Monitoring device, threshold setting device, cause analysis device, monitoring method

Abstract

The present invention relates to a monitoring device, a threshold setting device, a cause analysis device, and a monitoring method. Further, a technique is provided that can suppress the trouble of setting a reference for abnormality determination and easily achieve cause inference at the time of an abnormality occurrence for a monitoring target device that has a thermal energy input / output including heat generation or heat absorption. The thermal energy monitoring device (20) according to one embodiment of the present disclosure includes: a heat balance calculation unit (201) that acquires data related to the state of the sterilization device (50) and calculates a plurality of types of thermal energy (heat quantities Q1 to Q5) that constitute the heat balance of the sterilization device (50) based on the data; and a monitoring unit (203) that monitors whether the thermal energy (heat quantity QX) of the target type deviates from the normal range defined by the upper limit threshold and the lower limit threshold for each type of thermal energy (heat quantities Q1 to Q5) calculated by the heat balance calculation unit (201).

Description

Technical Field

[0001] The present disclosure relates to a monitoring device and the like. Background Art

[0002] For example, a technique is known in which the presence or absence of an abnormality in a monitored object device is determined by monitoring state data (measurement values) indicating the state of the monitored object device (see Patent Document 1).

[0003] Patent Document 1 discloses a technique in which, for an industrial furnace as a monitored object device, a flame voltage is monitored, and when the flame voltage becomes equal to or lower than a threshold value, alarm information is transmitted to the outside.

[0004] In addition, for example, a technique is known in which a relatively large number of types of state data indicating the state of a monitored object device are reduced to relatively few variables, and the monitored object device is monitored using the reduced variables (see Patent Document 2).

[0005] Patent Document 2 discloses a technique in which, for a refrigeration cycle device as a monitored object device, a plurality of state data are reduced to one Mahalanobis distance, and the Mahalanobis distance is used for abnormality monitoring.

[0006] <Prior Art Documents>

[0007] <Patent Documents>

[0008] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2019-100572

[0009] Patent Document 2: Japanese Unexamined Patent Application Publication No. 2005-345096 Summary of the Invention

[0010] <Problems to be Solved by the Invention>

[0011] However, for example, as shown in Patent Document 1, when monitoring the state data of a monitored object device, if the number of types of state data to be monitored is relatively large, it is necessary to prepare an abnormality determination criterion for each type, and thus there may be a lot of trouble.

[0012] On the other hand, for example, as shown in Patent Document 2, if a plurality of types of state data are reduced to fewer variables, the trouble in preparing an abnormality determination criterion is reduced. However, it may be difficult to easily determine which state item corresponding to which type of state data is the cause of the abnormality when an abnormality occurs.

[0013] Therefore, in view of the above problems, an object is to provide a technique that can suppress the trouble of setting a reference for abnormality determination and easily achieve cause inference when an abnormality occurs for a monitoring target device that generates or absorbs heat energy including heat generation or heat absorption.

[0014] <Means for Solving the Problem>

[0015] To achieve the above object, in one embodiment of the present disclosure, there is provided a monitoring device including: a heat energy calculation unit that acquires data related to the state of a monitoring target device and calculates multiple types of heat energy that constitute the heat balance of the monitoring target device based on the data; and a monitoring unit that monitors whether the heat energy of the target type deviates from a predetermined range defined by an upper threshold and a lower threshold for each type of heat energy calculated by the heat energy calculation unit.

[0016] In addition, in another embodiment of the present disclosure, there is provided a threshold setting device for setting the upper threshold and the lower threshold used in the above monitoring device. The threshold setting device includes: a setting unit that sets the upper threshold and the lower threshold based on the time series data of the multiple types of heat energy calculated by the heat energy calculation unit.

[0017] In addition, in yet another embodiment of the present disclosure, there is provided a cause analysis device including: an extraction unit that, when a predetermined heat energy among the multiple types of heat energy detected by the above monitoring device deviates from the predetermined range, extracts a state item indicating the cause of the deviation of the predetermined heat energy from the multiple state items representing the state of the monitoring target device associated with the predetermined heat energy.

[0018] In addition, in yet another embodiment of the present disclosure, there is provided a monitoring method executed by a monitoring device, including: a heat energy calculation step of acquiring data related to the state of a monitoring target device and calculating multiple types of heat energy that constitute the heat balance of the monitoring target device based on the data; and a monitoring step of monitoring whether the heat energy of the target type deviates from a predetermined range defined by an upper threshold and a lower threshold for each type of heat energy calculated in the heat energy calculation step.

[0019] <Effects of the Invention>

[0020] According to the above embodiment, it is possible to suppress the trouble of setting a reference for abnormality determination and easily achieve cause inference when an abnormality occurs for a monitoring target device that generates or absorbs heat energy including heat generation or heat absorption. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a diagram showing an example of the configuration of a thermal energy monitoring system.

[0022] Figure 2 This is a diagram showing an example of the configuration of a sterilization device that is the object of monitoring by the thermal energy monitoring system.

[0023] Figure 3 This is a diagram showing an example of the hardware configuration of the thermal energy monitoring device.

[0024] Figure 4 This is a flowchart schematically showing an example of the processing related to the monitoring of thermal energy performed by the thermal energy monitoring device.

[0025] Figure 5 This is a flowchart schematically showing an example of the processing related to the threshold setting performed by the monitoring support device.

[0026] Figure 6 This is a diagram showing an example of the input screen for threshold setting.

[0027] Figure 7 This is a diagram showing an example of the final threshold setting screen.

[0028] Figure 8 This is a diagram showing an example of the abnormal occurrence history screen.

[0029] Figure 9 This is a diagram schematically showing the processing flow related to the abnormal cause analysis performed by the monitoring support device.

[0030] Figure 10 This is a diagram showing an example of the analysis result screen.

[0031] Figure 11 This is a diagram showing another example of the analysis result screen.

[0032] Symbol Explanation

[0033] 1 Thermal energy monitoring system

[0034] 10 Measuring device

[0035] 11 Temperature sensor

[0036] 12 Pressure sensor

[0037] 13 Flow rate sensor

[0038] 20 Thermal energy monitoring device (monitoring device)

[0039] 21 Driving device

[0040] 21A Recording medium

[0041] 22 Auxiliary storage device

[0042] 23 Memory device

[0043] 24 CPU

[0044] 25 Interface device

[0045] 26 Display device

[0046] 27 Input device

[0047] 30 Monitoring support device (threshold setting device, cause analysis device)

[0048] 36 Display device (display unit)

[0049] 40 Production management system

[0050] 50 Sterilization device (device under monitoring)

[0051] 51 Product passing path

[0052] 52 High-temperature water circulation path

[0053] 52A Pump

[0054] 53 Steam inflow path

[0055] 54 Drainage path

[0056] 55 Cooling water passing path

[0057] 56 Heating unit

[0058] 57 Cooling unit

[0059] 201 Heat balance calculation unit (heat energy calculation unit)

[0060] 202 Storage unit

[0061] 202A Threshold

[0062] 203 Monitoring unit

[0063] 301 Database

[0064] 302 Threshold setting unit (setting unit)

[0065] 303 Alarm output unit

[0066] 304 Analysis data generation unit

[0067] 305 Cause analysis unit (extraction unit)

[0068] 600 Threshold setting input screen

[0069] 700 Threshold Final Setting Screen

[0070] 800 Abnormality Occurrence History Screen

[0071] 1000, 1100 Analysis Result Screen Detailed Implementation Manner

[0072] Hereinafter, the implementation manner will be described with reference to the accompanying drawings.

[0073] [Overview of Thermal Energy Monitoring System]

[0074] First, refer to Figure 1 to describe the thermal energy monitoring system 1 according to this implementation manner.

[0075] Figure 1 is a diagram showing an example of the configuration of the thermal energy monitoring system 1 according to this implementation manner.

[0076] The thermal energy monitoring system 1 according to this implementation manner monitors the balance of thermal energy in the sterilization device 50 as the monitoring object, thereby determining whether there is an abnormality.

[0077] As Figure 1 shown, the thermal energy monitoring system 1 includes a measuring device 10, a thermal energy monitoring device 20, and a monitoring support device 30. In addition, the thermal energy monitoring system 1 cooperates with the production management system 40.

[0078] The measuring device 10 is installed in the sterilization device 50 or disposed around the sterilization device 50, measures various states of the sterilization device 50, and outputs measurement data related to the dynamic state of the sterilization device 50. The dynamic state of the sterilization device 50 refers to a state that can change dynamically as the sterilization device 50 operates. The dynamic state of the sterilization device 50 includes, for example, the state of the temperature, pressure, and flow rate inside the sterilization device 50. The measurement data output from the measuring device 10 is sent to the thermal energy monitoring device 20 through a predetermined communication line. The predetermined communication line is, for example, a one-to-one communication line. In addition, the predetermined communication line can be, for example, a local area network (LAN: Local Area Network) in the factory where the sterilization device 50 is installed, such as a field network. In addition, the predetermined communication line can include, for example, a wide area network (WAN: Wide Area Network) outside the factory where the sterilization device 50 is installed. The wide area network can include, for example, a mobile communication network with a base station as a terminal, a satellite communication network using communication satellites, the Internet, etc. In addition, the predetermined communication line can include a short-range communication line based on wireless communication standards such as WiFi or Bluetooth (registered trademark).

