JP2022101345A - Monitoring device, threshold value setting device, factor analysis device, and monitoring method - Google Patents

Abstract

To provide a technique capable of easily estimating a factor when an abnormality occurs while suppressing the trouble of setting a standard for abnormality determination, regarding a monitored device which heat energy goes into and out from, including heat generation and absorption.SOLUTION: A heat energy monitoring device 20 according to an embodiment of the present disclosure includes: a heat balance calculation unit 201 that acquires data about a state of a sterilizer 50, and based on the data, calculates multiple types of heat energy (heat amounts Q1 to Q5) that constitute heat balance of the sterilizer 50; and a monitoring unit 203 that monitors presence or absence of deviation of the heat energy (heat amount QX) of a target type from a normal range defined by upper and lower threshold values for each of the multiple types of heat energy (heat amounts Q1 to Q5) calculated by the heat balance calculation unit 201.SELECTED DRAWING: Figure 1

Description

This disclosure relates to a monitoring device and the like.

For example, there is known a technique for determining the presence or absence of an abnormality in a monitored device by monitoring state data (measured value) representing the state of the monitored device (see Patent Document 1).

Patent Document 1 discloses a technique of monitoring a frame voltage of an industrial furnace as a monitored device and transmitting alarm information to the outside when the frame voltage becomes equal to or less than a threshold value.

Further, for example, a technique is known in which many types of state data representing the state of a monitored device are reduced to relatively few variables, and the reduced variables are used to monitor the monitored device. (See Patent Document 2).

Patent Document 2 discloses a technique for reducing a plurality of state data to one Mahalanobis distance and monitoring an abnormality using the Mahalanobis distance for a refrigeration cycle device as a monitored device.

Japanese Unexamined Patent Publication No. 2019-100572 Japanese Unexamined Patent Publication No. 2005-345096

However, for example, in the case of monitoring the state data of the monitored device as in Patent Document 1, when the types of state data to be monitored are relatively large, it becomes necessary to prepare the criteria for abnormality determination for each type. As a result, a lot of hassle can occur.

On the other hand, for example, as in Patent Document 2, if a plurality of types of state data are reduced to fewer variables, the time and effort required to prepare the criteria for determining an abnormality is reduced, but which type of state data corresponds to when an abnormality occurs. It may not be possible to easily determine whether the status item to be used is the cause of the abnormality.

Therefore, in view of the above problems, it is necessary to easily realize the factor estimation at the time of abnormality occurrence while suppressing the trouble of setting the standard for abnormality determination for the monitored device in which heat generation and heat energy including heat absorption are generated and discharged. The purpose is to provide the technology that is possible.

In order to achieve the above object, in one embodiment of the present disclosure,
A thermal energy calculation unit that acquires data on the state of the monitored device and calculates a plurality of types of thermal energy constituting the heat balance of the monitored device based on the data.
For each of the plurality of types of thermal energy calculated by the thermal energy calculation unit, a monitoring unit for monitoring the presence or absence of deviation of the target type of thermal energy from a predetermined range defined by the upper limit threshold and the lower limit threshold. Prepare, prepare
A monitoring device is provided.

Also, in other embodiments of the present disclosure,
A threshold value setting device for setting the upper limit threshold value and the lower limit threshold value used in the above-mentioned monitoring device.
A setting unit for setting the upper limit threshold value and the lower limit threshold value based on the time series data of the plurality of types of thermal energy calculated by the thermal energy calculation unit is provided.
A threshold setting device is provided.

Further, in still other embodiments of the present disclosure,
When the above-mentioned monitoring device detects a deviation of a predetermined thermal energy from the predetermined range among the plurality of types of thermal energy, a plurality representing the state of the monitored device related to the predetermined energy. The present invention includes an extraction unit for extracting a state item representing a factor of deviation of the predetermined thermal energy from the predetermined range from the state items of the above.
A factor analyzer is provided.

Further, in still other embodiments of the present disclosure,
It is a monitoring method executed by the monitoring device.
A thermal energy calculation step of acquiring data on the state of the monitored device and calculating a plurality of types of thermal energy constituting the heat balance of the monitored device based on the data.
For each of the plurality of types of thermal energy calculated in the thermal energy calculation step, a monitoring step for monitoring the presence or absence of deviation of the thermal energy of the target type from a predetermined range defined by the upper limit threshold and the lower limit threshold. include,
A monitoring method is provided.

According to the above-described embodiment, it is possible to easily estimate the cause of an abnormality in a monitored device in which heat is generated or heat energy including endothermic is input and output, while suppressing the trouble of setting a standard for determining an abnormality. be able to.

It is a figure which shows an example of the structure of a thermal energy monitoring system. It is a figure which shows an example of the structure of the sterilizer as a monitoring target of a thermal energy monitoring system. It is a figure which shows an example of the hardware composition of the thermal energy monitoring apparatus. It is a flowchart which shows typically an example of the process which concerns on the monitoring of thermal energy by a thermal energy monitoring apparatus. It is a flowchart which shows typically an example of the processing about the setting of the threshold value by a monitoring support device. It is a figure which shows an example of the input screen for threshold value setting. It is a figure which shows an example of a threshold value final setting screen. It is a figure which shows an example of an abnormality occurrence history screen. It is a figure which shows the process flow about the cause analysis of an abnormality by a monitoring support device. It is a figure which shows an example of the analysis result screen. This is a screen showing another example of the analysis result screen.

Hereinafter, embodiments will be described with reference to the drawings.

[Overview of thermal energy monitoring system]
First, the thermal energy monitoring system 1 according to the present embodiment will be described with reference to FIG.

FIG. 1 is a diagram showing an example of the configuration of the thermal energy monitoring system 1 according to the present embodiment.

The thermal energy monitoring system 1 according to the present embodiment determines the presence or absence of an abnormality by monitoring the balance of thermal energy in the sterilizer 50 as a monitoring target.

As shown in FIG. 1, the thermal energy monitoring system 1 includes a measuring device 10, a thermal energy monitoring device 20, and a monitoring support device 30. Further, the thermal energy monitoring system 1 cooperates with the production control system 40.

The measuring device 10 is attached to the sterilizing device 50 or installed around the sterilizing device 50, measures various states of the sterilizing device 50, and outputs measurement data regarding the dynamic state of the sterilizing device 50. The dynamic state of the sterilizer 50 means a state that can change dynamically with the operation of the sterilizer 50. The dynamic state of the sterilizer 50 includes, for example, a temperature state, a pressure state, a flow rate state, and the like inside the sterilizer 50. The measurement data output from the measuring device 10 is taken into the thermal energy monitoring device 20 through a predetermined communication line. The predetermined communication line is, for example, a one-to-one communication line. Further, the predetermined communication line may be, for example, a local network (LAN: Local Area Network) in the factory where the sterilizer 50 is installed, such as a field network. Further, the predetermined communication line may include, for example, a wide area network (WAN: Wide Area Network) outside the factory where the sterilizer 50 is installed. The wide area network may include, for example, a mobile communication network having a base station as an end, a satellite communication network using a communication satellite, an Internet network, and the like. Further, the predetermined communication line may include a short-range communication line based on a wireless communication standard such as WiFi or Bluetooth (registered trademark).

The thermal energy monitoring device 20 (an example of the monitoring device) monitors the operating state of the sterilizer 50. Specifically, the heat energy monitoring device 20 heats the sterilizer 50 based on the measurement data acquired from the measuring device 10 and the data regarding the static state of the sterilizer 50 acquired from the production control system 40. The energy balance is monitored and the presence or absence of abnormality in the sterilizer 50 is determined. The thermal energy monitoring device 20 may be installed in the same factory as the sterilizer 50, for example. Further, the thermal energy monitoring device 20 may be installed in a facility (for example, a monitoring center or the like) outside the factory where the sterilizing device 50 is installed, for example. The thermal energy monitoring device 20 is, for example, a server device. In this case, the thermal energy monitoring device 20 may be a cloud server, an on-premises server, or an edge server. Further, the thermal energy monitoring device 20 may be, for example, a terminal device such as a computer terminal in a factory where the sterilizer 50 is installed.

