Waste heat source diagnostic system and waste heat source diagnostic method

Abstract

To enable the rapid detection of waste heat sources from which heat can be recovered. [Solution] The waste heat source diagnostic system 1 comprises a case study database 34 which has accumulated heat recovery cases as knowledge information 80, a heat medium information database 35 which has registered heat medium information 82 related to the heat medium consumed by the industrial equipment 2 to be diagnosed, a waste heat source information generation module 32 which generates waste heat source information 81 including at least the type of waste heat-containing fluid, representative temperature and heat generation amount using time-series environmental data 50 acquired for specific locations of the industrial equipment 2, and a heat recovery determination module 33 which determines whether or not heat can be recovered from the waste heat-containing fluid 70 by comparing the waste heat source information 81 and heat medium information 82 with the case study database 34.

Description

Technical Field

[0001] The technology disclosed in this specification relates to a waste heat source diagnosis system and a waste heat source diagnosis method.

Background Art

[0002] In the technical field related to industrial equipment, a system for supplying heat in a workplace as disclosed in Patent Document 1 is known. In a workplace or the like, a heat source device for generating a heat medium such as hot water and load equipment (production equipment, air conditioning equipment, cleaning equipment, finishing equipment, etc.) that uses the generated heat medium are provided.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Waste heat is generated from industrial equipment such as heat source devices and load equipment. The waste heat is discharged from the industrial equipment in the form of waste heat-containing fluids such as water (drain water) and air (exhaust gas). From the viewpoints of improving the energy-saving effect of production activities and reducing the emissions of greenhouse gases (such as carbon dioxide), it is desirable to recover heat from the waste heat-containing fluids. However, it is often difficult to discover a waste heat source from which heat can be recovered from an operating factory or the like, and the waste heat is often discarded without being recovered. Therefore, it is desirable to be able to quickly discover a waste heat source from which heat can be recovered.

[0005] The technology disclosed in this specification aims to enable quick discovery of a waste heat source from which heat can be recovered.

Means for Solving the Problems

[0006] This specification provides a waste heat source diagnostic system. The waste heat source diagnostic system is a computer-based system that diagnoses whether or not heat can be recovered from waste heat sources generated in industrial equipment, and comprises: a case study database that collects heat recovery cases as knowledge information; a heat transfer medium information database that registers heat transfer medium information related to the heat transfer medium consumed by the industrial equipment to be diagnosed; a waste heat source information generation module that generates waste heat source information including at least the type of waste heat-containing fluid, representative temperature, and calorific value using time-series environmental data acquired for specific locations in the industrial equipment; and a heat recovery determination module that determines whether or not heat can be recovered from the waste heat-containing fluid by comparing the waste heat source information and heat transfer medium information with the case study database. [Effects of the Invention]

[0007] The technology disclosed herein enables the rapid detection of waste heat sources from which heat can be recovered. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a schematic diagram showing a waste heat source diagnostic system according to an embodiment. [Figure 2] Figure 2 is a schematic diagram showing industrial equipment according to an embodiment. [Figure 3] Figure 3 is a hardware configuration diagram showing an information processing device according to an embodiment. [Figure 4] Figure 4 is a diagram illustrating the hierarchical structure of the information processing device according to the embodiment. [Figure 5] Figure 5 is a functional block diagram showing an information processing device according to an embodiment. [Figure 6] Figure 6 shows the types of environmental data used to detect waste heat sources. [Figure 7] Figure 7 is a schematic diagram illustrating the acquisition of environmental data at a specific location. [Figure 8] Figure 8 is a diagram illustrating knowledge information. [Figure 9] Figure 9 illustrates the process for determining whether or not heat recovery is possible. [Figure 10] FIG. 10 is a diagram for explaining an example of image analysis for visible image data and thermal image data. [Figure 11] FIG. 11 is a diagram for explaining the processing of the machine tool presentation module and the cost reduction prediction module. [Figure 12] FIG. 12 is a diagram for explaining a simulation using a virtual model. [Figure 13] FIG. 13 is a schematic diagram showing a first model case of heat recovery. [Figure 14] FIG. 14 is a schematic diagram showing a second model case of heat recovery. [Figure 15] FIG. 15 is a schematic diagram showing a third model case of heat recovery. [Figure 16] FIG. 16 is a schematic diagram showing a fourth model case of heat recovery. [Figure 17] FIG. 17 is a flowchart showing a waste heat source diagnosis method according to an embodiment. [Figure 18] FIG. 18 is a flowchart showing the processing when it is determined that heat recovery is possible.

BEST MODE FOR CARRYING OUT THE INVENTION

[0009] [1] Waste heat source diagnosis system FIG. 1 is a diagram schematically showing a waste heat source diagnosis system 1 according to an embodiment. The waste heat source diagnosis system 1 operates on a computer 10 and is a waste heat source diagnosis system for diagnosing the possibility of heat recovery from a waste heat source generated in industrial equipment 2. The waste heat source diagnosis system 1 acquires and accumulates environmental data 50 of the industrial equipment 2. The waste heat source diagnosis system 1 uses the environmental data 50 of the industrial equipment 2 and a database related to heat recovery to generate information regarding the possibility of heat recovery from the waste heat source. The waste heat source diagnosis system 1 supports the discovery and identification of waste heat sources capable of heat recovery by providing information regarding the possibility of heat recovery from the waste heat source to the user of the industrial equipment 2. <​The "equipment" refers to the devices installed in buildings such as factories. The "devices" are the general term for machines, instruments, and appliances. The "industrial equipment 2" refers to the mechanical appliances used for the production of goods or the provision of services. The industrial equipment 2 includes a utility conversion machine that converts the primary utility into a secondary utility that can be used by the demand equipment, a utility distribution network that distributes the secondary utility, and a demand terminal appliance that uses the primary utility or the secondary utility. The demand equipment (load equipment) composed of the demand terminal appliances is one form of the industrial equipment 2.

[0011] The "utility" refers to the energy source or fluid necessary for industrial activities. Examples of the primary utility input to the utility conversion machine include fuel (gas, oil), electricity, and raw water. Examples of the secondary utility output from the industrial equipment 2 include heat medium (steam, heat medium oil, warm water, cold water), compressed air, electricity, and treated water.

[0012] The demand equipment uses the secondary utility output from the utility conversion machine. The demand equipment uses the heat medium as the heat source for various production processes or air conditioning. The demand equipment uses the compressed air as the power source for pneumatic equipment or pneumatic tools. The demand equipment uses the electricity as the power source for electric equipment, electric tools, or lighting. The demand equipment uses the treated water as the process water for food, cosmetics, pharmaceuticals, or semiconductor manufacturing.

[0013] Examples of utility conversion machinery and equipment include thermal equipment, air compressors, generators, and water treatment equipment. Examples of thermal equipment include combustion steam boilers, electric heater steam boilers, heat recovery steam boilers, combustion heat transfer boilers, combustion hot water boilers, electric heater hot water boilers, heat recovery hot water boilers, electric heat pumps, electric chillers, electric heat pump chillers, and flash steam generators. Examples of air compressors include electric air compressors, heat recovery electric air compressors, and steam-driven air compressors. Examples of generators include monogenerators and cogeneration generators. Examples of water treatment equipment include reverse osmosis membrane systems, hard water softeners, deoxygenation systems, and various filtration systems.

[0014] Figure 2 is a schematic diagram showing industrial equipment 2 according to an embodiment. Multiple industrial equipment 2 are installed in a factory or the like. Primary and secondary utilities are supplied to the industrial equipment 2 via a supply line UL, and the industrial equipment 2 operates using the supplied utilities. Multiple industrial equipment 2 may be connected by a utility transmission and distribution network, such as between utility conversion machinery and equipment and demand equipment. Multiple industrial equipment 2 may constitute a processing line that executes a series of processes and may be connected by transport paths or the like to transfer the output of the processing.

[0015] Industrial equipment 2 may include medical machinery and equipment used in a series of processes from receiving to discharging items to be washed and sterilized, laundry machinery and equipment used in a series of processes from collecting to shipping items to be washed, and food and beverage manufacturing machinery and equipment used in a series of processes from receiving raw materials to storing products.