[0079] The thermal energy monitoring device 20 (an example of a monitoring device) monitors the operating status of the sterilization device 50. Specifically, the thermal energy monitoring device 20 monitors the thermal energy balance of the sterilization device 50 based on the measurement data obtained from the measurement device 10 and the data related to the static state of the sterilization device 50 obtained from the production management system 40, and determines whether there is an abnormality in the sterilization device 50. The thermal energy monitoring device 20 can be installed, for example, within the same factory as the sterilization device 50. Additionally, the thermal energy monitoring device 20 can be installed, for example, in a facility outside the factory where the sterilization device 50 is installed (such as a monitoring center, etc.). The thermal energy monitoring device 20 is, for example, a server device. In this case, the thermal energy monitoring device 20 can be a cloud server, an on-premises server, or an edge server. Additionally, the thermal energy monitoring device 20 can be a terminal device such as a computer terminal within the factory where the sterilization device 50 is installed.

[0080] The monitoring support device 30 (an example of a threshold setting device and a cause analysis device) provides user support related to the setting of a reference (threshold value described later) for monitoring the sterilization device 50 performed by the thermal energy monitoring device 20 and the cause analysis during the abnormality determination of the sterilization device 50 by the thermal energy monitoring device 20. Specifically, the monitoring support device 30 obtains various data from the thermal energy monitoring device 20 via a predetermined communication line, and based on the acquired data, sets a reference (threshold value) for monitoring or performs a cause analysis of the abnormality of the sterilization device 50. The monitoring support device 30 can be installed, for example, in the same factory as the sterilization device 50 together with the thermal energy monitoring device 20. In this case, the thermal energy monitoring device 20 is installed, for example, in a location relatively close to the sterilization device 50 within the factory, and the monitoring support device 30 is installed, for example, in a location such as a management office within the factory where users of the monitoring support device 30, such as operators or managers, conduct management operations related to the factory. Additionally, the monitoring support device 30 can also be installed in a facility outside the factory where the sterilization device 50 is installed (such as a monitoring center, etc.). The monitoring support device 30 is, for example, a server device. In this case, the monitoring support device 30 can be a cloud server, an on-premises server, or an edge server. Additionally, the monitoring support device 30 can be a terminal device such as a computer terminal installed in a management office within the factory.

[0081] The production management system 40 performs management related to the products produced in the factory. Specifically, the production management system 40 manages the quality of the products produced in the factory. For example, the production management system 40 controls the working state of the production line and the like. Specifically, the production management system 40 performs control related to various devices including the sterilization device 50 provided on the production line. The production management system 40 sends information related to the static state of the sterilization device 50 (hereinafter referred to as "status information") to the thermal energy monitoring device 20 through a predetermined communication line. The static state of the sterilization device 50 refers to a state that basically does not change unless there is an external operation or control instruction during the operation of the sterilization device 50. The static state of the sterilization device 50 includes the operation mode of the sterilization device 50 or the category of the product sterilized by the sterilization device 50 (hereinafter referred to as "product category") and the like. The product category is information that indirectly represents the control conditions of the sterilization device 50 (such as various temperature conditions or pressure conditions, etc.). The reason is that the control conditions of the sterilization device 50 vary according to the product category, and the product category is associated with the control conditions. Regarding the operation mode of the sterilization device 50, for example, multiple operation modes such as "operation period", "standby period", "stop period" are preset. The sterilization device 50 can basically operate while being maintained in a certain operation mode, and the operation mode is switched at the moment of switching the product category of the sterilization object, for example. For example, the operation mode of the sterilization device 50 can be appropriately set (changed) according to the operation of an operator or the like from the input unit of the sterilization device 50 or the operation terminal device of the production management system 40.

[0082] [Outline of Sterilization Device]

[0083] Next, an outline of the sterilization device 50 will be described.

[0084] Figure 2 FIG. is an example showing the configuration of the sterilization device 50 that is the monitoring object of the thermal energy monitoring system 1.

[0085] The sterilization device 50 sterilizes the products produced in the factory. The sterilization device 50 can, for example, sterilize the beverages produced in the factory. The products passing through the sterilization device 50 can be beverages in a state where they have been filled into packaging containers (hereinafter referred to as "individual beverages" for convenience), or beverages in a flowing liquid state before being filled into packaging containers (hereinafter referred to as "non-individual beverages" for convenience).

[0086] As Figure 2 shown, the sterilization device 50 includes a product passage path 51, a high-temperature water circulation path 52, a pump 52A, a steam inflow path 53, a drainage path 54, a cooling water passage path 55, a heating unit 56, and a cooling unit 57.

[0087] The product passage 51 is a path through which the product (beverage) flows into, passes through the interior of the sterilization device 50 , and then flows out to the outside.

[0088] The high-temperature water circulation path 52 is a path for circulating relatively high-temperature water (high-temperature water). A pump 52A is provided in the high-temperature water circulation path 52, and the high-temperature water is circulated by the pump 52A.

[0089] The steam inflow path 53 is a path for allowing very high-temperature steam to flow into the high-temperature water circulation path 52. This allows the temperature of the high-temperature water circulating in the high-temperature water circulation path 52 to be maintained at a relatively high temperature.

[0090] The drainage path 54 discharges the remaining high-temperature water to the outside from the high-temperature water circulation path 52. This is because the amount of high-temperature water in the high-temperature water circulation path 52 increases due to the inflow of steam.

[0091] The cooling water passage 55 is a passage through which cooling water for cooling the product flows in from the outside, passes through the inside of the sterilizer 50 , and then flows out to the outside.

[0092] The heating unit 56 exchanges heat between the high-temperature water in the high-temperature water circulation path 52 and the product (beverage) in the product passage path 51 to heat and sterilize the beverage in the product passage path 51. The heating unit 56 is arranged in the front half of the product passage path 51.

[0093] The cooling section 57 exchanges heat between the cooling water of the cooling water passage 55 and the product (beverage) of the product passage 51 to cool the product whose temperature has risen during the heat sterilization performed by the heating section 56. The cooling section 57 is arranged in the rear half of the product passage 51.

[0094] As described above, the sterilizer 50 is controlled by the production management system 40. Specifically, the sterilizer 50 is controlled so that the temperature of the product in the heating section 56 is above a predetermined value. This allows the sterilizer 50 to appropriately heat and sterilize the product under the control of the production management system 40. Furthermore, the sterilizer 50 is controlled so that the temperature of the product after passing through the cooling section 57 drops below a predetermined value.

[0095] [Details of the thermal energy monitoring system]

[0096] Next, refer to Figure 1 ,as well as Figures 3 to 11 , the details of the thermal energy monitoring system 1 are explained.

[0097] <Composition of measuring device>

[0098] As Figure 1 shown, the measuring device 10 includes a temperature sensor 11, a pressure sensor 12, and a flow rate sensor 13. Additionally, the measuring device 10 may include other types of sensors capable of measuring physical states of the sterilization device 50 other than the temperature state, the pressure state, and the flow rate state.

[0099] The temperature sensor 11 measures the temperature inside the sterilization device 50. The temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter referred to as "steam temperature") T1 of the steam flowing in from the steam inflow path 53. Additionally, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter referred to as "drain temperature") T2 of the drain water discharged from the drain path 54. Additionally, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter referred to as "product inlet temperature") T3 of the product (beverage) at the inlet of the product passage path 51. Additionally, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter referred to as "product outlet temperature") T4 of the product (beverage) at the outlet of the product passage path 51. Additionally, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter referred to as "cooling water inlet temperature") T5 of the cooling water at the inlet of the cooling water passage path 55. Additionally, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter referred to as "cooling water outlet temperature") T6 of the cooling water at the outlet of the cooling water passage path 55.

[0100] The pressure sensor 12 measures the pressure inside the sterilization device 50. The pressure sensor 12 includes, for example, a pressure sensor that measures the pressure (hereinafter referred to as "steam pressure") P1 of the steam flowing in from the steam inflow path 53. Additionally, the pressure sensor 12 includes, for example, a pressure sensor that measures the pressure (hereinafter referred to as "drain pressure") P2 of the drain water discharged from the drain path 54.