The monitoring support device 30 (an example of a threshold setting device and a factor analysis device) sets a reference for monitoring the sterilizer 50 by the heat energy monitoring device 20 (a threshold described later), and sets the sterilizer 50 by the heat energy monitoring device 20. Provides user support for factor analysis when determining anomalies. Specifically, the monitoring support device 30 acquires various data from the thermal energy monitoring device 20 through a predetermined communication line, sets a standard (threshold value) for monitoring based on the acquired data, and is a sterilizer. The cause of 50 abnormalities is analyzed. The monitoring support device 30 may be installed in the same factory as the sterilizer 50 together with the thermal energy monitoring device 20, for example. In this case, the thermal energy monitoring device 20 is installed in a relatively close place to the sterilizing device 50 in the factory, for example, and the monitoring support device 30 is, for example, a worker or a manager of a management office in the factory. It may be installed in a place where the user of the monitoring support device 30 of the above performs management work related to the factory. Further, the monitoring support device 30 may be installed in a facility (for example, a monitoring center or the like) outside the factory where the sterilizing device 50 is installed. The monitoring support device 30 is, for example, a server device. In this case, the monitoring support device 30 may be a cloud server, an on-premises server, or an edge server. Further, the monitoring support device 30 may be, for example, a terminal device such as a computer terminal installed in a management office or the like in a factory.

The production control system 40 manages the products produced in the factory. Specifically, the production control system 40 controls the quality of the products produced in the factory. For example, the production control system 40 controls the operating state of the production line and the like. Specifically, the production control system 40 controls various devices including the sterilizer 50 installed on the production line. The production control system 40 transmits information regarding the static state of the sterilizer 50 (hereinafter, “status information”) to the heat energy monitoring device 20 through a predetermined communication line. The static state of the sterilizer 50 means, for example, a state in which the sterilizer 50 basically does not change during operation unless there is an operation or a control command from the outside. The static state of the sterilizer 50 includes an operation mode of the sterilizer 50, a type of product sterilized by the sterilizer 50 (hereinafter, “product type”), and the like. The product type is information that indirectly represents the control conditions (for example, various temperature conditions, pressure conditions, etc.) of the sterilizer 50. This is because the control conditions of the sterilizer 50 differ depending on the product type, and the product type and the control conditions are associated with each other. A plurality of types of operation modes of the sterilizer 50 are set in advance, such as "operating", "standby", and "stopping". The sterilizer 50 is basically operated in a state of being maintained in one operation mode, and the operation mode may be switched, for example, at the timing when the product type to be sterilized is switched. For example, the operation mode of the sterilizer 50 can be appropriately set (changed) according to the operation of an operator or the like from the input unit of the sterilizer 50, the operation terminal device of the production control system 40, or the like.

[Overview of sterilizer]
Next, the outline of the sterilizer 50 will be described.

FIG. 2 is a diagram showing an example of the configuration of the sterilizer 50 as a monitoring target of the thermal energy monitoring system 1.

The sterilizer 50 sterilizes the products produced in the factory. The sterilizer 50 may, for example, sterilize a beverage produced in a factory. The product that passes through the sterilizer 50 may be a beverage that has already been filled in the packaging container (hereinafter, “individual beverage” for convenience), or flows as a liquid before being filled in the packaging container. Beverages (hereinafter, "non-individual beverages" for convenience) may be used.

As shown in FIG. 2, the sterilizer 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, and a heating unit 56. , The cooling unit 57 and the like.

The product passage path 51 is a route through which a product (beverage) flows in, passes through the inside of the sterilizer 50, and then flows out to the outside.

The high temperature water circulation path 52 is a path for circulating relatively high temperature water (high temperature water). A pump 52A is installed in the high temperature water circulation path 52, and the high temperature water is circulated by the pump 52A.

The steam inflow path 53 is a path for flowing very high temperature steam into the high temperature water circulation path 52. As a result, the temperature of the hot water circulating in the high temperature water circulation path 52 can be maintained at a relatively high temperature.

The drainage route 54 discharges excess high-temperature water to the outside from the high-temperature water circulation route 52. This is because the amount of hot water in the hot water circulation path 52 increases due to the inflow of steam.

The cooling water passage path 55 is a path that allows cooling water for cooling the product to flow in from the outside, passes through the inside of the sterilizer 50, and then flows out to the outside.

The heating unit 56 causes heat exchange between the high-temperature water in the high-temperature water circulation path 52 and the product (beverage) in the product passage path 51, and heats and sterilizes the beverage in the product passage path 51. The heating unit 56 is arranged in the first half of the product passage path 51.

The cooling unit 57 exchanges heat between the cooling water in the cooling water passage path 55 and the product (beverage) in the product passage path 51, and cools the product whose temperature has risen during heat sterilization by the heating unit 56. The cooling unit 57 is arranged in the latter half of the product passage path 51.

The sterilizer 50 is controlled by the production control system 40 as described above. Specifically, the sterilizer 50 is controlled so that the temperature of the product in the heating unit 56 becomes equal to or higher than a predetermined value specified in advance. As a result, the sterilizer 50 can appropriately heat sterilize the product under the control of the production control system 40. Further, the sterilizer 50 is controlled so that the temperature of the product after passing through the cooling unit 57 drops to a predetermined value or less specified in advance.

[Details of thermal energy monitoring system]
Next, in addition to FIG. 1, the details of the thermal energy monitoring system 1 will be described with reference to FIGS. 3 to 11.

<Configuration of measuring device>
As shown in FIG. 1, the measuring device 10 includes a temperature sensor 11, a pressure sensor 12, and a flow rate sensor 13. Further, the measuring device 10 may include other types of sensors capable of measuring a physical state other than the temperature state, the pressure state, and the flow rate state of the sterilizer 50.

The temperature sensor 11 measures the temperature inside the sterilizer 50. The temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter, “steam temperature”) T1 of the steam flowing in from the steam inflow path 53. Further, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter, “drainage temperature”) T2 of the drainage discharged from the drainage path 54. Further, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter, “product inlet temperature”) T3 of the product (beverage) at the inlet of the product passage path 51. Further, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature (hereinafter, “product outlet temperature”) T4 of the product (beverage) at the outlet of the product passage path 51. Further, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature of the cooling water (hereinafter, “cooling water inlet temperature”) T5 at the inlet of the cooling water passage path 55. Further, the temperature sensor 11 includes, for example, a temperature sensor that measures the temperature of the cooling water at the outlet of the cooling water passage path 55 (hereinafter, “cooling water outlet temperature”) T6.

The pressure sensor 12 measures the pressure inside the sterilizer 50. The pressure sensor 12 includes, for example, a pressure sensor that measures the pressure (hereinafter, “steam pressure”) P1 of the steam flowing in from the steam inflow path 53. Further, the pressure sensor 12 includes, for example, a pressure sensor that measures the pressure (hereinafter, “drainage pressure”) P2 of the drainage discharged from the drainage path 54.

The flow rate sensor 13 measures the flow rate inside the sterilizer 50. The flow rate sensor 13 includes, for example, a flow rate sensor that measures the flow rate (hereinafter, “steam flow rate”) F1 of the steam flowing in from the steam inflow path 53. Further, the flow rate sensor 13 includes, for example, a flow rate sensor that measures the flow rate (hereinafter, “drainage flow rate”) F2 of the drainage discharged from the drainage path 54. Further, the flow rate sensor 13 includes, for example, a flow rate sensor that measures the flow rate (hereinafter, “product inlet flow rate”) F3 of the product (beverage) at the inlet of the product passage path 51. Further, the flow rate sensor 13 includes, for example, a flow rate sensor that measures the flow rate (hereinafter, “product outlet flow rate”) F4 of the product (beverage) at the outlet of the product passage path 51. Further, the flow rate sensor 13 includes, for example, a flow rate sensor that measures the flow rate (hereinafter, “cooling water inlet flow rate”) F5 of the cooling water at the inlet of the cooling water passage path 55. Further, the flow rate sensor 13 includes, for example, a flow rate sensor that measures the flow rate (hereinafter, “cooling water outlet flow rate”) F6 of the cooling water at the outlet of the cooling water passage path 55.

<Structure of thermal energy monitoring device>
FIG. 3 is a diagram showing an example of the hardware configuration of the thermal energy monitoring device 20.

The function of the thermal energy monitoring device 20 may be realized by any hardware, or a combination of any hardware and software. As shown in FIG. 3, for example, the thermal energy monitoring device 20 includes a drive 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. , Each is connected by bus B.

