Information processing device, information processing method, and information processing program

Abstract

To efficiently reduce power consumption by reducing the data volume upon communication.SOLUTION: An information processor 100 acquires information related to the operation of a field device, uses the information related to the operation of the field device to calculate a model, performs predetermined determination based on comparison between the model and a determination model, and extracts information related to a polynomial coefficient by use of the model based on results of the predetermined determination performed by a determination part 133.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Diagnosis of facilities such as plants and factories is performed based on measurement values acquired by field devices (for example, devices that measure the opening degree, pressure, flow rate, etc. of valves, etc., hereinafter simply referred to as "field devices") and information regarding the operating status. In addition, there are various other types of field devices. For example, field devices that acquire data such as temperature, humidity, a predetermined gas concentration, differential pressure, and mechanical vibration are known.

[0003] In recent years, there has been a demand to detect in advance malfunctions that cause facilities and the like to fail based on the above-described information, and to capture minor omens. Therefore, for example, as a technique for performing various diagnoses based on operation data of valves, which are field devices, "Regulating Valve Maintenance Support System PLUG-IN Valstaff" is known (see, for example, Non-Patent Document 1). Also, as a cloud-based diagnosis form, "Dx Valve Cloud Service" that provides an extension of diagnosis items and algorithms by cloud-type diagnosis is known (see, for example, Non-Patent Document 2). Furthermore, for the acquisition and transmission of data by field devices, facility monitoring devices such as wireless sensors (for example, smart valve positioners, etc.) driven by batteries are known (see, for example, Non-Patent Document 3).

[0004] As a result of more accurate and higher-resolution condition monitoring, more data is being acquired than before, and the amount of communication data tends to increase. Furthermore, with the rapid increase in the need for diagnosis and maintenance in recent years, there are more cases where equipment monitoring devices are installed on existing equipment after the fact, and there is a growing need for wireless sensors that can be installed with low load (for example, with fewer construction hours and shorter construction periods). However, many of the aforementioned wireless sensors are powered by built-in batteries, and as the amount of data increases, the amount of wireless communication and the time required for wireless communication also increase. Consequently, the increased power consumption leads to a shorter battery life, which is a problem.

[0005] Therefore, in conventional technology, a technique is known for adjusting the communication cycle to extend battery life by measuring the number of operations or the operating time within a specified period and controlling it so that the operating cycle is not set to a short operating cycle that falls below a lower limit (see, for example, Patent Document 1). In addition, a technique is known for switching to a high-speed transmission mode with a short operating cycle when a change in the operating mode is necessary based on changes in the set value and the number of operations (see, for example, Patent Document 2). [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] Japanese Patent Publication No. 2010-166151 [Patent Document 2] Japanese Patent Publication No. 2010-220005 [Non-patent literature]

[0007] [Non-Patent Document 1] Control valve maintenance support system PLUG-IN Valstaff (CA1-VMS200-07.pdf), [Retrieved September 1, 2022], Internet<URL:https: / / www.azbil.com / jp / product / factory / download / catalog-spec / CA1-VMS200-07.pdf> [Non-Patent Document 2] Dx Valve Cloud Service, [Retrieved September 1, 2022], Internet <URL:https: / / www.azbil.com / jp / product / factory / support-training / lifecycle-support / control-valve-solution / services / dx-valve-cloud-service.html> [Non-Patent Document 3] Smart Valve Positioner (CA1-AVP700-04.pdf), [Retrieved September 1, 2022], Internet<URL:https: / / www.azbil.com / jp / product / factory / download / catalog-spec / CA1-AVP700-04.pdf> [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] However, conventional technologies were unable to reduce the amount of data transmitted during communication, making it difficult to efficiently reduce power consumption.

[0009] For example, in a battery-powered device that measures the opening degree of a valve to diagnose its operation and transmits the measurement data wirelessly, the power consumption of wireless transmission is generally greater than that of the measurement operation itself, and an increase in the amount of communication data can have a significant impact on battery life. However, conventional technologies have the problem that they do not affect the amount of data itself, as they involve techniques to set upper and lower limits on the number of communication operations or to adjust the measurement and communication frequency to improve responsiveness to sudden changes. [Means for solving the problem]

[0010] Therefore, in order to solve the above problems and achieve the objective, the information processing device of the present invention is characterized by comprising: an acquisition unit that acquires information on the operation of a field device; a calculation unit that calculates a model using the information on the operation of the field device; a determination unit that makes a predetermined determination based on a comparison of the model and a determination model; and an extraction unit that extracts information on polynomial coefficients using the model based on the result of the predetermined determination by the determination unit. [Effects of the Invention]

[0011] This invention has the effect of facilitating efficient power consumption reduction by reducing the amount of data transmitted during communication. [Brief explanation of the drawing]