[0101] The flow sensor 13 measures the flow rate inside the sterilization device 50. The flow sensor 13 includes, for example, a flow sensor that measures the flow rate of the steam flowing in from the steam inflow path 53 (hereinafter referred to as "steam flow rate") F1. In addition, the flow sensor 13 includes, for example, a flow sensor that measures the flow rate of the drainage discharged from the drainage path 54 (hereinafter referred to as "drainage flow rate") F2. In addition, the flow sensor 13 includes, for example, a flow sensor that measures the flow rate of the product (beverage) at the inlet of the product passage path 51 (hereinafter referred to as "product inlet flow rate") F3. In addition, the flow sensor 13 includes, for example, a flow sensor that measures the flow rate of the product (beverage) at the outlet of the product passage path 51 (hereinafter referred to as "product outlet flow rate") F4. In addition, the flow sensor 13 includes, for example, a flow sensor that measures the flow rate of the cooling water at the inlet of the cooling water passage path 55 (hereinafter referred to as "cooling water inlet flow rate") F5. In addition, the flow sensor 13 includes, for example, a flow sensor that measures the flow rate of the cooling water at the outlet of the cooling water passage path 55 (hereinafter referred to as "cooling water outlet flow rate") F6.

[0102] <Configuration of Thermal Energy Monitoring Device>

[0103] Figure 3 It is a diagram showing an example of the hardware configuration of the thermal energy monitoring device 20.

[0104] The functions of the thermal energy monitoring device 20 can be realized by any hardware, or by any combination of hardware and software, etc. As Figure 3 shown, for example, the thermal energy monitoring device 20 includes a driving device 21, an auxiliary storage device 22, a memory device 23, a CPU 24, an interface device 25, a display device 26, and an input device 27, and they are respectively connected through a bus B.

[0105] A program for realizing various functions of the thermal energy monitoring device 20 is provided by a portable recording medium 21A, for example. The recording medium 21A includes, for example, a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), a USB (Universal Serial Bus) memory, etc. When the recording medium 21A recording the program is set in the driving device 21, the program is installed in the auxiliary storage device 22 from the recording medium 21A via the driving device 21. In addition, the program can be downloaded from another computer via a predetermined communication line and installed in the auxiliary storage device 22.

[0106] The auxiliary storage device 22 stores various installed programs, and stores required files or data, etc.

[0107] When there is an instruction to start a program, the memory device 23 reads out and stores the program from the auxiliary storage device 22.

[0108] The CPU 24 executes various programs stored in the memory device 23, and implements various functions related to the thermal energy monitoring device 20 according to the programs.

[0109] The interface device 25 is used as an interface for connecting to a predetermined communication line.

[0110] The display device 26 displays a GUI (Graphical User Interface) according to, for example, the program executed by the CPU 24.

[0111] The input device 27 is used for an operator or a manager of the thermal energy monitoring device 20 to input various operation instructions regarding the thermal energy monitoring device 20.

[0112] As Figure 1 shown, the thermal energy monitoring device 20 includes a heat balance calculation unit 201, a storage unit 202, and a monitoring unit 203. The functions of the heat balance calculation unit 201 and the monitoring unit 203 can be implemented, for example, by loading the program installed in the auxiliary storage device 22 into the memory device 23 and executing it by the CPU 24. In addition, the function of the storage unit 202 can be implemented, for example, by a storage area specified in the auxiliary storage device 22.

[0113] The heat balance calculation unit 201 (an example of a thermal energy calculation unit) performs calculations related to the heat balance of the sterilization device 50. Specifically, the heat balance calculation unit 201 calculates multiple types of thermal energy that make up the heat balance of the sterilization device 50 based on the measurement data successively acquired from the measurement device 10 for each predetermined control cycle.

[0114] The multiple types of thermal energy that make up the thermal balance of the sterilization device 50 include steam heat Q1, drain heat Q2, product heat Q3, cooling water heat Q4, and other heat Q5. The steam heat Q1 represents the heat (thermal energy) of the steam flowing in from the steam inflow path 53. The drain heat Q2 represents the heat (thermal energy) of the drain discharged from the drain path 54. The product heat Q3 represents the heat (thermal energy) carried out of the sterilization device 50 by the product passing through the product passing path 51. The cooling water heat Q4 represents the heat (thermal energy) discharged to the outside by the cooling water passing through the cooling water passing path 55. The other heat Q5 represents the heat (thermal energy) discharged from the sterilization device 50 other than the drain heat Q2, the product heat Q3, and the cooling water heat Q4. Hereinafter, the steam heat Q1, the drain heat Q2, the product heat Q3, the cooling water heat Q4, and the other heat Q5 may be collectively referred to as heat Q1 to Q5. In addition, any one of the steam heat Q1, the drain heat Q2, the product heat Q3, the cooling water heat Q4, and the other heat Q5 may be individually referred to as heat QX (X: an integer from 1 to 5).

[0115] The relationship (thermal balance) expressed by the following formula (1) is satisfied among the steam heat Q1, the drain heat Q2, the product heat Q3, the cooling water heat Q4, and the other heat Q5.

[0116] [Mathematical formula 1]

[0117] Steam heat Q1 = Drain heat Q2 + Product heat Q3 + Cooling water heat Q4 + Other heat Q5 ··· (1)

[0118] The thermal balance calculation unit 201 calculates the steam heat Q1 using, for example, the following formula (2) and (3).

[0119] [Mathematical formula 2]

[0120]

[0121]

[0122] In addition, the thermal balance calculation unit 201 can calculate the steam heat Q1 using, for example, the following formula (4).

[0123] [Mathematical formula 3]

[0124]

[0125] Note that the "enthalpy of saturated steam", "specific volume", and "density" vary according to the steam temperature T1 and the steam pressure P1, respectively, and are obtained using a saturated steam table based on the measured values of the steam temperature T1 and the steam pressure P1. Data corresponding to the saturated steam table is, for example, pre-stored in the auxiliary storage device 22.

[0126] In addition, the heat balance calculation unit 201 calculates the drainage heat quantity Q2 using, for example, the following formula (5).

[0127] [Mathematical formula 4]

[0128]

[0129] Note that the "specific heat of water" is registered in the auxiliary storage device 22 or the like as a predefined value (for example, 4.22). In addition, the "steam mass flow rate" is calculated by the above formula (3). In addition, the "drainage inlet temperature" corresponds to the temperature of the high-temperature water before the steam inflow, and can be, for example, simply predefined in advance to be the same as the temperature inside the factory (for example, 20 °C), or the measured value can be specifically used. In the latter case, the temperature sensor 11 includes a temperature sensor for measuring the drainage inlet temperature.

[0130] In addition, the heat balance calculation unit 201 calculates the heat carried out by the product Q3 using, for example, the following formula (6).

[0131] [Mathematical formula 5]

[0132]

[0133] Note that in formula (6), instead of the product inlet flow rate F3, the product outlet flow rate F4 or the average value of the product inlet flow rate F3 and the product outlet flow rate F4 can also be used. The same applies to formulas (7) and (8) below.

[0134] In addition, more strictly speaking, the heat balance calculation unit 201 can calculate the heat carried out by the product Q3 using the following formula (7) or formula (8).

[0135] [Mathematical formula 6]

[0136]

[0137]

[0138] Note that formula (7) corresponds to the case where the sterilization target product of the sterilization device 50 is a non-individual beverage, and formula (8) corresponds to the case where the sterilization target product of the sterilization device 50 is an individual beverage.

[0139] In addition, the heat balance calculation unit 201 calculates the cooling water heat discharge amount Q4 using, for example, the following formula (9).

[0140] [Mathematical formula 7]

[0141]

[0142] It should be noted that in formula (9), instead of the cooling water inlet flow rate F5, the cooling water outlet flow rate F6 or the average value of the cooling water inlet flow rate F5 and the cooling water outlet flow rate F6 can also be used.

[0143] In addition, the heat balance calculation unit 201 calculates other heat discharge amounts Q5 using, for example, the following formula (10) derived from the above formula (1).

[0144] [Mathematical formula 8]

[0145] Other heat discharge amount Q5 [kw] =

[0146] Steam heat Q1 [kw] - Drain heat discharge amount Q2 [kw] - Product carried-out heat Q3 [kw] - Cooling water heat discharge amount Q4 [kw] ··· (10)

[0147] In the storage unit 202, a threshold value 202A used in the monitoring unit 203 is stored. The threshold value 202A includes an upper limit threshold value QX_THU and a lower limit threshold value QX_THL (X: an integer from 1 to 5) specified for each of the heat amounts Q1 to Q5. In addition, in the storage unit 202, the threshold value 202A (upper limit threshold value QX_THU and lower limit threshold value QX_THL) can be specified for each category of the static state (e.g., operation mode or product category) of the sterilization device 50, and stored in the storage unit 202.

[0148] The monitoring unit 203 monitors whether the heat amounts Q1 to Q5 successively calculated by the heat balance calculation unit 201 deviate from the normal range (an example of a predetermined range) specified by the threshold value 202A. The monitoring unit 203 grasps the static state such as the operation mode or product category of the current sterilization device 50 based on the state information successively obtained from the production management system 40, for example. And the monitoring unit 203 monitors whether the target heat amount QX deviates from the normal range using the threshold value 202A suitable for the static state of the current sterilization device 50 for each of the heat amounts Q1 to Q5. When all of the heat amounts Q1 to Q5 do not deviate from the normal range, the monitoring unit 203 outputs a monitoring result indicating that the heat is normal. When a part or all of the heat amounts Q1 to Q5 deviate from the normal range, the monitoring unit 203 outputs a monitoring result indicating that the heat is abnormal. In the monitoring result indicating abnormality, the type of the heat amount that deviates from the normal range among the heat amounts Q1 to Q5 is naturally specified.