A program that realizes various functions of the thermal energy monitoring device 20 is provided by, for example, a portable recording medium 21A. 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, and the like. When the recording medium 21A on which the program is recorded is set in the drive device 21, the program is installed in the auxiliary storage device 22 from the recording medium 21A via the drive device 21. Further, the program may be downloaded from another computer via a predetermined communication line and installed in the auxiliary storage device 22.

The auxiliary storage device 22 stores various installed programs, and also stores necessary files, data, and the like.

The memory device 23 reads and stores the program from the auxiliary storage device 22 when the program is instructed to start.

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

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

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

The input device 27 is used to have the operator, the manager, or the like of the thermal energy monitoring device 20 input various operation instructions regarding the thermal energy monitoring device 20.

As shown in FIG. 1, 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 may be realized, for example, by loading a program installed in the auxiliary storage device 22 into the memory device 23 and executing the program in the CPU 24. Further, the function of the storage unit 202 may be realized by, for example, a storage area defined in the auxiliary storage device 22.

The heat balance calculation unit 201 (an example of the heat energy calculation unit) performs calculations related to the heat balance of the sterilizer 50. Specifically, the heat balance calculation unit 201 calculates a plurality of types of heat energy constituting the heat balance of the sterilizer 50 based on the measurement data sequentially taken from the measuring device 10 at predetermined control cycles.

The plurality of types of heat energy constituting the heat balance of the sterilizer 50 include steam heat amount Q1, waste heat exhaust heat amount Q2, product carry-out heat amount Q3, cooling water exhaust heat amount Q4, and other heat exhaust amount Q5. The steam heat quantity Q1 represents the heat quantity (heat energy) of the steam flowing in from the steam inflow path 53. The wastewater waste heat amount Q2 represents the heat amount (heat energy) of the wastewater discharged from the drainage path 54. The product carry-out heat amount Q3 represents the heat amount (heat energy) carried out to the outside of the sterilizer 50 by the product passing through the product passage path 51. The cooling water exhaust heat amount Q4 represents the amount of heat (heat energy) discharged to the outside through the cooling water passing through the cooling water passage path 55. The other exhaust heat amount Q5 represents the amount of heat (heat energy) discharged from the sterilizer 50 in addition to the waste heat exhaust amount Q2, the product carry-out heat amount Q3, and the cooling water exhaust heat amount Q4. Hereinafter, the steam heat amount Q1, the waste heat exhaust amount Q2, the product carry-out heat amount Q3, the cooling water exhaust heat amount Q4, and the other waste heat amount Q5 may be collectively referred to as the heat amounts Q1 to Q5. Further, any one of the steam heat amount Q1, the waste heat exhaust amount Q2, the product carry-out heat amount Q3, the cooling water exhaust heat amount Q4, and the other waste heat amount Q5 may be individually referred to as the heat amount QX (X: 1 to 5). integer).

The relationship (heat balance) of the following formula (1) is established between the steam heat amount Q1, the waste heat exhaust amount Q2, the product carry-out heat amount Q3, the cooling water exhaust heat amount Q4, and the other waste heat amount Q5.

The heat balance calculation unit 201 calculates the steam heat quantity Q1 using, for example, the following equations (2) and (3).

Further, the heat balance calculation unit 201 may calculate the steam heat quantity Q1 by using, for example, the following equation (4).

The "saturated steam enthalpy", "specific volume", and "density" change according to the steam temperature T1 and the steam pressure P1, respectively, and are based on the measured values of the steam temperature T1 and the steam pressure P1, respectively. Is obtained using. The data corresponding to the saturated steam table is stored in advance in, for example, the auxiliary storage device 22.

Further, the heat balance calculation unit 201 calculates the wastewater waste heat amount Q2 by using, for example, the following equation (5).

The "specific heat of water" is registered in the auxiliary storage device 22 or the like as a predetermined value (for example, 4.22). Further, the "steam mass flow rate" is calculated from the above equation (3). Further, the "drainage inlet temperature" corresponds to the temperature of the high-temperature water before the steam inflow, and may be simply defined in advance as, for example, the same as the temperature in the factory (for example, 20 ° C.), or specifically. Measured values may be used. In the latter case, the temperature sensor 11 includes a temperature sensor that measures the drainage inlet temperature.

Further, the heat balance calculation unit 201 calculates the product carry-out heat amount Q3 by using, for example, the following equation (6).

In the formula (6), instead of the product inlet flow rate F3, the average value of the product outlet flow rate F4, the product inlet flow rate F3, and the product outlet flow rate F4 may be used. Hereinafter, the same may apply to the cases of equations (7) and (8).

Further, the heat balance calculation unit 201 may, for example, more strictly calculate the product carry-out heat amount Q3 by using the following formula (7) or formula (8).

The formula (7) corresponds to the case where the product to be sterilized by the sterilizer 50 is a non-individual beverage, and the formula (8) corresponds to the case where the product to be sterilized by the sterilizer 50 is a solid beverage.

Further, the heat balance calculation unit 201 calculates the cooling water exhaust heat amount Q4 by using, for example, the following equation (9).

In the formula (9), instead of the cooling water inlet flow rate F5, an average value of the cooling water outlet flow rate F6, the cooling water inlet flow rate F5, and the cooling water outlet flow rate F6 may be used.

Further, the heat balance calculation unit 201 calculates the other heat exhausted amount Q5 by using the following formula (10) derived from the above formula (1), for example.

The storage unit 202 stores the threshold value 202A used by the monitoring unit 203. The threshold value 202A includes an upper limit threshold value QX_THU and a lower limit threshold value QX_THL (an integer of X: 1 to 5) defined for each of the calories Q1 to Q5. Further, in the storage unit 202, for example, the threshold value 202A (upper limit threshold value QX_THU and lower limit threshold value QX_THL) is defined for each type of static state (for example, operation mode or product type) of the sterilizer 50, and is defined in the storage unit 202. It may be stored in.

The monitoring unit 203 monitors whether or not the heat quantities Q1 to Q5 sequentially calculated by the heat balance calculation unit 201 deviate from the normal range (an example of a predetermined range) defined by the threshold value 202A. The monitoring unit 203 grasps, for example, a static state such as an operation mode and a product type of the current sterilizer 50 based on the status information sequentially acquired from the production control system 40. Then, the monitoring unit 203 monitors whether or not the target calorific value QX deviates from the normal range by using the threshold value 202A that matches the static state of the current sterilizer 50 for each calorific value Q1 to Q5. .. When all the calories Q1 to Q5 do not deviate from the normal range, the monitoring unit 203 outputs a monitoring result indicating that the calories are normal, and when a part or all of the calories Q1 to Q5 deviates from the normal range. , Outputs the monitoring result indicating that it is abnormal. As a matter of course, the type of heat amount deviating from the normal range among the heat amounts Q1 to Q5 is specified in the monitoring result indicating the abnormality.

The monitoring unit 203 has monitoring results, the latest measurement data from the measuring device 10, the latest status information from the production control system 40, and the latest heat balance (heat amount Q1) by the heat balance calculation unit 201 for each predetermined control cycle. The calculation result of Q5) is transmitted to the monitoring support device 30.

<Processing flow of thermal energy monitoring device>
FIG. 4 is a flowchart schematically showing an example of processing related to monitoring of thermal energy (heat amounts Q1 to Q5) by the thermal energy monitoring device 20. This flowchart is repeatedly executed, for example, at predetermined control cycles.

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

When the process of step S102 is completed, the thermal energy monitoring device 20 proceeds to step S104.

In step S104, the monitoring unit 203 acquires a threshold value 202A (upper limit threshold value QX_THU and lower limit threshold value QX_THL) that matches the latest status information for each of the calories Q1 to Q5 based on the latest status information.

When the process of step S104 is completed, the thermal energy monitoring device 20 proceeds to step S106.

In step S106, the monitoring unit 203 determines whether or not the monitoring target period is reached. The monitoring target period is, for example, a period excluding the status information of the sterilizer 50, that is, a predetermined time (for example, several minutes to several tens of minutes) after the static state is switched. This is because it may take some time for the dynamic state of the sterilizer 50 to stabilize immediately after the static state of the sterilizer 50 is switched. The monitoring unit 203 proceeds to step S108 if it is in the monitoring target period, and proceeds to step S112 if it is not in the monitoring target period.