[0012] [Figure 1] Figure 1 shows an example of an overview of information processing according to the embodiment. [Figure 2] Figure 2 shows an example of the device configuration of the information processing device according to the present invention. [Figure 3] Figure 3 shows an example of a sigmoid function model according to the embodiment. [Figure 4] Figure 4 shows an example of a valve operation model based on a sigmoid function according to the embodiment. [Figure 5] Figure 5 shows an example of a determination model according to the embodiment. [Figure 6] Figure 6 shows an example of a comparison between the valve operation model and the determination model according to the embodiment. [Figure 7] Figure 7 shows an example of a comparison between the valve operation model and the determination model according to the embodiment. [Figure 8] Figure 8 shows an example of a comparison between the valve operation model and the determination model according to the embodiment. [Figure 9] Figure 9 shows an example of a comparison between the valve operation model and the determination model according to the embodiment. [Figure 10]FIG. 10 is a flowchart of an information processing procedure according to the prior art of the present embodiment. [Figure 11] FIG. 11 is a flowchart of an information processing procedure according to the present embodiment. [Figure 12] FIG. 12 is a flowchart of an information processing procedure according to Application Example 1 of the present embodiment. [Figure 13] FIG. 13 is a flowchart of an information processing procedure according to Application Example 2 of the present embodiment. [Figure 14] FIG. 14 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing apparatus.

Mode for Carrying Out the Invention

[0013] Hereinafter, the embodiments (hereinafter referred to as "embodiments") will be described with reference to the drawings. In the following description, common components are denoted by the same reference numerals, and repeated descriptions are omitted. Further, the description of this embodiment does not limit the information processing apparatus, information processing method, and information processing program according to the present invention.

[0014] 〔1. Outline of Information Processing Method〕 The acquisition unit 131 of the information processing apparatus 100 acquires the operation data of the field device as information regarding the operation of the field device. Next, the calculation unit 132 of the information processing apparatus calculates a model using the operation data acquired by the acquisition unit 131.

[0015] The determination unit 133 of the information processing apparatus 100 compares the model calculated by the calculation unit 132 with the determination model to determine whether an abnormality has occurred in the field device. Subsequently, the extraction unit 134 of the information processing apparatus 100 extracts information regarding the polynomial coefficient from the model based on the determination result of the determination unit 133. Further, the transmission unit 135 of the information processing apparatus 100 transmits data to be transmitted based on the determination result (for example, data such as operation data, extracted polynomial coefficients, etc.).

[0016] From here, we will use Figure 1 to explain the determination of abnormalities in field equipment and the modeling of operating data performed by the information processing device 100. Unless otherwise specified in the following sections, information regarding the operation of field equipment will be referred to as "operating data (data related to the monotonic operation of valves, etc.)", and the information processing performed by the equipment that acquires the valve operation data (for example, acquisition of operating data, modeling, determination, etc.) will be carried out by the information processing device 100. However, the items described above in this embodiment are merely examples and are not limiting.

[0017] Figure 1 shows a graph of typical ON / OFF valve openings acquired by the information processing device 100 of this embodiment (see Figure 1(1)). The aforementioned graph shows how the valve opening fluctuates from 0% to 100% in conjunction with the valve's operation (see Figure 1(2)). The information processing device 100 then acquires information regarding the ON / OFF valve operation of the valve (hereinafter referred to as "operation data") (see Figure 1(3)).

[0018] The valves targeted by the information processing device 100 for acquiring operating data are opened and closed by force such as air pressure or springs, and smooth operation can be confirmed if no problems occur (see (4) and (5) in Figure 1). However, if an abnormality occurs in the valve or an event that foreshadows an abnormality occurs due to aging or other reasons, abnormalities will also occur in the operation of the valve.

[0019] For example, the information processing device 100 acquires operating data that shows smooth operation up to a certain point (see (6) in Figure 1), but if some kind of abnormality occurs in the valve (see (7) in Figure 1), it acquires operating data that includes the abnormality. Specifically, the information processing device 100 acquires a graph like the one shown in (8) in Figure 1. In (8) in Figure 1, the shape of the operating data acquired by the information processing device 100 is different from that in (5) in Figure 1. In response to such an abnormality, the information processing device 100 models the operating data, compares it with a judgment model, and determines whether or not an abnormality has occurred. Then, based on the judgment result, the information processing device 100 switches the data to be transmitted (for example, operating data, extracted polynomial coefficients, etc.) and transmits the data.

[0020] [2. Configuration of the Information Processing Device] From here, the configuration of the information processing device 100 according to the embodiment will be described with reference to Figure 2. As shown in Figure 2, the information processing device 100 includes a communication unit 110, a storage unit 120, a control unit 130, and a power supply unit 140. Although not shown in Figure 2, the information processing device 100 may also include an input unit that accepts various operations (for example, a touch panel, a keyboard, a mouse, etc.).

[0021] Furthermore, although the information processing device 100 according to this embodiment will be described on the premise that it is implemented and operates within a field device, the form of the information processing device is not limited and may be a desktop personal computer, a notebook PC, a virtual PC, a smartphone or tablet, a PDA (Personal Digital Assistant), etc. The detailed functions of each part will be described below.