[0149] The monitoring unit 203 sends the monitoring results, the latest measurement data from the measurement device 10, the latest status information from the production management system 40, and the calculation results of the latest heat balance (heat quantities Q1 to Q5) calculated by the heat balance calculation unit 201 to the monitoring support device 30 in each predetermined control cycle.

[0150] <Processing flow of the thermal energy monitoring device>

[0151] Figure 4 It is a flowchart schematically showing an example of the processing related to the monitoring of thermal energy (heat quantities Q1 to Q5) performed by the thermal energy monitoring device 20. This process is repeatedly executed, for example, in each predetermined control cycle.

[0152] As Figure 4 shown, in step S102, the heat balance calculation unit 201 performs a heat balance calculation. Specifically, the heat balance calculation unit 201 calculates the heat quantities Q1 to Q5 based on the measurement data of the measurement device 10.

[0153] When the thermal energy monitoring device 20 finishes the processing of step S102, it proceeds to step S104.

[0154] In step S104, the monitoring unit 203 obtains the thresholds 202A (upper limit threshold QX_THU and lower limit threshold QX_THL) suitable for the latest status information of each of the heat quantities Q1 to Q5 based on the latest status information.

[0155] When the thermal energy monitoring device 20 finishes the processing of step S104, it proceeds to step S106.

[0156] In step S106, it is determined whether the monitoring unit 203 is in the monitoring target period. The monitoring target period is, for example, a period other than the predetermined time (for example, several minutes to several tens of minutes) after the status information of the sterilization device 50, that is, after the static state is switched. The reason is that it may take a certain amount of time until the dynamic state of the sterilization device 50 stabilizes immediately after the static state of the sterilization device 50 is switched. If the monitoring unit 203 is in the monitoring target period, it proceeds to step S108, and if the monitoring unit 203 is not in the monitoring target period, it proceeds to step S112.

[0157] In step S108, the monitoring unit 203 monitors whether each of the heat quantities Q1 to Q5 calculated by the heat balance calculation unit 201 deviates from the normal range defined by the upper limit threshold QX_THU and the lower limit threshold QX_THL.

[0158] When the thermal energy monitoring device 20 finishes the processing of step S108, it proceeds to step S110.

[0159] In step S110, the monitoring unit 203 determines whether all of the heats Q1 to Q5 are within the normal range. When the monitoring unit 203 determines that all of the heats Q1 to Q5 are within the normal range, it proceeds to step S112. When at least a part of the heats Q1 to Q5 is out of the normal range, it proceeds to step S114.

[0160] In step S112, the monitoring unit 203 sends data including a monitoring result indicating normality to the monitoring support device 30 through the interface device 25.

[0161] On the other hand, in step S114, the monitoring unit 203 sends data including a monitoring result indicating abnormality to the monitoring support device 30 through the interface device 25.

[0162] When the heat energy monitoring device 20 finishes the processing of step S112 or step S114, the processing of this flow is ended.

[0163] In this way, the heat energy monitoring device 20 can determine the normality or abnormality of the sterilization device 50 by monitoring whether each of the heats Q1 to Q5 is out of the normal range defined by the upper limit threshold QX_THU and the lower limit threshold QX_THL.

[0164] <Configuration of Monitoring Support Device>

[0165] The functions of the monitoring support device 30 can be implemented by any hardware, or any combination of hardware and software, etc. For example, the hardware configuration of the monitoring support device 30 can be the same as the hardware configuration of the heat energy monitoring device 20. Hereinafter, in the description of the monitoring support device 30, sometimes Figure 3 the symbols "21", "21A", "22", "23", "24", "25", "26" and "27" in are respectively replaced with "31", "31A", "32", "33", "34", "35", "36" and "37" for description.

[0166] The monitoring support device 30 includes a driving device 31, an auxiliary storage device 32, a memory device 33, a CPU 34, an interface device 35, a display device 36 (an example of a display unit), and an input device 37, and they are respectively connected through a bus B.

[0167] As Figure 1 shown, the monitoring support device 30 includes a database (DB: Data Base) 301, a threshold setting unit 302, an alarm output unit 303, an analysis data generation unit 304, and a cause analysis unit 305.

[0168] The functions of the DB301, threshold setting unit 302, alarm output unit 303, analysis data generation unit 304, and cause analysis unit 305 can be implemented, for example, by loading the program installed in the auxiliary storage device 32 into the memory device 23 and executing it by the CPU 34. In addition, the data corresponding to the DB301 can be stored in the auxiliary storage device 32.

[0169] The DB301 is configured as a record group capable of being retrieved according to a predetermined retrieval condition in a form in which records corresponding to the data successively received from the thermal energy monitoring device 20 are accumulated. The records include, for example, information related to date and time, measurement data of the measurement device 10, status information of the sterilization device 50 (such as the category of product type or operation mode, etc.), calculated values of the heat quantities Q1 to Q5, and monitoring results (distinguished as normal or abnormal), etc.

[0170] The DB301 includes reference data 301A corresponding to the record data with a normal monitoring result and abnormal-time data 301B corresponding to the record data with an abnormal monitoring result.

[0171] The threshold setting unit 302 (an example of a setting unit) sets the thresholds 202A (upper limit threshold QX_THU and lower limit threshold QX_THL) used in the thermal energy monitoring device 20 based on the reference data 301A included in the DB301. Details of the threshold setting unit 302 will be described later.

[0172] When the monitoring result indicating an abnormality is included in the data successively received from the thermal energy monitoring device 20, the alarm output unit 303 outputs an alert to the user. Specifically, the alarm output unit 303 causes the display device 36 to display a screen (hereinafter referred to as "monitoring screen") for indicating that an abnormal monitoring result has been output by the thermal energy monitoring device 20. Thereby, the user can grasp the occurrence of an abnormality in the sterilization device 50 by visually confirming the display device 36. In addition, in the alarm screen, the time series data of the heat quantity QX that has deviated from the normal range among the heat quantities Q1 to Q5, and the upper limit threshold QX_THU and the lower limit threshold QX_THL can be displayed. Thereby, the user can grasp in which direction and to what extent the heat quantity QX of the object has deviated from the predetermined range. In addition, in the monitoring screen, the measurement data associated with the heat quantity QX that has deviated from the normal range can be displayed.

[0173] The analysis data generation unit 304 generates data for analyzing the cause of the abnormality corresponding to the abnormal-time data 301B (hereinafter referred to as "analysis data") based on the data of the DB301, specifically, based on the reference data 301A and the abnormal-time data 301B. Details of the analysis data generation unit 304 will be described later.

[0174] The cause analysis unit 305 (an example of an extraction unit) extracts the state of the sterilization device 50 corresponding to the cause of the abnormality where the heat quantity QX deviates from the normal range, based on the analysis data generated by the analysis data generation unit 304. Specifically, the cause analysis unit 305 extracts the state items corresponding to the cause of the abnormality from among the multiple state items of the sterilization device 50 represented by each of the multiple measurement data obtained by the measurement device 10. The state items may include, for example, the above-described steam temperature T1, drain temperature T2, product inlet temperature T3, product outlet temperature T4, cooling water inlet temperature T5, cooling water outlet temperature T6, etc. In addition, the state items may include, for example, the steam pressure P1, drain pressure P2, steam flow rate F1, drain flow rate F2, product inlet flow rate F3, product outlet flow rate F4, cooling water inlet flow rate F5, and cooling water outlet flow rate F6, etc. Details of the cause analysis unit 305 will be described later.

[0175] <Details of the processing related to threshold setting>

[0176] Figure 5 is a flowchart schematically showing an example of the processing related to the threshold setting performed by the monitoring support device 30. Figure 6 is a diagram showing an example (threshold setting input screen 600) of a screen (hereinafter referred to as "threshold setting input screen") for enabling a user to perform threshold setting and displayed on the display device 36. Figure 7 is a diagram showing an example (threshold final setting screen 700) of a screen (hereinafter referred to as "threshold final setting screen") for enabling a user to finally set a threshold based on the calculated candidate thresholds and displayed on the display device 36.

[0177] For example, when an input for causing the display device 36 to display the threshold setting input screen is received through the input device 37, the execution of Figure 5 the process starts.

[0178] As Figure 5 shown, in step S202, the threshold setting unit 302 receives, through the input device 37, an input of the extraction conditions for extracting the data for threshold setting from the reference data 301A of the DB 301.

[0179] For example, as Figure 6 shown, the threshold setting input screen 600 includes an extraction condition input unit 601.