In step S108, the monitoring unit 203 monitors for each of the heat quantities Q1 to Q5 calculated by the heat balance calculation unit 201 whether or not there is a deviation from the normal range defined by the upper limit threshold value QX_THU and the lower limit threshold value QX_THL.

When the process of step S108 is completed, the thermal energy monitoring device 20 proceeds to step S110.

In step S110, the monitoring unit 203 determines whether or not all the heat quantities Q1 to Q5 are within the normal range. The monitoring unit 203 proceeds to step S112 when all the heat quantities Q1 to Q5 are in the normal range, and proceeds to step S114 when at least a part of the heat quantities Q1 to Q5 deviates from the normal range.

In step S112, the monitoring unit 203 transmits data including the monitoring result indicating normality to the monitoring support device 30 through the interface device 25.

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

When the process of step S112 or step S114 is completed, the thermal energy monitoring device 20 ends the process of the current flowchart.

In this way, the thermal energy monitoring device 20 monitors whether or not there is a deviation from the normal range defined by the upper limit threshold value QX_THU and the lower limit threshold value QX_THL for each of the heat quantities Q1 to Q5, thereby checking the normality / abnormality of the sterilizer 50. You can judge.

<Configuration of monitoring support device>
The function of the monitoring support device 30 may be realized by any hardware, or a combination of any hardware and software. For example, the hardware configuration of the monitoring support device 30 may be the same as the hardware configuration of the thermal energy monitoring device 20. Hereinafter, in the description of the monitoring support device 30, the reference numerals "21", "21A", "22", "23", "24", "25", "26", and "27" in FIG. 3 are used, respectively. The explanation may be replaced with "31", "31A", "32", "33", "34", "35", "36", and "37".

The monitoring support device 30 includes a drive 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, each of which is a bus. Connected by B.

As shown in FIG. 1, the monitoring support device 30 includes a database (DB: Data Base) 301, a threshold value setting unit 302, an alarm output unit 303, an analysis data creation unit 304, and a factor analysis unit 305. ..

The functions of the DB 301, the threshold setting unit 302, the alarm output unit 303, the analysis data creation unit 304, and the factor analysis unit 305 are, for example, a program installed in the auxiliary storage device 32 loaded into the memory device 23 and executed by the CPU 34. It may be realized by. Further, the data corresponding to the DB 301 may be stored in the auxiliary storage device 32.

The DB 301 is configured as a searchable record group according to a predetermined search condition in a mode in which records corresponding to data sequentially received from the thermal energy monitoring device 20 are accumulated. The records include, for example, information on the date and time, measurement data of the measuring device 10, status information of the sterilizing device 50 (for example, product type, operation mode type, etc.), calculated values of heat quantities Q1 to Q5, and monitoring results (normal or normal). (Abnormal) etc. are included.

The DB 301 includes reference data 301A corresponding to record data whose monitoring result is normal, and abnormal time data 301B corresponding to record data whose monitoring result is abnormal.

The threshold value setting unit 302 (an example of the setting unit) sets the threshold value 202A (upper limit threshold value QX_THU and lower limit threshold value QX_THL) used in the thermal energy monitoring device 20 based on the reference data 301A included in the DB 301. The details of the threshold value setting unit 302 will be described later.

The alarm output unit 303 outputs an alarm (alert) to the user when the monitoring result indicating an abnormality is included in the data sequentially received from the thermal energy monitoring device 20. Specifically, the alarm output unit 303 causes the display device 36 to display a screen (hereinafter, “monitoring screen”) indicating that the abnormality monitoring result has been output by the thermal energy monitoring device 20. As a result, the user can grasp the occurrence of an abnormality in the sterilizer 50 by visually recognizing the display device 36. Further, the alarm screen may display time-series data of the amount of heat QX deviating from the normal range of the amounts of heat Q1 to Q5, an upper limit threshold value QX_THU, and a lower limit threshold value QX_THL. As a result, the user can grasp in which direction and how much the target heat quantity QX deviates from a predetermined range. Further, the monitoring screen may display measurement data related to the calorific value QX that deviates from the normal range.

The analysis data creation unit 304 is based on the data of the DB 301, specifically, the reference data 301A and the abnormality data 301B, and the data for performing the factor analysis of the abnormality occurrence corresponding to the abnormality data 301B (hereinafter, "analysis"). Data ") is created. The details of the analysis data creation unit 304 will be described later.

The factor analysis unit 305 (an example of the extraction unit) determines the state of the sterilizer 50 corresponding to the cause of the abnormal occurrence of the deviation from the normal range of the calorific value QX based on the analysis data created by the analysis data creation unit 304. Extract. Specifically, the factor analysis unit 305 extracts a state item corresponding to the cause of the abnormality from the plurality of state items of the sterilizer 50 represented by each of the plurality of measurement data by the measuring device 10. The state items may include, for example, the above-mentioned steam temperature T1, drainage temperature T2, product inlet temperature T3, product outlet temperature T4, cooling water inlet temperature T5, cooling water outlet temperature T6, and the like. Further, the state items include, for example, steam pressure P1, drainage pressure P2, steam flow rate F1, drainage flow rate F2, product inlet flow rate F3, product outlet flow rate F4, cooling water inlet flow rate F5, cooling water outlet flow rate F6, and the like. You can do it. The details of the factor analysis unit 305 will be described later.

<Details of processing related to threshold setting>
FIG. 5 is a flowchart schematically showing an example of processing related to setting a threshold value by the monitoring support device 30. FIG. 6 is a diagram showing an example (threshold value setting input screen 600) displayed on the display device 36 for the user to input for threshold value setting (hereinafter, “threshold value setting input screen”). .. FIG. 7 is an example (hereinafter, “threshold final setting screen”) of a screen (hereinafter, “threshold final setting screen”) for finally setting a threshold based on a threshold calculated as a candidate by the user, which is displayed on the display device 36 (threshold final setting screen 700). ).

The flowchart of FIG. 5 starts execution when, for example, an input for displaying the threshold value setting input screen on the display device 36 is received through the input device 37.

As shown in FIG. 5, in step S202, the threshold value setting unit 302 receives the input of the extraction condition for extracting the data used for setting the threshold value from the reference data 301A of the DB 301 through the input device 37.

For example, as shown in FIG. 6, the threshold value setting input screen 600 includes an extraction condition input unit 601.

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

The product type condition input unit 601A is used for the user to input the extraction condition related to the product type. The user operates the product type condition input unit 601A through the input device 37 to input the extraction condition related to the product type. As a result, the threshold value setting unit 302 can extract records limited to the product type, which is one of the static states of the sterilizer 50, from the record group corresponding to the reference data 301A.

The operation mode condition input unit 601B is used for 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 and inputs the extraction conditions related to the operation mode. As a result, the threshold value setting unit 302 can extract a record limited to the operation mode, which is one of the static states of the sterilizer 50, from the record group corresponding to the reference data 301A.

The start date / time condition input unit 601C is used for the user to input the start date / time condition corresponding to the start of the extraction conditions that limit the period. Further, the end date / time condition input unit 601D is used by the user to input the end date / time condition corresponding to the end of the extraction conditions that limit the period. The user operates the start date / time condition input unit 601C and the end date / time condition input unit 601D through the input device 37, and inputs the extraction conditions (start date / time and end date / time of the period) that limit the period. As a result, the threshold value setting unit 302 can extract records limited to a specific period from the record group corresponding to the reference data 301A.

The exclusion condition input unit 601E is used for the user to input a condition for excluding data (record) that matches a specific condition (hereinafter, “exclusion condition”). The user operates the exclusion condition input unit 601E through the input device 37 and inputs the exclusion condition. As a result, when the threshold setting unit 302 extracts a record that matches the extraction conditions related to the above-mentioned product type, operation mode, and period from the record group corresponding to the reference data 301A, the data that matches the exclusion condition. Records can be extracted by excluding.

The exclusion condition excludes, for example, data for a predetermined period (for example, between several minutes and a dozen minutes) after switching status information such as product type and operation mode (that is, the static state of the sterilizer 50). Conditions are included. As a result, the user excludes the data (record) for a predetermined period after the static state of the sterilizer 50 such as the product type and the operation mode is switched from the data used for setting the threshold value. Can be made to. This is because, as described above, immediately after the static state of the sterilizer 50 is switched, it may take some time for the dynamic state of the sterilizer 50 to stabilize.