[0016] Examples of medical equipment include washers and sterilizers. Examples of washers include vacuum boiling washers and ultrasonic washers. Examples of sterilizers include steam sterilizers and gas sterilizers. Medical equipment is installed in the central sterile supply department of a medical institution.

[0017] Examples of laundry machinery include washing machines, dryers, and finishing machines. Examples of washing machines include continuous washing machines, water washing machines, and dry cleaning machines. Examples of dryers include gas dryers and steam dryers. Examples of finishing machines include gas roll ironers and steam roll ironers. Laundry machinery is installed in laundry factories.

[0018] Examples of machinery and equipment for food and beverage manufacturing include thawers, cooking machines, coolers, and sterilizers. Examples of thawers include vacuum steam thawers, microwave thawers, high-frequency thawers, and running water thawers. Examples of cooking machines include steam kneaders, steam kettles, and saturated steam cookers. Examples of coolers include vacuum coolers, chilled water coolers, and cold air coolers. Examples of sterilizers include retort sterilizers and pasteurizers. Machinery and equipment for food and beverage manufacturing are installed in food and beverage factories.

[0019] Each industrial equipment 2 may discharge waste heat-containing fluid 70 during its operation. Waste heat-containing fluid 70 can be a liquid such as waste hot water or drain water (steam condensate), or a gas such as air or exhaust gas. Not all industrial equipment 2 discharge waste heat-containing fluid 70, and there may be industrial equipment 2 in factory 4 that do not discharge waste heat-containing fluid 70.

[0020] Returning to Figure 1, Establishment 3 refers to an individual place where the production of goods or the provision of services is carried out as a business. Industrial equipment 2 is installed in Establishment 3. Factory 4 is provided in Establishment 3 where goods are produced, etc. Examples of factory 4 include food factories, beverage factories, metal product factories, plastic product factories, textile factories, and laundry factories. Industrial equipment 2 is installed in factory 4.

[0021] Furthermore, a factory 4 is not required to be established at business establishment 3, which provides the services. The business conducted at business establishment 3 may include public health services. Examples of public health services include hospitals, clinics, and public health centers. Business establishment 3 may also include a school lunch center.

[0022] In the example shown in Figure 1, a certain business operator has three business establishments 3. Business establishments 3 include the first business establishment 3A, the second business establishment 3B, and the third business establishment 3C. A factory 4 is located in the second business establishment 3B. The factory 4 located in the second business establishment 3B includes the first factory 4A and the second factory 4B. Alternatively, a factory 4 may be located in either the first business establishment 3A or the third business establishment 3C, or both.

[0023] Industrial equipment 2 is installed in both the first factory 4A and the second factory 4B. Data collection terminals 7 are installed in both the first factory 4A and the second factory 4B. Data collection terminals 7 is a general term for devices used for data collection at the business establishment 3.

[0024] The waste heat source diagnostic system 1 may include a plurality of environmental data acquisition devices 5 located in the industrial equipment 2, a plurality of controllers 61 equipped in the industrial equipment 2, and a plurality of information processing devices 6 configured to acquire and store environmental data 50 detected by the environmental data acquisition devices 5 and operational information generated by the controllers 61.

[0025] The environmental data acquisition equipment 5 includes, for example, environmental sensors and environmental cameras, and acquires environmental data 50 of the industrial equipment 2. The environmental data 50 of the industrial equipment 2 refers to the environmental state or environmental conditions of the space in which the industrial equipment 2 operates. The environmental data 50 of the industrial equipment 2 includes the environmental data 50 of the business establishment 3 (factory 4) where the industrial equipment 2 is installed. The environmental data 50 includes physical parameters of the main body and surroundings of the industrial equipment 2. Some of the detection data from the environmental data acquisition equipment 5 is used for the operation or control of the industrial equipment 2. Examples of environmental data acquisition equipment 5 include temperature sensors, humidity sensors, pressure sensors, water level sensors, flow rate sensors, electrical conductivity sensors (EC sensors), power sensors, distance sensors, force sensors, visible light cameras, and infrared cameras.

[0026] The environmental data acquisition device 5 is connected to the controller 61 of the industrial equipment 2 and the controller 61 of the data acquisition terminal 7, respectively.

[0027] The controller 61 has functions to control the operation of industrial equipment 2 and to control data collection. The controller 61 is mainly used for autonomous operation control of machinery and equipment (heat equipment, water treatment equipment, water quality measuring equipment, etc.). The controller 61 is connected to environmental data acquisition equipment 5 attached to the machinery and equipment. The controller 61 may also be configured as part of a data collection terminal 7 that specializes in collecting information from environmental data acquisition equipment 5 that is not attached to the machinery and equipment (environmental sensors that are retrofitted to machinery and equipment or retrofitted to piping networks, etc.).

[0028] The controller 61 is incorporated into the industrial equipment 2 and the data acquisition terminal 7. Examples of the controller 61 incorporated into the industrial equipment 2 include a microcomputer 61A and a programmable logic controller 61B (PLC). An example of the controller 61 incorporated into the data acquisition terminal 7 is the microcomputer 61A.

[0029] The controller 61 of the industrial equipment 2 uses the environmental data 50 collected from the environmental data acquisition device 5 to control the operation of the industrial equipment 2 and records it for operational management.

[0030] The controller 61 of the data collection terminal 7 is connected to each of the multiple environmental data acquisition devices 5 scattered throughout the business premises 3. The controller 61 of the data collection terminal 7 is connected to multiple environmental data acquisition devices 5 of different types.

[0031] The controller 61 generates operating information for the industrial equipment 2. The controller 61 may also generate operating information for the industrial equipment 2 based on detection data from the environmental data acquisition device 5.

[0032] [2] Hardware configuration of the information processing device The waste heat source diagnostic system 1 has a plurality of information processing devices 6. The information processing devices 6 include a controller 61, an edge computer 62, a gateway 63, a guest computer 64, and a host computer 65.

[0033] Figure 3 is a hardware configuration diagram showing an information processing device 6 according to an embodiment. The information processing device 6 includes a computer 10. The controller 61, edge computer 62, gateway 63, guest computer 64, and host computer 65 each include the computer 10. The computer 10 has a processor 11, a storage device 12, a communication interface 13, and an input / output interface 14. The information processing device 6 also has a power supply (not shown).

[0034] The processor 11 includes a CPU (Central Processing Unit). The processor 11 may also include a GPU (Graphics Processing Unit). The storage device 12 includes a recording medium on which computer programs and data are recorded in a readable format by the processor 11. The storage device 12 includes onboard system memory such as RAM (Random Access Memory) or ROM (Read Only Memory), high-capacity flash memory such as an SD card or USB memory, and high-capacity storage such as an HDD (Hard Disk Drive) or SSD (Solid State Drive).

[0035] The communication interface 13 communicates via the communication network 8. Examples of the communication network 8 include a local area network (LAN), a wide area network (WAN), and commercial networks such as the internet. The local area network may be a wired LAN or a wireless LAN. The wide area network may include mobile lines or satellite communication lines. Computer 10 transmits data to an external computer via the communication network 8. Computer 10 receives data from an external computer via the communication network 8. Computer 10 is connected to an external device via the input / output interface 14.

[0036] The storage device 12 stores various software programs. The storage device 12 also stores an application program 100 for operating the computer 10 as the waste heat source diagnostic system 1 according to the embodiment. The processor 11 reads the software program from the storage device 12, loads it into system memory, and executes processing according to the software program. In other words, the processor 11 can be considered to have multiple functional units. The functions of the processor 11 are realized by the software program. The software program may be distributed to the computer 10 via the communication network 8.

[0037] A software program that implements a specific function on a computer is called an application or engine (hereinafter referred to as "application, etc."), and the functional unit of an application, etc. is called a module. An engine may be installed on a computer as a single software package containing all its functions, but it is preferable that it be installed on a computer as individual software modules, each for each functional unit of an application, etc. Modularizing the functional units of an engine makes it easier to update when functional modifications are made. An application that runs on an edge computer 62 is sometimes called an edge application.