[0180] The extraction condition input unit 601 includes a product category condition input unit 601A, an operation mode condition input unit 601B, a start date and time condition input unit 601C, an end date and time condition input unit 601D, and an exclusion condition input unit 601E.

[0181] The product category condition input unit 601A is used to enable the user to input extraction conditions related to the product category. The user operates the product category condition input unit 601A through the input device 37 to input extraction conditions related to the product category. Thus, the threshold setting unit 302 can extract records limited by the product category, which is one of the static states of the sterilization device 50, from the record group corresponding to the reference data 301A.

[0182] The operation mode condition input unit 601B is used to enable the user to input extraction conditions related to the operation mode. The user operates the operation mode condition input unit 601B through the input device 37 to input extraction conditions related to the operation mode. Thus, the threshold setting unit 302 can extract records limited by the operation mode, which is one of the static states of the sterilization device 50, from the record group corresponding to the reference data 301A.

[0183] The start date and time condition input unit 601C is used to enable the user to input the start date and time condition corresponding to the start time among the extraction conditions for limiting the period. In addition, the end date and time condition input unit 601D is used to enable the user to input the end date and time condition corresponding to the end time among the extraction conditions for limiting the period. The user operates the start date and time condition input unit 601C and the end date and time condition input unit 601D through the input device 37 to input the extraction conditions for limiting the period (the start date and time and the end date and time of the period). Thus, the threshold setting unit 302 can extract records limited to a specific period from the record group corresponding to the reference data 301A.

[0184] The exclusion condition input unit 601E is used to enable the user to input conditions (hereinafter referred to as "exclusion conditions") for excluding data (records) that meet specific conditions. The user operates the exclusion condition input unit 601E through the input device 37 to input the exclusion conditions. Thus, when the threshold setting unit 302 extracts records that meet the extraction conditions related to the above-mentioned product category, operation mode, and period from the record group corresponding to the reference data 301A, it can exclude the data that meets the exclusion conditions and perform the extraction of records.

[0185] Exclusion conditions include, for example, conditions for excluding data for a predetermined period (e.g., several minutes to more than ten minutes) after switching of status information such as product categories or operation modes (i.e., the static state of the sterilization device 50). Thereby, the user can exclude data (records) for a predetermined period after switching the static state of the sterilization device 50 such as product categories or operation modes from the data used for threshold setting. The reason is that, as described above, it may take a certain amount of time until the dynamic state of the sterilization device 50 stabilizes after just switching the static state of the sterilization device 50.

[0186] Return Figure 5 , in step S204, the threshold setting unit 302 receives an input of conditions for setting a threshold (hereinafter referred to as "threshold conditions") through the input device 37.

[0187] For example, as Figure 6 shown, the threshold setting input screen 600 includes a threshold condition input unit 602.

[0188] The threshold condition input unit 602 is used for the user to input threshold conditions. The user operates the threshold condition input unit 602 through the input device 37 to input threshold conditions. Thereby, the threshold setting unit 302 can set thresholds (upper threshold QX_THU and lower threshold QX_THL) that meet the threshold conditions based on the records extracted according to the extraction conditions input in step S202.

[0189] In this example, the threshold condition is a condition for setting thresholds in such a way as to represent the upper limit value and the lower limit value of the heat QX of the object of the data extracted from the reference data 301A (data in the normal state) according to the extraction conditions, and ensuring a surplus amount of a certain percentage. In other words, it is a condition representing the surplus m [%] of the upper threshold QX_THU and the lower threshold QX_THL for the upper limit value and the lower limit value of the extracted data, respectively.

[0190] It should be noted that the processes of steps S202 and S204 can be executed in parallel according to the operation of the input device 37 by the user.

[0191] When the monitoring support device 30, in a state where the input of the extraction conditions and the threshold conditions in steps S202 and S204 is completed, performs an operation for requesting calculation (arithmetic) of the threshold through the input device 37, it proceeds to step S206.

[0192] For example, as Figure 6 shown, the threshold setting input screen 600 includes a calculation request input unit 603.

[0193] The calculation request input unit 603 is used to enable the user to perform an operation for calculating (computing) a request threshold. The user operates the calculation request input unit 603 through the input device 37. Thus, in a state where the threshold setting unit 302 has completed the input of the extraction condition input unit 601 and the threshold condition input unit 602, the process proceeds to step S206.

[0194] Return Figure 5 , in step S206, the threshold setting unit 302 calculates a threshold according to the threshold condition input in step S204 based on the upper limit value and the lower limit value of the heat QX of the object of the data extracted according to the extraction condition input in step S204. The threshold setting unit 302 calculates the thresholds (upper threshold QX_THU and lower threshold QX_THL) using, for example, the following formulas (11) and (12).

[0195] [Mathematical formula 9]

[0196] Upper threshold QX_THU = upper limit value of the extracted data × (100 + m) / 100 ··· (11)

[0197] Lower threshold QX_THL = lower limit value of the extracted data × (100 - m) / 100 ··· (12)

[0198] The threshold setting unit 302 can display the calculation result of the threshold on the threshold setting input screen 600.

[0199] For example, as Figure 6 shown, the threshold setting input screen 600 includes a current threshold display section 604 and a threshold calculation result display section 605.

[0200] The current threshold display section 604 displays the respective thresholds (upper threshold QX_THU and lower threshold QX_THL) of the currently set heats Q1 to Q5. Thus, the user can confirm the currently set thresholds (upper threshold QX_THU and lower threshold QX_THL).

[0201] The newly calculated thresholds (upper threshold QX_THU and lower threshold QX_THL) are displayed on the threshold calculation result display section 605. Thus, the user can confirm the calculation result of the thresholds (upper threshold QX_THU and lower threshold QX_THL) based on the new extracted data. In addition, on the threshold calculation result display section 605, the average value, upper limit value, lower limit value, etc. of the heat QX of the object of the extracted data can be displayed together.

[0202] Return Figure 5 , when the monitoring support device 30 receives an input for requesting a transfer to the threshold final setting screen through the input device 37 after the process of step S206, it proceeds to step S208.

[0203] In step S208, the threshold setting unit 302 causes the display content of the display device 36 to transfer from the input screen for threshold setting to the final threshold setting screen.

[0204] For example, as Figure 6 shown, the input screen 600 for threshold setting includes a display request input unit 606.

[0205] The display request input unit 606 is used to enable the user to request a transfer to the final threshold setting screen. The user operates the display request input unit 606 through the input device 37. Thus, on the premise that the process of threshold calculation (step S206) has been completed, the threshold setting unit 302 causes the display content of the display device 36 to transfer from the input screen 600 for threshold setting to the final threshold setting screen 700.

[0206] For example, as Figure 7 shown, the final threshold setting screen 700 includes a time series display unit 701, a frequency distribution display unit 702, an object heat selection unit 703, a modification request input unit 704, and an end request input unit 705.

[0207] In the time series display unit 701, the data extracted according to the extraction conditions input in step S202 is displayed in a time series chart. In this example, the data extracted according to the extraction conditions is displayed, and the data excluded by the exclusion conditions, that is, the data for a predetermined period immediately after the state information corresponding to the static state of the sterilization device 50 is switched, is displayed as a dashed line.

[0208] In the time series display unit 701, an upper threshold line 701A and a lower threshold line 701B corresponding to the upper threshold QX_THU and the lower threshold QX_THL are respectively displayed. Thus, the user can visually confirm the relationship between the change in the time series of the extracted data and the upper threshold QX_THU and the lower threshold QX_THL.

[0209] In the frequency distribution display unit 702, the data extracted according to the extraction conditions input in step S202 is displayed as a frequency distribution according to intervals of values at equal intervals.

[0210] In the frequency distribution display unit 702, an upper threshold line 702A and a lower threshold line 702B corresponding to the upper threshold QX_THU and the lower threshold QX_THL are displayed. Thus, the user can visually confirm the relationship between the frequency distribution of the extracted data and the upper threshold QX_THU and the lower threshold QX_THL.

[0211] The object heat selection unit 703 is used to enable the user to select the heat QX of the object to be displayed from the heats Q1 to Q5. The user can operate the object heat selection unit 703 through the input device 37 to switch the heat QX of the object displayed on the threshold final setting screen.

[0212] The modification request input unit 704 is used to perform an input for enabling the user to request a modification of the calculated thresholds (the upper threshold QX_THU and the lower threshold QX_THL). The user operates the modification request input unit 704 through the input device 37. In this case, the threshold setting unit 302 allows the calculated thresholds to be modified. Specifically, the threshold setting unit 302 can cause the threshold final setting screen 700 to display an input box capable of directly inputting the numerical value of the threshold. In addition, the threshold setting unit 302 can allow, for example, the upper threshold lines 701A, 702A or the lower threshold lines 701B, 702B of the threshold final setting screen 700 to be directly moved through the input device 37. For example, the threshold setting unit 302 allows the modification of the threshold in a form in which the user moves the upper threshold lines 701A and 702A or the lower threshold lines 701B, 702B of the threshold final setting screen 700 by using a touch panel installed on the display device.