Returning to FIG. 5, in step S204, the threshold value setting unit 302 receives the input of the condition for setting the threshold value (hereinafter, “threshold value condition”) through the input device 37.

For example, as shown in FIG. 6, the threshold value setting input screen 600 includes a threshold value condition input unit 602.

The threshold condition input unit 602 is used for the user to input the threshold condition. The user operates the threshold value condition input unit 602 through the input device 37 to input the threshold value condition. Thereby, the threshold value setting unit 302 can set the threshold value (upper limit threshold value QX_THU and lower limit threshold value QX_THL) that matches the threshold value condition based on the record extracted according to the extraction condition input in step S202.

In this example, the threshold condition is a percentage of the upper and lower limits of the calorific value QX of the target of the data extracted according to the extraction condition from the reference data 301A (data at the normal time). It is a condition that indicates whether to set a threshold value by taking a margin. That is, it is a condition representing the margin m [%] of the upper limit threshold value QX_THU and the lower limit threshold value QX_THL for each of the upper limit value and the lower limit value of the extracted data.

The processes of steps S202 and S204 may be performed in parallel according to the operation from the user through the input device 37.

The monitoring support device 30 proceeds to step S206 when an operation for requesting calculation (calculation) of the threshold value is performed through the input device 37 in a state where the input of the extraction condition and the threshold value condition in steps S202 and S204 is completed.

For example, as shown in FIG. 6, the threshold value setting input screen 600 includes a calculation request input unit 603.

The calculation request input unit 603 is used for the user to perform an operation for requesting the calculation (calculation) of the threshold value. The user operates the calculation request input unit 603 through the input device 37. As a result, the threshold value setting unit 302 shifts to the process of step S206 in a state where the input of the extraction condition input unit 601 and the threshold value condition input unit 602 is completed.

Returning to FIG. 5, in step S206, the threshold setting unit 302 is input in step S204 based on the upper limit value and the lower limit value of the calorific value QX of the target of the data to be extracted according to the extraction condition input in step S202. Calculate the threshold value according to the threshold value condition. The threshold value setting unit 302 calculates a threshold value (upper limit threshold value QX_THU and lower limit threshold value QX_THL) using, for example, the following equations (11) and (12).

The threshold value setting unit 302 may display the threshold value calculation result on the threshold value setting input screen 600.

For example, as shown in FIG. 6, the threshold value setting input screen 600 includes a current threshold value display unit 604 and a threshold value calculation result display unit 605.

The current threshold value display unit 604 displays the currently set threshold values (upper limit threshold value QX_THU and lower limit threshold value QX_THL) for each of the calories Q1 to Q5. As a result, the user can confirm the currently set threshold values (upper limit threshold value QX_THU and lower limit threshold value QX_THL).

The newly calculated threshold value (upper limit threshold value QX_THU and lower limit threshold value QX_THL) is displayed on the threshold value calculation result display unit 605. As a result, the user can confirm the calculation result of the threshold value (upper limit threshold value QX_THU and lower limit threshold value QX_THL) based on the new extracted data. In addition, the threshold value calculation result display unit 605 may also display the average value, the upper limit value, the lower limit value, and the like of the calorific value QX of the target of the extraction data.

Returning to FIG. 5, the monitoring support device 30 proceeds to step S208 when the input requesting the transition to the threshold final setting screen is received through the input device 37 after the processing of step S206.

In step S208, the threshold value setting unit 302 shifts the display content of the display device 36 from the threshold value setting input screen to the threshold value final setting screen.

For example, as shown in FIG. 6, the threshold value setting input screen 600 includes a display request input unit 606.

The display request input unit 606 is used for the user to request a transition to the threshold final setting screen. The user operates the display request input unit 606 through the input device 37. As a result, the threshold value setting unit 302 shifts the display content of the display device 36 from the threshold value setting input screen 600 to the threshold value final setting screen 700 on the premise that the threshold value calculation process (step S206) has been completed.

For example, as shown in FIG. 7, the threshold final setting screen 700 includes a time series display unit 701, a frequency distribution display unit 702, a target heat quantity selection unit 703, a correction request input unit 704, and an end request input unit 705. including.

The data extracted according to the extraction conditions input in step S202 is displayed in a time-series graph on the time-series display unit 701. In this example, the data extracted according to the extraction condition is displayed as a solid line, and the data excluded by the exclusion condition, that is, the data for a predetermined period immediately after switching the status information corresponding to the static state of the sterilizer 50. Is displayed as a dotted line.

The time series display unit 701 displays an upper limit threshold line 701A and a lower limit threshold line 701B corresponding to the upper limit threshold value QX_THU and the lower limit threshold value QX_THL, respectively. As a result, the user can visually confirm the relationship between the change in the extracted data in time series and the upper limit threshold value QX_THU and the lower limit threshold value QX_THL.

The data extracted according to the extraction conditions input in step S202 is displayed on the frequency distribution display unit 702 as a frequency distribution for each category of equally spaced values.

The frequency distribution display unit 702 displays an upper limit threshold line 702A and a lower limit threshold line 702B corresponding to the upper limit threshold value QX_THU and the lower limit threshold value QX_THL, respectively. As a result, the user can visually confirm the relationship between the frequency distribution of the extracted data and the upper limit threshold value QX_THU and the lower limit threshold value QX_THL.

The target heat quantity selection unit 703 is used for the user to select the target calorific value QX to be displayed from the calorific values Q1 to Q5. The user can operate the target heat quantity selection unit 703 through the input device 37 to switch the target heat quantity QX to be displayed on the threshold final setting screen.

The correction request input unit 704 is used to input a user requesting correction of the calculated threshold values (upper limit threshold value QX_THU and lower limit threshold value QX_THL). The user operates the correction request input unit 704 through the input device 37. In this case, the threshold value setting unit 302 permits the correction of the calculated threshold value. Specifically, the threshold value setting unit 302 may display an input box in which the numerical value of the threshold value can be directly input on the threshold value final setting screen 700. Further, the threshold value setting unit 302 may allow, for example, the upper limit threshold value lines 701A and 702A and the lower limit threshold value lines 701B and 702B of the threshold value final setting screen 700 to be directly moved and operated through the input device 37. For example, the threshold value setting unit 302 moves the upper limit threshold value lines 701A and 702A and the lower limit threshold value lines 701B and 702B of the threshold value final setting screen 700 to the user by using the touch panel mounted on the display device 36. Allow the threshold to be modified.

The end request input unit 705 is used for the user to request the completion of the threshold setting (setting end) in the content displayed on the threshold final setting screen 700. The user operates the end request input unit 705 through the input device 37.

Returning to FIG. 5, the monitoring support device 30 proceeds to step S210 when the processing of step S208 is completed.

In step S210, the threshold value setting unit 302 determines whether or not the threshold value setting end (setting completion) has been input (for example, the operation of the end request input unit 705) through the input device 37. When the threshold value setting end is input, the threshold value setting unit 302 sets and saves the threshold value (upper limit threshold value QX_THU and lower limit threshold value QX_THL) in the value corresponding to the display content of the threshold value final setting screen, and processes the current flowchart. finish. On the other hand, the threshold value setting unit 302 proceeds to step S212 when an input requesting correction of the threshold value (for example, an operation of the correction request input unit 704) is input instead of the input of the end of setting the threshold value.

In step S212, the threshold value setting unit 302 corrects the threshold value according to the input from the input device 37.

When the processing of step S212 is completed, the monitoring support device 30 returns to step S208, and the threshold value setting unit 302 corrects and displays the contents of the threshold value final setting screen so as to correspond to the corrected threshold value.

In this way, the threshold value setting unit 302 calculates and sets 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 calorific value QX of the data extracted according to the extraction condition in response to the request from the user. be able to.

<Details of processing related to factor analysis>
FIG. 8 is a diagram showing an example of an abnormality occurrence history screen (abnormality occurrence history screen 800). FIG. 9 is a diagram schematically showing a processing flow relating to analysis of the cause of abnormality by the thermal energy monitoring device 20. FIG. 10 is a diagram showing an example (analysis result screen 1000) of a screen (hereinafter, “analysis result screen”) showing the result of the factor analysis process by the factor analysis unit 305. FIG. 11 is a diagram showing another example of the analysis result screen (analysis result screen 1100).