[0022] (Communications Department 110) The communication unit 110 is implemented using a NIC (Network Interface Card) or the like. The communication unit 110 can be connected to the network via wired or wireless connection as needed, and can transmit and receive information bidirectionally. In this embodiment, the explanation will be based on the premise of wireless communication.

[0023] (Storage unit 120) The memory unit 120 includes an operational information memory unit 121, a model memory unit 122, and a transmission information memory unit 123. The memory unit 120 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) or flash memory, or by a storage device such as a hard disk or optical disc.

[0024] (Operation information storage unit 121) The operation information storage unit 121 stores information related to the operation of the field device (such as operating data) acquired by the acquisition unit 131. For example, the operation information storage unit 121 stores information related to the monotonous operation of a valve as shown in (3) of Figure 1 as operating data. In addition to the aforementioned operating data, the operation information storage unit 121 may also store any other information related to the operation of the field device.

[0025] (Model memory unit 122) The model storage unit 122 stores information about the model calculated by the calculation unit 132 using the operating data, etc. For example, the model storage unit 122 stores a model calculated based on a sigmoid function using the aforementioned operating data. Furthermore, the model storage unit 122 stores a judgment model used by the judgment unit 133 when making a judgment.

[0026] Furthermore, the model storage unit 122 is not limited to the information described above, and may store information within the scope of the model in this embodiment. For example, the model storage unit 122 may store models calculated based on mathematical formulas other than the sigmoid function, or information for the determination unit 133.

[0027] (Transmission information storage unit 123) The transmission information storage unit 123 stores information regarding the polynomial coefficients extracted by the extraction unit 134 as transmission information. The transmission information storage unit 123 is not limited to the aforementioned information; for example, it may store information included within the scope of the data to be transmitted as transmission information.

[0028] (Control unit 130) The control unit 130 includes an acquisition unit 131, a calculation unit 132, a determination unit 133, an extraction unit 134, and a transmission unit 135. The control unit 130 is implemented by a processor, MPU (Micro Processing Unit), CPU (Central Processing Unit), etc., executing various programs stored in the memory unit 120 using RAM as a working area. The control unit 130 is also implemented by an IC (Integrated Circuit), such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0029] (Acquisition part 131) The acquisition unit 131 acquires information regarding the operation of the field equipment. Specifically, the acquisition unit 131 acquires operating data of the field equipment as information regarding the operation of the field equipment.

[0030] (Calculation unit 132) The calculation unit 132 calculates a model using information about the operation of the field equipment. For example, the calculation unit 132 uses the operation data acquired by the acquisition unit 131 (for example, data on the opening degree in the ON / OFF operation of the valve) to calculate a model used for the determination unit 133.

[0031] From here, an example of how the calculation unit 132 calculates a model will be explained using Figures 3 and 4. In this example, the calculation unit 132 will be explained on the premise that it calculates a model based on a sigmoid function using operating data. In this example, the sigmoid function is used based on the degree of fit to the curve of the valve opening and closing operation. Note that the method used by the calculation unit 132 to model the operating data in this embodiment is not limited to the sigmoid function described above, and other methods that can be used for modeling may be used depending on the type of operating data to be modeled. For example, the calculation unit 132 may use a sine wave from -180° to 180° as a model.

[0032] First, we will explain the sigmoid function using Figure 3. The sigmoid function is generally expressed by the following equation (1).

[0033]

number

[0034] As a premise, it is known that the ON / OFF operation of a valve exhibits behavior similar to a step response based on an operation command of valve open (ON) or valve closed (OFF). Therefore, the sigmoid function is sometimes used to simulate such behavior. As shown in Figure 3, for models C1 and C2 calculated based on the sigmoid function, the value of model C1 increases from 0 to 1, and the value of model C2 decreases from 1 to 0. Furthermore, since the curves of models C1 and C2 vary depending on the variables in the formula, the models can be fitted to the ON / OFF valve operation of a valve.

[0035] Next, using Figure 4, we will explain an application example of modeling the ON / OFF valve operation of a valve using the sigmoid function. Note that models C3, C4, and C5 in Figure 4 can be expressed using the following equation (2).

[0036]

number

[0037] In Figure 4, each model has the following variables: Model C3 has "G=100, Offset=0, a=0.02", Model C4 has "G=108, Offset=3, a=0.03", and Model C5 has "G=94, Offset=4, a=0.05". As the model changes depending on the variables in the function, the calculation unit 132 can use the sigmoid function to represent the opening degree value for opening and closing the valve, that is, the ON / OFF valve operation of the valve.

[0038] (Judgment unit 133) Now, let's return to Figure 2 and continue the explanation. The determination unit 133 makes a predetermined determination based on a comparison between the model calculated by the calculation unit 132 and the determination model. Specifically, the determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and makes a predetermined determination of abnormality if the models satisfy predetermined difference conditions. For example, the determination unit 133 compares the model calculated by the calculation unit 132 using operating data with a pre-prepared determination model and determines whether an abnormality has occurred using the deviation or error between the respective models as an indicator. Note that the method for determining the deviation or error is not particularly limited, and the determination unit 133 may use any method that can determine the deviation or error of the aforementioned models. For example, the determination unit 133 may use the mean squared deviation or the mean absolute error to make the determination.