[0038] The environmental data acquisition device 5 is connected to the input / output interface 14 of the controller 61. Multiple environmental data acquisition devices 5 are connected to one controller 61. The controller 61 collects environmental data 50 from the environmental data acquisition devices 5 in real time. The communication interface 13 of the controller 61 transmits the real-time environmental data 50 and real-time operational information to the edge computer 62 via the communication network 8 (LAN).

[0039] The edge computer 62 is installed in factory 4. One or more edge computers 62 are installed in each factory 4. The communication interface 13 of the edge computer 62 communicates with each of the multiple controllers 61 belonging to factory 4 where the edge computer 62 is located, via the communication network 8 (LAN). The edge computer 62 receives environmental data 50 and operational information from the controllers 61 via the communication network 8.

[0040] The edge computer 62 has approximately 5GB of onboard memory as storage device 12 so as to be able to store a sufficient amount of information. The edge computer 62 may also have an AI engine (Neural Network Processing Unit: NPU) so as to be able to perform the training and inference phases in machine learning.

[0041] Gateway 63 constitutes a connection node between the local area network and the internet and has performance and specifications equivalent to that of the edge computer 62. Gateway 63 is installed at business establishment 3. One or more gateways 63 are installed at a single business establishment 3. The communication interface 13 of gateway 63 communicates with each of the multiple edge computers 62 belonging to business establishment 3 where gateway 63 is located, via the communication network 8 (LAN). Gateway 63 receives environmental data 50 and operational information from the edge computers 62 via the communication network 8. If the factory 4 located at business establishment 3 is a single building, the edge computer 62 and gateway 63 may be integrated and configured as a single computer.

[0042] The guest computer 64 is located outside of the business premises 3. For example, the guest computer 64 is installed at a regional base of a service provider that undertakes tasks such as monitoring the status of industrial equipment 2 installed at business premises 3 and performing maintenance and inspections. One guest computer 64 is installed at each management base. The guest computer 64 includes a local server. The communication interface 13 of the guest computer 64 communicates with the gateway 63 belonging to business premises 3 via the communication network 8 (Internet). The guest computer 64 receives environmental data 50 and operational information from the gateway 63 via the communication network 8. If a guest computer 64 is not installed, the gateway 63 and the host computer 65 (described later) will be connected via the communication network 8.

[0043] The host computer 65 is located outside of the business premises 3. The host computer 65 is installed, for example, at the central headquarters of a service provider. The host computer 65 includes a cloud server. The communication interface 13 of the host computer 65 communicates with each of the multiple guest computers 64 via the communication network 8 (Internet). The host computer 65 receives environmental data 50 and operational information from the guest computers 64 via the communication network 8.

[0044] [3] Hierarchical structure of information processing equipment Figure 4 is a diagram illustrating the hierarchical structure of the information processing device 6 according to the embodiment. The multiple information processing devices 6 have a hierarchical structure that transmits environmental data 50 detected by the environmental data acquisition device 5 and operational information generated by the controller 61 from the downstream side to the upstream side. Of the multiple information processing devices 6, the controller 61 to which the environmental data acquisition device 5 is connected is the most downstream (lower layer, lower level) information processing device 6, followed by the edge computer 62 as the next downstream information processing device 6, followed by the gateway 63 as the next downstream information processing device 6, followed by the guest computer 64 as the next downstream information processing device 6, and the host computer 65 as the most upstream (upper layer, higher level) information processing device 6.

[0045] The information processing devices 6 are connected to each other via a communication network 8. Inside buildings and ships, a local area network is used as the communication network 8, while outside buildings and ships, a commercial wide area network such as an internet connection or a mobile network is used as the communication network 8.

[0046] Environmental data 50 is detected by the environmental data acquisition device 5. The controller 61, which is a lower-level information processing device in the hierarchical structure, acquires real-time environmental data 50 from the environmental data acquisition device 5. The real-time environmental data 50 detected by the environmental data acquisition device 5 and collected by the controller 61 is transmitted from the controller 61 to the edge computer 62 via the communication network 8. Real-time operational information generated by the controller 61 is also transmitted from the controller 61 to the edge computer 62 via the communication network 8. The environmental data 50 and operational information transmitted to the edge computer 62 are transmitted from the edge computer 62 to the gateway 63 via the communication network 8. The environmental data 50 and operational information transmitted to the gateway 63 are transmitted from the gateway 63 to the guest computer 64 via the communication network 8. The environmental data 50 and operational information transmitted to the guest computer 64 are transmitted from the guest computer 64 to the host computer 65 via the communication network 8.

[0047] The controller 61 is a lower-level information processing unit in the hierarchical structure. The edge computer 62, gateway 63, and guest computer 64 are intermediate information processing units in the hierarchical structure. The host computer 65 is a higher-level information processing unit in the hierarchical structure.

[0048] The lower-level information processing device functions as an IoT device to which the environmental data acquisition device 5 is connected. The lower-level information processing device can transmit various environmental data 50 and operational information to the intermediate information processing device. The intermediate information processing device functions as a relay between the lower-level information processing device and the upper-level information processing device. The intermediate information processing device can receive various environmental data 50 and operational information from the lower-level information processing device and can transmit various environmental data 50 and operational information to the upper-level information processing device. The upper-level information processing device can receive various environmental data 50 and operational information from the intermediate information processing device. The upper-level information processing device has an information storage platform. The information storage platform is, for example, an open IoT operating system based on cloud computing, and is capable of systematic storage of information aggregates, etc., as described later. Some or all of the functions realized by the information storage platform may be incorporated into the intermediate information processing device.

[0049] [4] Software configuration of the information processing device Figure 5 is a functional block diagram showing an information processing device 6 according to an embodiment. As shown in Figure 3, the information processing device 6 includes a computer 10 having a processor 11. The information processing device 6 comprises an information processing module 31, a waste heat source information generation module 32, a heat recovery discrimination module 33, a case study database 34, a heat transfer medium information database 35, and an information storage platform 36. In the example of Figure 5, the information processing device 6 further comprises a machine and equipment presentation module 37, an existing equipment database 38, an uninstalled equipment database 39, a model management database 40, a cost reduction prediction module 41, and a UI provision module 42. Note that the information processing device 6 does not necessarily have to include the machine and equipment presentation module 37, the existing equipment database 38, the uninstalled equipment database 39, the model management database 40, the cost reduction prediction module 41, and the UI provision module 42.

[0050] A user terminal 45 is connected to an information processing device 6. Examples of user terminals 45 include personal computers, tablet devices, and smartphones. The user terminal 45 includes a display device such as a liquid crystal display or an organic EL display.

[0051] The multiple information processing devices 6 (61, 62, 63, 64, 65) each have, at one or more layers, an information processing module 31, a waste heat source information generation module 32, a heat recovery discrimination module 33, a case study database 34, a heat transfer medium information database 35, an information storage platform 36, a machine and equipment presentation module 37, an existing equipment database 38, an uninstalled equipment database 39, a model management database 40, a cost reduction prediction module 41, and a UI provision module 42. In other words, each of the information processing module 31, the waste heat source information generation module 32, the heat recovery discrimination module 33, the case study database 34, the heat transfer medium information database 35, the information storage platform 36, the machine and equipment presentation module 37, the existing equipment database 38, an uninstalled equipment database 39, a model management database 40, a cost reduction prediction module 41, and a UI provision module 42 can be a functional unit at one or more layers of the multiple information processing devices 6 (61, 62, 63, 64, 65).

[0052] Furthermore, the information processing module 31 is preferably a functional unit of the edge computer 62 or gateway 63, while the waste heat source information generation module 32, heat recovery discrimination module 33, case study database 34, heat transfer medium information database 35, information storage platform 36, machine and equipment presentation module 37, existing equipment database 38, uninstalled equipment database 39, model management database 40, cost reduction prediction module 41, and UI provision module 42 are preferably functional units of the gateway 63 or host computer 65. When the waste heat source diagnostic system 1 is completed within the factory building (factory building) of factory 4 at the request of the operations manager of business site 3, all modules, platforms, and databases may be functional units of the edge computer 62.

[0053] <4-1> Information Processing Engine The information processing module 31 performs predefined information processing on the acquired environmental data 50 and operational information. The information processing performed by the information processing module 31 includes batch processing to adjust the time-series environmental data 50 and operational information to the required time granularity. The information processing performed by the information processing module 31 also includes grouping processing to integrate multiple environmental data 50 and operational information of different types into an information set linked to the hierarchical level of industrial activity.