The monitoring support device 30 causes the display device 36 to display an abnormality occurrence history screen showing an abnormality occurrence history (record) corresponding to a deviation from the normal range of the calorific value QX in response to a request from the user through the input device 37. .. In the history of abnormality occurrence (record), for example, the type of abnormality, the date and time of abnormality occurrence, the date and time of abnormal termination (normal recovery), the product type at the time of abnormality occurrence, the operation mode at the time of abnormality occurrence, and the amount of heat Q1 at the time of abnormality occurrence. ~ Q5 calculated value and the like may be included.

For example, as shown in FIG. 8, the display device 36 displays the abnormality occurrence history screen 800.

The abnormality occurrence history screen 800 includes an abnormality type condition input unit 801, a start date / time condition input unit 802, an end date / time condition input unit 803, a product type condition input unit 804, an operation mode condition input unit 805, and a display request input. A unit 806 and an abnormality occurrence history display unit 810 are included.

The abnormality type condition input unit 801 is used for the user to input a condition related to the type of abnormality when extracting the history of abnormality occurrence from the abnormality data 301B. The user operates the abnormality type condition input unit 801 through the input device 37 to input the condition related to the abnormality type.

The start date / time condition input unit 802 is used for the user to input the condition of the start date / time corresponding to the start of the period when the history of abnormality occurrence is extracted from the abnormality data 301B. The user operates the start date / time condition input unit 802 through the input device 37 and inputs the condition regarding the start date / time.

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

The product type condition input unit 804 is used for the user to input the condition regarding the product type at the time of abnormality occurrence when extracting the history of abnormality occurrence from the abnormality time data 301B. The user operates the product type condition input unit 804 through the input device 37 and inputs the condition related to the product type.

The operation mode condition input unit 805 is used for the user to input conditions related to the operation mode at the time of abnormality occurrence when extracting the history of abnormality occurrence from the abnormality time data 301B. The user operates the operation mode condition input unit 805 through the input device 37 and inputs the conditions related to the operation mode.

The display request input unit 806 is used for the user to input a display request of the abnormality occurrence history according to the conditions input by the condition input units 801 to 805. The user operates the display request input unit 806 through the input device 37 and inputs a display request for the abnormality occurrence history.

The abnormality occurrence history display unit 810 displays the abnormality occurrence history (record) according to the operation of the display request input unit 806, that is, the condition input by the condition input units 801 to 805 in response to the display request. Through the input device 37, the user can select any one (one row) from the records of the abnormality occurrence history corresponding to each example in the figure. As a result, the monitoring support device 30 activates the process related to the factor analysis of the abnormality occurrence corresponding to the record of the selected abnormality occurrence history.

For example, as shown in FIG. 9, first, the analysis data creation unit 304 executes a data creation process for creating analysis data 304A based on the reference data 301A and the abnormality data 301B. Specifically, the analysis data creation unit 304 is for analysis from the time series data of the dynamic state of each sterilizer 50 at the time of abnormality occurrence corresponding to the record selected on the abnormality occurrence history screen and at the normal time. Create data 304A. The time-series data in the dynamic state corresponds to, for example, the time-series data of the measurement data (measured value) of the measuring device 10. Further, the time-series data in the dynamic state at the normal time is, for example, the dynamic state included in the reference data 301A (extracted data) used for setting the upper limit threshold value QX_THU and the lower limit threshold value QX_THL by the threshold value setting unit 302. It is preferably time series data. This is because the data for which the criteria for normality / abnormality are consistent should be compared.

For example, the analysis data 304A may be tabular (matrix format) data such as a CSV (Comma Separated Value) file. Specifically, in the analysis data 304A, records having different dates and times (time) are arranged in the row direction, and in the column direction, a plurality of state items indicating a dynamic state and an item indicating whether normal or abnormal are used. It may be in a format in which a plurality of data items including are arranged.

When the analysis data 304A is output from the analysis data creation unit 304, the factor analysis unit 305 uses the analysis data 304A to generate an abnormality corresponding to the record of the abnormality occurrence history selected on the abnormality occurrence history screen. Perform factor analysis processing. Specifically, the factor analysis unit 305 uses the analysis data 304A to extract a state item corresponding to the cause of the abnormality from a plurality of state items representing the dynamic state of the sterilizer 50.

For example, the factor analysis unit 305 uses two factor analysis methods, correlation analysis and decision tree analysis, based on the analysis data 304A, to generate an abnormality from a plurality of state items representing the dynamic state of the sterilizer 50. The state items corresponding to the factors of are extracted. Specifically, the factor analysis unit 305 distinguishes between abnormal and normal data (measurement data) for each of a plurality of state items and data indicating the distinction between abnormal and normal (for example, "0" or "1"). The correlation coefficient with the data and the importance of the variable may be calculated.

The correlation coefficient is calculated in the range of -1 to +1 in the correlation analysis, and the larger the absolute value, the higher the correlation (linear relationship) between the target state item and whether it is abnormal or normal, that is, It is considered that the degree of indicating the cause of the abnormality of the target state item is high. Further, the variable importance is calculated in the range of 0 to 1 in the decision tree analysis, and represents the importance as a factor of the abnormality of the target state item.

The factor analysis unit 305 calculates the correlation coefficient with the data indicating whether it is abnormal or normal for each of the plurality of state items, and the state item in which the absolute value of the correlation coefficient among the plurality of state items is relatively large. May be extracted as a factor (candidate) for the occurrence of an abnormality. For example, the factor analysis unit 305 has a state item in which the absolute value of the correlation coefficient among the plurality of state items is equal to or higher than a predetermined threshold value, or a state item having a larger absolute value of the correlation coefficient among the plurality of state items. State items that fall within a predetermined number (for example, three) may be extracted.

Similarly, the factor analysis unit 305 calculates the variable importance of the data indicating whether the abnormality or normal is different for each of the plurality of state items, and the variable importance of the plurality of state items is relatively large. May be extracted as a factor (candidate) for the occurrence of an abnormality. For example, the factor analysis unit 305 has a state item in which the variable importance of the plurality of state items is equal to or higher than a predetermined threshold value, or a predetermined number (for example, 3) having a higher variable importance among the plurality of state items. One) State items that fall within may be extracted.

The factor analysis unit 305 outputs the analysis result data 305A representing the result of the factor analysis process. The analysis result data 305A includes, for example, the calculated values of the correlation coefficient and the importance coefficient between the abnormal / normal cases for each of a plurality of state items. Further, the analysis result data 305A includes, for example, information on a state item having a relatively large correlation coefficient and a state item having a relatively large importance coefficient for the distinction between abnormality and normal as candidates for the cause of abnormality occurrence. You can do it.

Further, the factor analysis unit 305 may display a screen (analysis result screen) showing the result of the factor analysis process on the display device 36 based on the analysis result data 305A.

For example, as shown in FIG. 10, the factor analysis unit 305 may display the analysis result screen 1000 on the display device 36.

The "Tag name" in FIG. 10 corresponds to the type of state item. Hereinafter, the same applies to the case of FIG.

On the analysis result screen 1000, for each of the correlation coefficient (absolute value) and the variable importance calculated by the correlation analysis and the decision tree analysis, the state items ("Tag name") are displayed in order from the top to the bottom. It is listed towards you.

In the analysis result screen 1000, neither the correlation coefficient nor the variable importance is displayed as a state item calculated as zero (0). Therefore, in the decision tree analysis, only the variable importance of the three state items is displayed.

Further, for example, as shown in FIG. 11, the factor analysis unit 305 may display the analysis result screen 1100 on the display device 36.

On the analysis result screen 1100, a scatter diagram relating to the time-series data of the three state items from the largest to the highest of the correlation coefficient (absolute value) and the variable importance calculated by the correlation analysis and the decision tree analysis is displayed. Will be done. Specifically, on the analysis result screen 1100, the three state items from the highest to the highest of the correlation coefficient (absolute value) and the variable importance, and the calorific value QX outside the normal range (cooling in this example). A scatter diagram showing the relationship with the amount of heat discharged from water Q4) is displayed. At this time, each plot of the scatter plot is displayed in a mode in which it can be distinguished whether it is a normal time or an abnormal time. For example, each plot of the spraying portion may be distinguished by color or shape between the normal case and the abnormal case.