[0039] Next, the determination model will be explained using Figure 5. The determination model C6 shown in Figure 5 is a determination model that models the ideal ON / OFF valve operation of the valve based on the sigmoid function described above. The determination model C6 includes information on "fully open," "fully closed," "intermediate open," "operating time," and "center time." Although Figure 5 only describes the determination model for the OFF valve operation among the ON / OFF valve operation of the valve, the determination unit 133 can use a determination model for the ON valve operation as a model for other operations, for example.

[0040] The determination unit 133 determines, based on the aforementioned indicators, how much the model calculated based on the operating data acquired by the acquisition unit 131 deviates. Note that the determination unit 133 in this embodiment is not limited to the aforementioned determination model C6, but can use other determination models. For example, the determination unit 133 may create a determination model as needed based on the type of field equipment, usage period, frequency of use, usage intensity, surrounding environment, etc., and perform the determination.

[0041] From here, using Figures 6 to 9, we will explain an example of a model corresponding to an abnormality in the ON / OFF valve operation, comparing it with a judgment model. Figures 6 to 9 illustrate the case of the OFF valve operation as an example. Furthermore, the models shown in Figures 6 to 9 are merely examples, and actual models based on the ON / OFF valve operation of a valve may show behavior other than that of models C7 to C10 shown later.

[0042] Figure 6 illustrates a situation where an abnormality occurs, such as "the valve does not close to the predetermined position." Model C7 in Figure 6 shows a higher valve opening value compared to the judgment model C6 (see (1) in Figure 6). Therefore, the judgment unit 133 determines that "the valve does not close to the predetermined position," i.e., there is an abnormality in the valve. The judgment unit 133 also determines whether "the valve does not open to the predetermined position" based on the valve opening.

[0043] Figure 7 illustrates a situation where an abnormality occurs, such as "the valve does not operate within a predetermined time." Compared to the judgment model C6, model C8 in Figure 7 shows that the center time, which is the time it takes for the valve to reach an intermediate opening, is delayed in the time series direction (see (2) in Figure 7). Therefore, the judgment unit 133 determines that "the valve does not operate within a predetermined time," i.e., there is an abnormality in the valve. The judgment unit 133 also makes a similar determination for the abnormality "the valve operates earlier than the predetermined time" by comparing the center times.

[0044] Figure 8 illustrates a situation where an abnormality occurs, such as "a sticking occurs when the valve starts operating." Compared to the judgment model C6, model C9 in Figure 8 shows a high valve opening in the first half of the operating time, and then the valve opening decreases rapidly (see (3) in Figure 8). Therefore, the judgment unit 133 determines that "a sticking occurs when the valve starts operating," that is, there is an abnormality in the valve.

[0045] Figure 9, like Figure 8, shows a situation where an abnormality occurs, such as "a jam occurring during valve operation." Compared to the judgment model C6, model C10 in Figure 9 shows a decrease in valve opening degree up to a certain point in the operation time, and then the rate of decrease in valve opening degree changes (see (4) in Figure 8). Therefore, the judgment unit 133 determines that "a jam occurs during valve operation," that is, there is an abnormality in the valve.

[0046] Furthermore, the determination unit 133 makes a predetermined determination that a change has occurred if a predetermined change has occurred in the information regarding the polynomial coefficients extracted by the extraction unit 134, which will be described later. For example, the determination unit 133 determines that a predetermined change has occurred if the polynomial coefficients included in the aforementioned information regarding polynomial coefficients, or the error between the polynomial coefficients and the determination data, is not within a predetermined range or exceeds a predetermined threshold, or if other conditions are met.

[0047] (Extraction part 134) Now, let's return to Figure 2 and continue the explanation. The extraction unit 134 extracts information about the polynomial coefficients using a model based on the predetermined determination result of the determination unit 133. For example, if the determination unit 133 determines that there is no abnormality in the operation of the valve, the extraction unit 134 extracts the polynomial coefficients, degree, etc. from the model calculated by the calculation unit 132 using the aforementioned valve operation data. If the determination unit 133 determines that there is an abnormality in the operation of the valve, the extraction unit 134 does not extract the polynomial coefficients, degree, etc. from the model calculated by the calculation unit 132 using the aforementioned valve operation data. Note that the extraction method of the extraction unit 134 is not particularly limited, and the information to be extracted may be appropriately set and extracted according to the type of field equipment, operating conditions, etc.

[0048] (Transmitter 135) If the determination unit 133 determines that there is an abnormality, the transmission unit 135 transmits the operating data acquired by the acquisition unit 131 as is. Specifically, if the determination unit 133 determines that there is an abnormality in the operation of the valve, the transmission unit 135 transmits the operating data (for example, information regarding the operation of the valve) as is, without polynomialization or other processing. On the other hand, if the determination unit 133 determines that there is no abnormality, the transmission unit 135 transmits the information regarding the polynomial coefficients extracted by the extraction unit 134 (for example, information regarding the polynomial coefficients and degree).