[0054] <4-1-1> Generation process of environmental data and operational information The generation process for real-time environmental data 50 and real-time operational information is performed in the information processing module 31 of the lower-level information processing device. Alternatively, the generation process for real-time environmental data 50 and real-time operational information may be performed in the information processing module 31 of the intermediate information processing device or the information processing module 31 of the higher-level information processing device.

[0055] The information processing module 31 acquires and stores real-time environmental data 50 from the environmental data acquisition device 5 at predetermined sampling intervals. The information processing module 31 has an A / D conversion function to convert the analog signal of the environmental data acquisition device 5 into a digital signal, a function to replace the A / D value with a measurement sample value, a function to select and discard measurement sample values, a moving average function for measurement sample values, and a function to measure the period or frequency of the pulse signal, and uses these functions to calculate the confirmed measurement value in real time.

[0056] The information processing module 31 acquires and stores real-time operational information from the controller 61 at predetermined sampling intervals. For example, the controller 61 transmits an "operating" signal when the industrial equipment 2 is operating and a "stopped" signal when it is stopped. The information processing module 31 uses the "operating" signal received via the input / output interface 14 to measure the uptime (actual operating time information) of the industrial equipment 2. The information processing module 31 also uses the "stopped" signal received via the input / output interface 14 to measure the downtime (non-operating time information) of the industrial equipment 2.

[0057] The time granularity of the real-time environmental data 50 and real-time operational information depends on the sampling interval or recording interval, and is generally quite fine (for example, the latest values ​​are updated at intervals of 10ms to 1s). The information processing module 31 transmits the real-time environmental data 50, along with an identification number (measurement item ID, device ID, location ID, etc.) and the update time, to the higher-level information processing device 6.

[0058] <4-1-2> Batch Processing The environmental data 50 and operational information are time-series data that are generated sequentially over time in the information processing module 31. Batch processing refers to the process of adjusting the time-series real-time environmental data 50 and real-time operational information to the required time granularity. Time granularity is an indicator that represents the degree of fineness of time, and can be selected from, for example, seconds, minutes, hours, or days.

[0059] <4-1-3> Grouping process Grouping refers to the process of integrating multiple environmental data 50 and operational information (real-time environmental data 50, batch environmental data, real-time operational information, batch operational information) of different types into an information set linked to the hierarchical level of industrial activity. As shown in Figure 4, the hierarchical level of industrial activity includes one or more levels from among the machine level, machine group level, cell level, line level, building level, and business establishment level.

[0060] <4-2> Information Storage Platform The information storage platform 36 stores various numerical and image-based information and provides a foundational environment for operating software (engines, applications) and hardware. The information storage platform 36 is composed of, for example, an operating system and a database, enabling centralized management of diverse big data and facilitating the processing and utilization of information. The information storage platform 36 stores environmental data 50 and operational information that have undergone prescribed information processing by the information processing module 31, as well as various registration information registered via input devices.

[0061] <4-2-1> Temperature data and flow rate data Figure 6 shows the types of environmental data 50 used to detect waste heat sources. Of the environmental data 50 acquired by the environmental data acquisition device 5, the environmental data 50 used to detect waste heat sources includes, for example, temperature data 51 and flow rate data 52. In this embodiment, the temperature data 51 and flow rate data 52 are time-series data acquired by an environmental sensor 5A attached to a specific location on the industrial equipment 2.

[0062] The specified locations of industrial equipment 2 are the flow paths of waste heat-containing fluids discharged from industrial equipment 2. Examples of specified locations include drainage pits, drain pits, exhaust duct outlets, exhaust fan outlets, and ventilation fan outlets of factory equipment. Liquid waste heat-containing fluids such as wastewater and drain water (condensed water) flow through drainage pits and drain pits. Gaseous waste heat-containing fluids such as air and exhaust gas flow through exhaust duct outlets, exhaust fan outlets, and ventilation fan outlets.

[0063] Figure 7 is a schematic diagram illustrating the acquisition of environmental data 50 at a specific location. In Figure 7, an example is shown where the outlet of the waste heat-containing fluid 70 of the industrial equipment 2 is at a specific location SL. The environmental sensor 5A can be installed at the specific location SL in a manner that it is in contact with the waste heat-containing fluid 70.

[0064] The temperature data 51 and flow rate data 52 make it possible to determine the heat generation [W] and heat quantity [J] of the waste heat-containing fluid. The environmental sensor 5A that acquires the temperature data 51 and flow rate data 52 includes a temperature sensor and a flow rate sensor. The environmental sensor 5A includes a temperature sensor and flow rate sensor that are pre-installed on a specific location SL, or a temperature sensor and flow rate sensor that are retrofitted to a specific location SL. When the environmental sensor 5A is retrofitted, it is preferable to use a thermal flow meter as the environmental sensor 5A that can be installed in a liquid or gas flow field and can acquire temperature data 51 and flow rate data 52 simultaneously. The flow rate data 52 is preferably measurement data of mass flow rate.

[0065] <4-2-2> Visible image data and thermal image data Furthermore, the environmental data 50 used to detect waste heat sources may also include visible image data 53 and thermal image data 54. The visible image data 53 and thermal image data 54 are image data of a specific location SL of the industrial equipment 2 and are captured by an environmental camera 5B. As shown in the example in Figure 7, the environmental camera 5B can capture an area at the specific location SL that includes an opening OP from which waste heat-containing fluid 70 flows out.

[0066] Visible image data 53 and thermal image data 54 are time-series image data (dynamic image data) captured at predetermined time intervals. By analyzing the visible image data 53 and thermal image data 54, it is possible to determine the heat generation amount [W] and heat quantity [J] of the waste heat-containing fluid 70. Visible images are images that observe the reflection of electromagnetic waves corresponding to visible light, captured by a visible light camera. Thermal images are images that visualize the temperature distribution of an object, captured by an infrared camera. Thermal images are also called thermographic images.

[0067] The environmental camera 5B that captures visible image data 53 and thermal image data 54 includes a visible light camera and an infrared camera capable of capturing images of a specific location SL at predetermined time intervals. The environmental camera 5B may be a fixed-installation type like an industrial camera or surveillance camera, a type carried by the photographer, or a type mounted on a drone (a remotely operated unmanned vehicle or unmanned aerial vehicle) for mobile use.

[0068] The environmental data 50 used to detect waste heat sources may be a combination of temperature data 51 and flow rate data 52, or a combination of visible image data 53 and thermal image data 54; it is sufficient to collect and store any of these data sets.

[0069] <4-3>Case Study Database The Case Study Database 34 will collect heat recovery case studies as Knowledge Information 80. The heat recovery case studies collected as Knowledge Information 80 will include actual heat recovery examples (cases actually in operation by a user), proposed examples (cases that were proposed to a user but were not adopted), literature examples (cases described in magazines and specialized books), and hypothetical examples (cases created by technical calculations using a hypothetical equipment configuration).

[0070] Figure 8 is a diagram illustrating the knowledge information. For each case, the knowledge information 80 includes at least waste heat source information 81 and heat transfer medium information 82.

[0071] The waste heat source information 81 is information that identifies the waste heat source to be input into the equipment used for heat recovery. The waste heat source information 81 includes at least the type of waste heat-containing fluid 70, a representative temperature (representative value or numerical range), and a calorific value (representative value or numerical range).

[0072] The heat transfer medium information 82 identifies the heat transfer medium that stores the heat recovered from the waste heat source and supplies it to the demand equipment (industrial equipment 2). The heat transfer medium information 82 includes the type of heat transfer medium, the representative temperature (representative value or numerical range), and the mass flow rate (representative value or numerical range).

[0073] Knowledge information 80 may include equipment information 83 relating to heat recovery machinery and equipment applicable to heat recovery. Equipment information 83 is information about equipment used for heat recovery from waste heat sources. Equipment information 83 includes the heat recovery mechanism and the capacity and specifications of the heat recovery machinery and equipment. The heat recovery mechanism may include, for example, information on using the waste heat-containing fluid 70 as a heat source for a heat exchanger, using the waste heat-containing fluid 70 as a heat source for a heat pump, or reusing (reheating, re-evaporating) the waste heat-containing fluid 70 as a raw material for a heat transfer medium.

