant models that are consistent between the object block and important machines. Additionally, the model extraction unit 10 can also extract variant models based on the similarity between the ontology representation of the object block and the ontology representation of the variant model.

[0068] Figure 9 This is another example of the information stored in the construction model storage unit 30. In this example, the construction model storage unit 30 stores the construction model of block units. Figure 5 Similar to the example, the construction model storage unit 30 can store construction models for each machine.

[0069] In addition to the construction model storage unit 30 Figure 5 In addition to the attribute information of the example, it is possible to... Figure 8 The block structure and block function described herein are stored as attribute information of the variable model as a block unit. The model extraction unit 10 extracts the construction model corresponding to the object block based on the similarity between the construction of the object block (e.g., block 770 and block 772) and the construction of their respective construction models. The method for calculating the construction similarity is similar to... Figure 8 The same example applies. Furthermore, the model extraction unit 10 can also extract the construction model based on the similarity between the ontology representation of the object block and the ontology representation of the construction model.

[0070] Figure 10 This illustrates other configuration examples of the parsing device 100. The parsing device 100 in this example, besides... Figures 1 to 9 In addition to the analytical device 100 described herein, it further includes a model generation unit 50. Other configurations are similar to those described in the previous section. Figures 1 to 9 The analytical device 100 described herein is the same.

[0071] The model generation unit 50 generates a modified model based on the motion information of each machine in the existing unit. The motion information can be obtained by measuring the actual motion results of each machine. The model generation unit 50 can be assigned a structural model of the existing unit corresponding to the motion information.

[0072] The model generation unit 50 can collect motion information from multiple existing units to generate multiple variable models. The motion information can include data representing the changes in the characteristics of each machine over time. For example, the motion information may include control data and historical motion results for each machine. The motion information may also include attribute information used to generate the variable models, such as the type of existing unit, temperature, and humidity. Furthermore, the model generation unit 50 can generate attribute information for the variable models based on the motion information of multiple existing units and the constructed models. The model generation unit 50 can establish a correspondence between the generated variable models and the input constructed models, and store them in the variable model storage unit 20 and the constructed model storage unit 30.

[0073] Furthermore, when replacing machines or other components in an existing unit, the model generation unit 50 can generate different modified models before and after the machine replacement. In other words, when machines or other components are replaced, a modified model is generated based on the operation information of the existing unit before the machine replacement, and a modified model is also generated based on the operation information of the existing unit after the machine replacement.

[0074] Figure 11 This illustrates another configuration example of the parsing device 100. In this example, the parsing unit 40 has multiple parsing modules 42. Other configurations are similar to those in... Figures 1 to 10 The analytical device 100 described herein is the same.

[0075] Each analysis module 42 performs different analyses on the target unit. Each analysis module 42 can be a simulator that uses a variable model, a constructed model, and the input condition information to simulate the actions of the target unit. Different analyses mean that at least a part of the analysis processing is different. The input parameters and output parameters of each analysis module 42 can be the same or different.

[0076] The analysis unit 40 selects an analysis module 42 based on the type of variation model to analyze the target unit. The variation model can be a type of parameter that changes over time. For example, different analysis modules 42 can be used to analyze a variation model simulating a gradual decrease in pipe flow due to blockage by foreign objects and a variation model simulating a gradual decrease in pump flow due to the accumulation of foreign objects in the pump. Each analysis module 42 can optimize the analysis for a specific type of variation model. This improves both the accuracy and speed of the analysis.

[0077] Figure 12 This is a diagram illustrating an example of a parsing method for a parsing object unit. The various processes of the parsing method are related to... Figures 1 to 11 The operation is the same as that of the analytical device 100 described in the text.

[0078] First, the variation model storage unit 20 stores multiple variation models (section S1101) representing variations in the characteristics of the unit corresponding to the unit's operating conditions. Thus, a database of variation models is pre-built.

[0079] Next, the model extraction unit 10 obtains the structural model of the target unit (S1102). The model extraction unit 10 can obtain structural information containing the structural model, or it can extract the structural model from the structural model storage unit 30 based on the structural information.