[0049] Furthermore, the transmitting unit 135 transmits information regarding the polynomial coefficients (for example, information such as the polynomial coefficients and degree) when the determination unit 133 determines, as predetermined, that there is no abnormality and that there is a change.

[0050] Furthermore, the transmitting unit 135 transmits information regarding the polynomial coefficients (for example, information such as the polynomial coefficients and degree) if the determination unit 133 has determined, as a predetermined determination, that there is no abnormality and no change, and that a predetermined communication period has passed.

[0051] Furthermore, the transmitting unit 135 may use one or more of the following as transmission conditions: the "determination result regarding the presence or absence of an abnormality," the "determination result regarding the presence or absence of changes in information related to the polynomial coefficients," and "whether or not it is a predetermined communication period." In addition, although this embodiment has been described on the premise that the transmitting unit 135 communicates various data and information via wireless communication, it may also communicate various data and information via wired communication.

[0052] (Power supply section 140) The power supply unit 140 is the power source for driving the information processing device 100. The power supply unit 140 can be supplied with power from a wiring plug connector (such as an outlet) or from a battery or the like. In this embodiment, it is assumed that power will be supplied from a battery or the like.

[0053] [3. Application Examples] Next, we will describe some application examples that the information processing device 100 can implement. The application examples described below can be implemented using the functions of the information processing device 100 in this embodiment. Furthermore, the information processing device 100 can be implemented by combining the functions of each embodiment as needed.

[0054] (Prerequisite technology) The prerequisite technology is the basis for the information processing device 100 to realize this embodiment, and is the most basic process. The acquisition unit 131 acquires field device operation data as information related to the operation of the field device. Next, the calculation unit 132 calculates a model using the operation data acquired by the acquisition unit 131. Subsequently, the extraction unit 134 extracts information about polynomial coefficients from the model. Then, the transmission unit 135 transmits the extracted information about polynomial coefficients.

[0055] (This embodiment: Conversion and transmission of operating data based on the presence or absence of abnormalities) "Conversion and transmission of operating data based on the presence or absence of abnormalities" is the basic flow in this embodiment, and is an embodiment in which the data to be transmitted is changed and transmitted based on the determination of the presence or absence of abnormalities. The acquisition unit 131 acquires operating data of the field equipment as information related to the operation of the field equipment. Next, the calculation unit 132 calculates a model using the operating data acquired by the acquisition unit 131. If the determination unit 133 determines that there is an abnormality, the transmission unit 135 transmits the operating data (measurement data) of the field equipment acquired by the acquisition unit 131 as is. If the determination unit 133 determines that there is no abnormality, the transmission unit 135 transmits information related to the polynomial coefficients extracted from the model by the extraction unit 134.

[0056] (Application Example 1: Data transmission based on changes in information regarding the presence or absence of anomalies and polynomial coefficients) Application Example 1 is an embodiment (Application Example 1) in which predetermined data is transmitted based on the determination of whether or not there is an abnormality by the determination unit 133 and the determination of whether or not there is a change in the information regarding the extracted polynomial coefficients. First, the acquisition unit 131 acquires field device operation data as information regarding the operation of the field device. Next, the calculation unit 132 calculates a model using the operation data acquired by the acquisition unit 131. Then, if the determination unit 133 determines that there is an abnormality, the transmission unit 135 transmits the operation data as is.

[0057] On the other hand, if the determination unit 133 determines that there is no abnormality, the extraction unit 134 extracts information about the polynomial coefficients from the model. Furthermore, if the determination unit 133 determines that a predetermined change has occurred in the information about the polynomial coefficients extracted by the extraction unit 134, the transmission unit 135 transmits the extracted information about the polynomial coefficients. On the other hand, if the determination unit 133 determines that there is no abnormality and no change, the transmission unit 135 does not transmit the information about the polynomial coefficients.

[0058] (Application example 2: Data transmission based on the presence or absence of anomalies, changes in information regarding polynomial coefficients, and communication cycle) Application Example 2 is an embodiment that transmits predetermined data based on the presence or absence of abnormalities, the presence or absence of changes in information regarding polynomial coefficients, and the communication cycle. First, the acquisition unit 131 acquires field device operation data as information regarding the operation of the field device. Next, the calculation unit 132 calculates a model using the operation data acquired by the acquisition unit 131. Then, the determination unit 133 determines whether or not an abnormality has occurred based on the model calculated by the calculation unit 132. If the determination unit 133 determines that an abnormality exists, the transmission unit 135 transmits the operation data as is.

[0059] On the other hand, if the determination unit 133 determines that there is no abnormality, the extraction unit 134 extracts information about the polynomial coefficients from the model. If the determination unit 133 determines that a predetermined change has occurred in the information about the polynomial coefficients extracted by the extraction unit 134, the transmission unit 135 transmits the extracted information about the polynomial coefficients.