[0074] Examples of heat recovery machinery and equipment include heat recovery heat pumps, heat recovery heat exchangers, flash steam generators, and steam drain recovery tanks. A heat recovery heat pump is a heat recovery machine that extracts heat from waste heat-containing fluids 70 such as waste hot water and high-temperature exhaust gas to produce a higher-temperature heat transfer medium (e.g., hot water or steam). A heat recovery heat exchanger is a heat recovery machine that recovers heat by exchanging heat between a heat transfer medium and a waste heat-containing fluid 70 such as waste hot water and high-temperature exhaust gas. Unlike a heat recovery heat pump, a heat recovery heat exchanger produces a heat transfer medium at a lower temperature than the waste heat-containing fluid 70. A flash steam generator is a heat recovery machine that produces low-pressure steam by introducing high-pressure, high-temperature drain water (steam condensate) and other waste heat-containing fluids 70 into a low-pressure tank and re-evaporating it. When high-pressure, high-temperature condensate water is exposed to a low-pressure atmosphere in a flash tank used for condensate recovery, the boiling point drops and part of the condensate water turns into steam. This phenomenon is called flashing or re-evaporation, and the steam generated in this way is called flash steam or re-evaporated steam. The low-pressure steam produced is supplied to industrial equipment 2 as a heat transfer medium and reused. When part of the condensate water undergoes re-evaporation, the remaining condensate water becomes warm water with a lower temperature. The resulting warm water can be reused, for example, as feedwater for a steam boiler or as a heat transfer medium for hot water utilization equipment. A steam condensate recovery tank is a heat recovery device that recovers waste heat-containing fluids 70, such as high-temperature condensate water, in a low-pressure tank and reuses them as a heat transfer medium for hot water.

[0075] The knowledge information 80 accumulated in the case study database 34 allows us to understand what methods are used to recover heat from a given waste heat-containing fluid 70 and what amount of heat transfer medium can be expected to be generated.

[0076] <4-4> Heat Transfer Medium Information Database The heat transfer medium information database 35 stores heat transfer medium information 82 related to the heat transfer medium consumed by the industrial equipment 2 being diagnosed. For example, as shown in Figure 2, when multiple industrial equipment 2 are installed in a factory 4, the heat transfer medium information database 35 includes information on the heat transfer medium used in business activities such as production and air conditioning by each industrial equipment 2.

[0077] The heat transfer medium information 82 includes information on the type of heat transfer medium (hot water, steam, etc.), the required temperature (typical value or numerical range), and the mass flow rate (typical value or numerical range). If the heat transfer medium is steam, the required temperature can be substituted with the required pressure.

[0078] The heat transfer medium information 82 registered in the heat transfer medium information database 35 allows for the identification of the heat transfer medium used in the industrial equipment 2 being diagnosed.

[0079] <4-5> Waste Heat Source Information Generation Module Figure 9 illustrates the process for determining whether heat recovery is possible. As shown in Figure 9, the waste heat source information generation module 32 uses time-series environmental data 50 acquired for a specific location SL of the industrial equipment 2 to generate waste heat source information 81, which includes at least the type of waste heat-containing fluid 70, its representative temperature, and its calorific value.

[0080] The types of waste heat-containing fluids 70 include waste hot water, steam condensate, combustion exhaust gas, and high-temperature air. The representative temperature is the representative value of the temperature of the waste heat-containing fluid 70 at a specific location SL. The heat generation is the amount of thermal energy generated per unit time (W = J / s).

[0081] The time-series environmental data 50 is obtained by collecting data at predetermined time intervals using environmental sensors 5A and environmental cameras 5B at specific locations SL of the industrial equipment 2. The waste heat source information generation module 32 takes the acquired time-series environmental data 50 as input and generates and outputs waste heat source information 81 by performing heat quantity calculations according to predetermined calculation formulas and inference processing using a trained learning model. The waste heat source information generation module 32 generates waste heat source information 81 by processing according to the type of environmental data 50.

[0082] <4-5-1> Temperature data and flow rate data If the environmental data 50 is temperature data 51 and flow rate data 52 of a waste heat-containing fluid 70 at a specific location SL, the waste heat source information generation module 32 takes the acquired time-series temperature data 51 and flow rate data 52 as input and outputs waste heat source information 81 by calculating the heat quantity according to a predetermined calculation formula. The type of waste heat-containing fluid 70 can be estimated from the flow velocity obtained from the flow rate data 52 and the representative temperature extracted from the temperature data 51. This makes it easy to obtain waste heat source information 81. The representative temperature is one of the mode, median, or mean values ​​of the time-series temperature data during a predetermined data collection period.

[0083] <4-5-2> Visible image data and thermal image data If the environmental data 50 consists of visible image data 53 and thermal image data 54 of waste heat-containing fluid 70 at a specific location SL, the waste heat source information generation module 32 generates waste heat source information 81 through image analysis. In this case, the waste heat source information generation module 32 includes an image analysis module 32A and a waste heat source inference module 32B, as shown in Figure 5.

[0084] <4-5-2-1> Image Analysis Module The image analysis module 32A performs predetermined image analysis on the visible image data 53 and the thermal image data 54.

[0085] Figure 10 illustrates an example of image analysis for visible image data 53 and thermal image data 54. For example, when the opening OP of a specific location SL shown in Figure 7 is photographed, the visible image data 53 and thermal image data 54 include the image portion containing the opening OP. The visible image data 53 and thermal image data 54 can be considered to be images of substantially the same field of view. When a high-temperature waste heat-containing fluid 70 flows out from the opening OP, a high temperature value is detected in the thermal image data 54 at the location corresponding to the opening OP. For convenience, in Figure 10, the temperature range in the thermal image data 54 is shown by the density of the hatching, with higher density indicating a higher temperature.

[0086] The image analysis module 32A determines the dimensions (length) of any subject (structure at a specific location SL) included in the visible image data 53 through image analysis. Image analysis can utilize, for example, edge extraction, subpixel processing, and inter-edge subpixel counting. The image analysis module 32A creates a two-dimensional mesh image by dividing the image's shooting space into a predetermined mesh size MS. The mesh size is not particularly limited, but can be, for example, 5cm x 5cm. Figure 10 shows an example of a two-dimensional mesh image created by mesh processing.

[0087] The image analysis module 32A applies a mesh MS of the same size as the visible image data 53 to the thermal image data 54 to create a two-dimensional mesh map with different colors for each temperature range. The temperature range assigned to a unit mesh is, for example, the temperature range corresponding to the pixel with the most frequently occurring color tone within the unit mesh. As a result, each mesh MS is assigned a corresponding temperature value (representative temperature), as illustrated in Figure 10.

[0088] <4-5-2-2> Waste Heat Source Inference Module The waste heat source inference module 32B receives visible image data 53 and thermal image data 54 that have undergone predetermined image analysis as input, and infers waste heat source information 81 according to pre-created processing rules.

[0089] The waste heat source inference module 32B includes several inference functions, as listed below.

[0090] The waste heat source inference module 32B, as its first inference function, infers the type of waste heat-containing fluid 70 using the appearance and contour of the subject (structure) in the visible image data 53 as features. The types of waste heat-containing fluids 70 include, for example, waste hot water, steam condensate, combustion exhaust gas, and high-temperature air, and the appearance of the structure through which these fluids flow usually differs depending on the type of fluid. Therefore, the type of waste heat-containing fluid 70 can be classified based on the differences in the appearance of the structure.

[0091] As a second inference function, the waste heat source inference module 32B infers the representative temperature of the waste heat-containing fluid 70 using the area distribution of the two-dimensional mesh map of the thermal image data 54 as a feature. For example, the waste heat source inference module 32B uses the median value of the temperature zone with the largest area as the representative temperature.