[0213] The end request input unit 705 is used to enable the user to request the completion (end of setting) of the threshold setting under the content displayed by the threshold final setting screen 700. The user operates the end request input unit 705 through the input device 37.

[0214] Return Figure 5 When the monitoring support device 30 finishes the process of step S208, it proceeds to step S210.

[0215] In step S210, the threshold setting unit 302 determines whether an input for the end of the threshold setting (setting completion) (for example, the operation of the end request input unit 705) has been made through the input device 37. In the case where an input for the end of the threshold setting has been made, the threshold setting unit 302 sets and saves the values corresponding to the display content of the threshold final setting screen as the thresholds (the upper threshold QX_THU and the lower threshold QX_THL), and ends the processing of this flow. On the other hand, in the case where the threshold setting unit 302 has made an input for requesting a threshold modification (for example, the operation of the modification request input unit 704) instead of an input for the end of the threshold setting, it proceeds to step S212.

[0216] In step S212, the threshold setting unit 302 modifies the threshold according to the input from the input device 37.

[0217] When the monitoring support device 30 finishes the processing of step S212, it returns to step S208, and the threshold setting unit 302 modifies and displays the content of the threshold final setting screen in a manner corresponding to the modified threshold value.

[0218] In this way, the threshold setting unit 302 can calculate and set the upper limit threshold value QX_THU and the lower limit threshold value QX_THL from the upper limit value and the lower limit value of the heat QX of the data extracted according to the extraction conditions, based on a request from the user.

[0219] <Details of the processing related to cause analysis>

[0220] Figure 8 It is a diagram showing an example of an abnormal occurrence history screen (abnormal occurrence history screen 800). Figure 9 It is a diagram schematically showing the processing flow related to the abnormal cause analysis performed by the monitoring support device 20. Figure 10 It is a diagram showing an example of a screen (hereinafter referred to as "analysis result screen") for representing the result of the cause analysis processing obtained by the cause analysis unit 305 (analysis result screen 1000). Figure 11 It is a diagram showing another example of the analysis result screen (analysis result screen 1100).

[0221] The monitoring support device 30 causes the display device 36 to display an abnormal occurrence history screen according to a request from the user through the input device 37. This abnormal occurrence history screen is used to represent the history (record) of abnormal occurrences corresponding to the heat QX deviating from the normal range. The history (record) of abnormal occurrences can include, for example, the type of abnormality, the date and time of abnormal occurrence, the date and time of abnormal end (return to normal), the product category at the time of abnormal occurrence, the operation mode at the time of abnormal occurrence, the calculated values of the heats Q1 to Q5 at the time of abnormal occurrence, etc.

[0222] For example, as Figure 8 shown, the display device 36 displays the abnormal occurrence history screen 800.

[0223] The abnormal occurrence history screen 800 includes an abnormal type condition input unit 801, a start date and time condition input unit 802, an end date and time condition input unit 803, a product category condition input unit 804, an operation mode condition input unit 805, a display request input unit 806, and an abnormal occurrence history display unit 810.

[0224] The abnormal type condition input unit 801 is used for the user to input conditions related to the type of abnormality when extracting the history of abnormal occurrences from the abnormal time data 301B. The user operates the abnormal type condition input unit 801 through the input device 37 to input conditions related to the type of abnormality.

[0225] The start date / time condition input unit 802 is used to enable the user to input a condition for the start date / time corresponding to the start time of the period when extracting the history of the occurrence of an abnormality from the abnormality-time data 301B. The user operates the start date / time condition input unit 802 through the input device 37 to input a condition related to the start date / time.

[0226] The end date / time condition input unit 803 is used to enable the user to input a condition for the end date / time corresponding to the end time of the period when extracting the history of the occurrence of an abnormality from the abnormality-time data 301B. The user operates the end date / time condition input unit 803 through the input device 37 to input a condition related to the end date / time.

[0227] The product category condition input unit 804 is used to enable the user to input a condition related to the product category when extracting the history of the occurrence of an abnormality from the abnormality-time data 301B. The user operates the product category condition input unit 804 through the input device 37 to input a condition related to the product category.

[0228] The operation mode condition input unit 805 is used to enable the user to input a condition related to the operation mode when extracting the history of the occurrence of an abnormality from the abnormality-time data 301B. The user operates the operation mode condition input unit 805 through the input device 37 to input a condition related to the operation mode.

[0229] The display request input unit 806 is used to enable the user to input a display request for the history of the occurrence of an abnormality according to the conditions input in the condition input units 801 to 805. The user operates the display request input unit 806 through the input device 37 to input a display request for the history of the occurrence of an abnormality.

[0230] The abnormality occurrence history display unit 810 displays the history (record) of the occurrence of an abnormality according to the operation of the display request input unit 806, that is, the display request, based on the conditions input in the condition input units 801 to 805. The user can select any one (column) from the records of the history of the occurrence of an abnormality corresponding to each example in the figure through the input device 37. Thereby, the monitoring support device 30 starts the process of analyzing the cause of the occurrence of an abnormality corresponding to the selected record of the history of the occurrence of an abnormality.

[0231] For example, as Figure 9As shown, first, the analysis data generation unit 304 executes data generation processing for generating analysis data 304A based on reference data 301A and abnormal-time data 301B. Specifically, the analysis data generation unit 304 generates analysis data 304A according to the time-series data of the respective dynamic states of the sterilization device 50 at the time of abnormal occurrence and normal time corresponding to the record selected in the abnormal occurrence history screen. The time-series data of the dynamic state corresponds, for example, to the time-series data of the measurement data (measurement values) of the measurement device 10. In addition, the time-series data of the dynamic state during normal time is preferably, for example, the time-series data of the dynamic state included in the reference data 301A (extracted data) used in the setting of the upper threshold QX_THU and the lower threshold QX_THL performed by the threshold setting unit 302. The reason is that data for which the matching of the determination criteria for normal or abnormal should be ensured are compared with each other.

[0232] For example, the analysis data 304A can be data in a tabular form (matrix form) such as a CSV (Comma Separated Value) file. Specifically, the analysis data 304A can be in the following form: in the row direction, records with different date and times (moments) are arranged, and in the column direction, a plurality of status items representing the dynamic state and a plurality of data items including an item indicating the distinction between normal or abnormal are arranged.

[0233] After the analysis data 304A is output from the analysis data generation unit 304, the cause analysis unit 305 uses the analysis data 304A to perform cause analysis processing for the abnormal occurrence corresponding to the record of the abnormal occurrence history selected in the abnormal occurrence history screen. Specifically, the cause analysis unit 305 uses the analysis data 304A to extract the status item corresponding to the cause of the abnormal occurrence from the plurality of status items representing the dynamic state of the sterilization device 50.

[0234] For example, the cause analysis unit 305 uses two cause analysis methods, correlation analysis and decision tree analysis, based on the analysis data 304A to extract the status item corresponding to the cause of the abnormal occurrence from the plurality of status items representing the dynamic state of the sterilization device 50. Specifically, the cause analysis unit 305 calculates the correlation coefficient and variable importance between the respective data (measurement data) of the plurality of status items and the data indicating the distinction between abnormal or normal (for example, data that distinguishes abnormal or normal by "0" or "1").

[0235] The correlation coefficient is calculated in a range of -1 to +1 in correlation analysis, and the larger its absolute value, the higher the correlation (linear relationship) between the target status item and the distinction between abnormal and normal. In other words, it indicates a higher degree of significance of the target status item as the cause of the abnormality. Furthermore, variable importance is calculated in a range of 0 to 1 in decision tree analysis and indicates the importance of the cause of the abnormality of the target status item.

[0236] The cause analysis unit 305 may calculate, for each of the multiple status items, a correlation coefficient between the item and the data indicating whether the item is abnormal or normal, and extract the item with the relatively large absolute value of the correlation coefficient from among the multiple status items and use it as a cause (candidate) of the abnormality. For example, the cause analysis unit 305 may extract the item with the absolute value of the correlation coefficient from among the multiple status items that is greater than a predetermined threshold, or a predetermined number (e.g., three) of the item that are ranked highest in descending order of the absolute value of the correlation coefficient from among the multiple status items.

[0237] Similarly, the cause analysis unit 305 can calculate the variable importance between each of the multiple status items and the data indicating the difference between abnormality and normality, and extract the status items with relatively large variable importance from the multiple status items and use them as the cause (candidate) of the abnormality. For example, the cause analysis unit 305 can extract the status items with variable importance above a predetermined threshold from the multiple status items, or a predetermined number (e.g., 3) of the status items that are ranked top in descending order of variable importance from the multiple status items.

[0238] Cause analysis unit 305 outputs analysis result data 305A indicating the results of the cause analysis process. Analysis result data 305A includes, for example, the calculated values of the correlation coefficient and importance coefficient for each of the plurality of status items with respect to the abnormal / normal distinction. Furthermore, analysis result data 305A may include, for example, information related to status items with high correlation coefficients or relatively high importance coefficients with respect to the abnormal / normal distinction, and these status items are identified as candidates for the causes of the abnormality.