[0060] Even if the determination unit 133 determines that there is no abnormality, if it is within a predetermined communication cycle, the transmission unit 135 transmits information regarding the polynomial coefficients extracted by the extraction unit 134. On the other hand, if the determination unit 133 determines that there is no abnormality and it is not within the predetermined communication cycle, the transmission unit 135 does not transmit data.

[0061] [4. Processing Procedure] Next, the information processing procedures of the information processing device 100 according to each embodiment will be described. Figures 10 to 13 are flowcharts showing examples of the information processing procedures according to the embodiments. The information processing procedures of the information processing device 100 are divided into "Flow 1: Prerequisite Technology," "Flow 2 (This Embodiment): Operation Data Conversion and Transmission Embodiment Based on Abnormality," "Flow 3 (Application Example 1): Data Transmission Based on Abnormality and Changes in Information Regarding Polynomial Coefficients," and "Flow 4 (Application Example 2): Data Transmission Based on Abnormality, Changes in Information Regarding Polynomial Coefficients, and Communication Cycle." Therefore, the procedures will also be explained in four parts.

[0062] First, "Flow 1: Prerequisite Technology" will be explained using Figure 10. The acquisition unit 131 acquires operating data (process S101). Next, the calculation unit 132 calculates a model using the operating data acquired by the acquisition unit 131 (process S102). Subsequently, the extraction unit 134 extracts information regarding the polynomial coefficients from the model calculated by the calculation unit 132 (process S103). Finally, the transmission unit 135 transmits the information regarding the polynomial coefficients extracted by the extraction unit 134, and the process ends (process S104).

[0063] Next, "Flow 2 (This Embodiment): Operation Data Conversion and Transmission Embodiment Based on Abnormality" will be explained using Figure 11. The acquisition unit 131 acquires operation data (step S201). Next, the calculation unit 132 calculates a model using the operation data acquired by the acquisition unit 131 (step S202). The determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and determines that there is an abnormality (Yes in step 203). In that case, the transmission unit 135 transmits the operation data of the field device acquired by the acquisition unit 131 as is (step S204), and the process ends.

[0064] On the other hand, the determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and determines that there is no abnormality (No. in step 203). In that case, the extraction unit 134 extracts information about the polynomial coefficients from the model calculated by the calculation unit 132 (step S205). Then, the transmission unit 135 transmits the information about the polynomial coefficients extracted by the extraction unit 134 (step S206), and the process ends.

[0065] Next, "Flow 3 (Application Example 1): Data Transmission Based on Changes in Information Regarding Abnormality and Polynomial Coefficients" will be explained using Figure 12. The acquisition unit 131 acquires operating data (step S301). Next, the calculation unit 132 calculates a model using the operating data acquired by the acquisition unit 131 (step S302). The determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and determines that there is an abnormality (Yes in step 303). In that case, the transmission unit 135 transmits the operating data of the field device acquired by the acquisition unit 131 as is (step S304), and the process ends.

[0066] On the other hand, the determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and determines that there is no abnormality (No in step 303). In that case, the extraction unit 134 extracts information about the polynomial coefficients from the model calculated by the calculation unit 132 (step S305). Furthermore, the determination unit 133 determines that a predetermined change has occurred in the information about the polynomial coefficients extracted by the extraction unit 134 (Yes in step S306). In that case, the transmission unit 135 transmits the information about the polynomial coefficients extracted by the extraction unit 134 (step S307), and the process ends.

[0067] On the other hand, the determination unit 133 determines that no predetermined change has occurred in the information regarding the polynomial coefficients extracted by the extraction unit 134 (No. in step S306). In that case, the transmission unit 135 does not transmit the information regarding the polynomial coefficients and terminates the process.

[0068] Next, "Flow 4 (Application Example 2): Data transmission based on the presence or absence of abnormalities, changes in information regarding polynomial coefficients, and communication cycle" will be explained using Figure 13. The acquisition unit 131 acquires operating data (step S401). Next, the calculation unit 132 calculates a model using the operating data acquired by the acquisition unit 131 (step S402). The determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and determines that there is an abnormality (Yes in step 403). In that case, the transmission unit 135 transmits the operating data of the field device acquired by the acquisition unit 131 as is (step S404), and the process ends.

[0069] On the other hand, the determination unit 133 compares the model calculated by the calculation unit 132 with the determination model and determines that there is no abnormality (No. in step S403). In that case, the extraction unit 134 extracts information regarding the polynomial coefficients from the model calculated by the calculation unit 132 (step S405).

[0070] Furthermore, the determination unit 133 determines that there is a predetermined change in the information regarding the polynomial coefficients extracted by the extraction unit 134 (Yes in step S406). In that case, the transmission unit 135 transmits the information regarding the polynomial coefficients extracted by the extraction unit 134 (step S407), and the process ends.