[0080] Furthermore, the model extraction unit 10 extracts the variable model from the variable model storage unit 20 (S1103). The model extraction unit 10 extracts the variable model corresponding to the constructed model. Next, the analysis unit 40 analyzes the analysis target unit based on the constructed model and the variable model (S1104). Regarding the analysis method, besides... Figure 12 In addition to the processing shown, it is possible to perform the following: Figures 1 to 11 The processing is explained in the text.

[0081] Figure 13This describes a configuration example of a computer 1200 that embodies, in whole or in part, multiple embodiments of the present invention. A program installed in the computer 1200 enables the computer 1200 to function as an operation associated with an apparatus of an embodiment of the present invention, or as one or more "parts" of that apparatus, or to perform that operation or one or more "parts" and / or to execute a process or stage of an embodiment of the present invention. Such a program, used to cause the computer 1200 to perform specific operations associated with some or all of the blocks in the flowcharts and block diagrams described in this specification, can be executed by the CPU 1212. Furthermore, the process or stage of an embodiment of the present invention can be executed in the cloud.

[0082] The computer 1200 of this embodiment includes a CPU 1212, RAM 1214, a graphics controller 1216, and a display device 1218, which are interconnected via a main controller 1210. The computer 1200 also includes input / output units such as a communication interface 1222, a hard disk drive 1224, a DVD-ROM drive 1226, and an IC card driver, which are connected to the main controller 1210 via an input / output controller 1220. The computer also includes conventional input / output units such as a ROM 1230 and a keyboard 1242, which are connected to the input / output controller 1220 via an input / output chip 1240.

[0083] CPU 1212 operates according to the program stored in ROM 1230 and RAM 1214, thereby controlling the various units. Graphics controller 1216 obtains the image data generated by CPU 1212 from the frame buffer or the like provided in RAM 1214 or from the graphics controller 1216 itself, and displays the image data on display device 1218.

[0084] Communication interface 1222 communicates with other electronic devices via a network. Hard disk drive 1224 stores programs and data used by CPU 1212 within computer 1200. DVD-ROM drive 1226 reads programs or data from DVD-ROM 1201 and provides programs or data to hard disk drive 1224 via RAM 1214. IC card drive reads programs and data from IC card and / or writes programs and data to IC card.

[0085] ROM1230 stores a boot program executed by computer 1200 when activated in internal storage, and / or programs dependent on the hardware of computer 1200. Input / output chip 1240 can also connect various input / output units to input / output controller 1220 via parallel port, serial port, keyboard port, mouse port, etc.

[0086] The program is provided by a computer-readable storage device such as a DVD-ROM 1201 or an IC card. The program is read from the computer-readable storage device, installed in a hard disk drive 1224, RAM 1214, or ROM 1230 (examples of computer-readable storage devices), and executed by the CPU 1212. The information processing recorded within these programs is read by the computer 1200, resulting in interaction between the program and the aforementioned hardware resources. The apparatus or method can be configured to perform information manipulation or processing according to the use of the computer 1200.

[0087] For example, when communication is performed between computer 1200 and an external unit, CPU 1212 can execute a communication program loaded in RAM 1214 and perform communication processing relative to communication interface 1222 based on the processing recorded in the communication program. Under the control of CPU 1212, communication interface 1222 reads transmission data stored in a transmission buffer provided in a recording medium such as RAM 1214, hard disk drive 1224, DVD-ROM 1201, or IC card, and sends the read transmission data to the network, or writes received data received from the network to a receive buffer provided on the recording medium.

[0088] Furthermore, the CPU 1212 can read all or necessary portions of files or databases stored on external recording media such as hard disk drive 1224, DVD-ROM drive 1226 (DVD-ROM 1201), IC cards, etc., and perform various types of processing on the data in RAM 1214. The CPU 1212 can then write the processed data back to the external recording media.

[0089] To process various types of information, such as programs, data, tables, and databases, these can be stored in a recording medium. For data read from RAM 1214, CPU 1212 can perform various types of processing, including operations specified by a sequence of program instructions, such as conditional judgment, conditional jumps, unconditional jumps, and information retrieval / replacement, as described at any location in this disclosure, and write the results back to RAM 1214. Furthermore, CPU 1212 can retrieve information from files, databases, etc., within the recording medium. For example, when multiple items, each having an attribute value associated with a second attribute, are stored in the recording medium, CPU 1212 can retrieve from these multiple items an item that matches a condition specifying the attribute value of the first attribute, read the attribute value of the second attribute stored in that item, and obtain the attribute value of the second attribute associated with the first attribute that satisfies the pre-set condition.