[0092] As a third inference function, the waste heat source inference module 32B infers the heat generation amount (amount of heat generated or transferred per unit time) of the waste heat-containing fluid 70 using the time evolution of the two-dimensional mesh map as a feature. That is, from the time-series thermal image data 54, the time evolution of the two-dimensional mesh map of the thermal image data 54 shown in Figure 10 is obtained as a series of frame images. For example, the waste heat source inference module 32B counts the number of meshes in the temperature range that contains the representative temperature for a two-dimensional mesh map for a predetermined period.

[0093] Once the number of meshes is calculated, the estimated heat generation per two-dimensional mesh map can be determined, for example, by the following calculation. Estimated heat generation per map [W] = Representative temperature × Specific heat of waste heat-containing fluid × Density of waste heat-containing fluid × Number of corresponding meshes per map × Volume per mesh ÷ Time interval between captures of the original map images

[0094] The specific heat and density are constants determined by the type of waste heat-containing fluid 70 that has been inferred. The estimated heat generation amount may be averaged from the estimated heat generation amounts for each of the multiple (time-series) maps. For example, the average value may be calculated by excluding the maximum and minimum values ​​of the heat generation amount. By integrating the heat generation amounts for each of the multiple (time-series) maps, the heat quantity [J=W·s] is obtained, and it is possible to estimate, for example, the scale of waste heat generated in one day.

[0095] These inference functions of the waste heat source inference module 32B may be implemented using a rule-based processing model that uses a predetermined calculation formula, a pre-trained learning model that has been created to perform inference processing using machine learning with environmental data 50, or a combination of a rule-based processing model and a pre-trained learning model.

[0096] A processing model is an algorithm that describes, in a programming language, the process (procedure) for deriving output information from input information. Examples of algorithms that correspond to process maps such as flowcharts are given.

[0097] The trained learning model is an algorithm that has been trained using the features contained in the training visible image data 53 and thermal image data 54 as training data. For example, the trained learning model uses the features contained in the evaluation visible image data 53 and thermal image data 54 as input information to infer the type of waste heat-containing fluid 70, its representative temperature, and its heat generation amount as output information.

[0098] As described above, when the environmental data 50 consists of visible image data 53 and thermal image data 54, the waste heat source information generation module 32 is configured to include an image analysis module 32A and a waste heat source inference module 32B. It takes the visible image data 53 and thermal image data 54, which have undergone predetermined image analysis, as input and outputs waste heat source information 81 through inference processing. This ensures that waste heat source information 81 can be reliably obtained even when it is difficult to install the environmental sensor 5A.

[0099] <4-6> Heat Recovery Discrimination Module As shown in Figure 9, the heat recovery discrimination module 33 determines whether or not heat can be recovered from the waste heat-containing fluid 70 by comparing the waste heat source information 81 and the heat transfer medium information 82 with the case study database 34.

[0100] As described above, the case study database 34 stores knowledge information 80 for each case, including waste heat source information 81 and heat transfer medium information 82. In addition, the heat transfer medium information database 35 registers heat transfer medium information 82 related to the heat transfer medium consumed by the industrial equipment 2 being diagnosed.

[0101] The heat recovery discrimination module 33 obtains waste heat source information 81 for a specific location SL generated by the waste heat source information generation module 32 and heat transfer medium information 82 for each industrial equipment 2 registered in the heat transfer medium information database 35. The heat recovery discrimination module 33 compares the waste heat source information 81, which can be linked to the heat input, and the heat transfer medium information 82, which can be linked to the heat output, with the case study database 34 to determine whether there are cases with similar sets of heat input and heat output. Then, the heat recovery discrimination module 33 determines that heat recovery is possible if similar cases exist, and that heat recovery is not possible if similar cases do not exist.

[0102] The determination result for whether heat recovery is possible is a binary value: heat recovery possible or heat recovery impossible. If the determination result for whether heat recovery is possible, the heat recovery determination module 33 outputs determination result data to the UI provision module 42, which includes, for example, waste heat source information 81 of a specific location SL, knowledge information 80 of similar cases, and heat transfer medium information 82 of industrial equipment 2 corresponding to the heat transfer medium information of similar cases, and can provide it to the operator or maintenance company of industrial equipment 2 (hereinafter referred to as "equipment manager, etc."). This makes it possible to quickly discover or identify waste heat sources from which heat can be recovered.

[0103] Furthermore, in a configuration that includes a machinery and equipment display module 37 and a cost reduction prediction module 41, the waste heat source diagnostic system 1 can provide additional information regarding heat recovery in addition to the results of determining whether heat recovery is possible.

[0104] <4-7> Machinery and Equipment Display Module Figure 11 illustrates the processing of the machinery and equipment presentation module and the cost reduction prediction module. As shown in Figure 11, when the heat recovery determination module 33 determines that heat recovery is possible, the machinery and equipment presentation module 37 extracts and presents at least one type of heat recovery machinery and equipment 90 used in the example of the knowledge information 80 that formed the basis of the determination.

[0105] In other words, if the heat recovery determination module 33 determines that heat recovery is possible based on the existence of similar cases, the machinery and equipment presentation module 37 extracts the heat recovery machinery and equipment 90 used in similar cases and outputs it to the UI provision module 42. The UI provision module 42 presents the information on the heat recovery machinery and equipment 90 to the facility manager, etc. This makes it possible to determine whether to implement equipment modification, equipment addition, or equipment replacement if heat recovery is adopted.

[0106] For example, if the heat recovery machinery 90 used in similar cases is already installed at Factory 4, etc., it may be possible to achieve heat recovery through equipment modification without adding new heat recovery machinery 90. On the other hand, if the heat recovery machinery 90 used in similar cases is not installed at Factory 4, etc., it may be necessary to add equipment for heat recovery.

[0107] Therefore, the machinery and equipment display module 37 compares the heat recovery machinery and equipment 90 used in similar cases with various databases to determine whether there is any equipment that matches the heat recovery machinery and equipment 90.

[0108] <4-7-1> Existing Equipment Database The existing equipment database 38 is a database in which existing heat supply machinery and equipment 91 are registered as industrial equipment 2. Existing means that the equipment has already been installed in the facility where the industrial equipment 2 is installed (this may be the factory 4 or the entire business establishment 3). The machinery and equipment presentation module 37 compares the heat recovery machinery and equipment 90 with the existing equipment database 38 and presents the heat supply machinery and equipment 91 if a heat supply machinery and equipment 91 that matches the heat recovery machinery and equipment 90 exists.

[0109] For example, if heat recovery from waste hot water is already being performed at factory 4 using a heat recovery heat exchanger, the existing heat recovery heat exchanger is registered in the existing equipment database 38 as heat supply machinery and equipment 91. The machinery and equipment presentation module 37 extracts items (in this case, heat recovery heat exchangers) that are compatible with the heat recovery machinery and equipment 90 from the existing heat supply machinery and equipment 91 registered in the existing equipment database 38, and presents them to the facility manager, etc., via the UI provision module 42. By presenting items that are compatible with the heat recovery machinery and equipment 90 from the existing heat supply machinery and equipment 91, it becomes possible to determine the feasibility of heat recovery using existing equipment through facility modification.

[0110] <4-7-2> Database of Uninstalled Equipment The Uninstalled Equipment Database 39 is a database in which heat supply machinery and equipment 91 that are not yet installed as industrial equipment 2 are registered. "Uninstalled" means that the equipment is not installed in the facility where industrial equipment 2 is to be installed (this may be the factory 4 or the entire business establishment 3). The Machinery and Equipment Presentation Module 37 compares the heat recovery machinery and equipment 90 with the Uninstalled Equipment Database 39 and, if a heat supply machinery and equipment 91 that matches the heat recovery machinery and equipment 90 exists, presents the heat supply machinery and equipment 91.

[0111] In cases where it is determined that heat can be recovered from a type of waste heat-containing fluid 70 that has not been subjected to heat recovery until now, it is likely that there are often no heat supply machinery or equipment 91 capable of heat recovery at the factory 4. The machinery and equipment presentation module 37 extracts heat supply machinery and equipment 91 that are not yet installed and that are compatible with the heat recovery machinery and equipment 90 from the uninstalled equipment database 39, and presents them to the equipment manager, etc., via the UI provision module 42. By presenting heat supply machinery and equipment 91 that are compatible with the heat recovery machinery and equipment 90 from the uninstalled heat supply machinery and equipment 91, it becomes possible to determine the feasibility of heat recovery through the addition or replacement of equipment.