[0071] Furthermore, the determination unit 133 determines that there is no predetermined change in the information regarding the polynomial coefficients extracted by the extraction unit 134 (No in step S406). Then, the transmission unit 135 determines that it is a predetermined communication cycle (Yes in step S408). In that case, the transmission unit 135 transmits the information regarding the polynomial coefficients extracted by the extraction unit 134 (step S407), and the process ends.

[0072] On the other hand, the determination unit 133 determines that there is no predetermined change in the information regarding the polynomial coefficients extracted by the extraction unit 134 (No. of step S406). The transmission unit 135 then determines that it is not within the predetermined communication cycle (No. of step S408). In that case, the transmission unit 135 does not transmit the information regarding the polynomial coefficients and terminates the process.

[0073] [4. Effects] In conventional technology, equipment operates on a daily basis, and depending on the operating conditions, the number of operations can reach an enormous level, leading to deterioration over time. Therefore, there is a growing need for high-quality diagnostics of field equipment to predict or detect abnormalities at an early stage.

[0074] Furthermore, in equipment diagnostics, the amount of data tends to increase in order to achieve high resolution for operational data and time-related data, and to reproduce precise operational trends. As a result, in conventional technology, the power consumption of wireless transmission in field equipment was greater than that of measurement operations, and the increase in data volume sometimes pressured the lifespan. However, reducing the number of sampling points for measurement and testing to reduce the amount of data led to problems such as a decrease in diagnostic quality and an increased risk of misdiagnosis.

[0075] Therefore, the information processing device 100 acquires information regarding the operation of the field device, calculates a model using the information regarding the operation of the field device, makes a predetermined determination based on a comparison of the model and a determination model, and extracts information regarding polynomial coefficients using the model based on the result of the predetermined determination by the determination unit 133. As a result, this embodiment has the effect of making it easy to efficiently reduce power consumption by reducing the amount of data during communication.

[0076] The information processing device 100 compresses the amount of data by having the calculation unit 132 model the operation data and the extraction unit 134 extract polynomial coefficients and degrees from the model. As a result, the information processing device 100 provides the effect of extending the life of the power supply (battery) by reducing the amount of data transmitted and the resulting reduction in power consumption.

[0077] Specifically, the majority of data acquired by field devices is information from normal operation; therefore, if no abnormality occurs, the data will simply repeat, indicating the same operating state. However, in conventional technology, this type of data is also transmitted, resulting in increased data volume and power consumption, which can shorten the lifespan of the power supply (battery). Therefore, the information processing device 100 uses a model created by the calculation unit 132, and the determination unit 133 determines whether or not an abnormality has occurred. If no abnormality is found, it transmits compressed data (for example, extracted polynomial coefficients). As a result, the information processing device 100 reduces the amount of data transmitted and, consequently, reduces power consumption, thereby extending the lifespan of the power supply (battery).

[0078] Conversely, the information processing device 100 transmits unmodeled operating data and other information as needed. This provides the effect of enabling accurate situation assessment in the event of an abnormality. Specifically, when the information processing device 100 determines that an abnormality exists, it transmits the acquired operating data as is, thereby preventing loss of information regarding the abnormality and enabling accurate situation assessment in the event of an abnormality.

[0079] Furthermore, the information processing device 100 provides the effect of enabling device health checks by transmitting data at a predetermined communication cycle even when no abnormality has occurred or there has been no change in the information regarding the polynomial coefficients.

[0080] In addition, the information processing device 100 can also provide insights into the occurrence of abnormalities in the equipment. For example, in the model for the occurrence of jamming events during the opening and closing operation of valves shown in Figures 8 and 9, even for the same jamming event, the curves that appear in the model are different. Therefore, if it is a specific abnormality, it can be estimated from the modeled information, and as a result, it provides the effect of extending the life of the power supply (battery) by reducing the amount of data transmitted and the resulting reduction in power consumption.

[0081] Furthermore, the reduction in the amount of data transmitted by the information processing device 100 is applicable not only to wireless communication but also to wired communication. In recent years, with the advancement of information technology, various devices are sending and receiving data, which has led to the problem of increasing communication costs (e.g., communication time, wiring, processing capacity, etc.). Therefore, the information processing device 100 provides the effect of reducing the amount of data even in wired communication by applying the functions of modeling the operation data in the calculation unit 132, determining the presence or absence of abnormalities in the determination unit 133, and extracting polynomial coefficients and degrees in the extraction unit 134.

[0082] [5. Hardware Configuration] The information processing device 100 according to this embodiment is implemented by a computer 1000 having the configuration shown in Figure 14. Figure 14 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device 100. The computer 1000 has a configuration in which a CPU 1100, RAM 1200, ROM 1300, auxiliary storage device 1400, communication interface 1500, and input / output interface 1600 are connected by a bus 1800.

[0083] The CPU 1100 operates based on programs stored in the ROM 1300 or auxiliary storage device 1400, and controls various parts. The ROM 1300 stores boot programs executed by the CPU 1100 when the computer 1000 starts up, as well as programs that depend on the computer 1000's hardware.