As a result, for example, the user attaches a star of the cause of the abnormality to the state items (Tag1, Tag30, etc. in this example) displayed at the top of both the correlation coefficient and the importance coefficient, and recovers from the abnormality. It is possible to take measures.

As described above, the monitoring support device 30 represents the dynamic state of the sterilizer 50 before it is reduced to the target calorific value QX at the time of an abnormality in which any calorific value QX of the calorific values Q1 to Q5 deviates from the normal range. The state item corresponding to the cause of the abnormality can be extracted from a plurality of state items. Further, the monitoring support device 30 applies two factor analysis methods (two indexes) of correlation analysis and determination tree analysis, so that the monitored device (sterilization device 50) is a linear device or a non-linear device. Regardless of whether it is, the state item corresponding to the factor can be extracted.

[Other embodiments]
Next, another embodiment will be described.

Modifications and changes may be added to the above-described embodiments as appropriate.

For example, in the above-described embodiment, the thermal energy monitoring device 20 monitors data including a monitoring result indicating that it is out of the monitoring target period when it is not in the monitoring target period (NO in step S106 of FIG. 4 above). It may be transmitted to the support device 30. Further, the process of step S106 in FIG. 4 may be omitted.

Further, for example, in the above-described embodiment or modification / modification, the heat balance calculation unit 201 replaces the logical formulas such as (2) to (9) above and the approximate formulas premised on the logical formulas. Experimental formulas based on empirical rules such as experiments and simulations may be used. In this case, the measurement data used in the empirical formula may include measurement data to be measured other than the temperature, pressure, and flow rate inside the sterilizer 50.

Further, for example, in the above-described embodiment or modification / modification, the function of the alarm output unit 303 may be provided in the thermal energy monitoring device 20 in place of or in addition to the monitoring support device 30. Further, the alarm output unit 303 transmits an alarm signal to a portable (portable) terminal device possessed by the user, such as a smartphone or tablet terminal, and issues an alarm (alert) to the user through the portable terminal device. It may be output. In this case, the alarm screen may be displayed on the portable terminal device possessed by the user.

Further, for example, in the above-described embodiment or modification / modification, a part or all of the functions of the monitoring support device 30 may be integrated into the thermal energy monitoring device 20. Further, a part of the function of the monitoring support device 30 may be transferred to another device. That is, the function of the monitoring support device 30 may be shared and realized by a plurality of devices. For example, the monitoring reference setting function and the factor analysis function of the monitoring support device 30 may be shared and realized by different devices.

Further, for example, in the above-described embodiment or modification / modification, the threshold value setting unit 302 uses all the data of the reference data 301A for the target heat quantity QX instead of the partial data extracted from the reference data 301A. You may set a threshold value. Further, the threshold value setting unit 302 may set the threshold value based on the average value instead of the upper limit value and the lower limit value of all data or partial data of the reference data 301A of the target calorific value QX.

Further, for example, in the above-described embodiment or modification / modification, the factor analysis unit 305 uses three or more types of factor analysis methods to sterilize a device corresponding to a factor of deviation from the normal range of the target calorific value QX. Fifty state items may be extracted. Further, the factor analysis unit 305 corresponds to a factor of deviation from the normal range of the calorific value QX of the target by using another factor analysis method instead of or in addition to at least one of the correlation analysis and the decision tree analysis. The state item of the sterilizer 50 may be extracted.

Further, for example, in the above-described embodiment or modification / modification example, the correlation coefficient (absolute value) and variable importance calculated by the correlation analysis and the decision tree analysis are displayed on the analysis result screen of the display device 36. It may be displayed in both the list display and the scatter plot display.

Further, for example, in the above-described embodiment or modification / modification, the monitored device of the heat energy monitoring system 1 (heat energy monitoring device 20) generates heat and heat balance (heat inflow and outflow) including heat absorption. Any device other than the sterilizing device 50 may be used.

[Action]
Next, the operation of the thermal energy monitoring system 1 according to the present embodiment will be described.

For example, when monitoring the state data (measurement data) of the monitored device as in Patent Document 1 described above, if the types of state data to be monitored are relatively large, the criteria for abnormality determination are prepared for each type. This can result in a lot of hassle.

On the other hand, for example, as in Patent Document 2 and the method of multivariate statistical process control (MSPC) described above, it is possible to reduce a plurality of types of state data to fewer variables.

However, although these methods reduce the time and effort required to prepare the criteria for determining an abnormality, it may not be possible to easily determine which type of state data corresponds to the cause of the abnormality when an abnormality occurs. In addition, although these methods are effective when the monitored device can be regarded as linear, they cannot be applied in the case of non-linearity, or even if they can be applied, it takes time to estimate (identify) the factors. May be hung.

On the other hand, 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 on the state of the monitored device, and based on the data, a plurality of types of heat energy (for example, heat quantities Q1 to Q5) constituting the heat balance of the monitored device. ) Is calculated. Then, the monitoring unit 203 monitors the presence or absence of deviation of the target type of thermal energy from the normal range defined by the upper limit threshold value and the lower limit threshold value for each of the plurality of types of thermal energy calculated by the heat balance calculation unit 201. do.

As a result, the thermal energy monitoring device 20 changes the object to be monitored into data of a large number of state items (for example, measurement data) related to the monitored device, and a plurality of types of thermal energy (for example, measurement data) constituting the heat balance. It can be reduced to 5 types). Therefore, it is possible to relatively reduce the time and effort required to prepare the criteria for determining the abnormality. Further, the thermal energy monitoring device 20 can be applied regardless of whether the monitored device is linear or non-linear by using the data of a plurality of types of thermal energy constituting the heat balance, and the factor estimation (factor estimation) is relatively easy. Specific) can be done.

Further, in the present embodiment, the data regarding the state of the monitored device includes data regarding a dynamic state including the temperature, pressure, and flow rate of the monitored device, and data regarding a static state including the operating state of the monitored device. And may be included.

As a result, the thermal energy monitoring device 20 calculates each of the plurality of types of thermal energy constituting the heat balance of the monitored device based on the data related to the plurality of state items corresponding to the dynamic states of the monitored device. be able to. Further, the thermal energy monitoring device 20 can monitor the presence or absence of deviation from the normal range in consideration of the static state.

Further, in the present embodiment, the monitoring unit 203 may have at least one of the upper limit threshold value and the lower limit threshold value different for each type of static state of the monitored device (for example, type of operation mode or product type).

As a result, the thermal energy monitoring device 20 can specifically monitor the presence or absence of deviation from the normal range in consideration of the static state.

Further, in the present embodiment, the monitoring unit 203 temporarily suspends monitoring of a plurality of types of thermal energy when the static state of the monitored device is switched. Then, the monitoring unit 203 may resume monitoring of a plurality of types of thermal energy after a predetermined time has elapsed after switching the static state of the monitored device.

As a result, the thermal energy monitoring device 20 can appropriately monitor a plurality of types of thermal energy in accordance with the static state switching of the monitored device. This is because 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.

Further, in the present embodiment, the monitoring support device 30 includes a threshold value setting unit 302. Specifically, the threshold value setting unit 302 may set the upper limit threshold value and the lower limit threshold value based on the time series data of a plurality of types of thermal energy calculated by the heat balance calculation unit 201.

As a result, the monitoring support device 30 is based on, for example, the normal time historical data of the target thermal energy (for example, the reference data 301A), that is, the normal time data of the target thermal energy accumulated in time series. , Upper limit threshold and lower limit threshold can be set.

Further, in the present embodiment, the threshold setting unit 302 has an upper limit threshold value and a lower limit threshold value for the thermal energy of the target type among the plurality of types of thermal energy based on the upper limit value, the lower limit value, or the average value of the time series data. May be set.

Thereby, the monitoring support device 30 can specifically set the upper limit threshold value and the lower limit threshold value based on the historical data (time series data) of the target thermal energy in the normal state.

Further, in the present embodiment, the threshold setting unit 302 is a condition regarding the type of static state of the monitored device from the entire time-series data for the thermal energy of the target type among the plurality of types of thermal energy. , And partial data that meets the extraction conditions including at least one of the conditions relating to time may be extracted, and the upper limit threshold and the lower limit threshold limit may be set based on the extracted partial data.