[0112] <4-8> Cost Reduction Forecasting Module The cost reduction prediction module 41 uses a virtual model 71 corresponding to the heat supply machinery and equipment 91 presented by the machinery and equipment presentation module 37 to predict the amount of reduction in at least one of the fuel cost and electricity cost that can be expected from heat recovery. The cost reduction prediction module 41 uses the virtual model 71 registered in the model management database 40 to calculate at least one of the fuel cost and electricity cost.

[0113] <4-8-1> Model Management Database The model management database 40 is a database in which virtual models 71 that simulate the operation of heat supply machinery and equipment 91 are registered.

[0114] The virtual model 71 is a digital twin simulator that simulates and reproduces the operation of heat supply machinery and equipment 91, such as a heat pump, in a virtual space created on an information storage platform 36 installed on a computer 10 (cloud server or edge computer). It estimates the operating results of the heat supply machinery and equipment 91 when operated under specific conditions using numerical calculations. These numerical calculations include, for example, calculations of the refrigeration cycle for a heat pump.

[0115] <4-8-2> Cost Reduction Forecast Figure 12 illustrates a simulation using a virtual model 71. The cost reduction prediction module 41 selects a virtual model 71 from the model management database 40 that corresponds to the heat supply machinery and equipment 91 presented by the machinery and equipment presentation module 37. Using the selected virtual model 71, the cost reduction prediction module 41 simulates the amount of heat fluid generated by heat recovery in relation to the heat input given by the waste heat source information 81. The cost reduction prediction module 41 then predicts the amount of reduction in running costs when the heat fluid generated by heat recovery is utilized. The cost reduction prediction module 41 outputs the predicted amount of reduction in running costs to the UI provision module 42 and presents it to the equipment manager, etc., via the UI provision module 42.

[0116] This allows for the estimation of the amortization period for equipment costs required for equipment modification, equipment addition, or equipment replacement. If the estimated amortization period is below a threshold (e.g., 5 years), the user can conclude that the introduction of heat recovery, including equipment costs, is likely to be cost-effective. The cost reduction prediction module 41 may also present the estimated amortization period and a comparison of the amortization period with the threshold (e.g., 5 years) based on the predicted reduction amount.

[0117] <4-8-3> Example of Heat Recovery Simulation Next, we will explain a specific example of a heat recovery simulation using the cost reduction prediction module 41.

[0118] <4-8-3-1> First Model Case Figure 13 is a schematic diagram showing the first model case of heat recovery. The first model case assumes a factory 4 that uses a gas-fired hot water boiler 101, which is industrial equipment 2, as a heat source device, and has a cooling tower 102 installed for circulating cooling of the cooling water used in the production equipment. In the first model case, a water source heat pump is presented as a heat supply machine 91 based on the waste heat source information 81 of the circulating cooling water and the heat transfer medium information 82. By adding a water source heat pump 103 as a heat supply machine 91, it is possible to produce hot water while recovering heat from the circulating cooling water, which is a waste heat-containing fluid 70. As a result, the amount of hot water produced by the hot water boiler can be reduced by the amount produced by the water source heat pump 103.

[0119] In the first model case, the cost reduction prediction module 41 performs the following steps:

[0120] The cost reduction prediction module 41 applies waste heat source information 81 to a virtual model 71 of the water source heat pump 103 to simulate the amount of hot water that can be produced per day Qh when expanded, and the amount of electricity Ea [kWh] required for this production.

[0121] The cost reduction prediction module 41 calculates the increase in electricity costs [¥] by multiplying the amount of electricity Ea by the electricity unit price [¥ / kWh].

[0122] The cost reduction prediction module 41 obtains information on the current daily hot water production amount Qb by the gas-fired hot water boiler 101, and applies this information to the virtual model 71 of the hot water boiler to determine the current gas fuel amount Fb [Nm³]. 3 Simulate ].

[0123] The cost reduction prediction module 41 calculates the daily amount of hot water produced by the gas-fired hot water boiler 101 after the addition of the heat pump, Qa (=Qb-Qh), and applies this information to a virtual model 71 of the gas-fired hot water boiler 101 to simulate the required amount of gas fuel Fa.

[0124] The cost reduction prediction module 41 calculates the fuel price [¥ / Nm] based on the difference in fuel amount Fb-Fa.3 Multiply by ] to calculate the fuel cost reduction amount [¥].

[0125] The cost reduction prediction module 41 calculates the reduction in running costs by adding up the increase in electricity costs and the reduction in fuel costs.

[0126] <4-8-3-2> Second Model Case Figure 14 is a schematic diagram showing a second model case of heat recovery. The second model case assumes a factory 4 where waste hot water is generated, as hot water produced by an existing air-source heat pump (not shown) is used in production facilities, which are industrial equipment 2. In the second model case, a water-source heat pump 104 is presented as the heat supply equipment 91 based on the waste heat source information 81 of the waste hot water, which is a waste heat-containing fluid 70, and the heat transfer medium information 82. In other words, by replacing the existing air-source heat pump with a water-source heat pump 104, it is possible to produce hot water while recovering heat from waste hot water.

[0127] In the second model case, the cost reduction prediction module 41 performs the following steps:

[0128] Applying the waste heat source information 81 to the hypothetical model 71 of the water-source heat pump 104, which is assumed to be replaced, the amount of electricity required per unit volume of hot water Ea [kWh / m³] is calculated. 3 Simulate ].

[0129] The amount of electricity Eb required per unit volume of hot water is simulated by applying representative temperature information such as outside air to a virtual model 71 of an existing air-source heat pump.

[0130] Multiply the difference in electricity consumption Eb-Ea by the electricity price [¥ / kWh] to find the reduction in electricity cost per unit of hot water [¥ / m 3 Calculate ].

[0131] <4-8-3-3> Third Model Case Figure 15 is a schematic diagram showing a third model case of heat recovery. The third model case assumes a factory 4 where compression heat is not recovered by the industrial equipment 2, the air compressor 105, and the compressed air is dissipated and cooled by an aftercooler. High-temperature exhaust from the air compressor 105 is discharged as waste heat-containing fluid 70. In the third model case, based on the waste heat source information 81 of the high-temperature exhaust from the air compressor 105 and the heat transfer medium information 82, the existing air heat source heat pump 106 is presented as the heat supply equipment 91. That is, it is possible to produce hot water while recovering heat from the high-temperature exhaust using the existing air heat source heat pump 106 as a heat source. For example, heat recovery is possible by rearranging the layout of the existing equipment and modifying the system to connect the exhaust port of the packaged air compressor 105 and the intake port of the air heat source heat pump 106 with a duct.

[0132] In the third model case, the cost reduction prediction module 41 performs the following steps:

[0133] By applying the waste heat source information 81 to the virtual model 71 of the air-source heat pump 106, the amount of electricity required per unit volume of hot water Ea [kWh / m³] is calculated. 3 Simulate ].

[0134] The current representative temperature information of the outside air, etc., is applied to the virtual model 71 of the air-source heat pump 106 to simulate the amount of electricity Eb required per unit volume of hot water.

[0135] Multiply the difference in electricity consumption Eb-Ea by the electricity price [¥ / kWh] to find the reduction in electricity cost per unit of hot water [¥ / m 3 Calculate ].

[0136] <4-8-3-4> Fourth Model Case Figure 16 is a schematic diagram showing the fourth model case of heat recovery. The fourth model case assumes a factory 4 where high-pressure steam produced by an existing gas-fired steam boiler 107 is used in industrial equipment 2, which is production equipment, and high-pressure condensate is generated. In the fourth model case, based on the waste heat source information 81 of the high-pressure condensate and the heat transfer medium information 82, an uninstalled flash steam generator 108 is suggested as the heat supply equipment 91. That is, by adding a flash steam generator 108, it is possible to recover heat by generating low-pressure steam and hot water as heat transfer mediums from the high-pressure condensate, which is waste heat-containing fluid 70. The low-pressure steam is used in other production equipment in factory 4, and the hot water is reused as feedwater for the gas-fired steam boiler 107.