[0239] Furthermore, the cause analysis unit 305 may cause the display device 36 to display a screen (analysis result screen) showing the result of the cause analysis process based on the analysis result data 305A.

[0240] For example, Figure 10 As shown, the cause analysis unit 305 may cause the display device 36 to display an analysis result screen 1000 .

[0241] It should be noted that Figure 10The "Tag name" in the is equivalent to the category of the status item. The same applies to the following Figure 11 situation.

[0242] In the analysis result screen 1000 , the correlation coefficients (absolute values) and variable importances calculated by the correlation analysis and decision tree analysis are listed in descending order of status items (“Tag name”).

[0243] It should be noted that the status items for which both the correlation coefficient and the variable importance are calculated to be zero (0) are not displayed in the analysis result screen 1000. Therefore, in the decision tree analysis, only the variable importance of the three status items is displayed.

[0244] In addition, for example, Figure 11 As shown, the cause analysis unit 305 may cause the display device 36 to display an analysis result screen 1100 .

[0245] Analysis result screen 1100 displays a scatter plot of time series data related to the top three status items, ranked in descending order of correlation coefficient (absolute value) and variable importance, calculated through correlation analysis and decision tree analysis. Specifically, analysis result screen 1100 displays a scatter plot showing the relationship between the top three status items, ranked in descending order of correlation coefficient (absolute value) and variable importance, and the amount of heat QX (in this example, cooling water heat Q4) that is outside the normal range. The individual charts of the scatter plot are displayed in a form that allows for distinction between normal and abnormal conditions. For example, the individual charts in the scattered portion can be distinguished by color or shape to indicate normal and abnormal conditions.

[0246] This allows the user to identify, for example, a status item (Tag 1 or Tag 30 in this example) that ranks high in both the correlation coefficient and the importance coefficient as the cause of the abnormality, thereby enabling measures to recover from the abnormality.

[0247] In this way, when an abnormality occurs, such as when any of the heat quantities QX among the heat quantities Q1 to Q5 deviates from the normal range, the monitoring support device 30 can extract the status item corresponding to the cause of the abnormality from the multiple status items representing the dynamic state of the sterilization device 50 before the target heat quantity QX is narrowed down. Furthermore, regardless of whether the monitored device (sterilization device 50) is a linear or nonlinear device, the monitoring support device 30 can apply both cause analysis methods (two indicators)—correlation analysis and decision tree analysis—to extract the status item corresponding to the cause.

[0248] [Other embodiments]

[0249] Next, other embodiments will be described.

[0250] Appropriate modifications or changes can be made to the above-described embodiments.

[0251] For example, in the above-described embodiment, the thermal energy monitoring device 20 can send data including a monitoring result indicating that it is outside the monitoring target period (when the answer is no in step S106 in the above Figure 4 ) to the monitoring support device 30 when it is not in the monitoring target period. Additionally, Figure 4 the process of step S106 can be omitted.

[0252] Furthermore, for example, in the above-described embodiment or its modifications or changes, the heat balance calculation unit 201 can use an experimental formula based on empirical rules obtained through experiments or simulations, etc., to replace the logical expressions of (2) to (9) above or an approximate expression premised on that logical expression. In this case, the measurement data used in the experimental formula can include measurement data of the measurement object other than the temperature, pressure, and flow rate inside the sterilization device 50.

[0253] Moreover, for example, in the above-described embodiment or its modifications or changes, the function of the alarm output unit 303 can be set in the thermal energy monitoring device 20 instead of being set in the monitoring support device 30, or in addition to being set in the monitoring support device 30, it can also be set in the thermal energy monitoring device 20. Additionally, the alarm output unit 303 can send an alarm signal to a portable (movable) terminal device held by the user, such as a smartphone or a tablet terminal, and output an alert to the user through the portable terminal device. In this case, the alarm screen can be displayed on the portable terminal device held by the user.

[0254] In addition, for example, in the above-described embodiment or its modifications or changes, part or all of the functions of the monitoring support device 30 can be integrated into the thermal energy monitoring device 20. Also, part of the functions of the monitoring support device 30 can be transferred to another device. That is, the functions of the monitoring support device 30 can be realized by multiple devices in a shared manner. For example, the function of setting the monitoring reference and the function of cause analysis of the monitoring support device 30 can be realized by different devices in a shared manner.

[0255] In addition, for example, in the above-described embodiments or variations or modifications, the threshold setting unit 302 may set a threshold for the heat quantity QX of the object using all of the data in the reference data 301A, instead of setting a threshold using a part of the data extracted from the reference data 301A. In addition, the threshold setting unit 302 may set a threshold using the average value as a reference, instead of setting a threshold using the upper limit value and the lower limit value of all or part of the data in the reference data 301A of the heat quantity QX of the object.

[0256] In addition, for example, in the above-described embodiments or variations or modifications, the cause analysis unit 305 may use three or more cause analysis methods to extract the state items of the sterilization device 50 corresponding to the cause of the heat quantity QX of the object deviating from the normal range. In addition, the cause analysis unit 305 may use other cause analysis methods instead of at least one of the correlation analysis and the decision tree analysis, or in addition to using at least one of the correlation analysis and the decision tree analysis, use other cause analysis methods to extract the state items of the sterilization device 50 corresponding to the cause of the heat quantity QX of the object deviating from the normal range.

[0257] In addition, for example, in the above-described embodiments or variations or modifications, in the analysis result screen of the display device 36, the correlation coefficient (absolute value) and the variable importance calculated by the correlation analysis and the decision tree analysis may be displayed by both list display and scatter plot display.

[0258] In addition, for example, in the above-described embodiments or variations or modifications, the monitored device of the heat energy monitoring system 1 (heat energy monitoring device 20) may be any device other than the sterilization device 50 as long as it is a device that generates a heat balance (heat input and output) including heat generation or heat absorption.

[0259] [Function]

[0260] Next, the function of the heat energy monitoring system 1 according to the present embodiment will be described.

[0261] For example, as shown in the above-mentioned Patent Document 1, when monitoring the state data (measurement data) of the monitored device, if the types of state data to be monitored are relatively numerous, it is necessary to prepare a reference for abnormality determination for each of these types, so there may be a lot of trouble.

[0262] On the other hand, for example, as shown in the above-mentioned Patent Document 2 or the method of multivariate statistical process control (MSPC: Multivariate Statistical Process Control), it is also possible to reduce multiple types of state data into fewer variables.

[0263] However, in the case of these methods, although the trouble caused when preparing the criteria for anomaly determination is reduced, it may be difficult to easily determine, when an anomaly occurs, which status item corresponding to which type of status data is the cause of the anomaly. In addition, although these methods are effective for cases where the monitored device can be regarded as linear, they may not be applicable to non-linear cases, or even if applicable, it may take time to infer (determine) the cause.

[0264] In contrast, in the present embodiment, the thermal energy monitoring device 20 includes a heat balance calculation unit 201 and a monitoring unit 203. Specifically, the heat balance calculation unit 201 acquires data related to the status of the monitored device, and calculates multiple types of thermal energy (such as heat quantities Q1 to Q5) that constitute the heat balance of the monitored device based on this data. And the monitoring unit 203 monitors whether the thermal energy of the target type deviates from the normal range defined by the upper limit threshold and the lower limit threshold for each type of thermal energy calculated by the heat balance calculation unit 201.

[0265] Thereby, the thermal energy monitoring device 20 can change the object to be monitored into data of a large number of status items related to the monitored device (such as measurement data), and condense it into multiple types of thermal energy (such as 5 types) that constitute the heat balance. Therefore, the trouble caused when preparing the criteria for anomaly determination can be relatively reduced. In addition, the thermal energy monitoring device 20 can be applied regardless of whether the monitored device is linear or non-linear by using data of multiple types of thermal energy that constitute the heat balance, and can relatively easily infer (determine) the cause.

[0266] In addition, in the present embodiment, the data related to the status of the monitored device may include data related to the dynamic status of the monitored device including temperature, pressure, and flow rate, and data related to the static status of the monitored device including the operating status.

[0267] Thereby, the thermal energy monitoring device 20 can calculate each type of thermal energy among the multiple types of thermal energy that constitute the heat balance of the monitored device based on the data regarding multiple status items corresponding to the dynamic status of the monitored device. In addition, the thermal energy monitoring device 20 can monitor whether it deviates from the normal range while considering the static status.

[0268] In addition, in the present embodiment, the monitoring unit 203 may make at least one of the upper limit threshold and the lower limit threshold different for each category of the static status of the monitored device (such as the category of the operating mode or the product category).

[0269] Thereby, the thermal energy monitoring device 20 can monitor whether it deviates from the normal range while specifically considering the static status.