As a result, the monitoring support device 30 limits the historical data of the target thermal energy in the normal state to the partial data according to the extraction conditions, and then sets the upper limit threshold value and the lower limit threshold value based on the limited partial data. Can be set. Therefore, the monitoring support device 30 can select more appropriate data as a reference for setting the upper limit threshold value and the lower limit threshold value, for example. Therefore, the monitoring support device 30 can set the upper limit threshold value and the lower limit threshold value more appropriately.

Further, in the present embodiment, the monitoring support device 30 includes a display device 36. Specifically, the display device 36 includes at least one of a time series graph, a frequency distribution graph, and a scatter diagram graph of the thermal energy of the target type among the plurality of types of thermal energy, and a threshold setting unit. Candidates for the upper limit threshold and the lower limit threshold calculated based on the time-series data of the thermal energy of the target type may be displayed by 302. Then, the display device 36 receives an input target (for example, an upper limit threshold line 701A, 702A or a lower limit threshold line that can be operated by the touch panel as the input device 37) for receiving input from the user for correcting the upper limit threshold value and the lower limit threshold value candidate. 701B, 702B, etc.) may be displayed.

As a result, the user can visually confirm the relationship between the historical data of the target thermal energy, which is the reference for calculating the upper limit threshold value and the lower limit threshold value, and the upper limit threshold value and the lower limit threshold value on the screen. In addition, the user can modify the candidates for the upper limit threshold value and the lower limit threshold value on the screen. Therefore, the monitoring support device 30 can improve the convenience of the user.

Further, in the present embodiment, the monitoring support device 30 includes a factor analysis unit 305. Specifically, the factor analysis unit 305 determines the state of the monitored device when the thermal energy monitoring device 20 detects a deviation of a predetermined thermal energy from a normal range among a plurality of types of thermal energy. A state item representing a factor of deviation from the normal range of a predetermined thermal energy may be extracted from a plurality of state items to be represented.

As a result, the monitoring support device 30 can specify (estimate) the state item of the monitored device corresponding to the factor when the predetermined thermal energy deviates from the normal range.

Further, in the present embodiment, the factor analysis unit 305 has time-series data of a plurality of state items when a deviation from the normal range of the predetermined thermal energy is detected, and a deviation from the normal range of the predetermined thermal energy. Based on the time series data of multiple state items when not present, using multiple factor analysis methods including at least one of correlation analysis and decision tree analysis, from the normal range of predetermined thermal energy from among multiple state items. A state item indicating the cause of the deviation may be extracted.

Thereby, the monitoring support device 30 can specifically specify (estimate) the state item of the monitored device, which corresponds to the cause of the abnormality of the deviation of the predetermined thermal energy from the normal range. Further, the monitoring support device 30 can perform factor estimation regardless of whether the monitored device is a linear device or a non-linear device by using a plurality of factor analysis methods, and can also perform factor estimation. The accuracy can be improved.

Further, in the present embodiment, the monitoring support device 30 includes a display device 36 that displays the extraction result of the factor analysis unit 305. Specifically, the display device 36 represents the degree of deviation of the predetermined thermal energy from the normal range for each of the plurality of state items (for example, the correlation coefficient of the correlation analysis, the variable importance of the determination tree analysis, etc.). ) May be displayed as a list or as a scatter plot for time series data of a given thermal energy.

As a result, the user can visually confirm the degree of the factor of deviation from the normal range of the predetermined thermal energy, and can grasp the state item of the monitored device corresponding to the factor from the degree.

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

1 Thermal energy monitoring system 10 Measuring device 11 Temperature sensor 12 Pressure sensor 13 Flow sensor 20 Thermal energy monitoring device (monitoring device)
21 Drive device 21A Recording medium 22 Auxiliary storage device 23 Memory device 24 CPU
25 Interface device 26 Display device 27 Input device 30 Monitoring support device (threshold setting device, factor analysis device)
36 Display device (display unit)
40 Production control system 50 Sterilizer (monitored equipment)
51 Product passage route 52 High temperature water circulation route 52A Pump 53 Steam inflow route 54 Drainage route 55 Cooling water passage route 56 Heating unit 57 Cooling unit 201 Heat balance calculation unit (heat energy calculation unit)
202 Storage unit 202A Threshold 203 Monitoring unit 301 Database 302 Threshold setting unit (setting unit)
303 Alarm output unit 304 Analysis data creation unit 305 Factor analysis unit (extraction unit)
600 Threshold setting input screen 700 Threshold final setting screen 800 Abnormal occurrence history screen 1000, 1100 Analysis result screen

Claims (12)

A thermal energy calculation unit that acquires data on the state of the monitored device and calculates a plurality of types of thermal energy constituting the heat balance of the monitored device based on the data.
For each of the plurality of types of thermal energy calculated by the thermal energy calculation unit, a monitoring unit for monitoring the presence or absence of deviation of the target type of thermal energy from a predetermined range defined by the upper limit threshold and the lower limit threshold. Prepare, prepare
Monitoring device. The data regarding the state of the monitored device includes data regarding a dynamic state including the temperature, pressure, and flow rate of the monitored device, and data regarding a static state including the operating state of the monitored device.
The monitoring device according to claim 1. The monitoring unit makes at least one of the upper limit threshold value and the lower limit threshold value different for each type of static state of the monitored device.
The monitoring device according to claim 2. When the static state of the monitored device is switched, the monitoring unit suspends monitoring of the plurality of types of thermal energy, and a predetermined time elapses after switching the static state of the monitored device. After that, the monitoring of the plurality of types of thermal energy is resumed.
The monitoring device according to claim 2 or 3. A threshold value setting device for setting the upper limit threshold value and the lower limit threshold value used in the monitoring device according to any one of claims 1 to 4.
A setting unit for setting the upper limit threshold value and the lower limit threshold value based on the time series data of the plurality of types of thermal energy calculated by the thermal energy calculation unit is provided.
Threshold setting device. The setting unit sets the upper limit threshold value and the lower limit threshold value for the thermal energy of the target type among the plurality of types of thermal energy based on the upper limit value, the lower limit value, or the average value of the time series data.
The threshold setting device according to claim 5. Regarding the thermal energy of the target type among the plurality of types of thermal energy, the setting unit determines the condition regarding the type of the static state of the monitored device and the condition regarding the time from the entire time series data. Partial data that meets the extraction conditions including at least one is extracted, and the upper limit threshold and the lower limit threshold are set based on the extracted partial data.
The threshold setting device according to claim 5 or 6. At least one of the time series graph, the frequency distribution graph, and the scatter diagram graph of the target type of the thermal energy among the plurality of types of thermal energy, and the time of the target type of thermal energy by the setting unit. It includes a display unit that displays the upper limit threshold and the candidate of the lower limit threshold calculated based on the series data, and displays the input target that accepts the input from the user for modifying the candidate.
The threshold value setting device according to any one of claims 5 to 7. When the monitoring device according to any one of claims 1 to 4 detects a deviation of a predetermined thermal energy from the predetermined range among the plurality of types of thermal energy, the predetermined energy is used. It is provided with an extraction unit for extracting a state item representing a factor of deviation of the predetermined thermal energy from the predetermined range from a plurality of state items representing the state of the monitored device.
Factor analyzer. The extraction unit has time-series data of the plurality of state items when the deviation of the predetermined thermal energy from the predetermined range is detected, and when there is no deviation of the predetermined thermal energy from the predetermined range. Based on the time-series data of the plurality of state items, the predetermined range of the predetermined thermal energy from the plurality of state items is used by using a plurality of factor analysis methods including at least one of correlation analysis and determination tree analysis. Extract state items that represent the cause of deviation from
The factor analyzer according to claim 9. A display unit for displaying the extraction result of the extraction unit is provided.
The display unit displays, for each of the plurality of state items, a list showing the degree of deviation of the predetermined thermal energy from the predetermined range, or as a scatter diagram for the time-series data of the predetermined thermal energy. ,
The factor analyzer according to claim 9 or 10. It is a monitoring method executed by the monitoring device.
A thermal energy calculation step of acquiring data on the state of the monitored device and calculating a plurality of types of thermal energy constituting the heat balance of the monitored device based on the data.
For each of the plurality of types of thermal energy calculated in the thermal energy calculation step, a monitoring step for monitoring the presence or absence of deviation of the thermal energy of the target type from a predetermined range defined by the upper limit threshold and the lower limit threshold. include,
Monitoring method.

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