[0090] The programs or software modules described above can be stored in computer 1200 or a computer-readable storage medium near computer 1200. Furthermore, recording media such as hard disks or RAM provided within a server system connected to a dedicated communication network or the Internet can be used as computer-readable storage media, thereby enabling the program to be provided to computer 1200 via the network.

[0091] The present invention has been described above using embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various changes or modifications can be made to the above embodiments. As can be clearly understood from the claims, solutions implementing such changes or modifications are also included within the technical scope of the present invention.

[0092] It should be noted that the execution order of actions, sequences, steps, stages, etc., in the apparatus, system, program, and method shown in the claims, specification, and drawings can be implemented in any order unless specifically stated as "before" or "before," or unless the output of the preprocessing is not used in the postprocessing. Even if the flow of actions in the claims, specification, and drawings is described using terms like "firstly" or "next" for convenience, it does not mean that they must be performed in that specific order.

Claims

1. An analytical apparatus, characterized in that, have: The model generation unit collects the structural model of the existing unit and the action information of each machine, thereby generating an overall variable model that includes multiple partial variable models. The action information is obtained by measuring the actual action results of each machine of the existing unit. The variable model storage unit stores multiple partial variable models representing variations in the characteristics of the machines of the existing unit corresponding to the operating conditions of the existing unit. Each of the multiple partial variable models is stored in a block unit containing one or more machines of the existing unit, and each of the multiple partial variable models is stored in a corresponding manner to the construction of the block. The model extraction unit obtains construction information representing the construction model of the existing parsing object group, and extracts a partial variation model of each block contained in the construction model of the existing parsing object group corresponding to the construction information. It also extracts the partial variation model corresponding to the object block contained in the construction model of the existing parsing object group from the variation model storage unit, and extracts the partial variation model corresponding to the object block based on the similarity between the construction of the object block and the construction of the block corresponding to the partial variation model. The analysis unit, based on the existing analysis target unit's construction model and the partial variation model extracted by the model extraction unit, outputs analysis results representing the future actions of the existing analysis target unit.

2. The analytical apparatus according to claim 1, The variation model storage unit stores one of the multiple variation models generated by the changes in the characteristics of the machine of the existing unit over time.

3. The analytical apparatus according to claim 1, Furthermore, it includes a construction model storage unit that stores multiple construction models of the existing unit. The parsing unit uses the construction model selected from the construction model storage unit based on the construction information to parse the existing parsing object unit.

4. The analytical apparatus according to claim 1, The variable model storage unit stores the multiple variable models generated from the actual action results of multiple existing units. The analysis unit combines the multiple variation models of different existing units to analyze the existing analysis target units.

5. The analytical apparatus according to any one of claims 1 to 4, The analysis unit has multiple analysis modules that perform different analyses on the existing analysis target unit, and selects the analysis module corresponding to the change model to analyze the existing analysis target unit.

6. An analytical method, characterized in that, The structural model of the existing unit and the action information of each machine are collected to generate an overall variation model that includes multiple component variation models. The action information is obtained by measuring the actual actions of each machine in the existing unit. The system stores multiple partial variation models representing variations in the characteristics of the machines in the existing unit corresponding to the operating conditions of the existing unit. Each of the multiple partial variation models is stored in a block unit containing one or more machines of the existing unit, and each of the multiple partial variation models is stored in a corresponding manner to the construction of the block. Obtain construction information representing the construction model of an existing parsing object group, and extract partial variation models of each block contained in the construction model of the existing parsing object group corresponding to the construction information. Extract the partial variation models corresponding to the object blocks contained in the construction model of the existing parsing object group. Based on the similarity between the construction of the object block and the construction of the block corresponding to the partial variation model, extract the partial variation model corresponding to the object block. Based on the existing analysis object unit's construction model and the extracted partial variation model, the analysis result representing the future actions of the existing analysis object unit is output.

7. A computer-readable medium, characterized in that, The document contains a program for causing a computer to execute the parsing method as described in claim 6.

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