[0270] In addition, in the present embodiment, when the static state of the monitored device is switched, the monitoring unit 203 temporarily stops monitoring multiple types of heat energy. And, after a predetermined time has elapsed after the switching of the static state of the monitored device, the monitoring unit 203 can start monitoring multiple types of heat energy again.

[0271] Thus, the heat energy monitoring device 20 can appropriately perform monitoring related to multiple types of heat energy along with the switching of the static state of the monitored device. The reason is that when the static state of the monitored device is switched, the heat balance of the monitored device fluctuates, and it takes time for the fluctuation to stabilize.

[0272] In addition, in the present embodiment, the monitoring support device 30 includes a threshold setting unit 302. Specifically, the threshold setting unit 302 can set an upper threshold and a lower threshold based on the time series data of multiple types of heat energy calculated by the heat balance calculation unit 201.

[0273] Thus, the monitoring support device 30 can, for example, set the upper threshold and the lower threshold based on the historical data of the normal heat energy of the object (for example, the reference data 301A), that is, the normal data of the heat energy of the object accumulated in time series as a reference.

[0274] In addition, in the present embodiment, the threshold setting unit 302 can set the upper threshold and the lower threshold for the heat energy of the target type among multiple types of heat energy based on the upper limit value, the lower limit value, or the average value of its time series data.

[0275] Thus, the monitoring support device 30 can set the upper threshold and the lower threshold specifically based on the historical data (time series data) of the normal heat energy of the object.

[0276] In addition, in the present embodiment, the threshold setting unit 302 can extract partial data that meets the extraction conditions from all the time series data of the heat energy of the target type among multiple types of heat energy, and set the upper threshold and the lower threshold based on the extracted partial data. The extraction conditions include at least one of a condition related to the category of the static state of the monitored device and a condition related to time.

[0277] Thus, the monitoring support device 30 can set the upper threshold value and the lower threshold value based on the partial data that meets the extraction conditions by limiting the historical data of the thermal energy of the object in the normal state, and use the limited partial data as a reference. Therefore, the monitoring support device 30 can, for example, select more appropriate data as the setting reference for the upper threshold value and the lower threshold value. Thus, the monitoring support device 30 can set the upper threshold value and the lower threshold value more appropriately.

[0278] In addition, in the present embodiment, the monitoring support device 30 includes a display device 36. Specifically, the display device 36 can display at least one of a time series graph, a frequency distribution graph, and a scatter graph of the thermal energy of the object type among multiple types of thermal energy, and candidates for the upper threshold value and the lower threshold value calculated by the threshold setting unit 302 based on the time series data of the thermal energy of the object type. Also, the display device 36 can display input objects (for example, the upper threshold lines 701A, 702A or the lower threshold lines 701B, 702B that can be operated by the touch panel as the input device 37) for receiving user input for modifying the candidates for the upper threshold value and the lower threshold value.

[0279] Thus, the user can visually confirm on the screen the relationship between the historical data of the thermal energy of the object, which is the calculation reference for the upper threshold value and the lower threshold value, and the upper threshold value and the lower threshold value. In addition, the user can modify the candidates for the upper threshold value and the lower threshold value on the screen. Therefore, the monitoring support device 30 can improve the convenience for the user.

[0280] In addition, in the present embodiment, the monitoring support device 30 includes a cause analysis unit 305. Specifically, when the thermal energy monitoring device 20 detects that a predetermined thermal energy among multiple types of thermal energy deviates from the normal range, the cause analysis unit 305 extracts the status item indicating the cause of the predetermined thermal energy deviating from the normal range from among multiple status items representing the status of the monitored object device.

[0281] Thus, when a predetermined thermal energy deviates from the normal range, the monitoring support device 30 can determine (infer) the status item of the monitored object device corresponding to the cause.

[0282] In addition, in the present embodiment, the cause analysis unit 305 uses multiple cause analysis methods including at least one of correlation analysis and decision tree analysis based on the time series data of multiple status items when a predetermined thermal energy is detected to deviate from the normal range and the time series data of multiple status items when the predetermined thermal energy does not deviate from the normal range, and extracts the status item indicating the cause of the predetermined thermal energy deviating from the normal range from among multiple status items.

[0283] Accordingly, the monitoring support device 30 can specifically determine (infer) the state items of the monitored device corresponding to the cause of the abnormality in which the predetermined thermal energy deviates from the normal range. In addition, by using a variety of cause analysis methods, the monitoring support device 30 can perform cause inference regardless of whether the monitored device is a linear device or a non-linear device, and can improve the accuracy of cause inference.

[0284] In addition, in the present embodiment, the monitoring support device 30 includes a display device 36 for displaying the extraction results of the cause analysis unit 305. Specifically, for each state item among the plurality of state items, the display device 36 displays the degree of the cause of the predetermined thermal energy deviating from the normal range (for example, the correlation coefficient of the correlation analysis or the variable importance of the decision tree analysis) as a list or a scatter diagram of the time series data of the predetermined thermal energy.

[0285] Accordingly, the user can visually confirm the degree of the cause of the predetermined thermal energy deviating from the normal range, and grasp the state items of the monitored device corresponding to the cause based on this degree.

[0286] Although the embodiments have been described in detail above, the present disclosure is not limited to the specific embodiments, and various modifications and changes can be made within the scope of the gist described in the claims.

Claims

1. A monitoring device, comprising: a heat energy calculation unit that acquires data related to the state of a monitored device and calculates multiple types of heat energy that constitute the overall heat balance in the monitored device based on the data; and a monitoring unit that monitors whether the heat energy of a target type among the multiple types of heat energy calculated by the heat energy calculation unit deviates from a predetermined range defined by an upper threshold and a lower threshold, the data related to the state of the monitored device includes data related to the dynamic state of the monitored device including temperature, pressure, and flow rate, and data related to the static state of the monitored device including the operating state, the monitoring unit makes at least one of the upper threshold and the lower threshold different for each category of the static state of the monitored device.

2. The monitoring device according to claim 1, wherein when the static state of the monitored device is switched, the monitoring unit temporarily stops monitoring the multiple types of heat energy, and after a predetermined time has elapsed after the switch of the static state of the monitored device, resumes monitoring the multiple types of heat energy.

3. A threshold setting device for setting the upper threshold and the lower threshold used in the monitoring device according to claim 1 or 2, the threshold setting device comprising: a setting unit that sets the upper threshold and the lower threshold based on the time series data of the multiple types of heat energy calculated by the heat energy calculation unit.

4. The threshold setting device according to claim 3, wherein the setting unit sets the upper threshold and the lower threshold for the heat energy of a target type among the multiple types of heat energy based on the upper limit value, the lower limit value, or the average value of its time series data.

5. The threshold setting device according to claim 3 or 4, wherein the setting unit extracts partial data that meets the extraction conditions from all of its time series data for the heat energy of a target type among the multiple types of heat energy, and sets the upper threshold and the lower threshold based on the extracted partial data, and the extraction conditions include at least one of a condition related to the category of the static state of the monitored device and a condition related to time.

6. The threshold setting device according to claim 3 or 4, further comprising: a display unit that displays at least one of a time series graph, a frequency distribution graph, and a scatter graph of the heat energy of a target type among the multiple types of heat energy, and candidates for the upper threshold and the lower threshold calculated by the setting unit based on the time series data of the heat energy of the target type, and displays an input object for receiving an input from a user for modifying the candidates.

7. A cause analysis device, comprising: Extraction unit: When a predetermined heat energy among the multiple types of heat energies detected by the monitoring device according to claim 1 or 2 deviates from the predetermined range, the extraction unit extracts a status item indicating the reason for the deviation of the predetermined heat energy from the predetermined range from among the multiple status items representing the status of the monitored device associated with the predetermined heat energy.

8. The cause analysis device according to claim 7, wherein the extraction unit uses multiple cause analysis methods including at least one of correlation analysis and decision tree analysis based on the time series data of the multiple status items when it is detected that the predetermined heat energy deviates from the predetermined range and the time series data of the multiple status items when the predetermined heat energy does not deviate from the predetermined range, and extracts a status item indicating the reason for the deviation of the predetermined heat energy from the predetermined range from among the multiple status items.

9. The cause analysis device according to claim 7 or 8, further comprising: display unit, which displays the extraction result of the extraction unit, wherein the display unit displays the degree of the reason for the deviation of the predetermined heat energy from the predetermined range as a list for each status item among the multiple status items, or as a scatter plot of the time series data of the predetermined heat energy.

10. A monitoring method performed by a monitoring device, comprising: heat energy calculation step: obtaining data related to the status of the monitored device, and calculating multiple types of heat energies that constitute the overall heat balance in the monitored device based on the data; and monitoring step: monitoring whether each type of heat energy calculated in the heat energy calculation step deviates from a predetermined range defined by an upper threshold and a lower threshold, the data related to the status of the monitored device includes data related to the dynamic status of the monitored device including temperature, pressure, and flow rate, and data related to the static status of the monitored device including the operating status, in the monitoring step, at least one of the upper threshold and the lower threshold is made different according to each category of the static status of the monitored device.

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