[0084] The auxiliary storage device 1400 stores programs executed by the CPU 1100, and data used by such programs. The communication interface 1500 receives data from other devices via a predetermined communication network NW and sends it to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the predetermined communication network NW. The CPU 1100 controls output devices such as displays and printers, and input / output devices 1700 such as keyboards and mice via the input / output interface 1600. The CPU 1100 acquires data from the input / output devices 1700 via the input / output interface 1600. The CPU 1100 also outputs the generated data to the input / output devices 1700 via the input / output interface 1600.

[0085] For example, when the computer 1000 functions as the information processing device 100 according to this embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control unit 130 by executing a program loaded on the RAM 1200.

[0086] [6. Other] Of the processes described in the embodiments and modifications described above, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings can be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0087] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads, usage conditions, etc.

[0088] The aforementioned components include those that are easily conceivable by those skilled in the art, those that are substantially identical, and those that fall within the so-called equivalent range. Furthermore, the embodiments and modifications described above can be combined as appropriate, as long as the processing content is not contradictory.

[0089] Furthermore, the terms "section," "module," and "unit" mentioned above can be replaced with "means" or "circuit," etc. For example, a control unit can be replaced with a control means or a control circuit.

[0090] Although several embodiments have been described in detail above with reference to the drawings, these are merely examples, and it is possible to implement these embodiments in various modified and improved forms based on the knowledge of those skilled in the art, starting with the embodiments described in the disclosure section of the invention. [Explanation of Symbols]

[0091] 100 Information Processing Devices 110 Communications Department 120 Storage section 121 Operation Information Storage Unit 122 Model Memory Unit 130 Control Unit 131 Acquisition Department 132 Calculation Section 133 Judgment section 134 Extraction part 135 Transmitter 140 Power supply section 1000 computers 1100 CPU 1200 RAM 1300 ROM 1400 Auxiliary storage 1500 Communication I / F 1600 Input / Output Interfaces 1700 Input / Output Device 1800 Bus C1, C2, C3, C4, C5, C7, C8, C9, C10 models C6 classification model

Claims

1. An acquisition unit that acquires information regarding the operation of field devices, A calculation unit that calculates a model using information regarding the operation of the field device, A determination unit that makes a predetermined determination based on a comparison between the aforementioned model and a determination model, The system includes an extraction unit that extracts information regarding polynomial coefficients using the model based on the result of the predetermined determination of the determination unit, The determination unit compares the model with the determination model and, if the model satisfies predetermined difference conditions, determines that there is an abnormality as the predetermined determination. If the determination unit determines that there is an abnormality as a predetermined determination, it transmits the operation data. If the predetermined determination is made that there is no abnormality, the transmitting unit transmits information regarding the polynomial coefficients. An information processing device characterized by further having the following.

2. The acquisition unit acquires operating data of the field device as information related to the operation of the field device. The information processing apparatus according to feature 1.

3. The determination unit, when it detects that a predetermined change has occurred in the information relating to the polynomial coefficients extracted by the extraction unit, makes a determination that a change has occurred as the predetermined determination. The transmitting unit transmits information regarding the polynomial coefficients when the determination unit determines, as predetermined, that there is no abnormality and that there is a change. The information processing apparatus according to feature 1.

4. The transmitting unit transmits information regarding the polynomial coefficients when the determination unit makes a predetermined determination of "no abnormality" and "no change," and when a predetermined communication period has elapsed. The information processing apparatus according to claim 1 or 3.

5. The calculation unit calculates the model based on the sigmoid function using the operating data. The information processing apparatus according to feature 2.

6. A process for acquiring information regarding the operation of field equipment, A step of calculating a model using information regarding the operation of the field device, A step of making a predetermined determination based on a comparison between the aforementioned model and the determination model, The process includes a step of extracting information regarding polynomial coefficients using the model based on the result of the predetermined determination by the determination unit, The process of making the predetermined determination involves comparing the model with the determination model, and if the model satisfies the predetermined difference conditions, the predetermined determination is made as an abnormality. If the predetermined determination process determines that there is an abnormality, the operation data is transmitted. If the predetermined determination is made that there is no abnormality, the process involves transmitting information regarding the polynomial coefficients. An information processing method characterized by further including the following.

7. Procedures for obtaining information regarding the operation of field devices, A procedure for calculating a model using information regarding the operation of the field equipment, A procedure for making a predetermined determination based on a comparison between the aforementioned model and the determination model, Based on the result of the predetermined determination by the determination unit, the procedure for extracting information about the polynomial coefficients using the model is performed by the computer. The procedure for making the predetermined determination involves comparing the model with the determination model, and if the model satisfies the predetermined difference conditions, determining that there is an abnormality. If the procedure for making the predetermined determination results in a determination of abnormality, the operation data is transmitted. If the predetermined determination is made that there is no abnormality, the procedure for transmitting information regarding the polynomial coefficients is as follows: An information processing program characterized by having a computer execute it further.

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