[0137] In the fourth model case, the cost reduction prediction module 41 performs the following steps:

[0138] The cost reduction prediction module 41 applies waste heat source information 81 to a virtual model 71 of the flash steam generator 108 to simulate the amount of low-pressure steam that can be generated per day Qf and the assumed pressure, as well as the amount of hot water that can be generated Qw and the assumed temperature.

[0139] The cost reduction prediction module 41 obtains information on the current daily steam production amount Qb and representative values ​​of the feedwater temperature from the gas-fired steam boiler 107. The cost reduction prediction module 41 applies this information to a virtual model 71 of the gas-fired steam boiler 107 to determine the current gas fuel amount Fb [Nm³]. 3 Simulate ].

[0140] The cost reduction prediction module 41 calculates the daily steam production amount Qa (=Qb-Qf) by the gas-fired steam boiler 107 after the addition of the flash steam generator 108. The cost reduction prediction module 41 also calculates the amount of hot water that can be generated Qw and the feedwater temperature that has been raised based on the assumed temperature. The cost reduction prediction module 41 applies this information to a virtual model 71 of the gas-fired steam boiler 107 to simulate the amount of gas fuel Fa after the addition of the flash steam generator 108.

[0141] The cost reduction prediction module 41 calculates the fuel price [¥ / Nm] based on the difference in fuel amount Fb-Fa. 3 Multiply by ] to calculate the fuel cost reduction amount [¥].

[0142] The cost reduction prediction module 41 may also calculate the water-saving effect from the use of hot water (amount of recycled water Qw) as the reduction in water procurement costs [Y].

[0143] <4-9> UI Provisioning Module As shown in Figure 5, the UI providing module 42 provides a user interface (UI) for displaying various information on the user terminal 45. The user interface is a means of accessing the waste heat source diagnostic system 1 for users, such as facility managers. The user interface mainly includes a function to display the UI screen on the user terminal 45 and a function to receive operation input for various functions provided via the UI screen.

[0144] The UI provision module 42 displays various types of information on the user terminal 45, such as environmental data 50, operating information of industrial equipment 2, knowledge information 80 accumulated in the case study database 34, heat transfer medium information 82 registered in the heat transfer medium information database 35, a map showing the overall or partial configuration of industrial equipment 2 and the factory 4, and location information of specific locations SL on the map, the results of the heat recovery determination module 33 determining whether heat recovery is possible, and information on heat recovery machinery 90 and heat supply machinery 91 provided by the machinery and equipment presentation module 37.

[0145] [5] Method for diagnosing waste heat sources Figure 17 is a flowchart illustrating the waste heat source diagnostic method according to the embodiment. Figure 17 is also an operation flowchart of the waste heat source diagnostic system 1 according to the embodiment.

[0146] The waste heat source diagnostic method according to this embodiment is performed by a computer 10 and diagnoses whether or not heat can be recovered from the waste heat source generated by the industrial equipment 2.

[0147] As shown in Figure 17, the waste heat source diagnostic method according to the embodiment includes (step S10) generating waste heat source information 81, which includes at least the type of waste heat-containing fluid 70, its representative temperature, and its heat generation amount, using time-series environmental data 50 acquired for a specific location SL of the industrial equipment 2 by the computer 10. The computer 10 operates as a waste heat source information generation module 32 and executes the process of generating waste heat source information 81 for the specific location SL.

[0148] The waste heat source diagnostic method according to this embodiment includes (step S11) obtaining heat medium information 82 from a heat medium information database 35 in which heat medium information 82 related to the heat medium consumed by the industrial equipment 2 to be diagnosed is registered by the computer 10. The computer 10 executes the process of obtaining heat medium information 82 from the heat medium information database 35 as part of the function of the heat recovery discrimination module 33.

[0149] The waste heat source diagnostic method according to the embodiment includes a computer 10 that determines whether heat can be recovered from the waste heat-containing fluid 70 by comparing waste heat source information 81 and heat transfer medium information 82 with a case study database 34 in which heat recovery cases are accumulated as knowledge information 80 (step S12). The computer 10 operates as a heat recovery determination module 33 and executes a process to generate a determination result of whether heat can be recovered from the waste heat-containing fluid 70 at a specific location SL. This makes it possible to quickly discover or identify waste heat sources from which heat can be recovered.

[0150] The computer 10, which operates as a heat recovery determination module 33, may output the determination result of whether or not the generated heat can be recovered to, for example, the UI provision module 42, and present it to the facility manager, etc., via the UI provision module 42 (step S13). The UI provision module 42 presents the determination result of whether or not heat can be recovered by, for example, displaying the information on the user terminal 45.

[0151] Figure 18 is a flowchart showing the process when it is determined that heat recovery is possible.

[0152] As shown in Figure 18, the waste heat source diagnostic method according to the embodiment includes, when the computer 10 determines that heat recovery is possible, extracting at least one type of heat recovery machinery 90 used in the example of the knowledge information 80 that formed the basis of the determination (step S20). The computer 10 operates as a machinery and equipment suggestion module 37 and executes a process to extract heat recovery machinery 90 used in similar cases. At this time, the machinery and equipment suggestion module 37 compares the heat recovery machinery 90 with the existing equipment database 38 and extracts the heat supply machinery 91 if there is a heat supply machinery 91 that matches the heat recovery machinery 90. The machinery and equipment suggestion module 37 also compares the heat recovery machinery 90 with the uninstalled equipment database 39 and extracts the heat supply machinery 91 if there is a heat supply machinery 91 that matches the heat recovery machinery 90.

[0153] The waste heat source diagnostic method according to the embodiment includes using a computer 10 to predict the amount of reduction in at least one of the fuel cost and electricity cost that can be expected from heat recovery, using a virtual model 71 corresponding to the extracted heat supply machinery and equipment 91 (step S21). The computer 10 operates as a cost reduction prediction module 41 and performs the process of predicting the cost reduction amount using the virtual model 71.

[0154] The waste heat source diagnostic method according to the embodiment includes presenting the extracted and predicted information using the computer 10 (step S22). Specifically, the computer 10, operating as a machine and equipment presentation module 37, outputs the extracted heat recovery machine and equipment 90 to, for example, the UI provision module 42, and presents it to the facility manager, etc., via the UI provision module 42. If there is extracted heat supply machine and equipment 91 (existing or not installed), the machine and equipment presentation module 37 presents the heat supply machine and equipment 91. The computer 10, operating as a cost reduction prediction module 41, outputs the cost reduction amount to, for example, the UI provision module 42, and presents it to the facility manager, etc., via the UI provision module 42.

[0155] [6] Effects As described above, in this embodiment, the waste heat source diagnostic system 1 is a waste heat source diagnostic system 1 that operates on a computer 10 and diagnoses whether or not heat can be recovered from a waste heat source generated in an industrial facility 2, and comprises: a case study database 34 which has accumulated heat recovery cases as knowledge information 80; a heat medium information database 35 which has registered heat medium information 82 relating to the heat medium consumed by the industrial facility 2 to be diagnosed; a waste heat source information generation module 32 which generates waste heat source information 81 including at least the type of waste heat-containing fluid 70, representative temperature and heat generation amount using time-series environmental data 50 acquired for a specific location SL of the industrial facility 2; and a heat recovery determination module 33 which determines whether or not heat can be recovered from the waste heat-containing fluid 70 by comparing the waste heat source information 81 and heat medium information 82 with the case study database 34.

[0156] According to this configuration, the waste heat source information generation module 32 takes acquired time-series environmental data 50 as input and outputs waste heat source information 81, including the type of waste heat-containing fluid 70, representative temperature, and heat generation amount, by performing heat quantity calculations according to a predetermined calculation formula and inference processing using a learning model. The heat recovery discrimination module 33 compares the waste heat source information 81 and heat transfer medium information 82 with the case study database 34 and determines whether there are cases with similar sets of waste heat source information 81 and heat transfer medium information 82. For example, if a similar case exists, the heat recovery discrimination module 33 determines that heat recovery is possible, and if no similar case exists, it determines that heat recovery is not possible. This makes it possible to quickly find waste heat sources from which heat can be recovered.

[0157] In this embodiment, the environmental data 50 includes temperature data and flow rate data detected by an environmental sensor 5A attached to a specific location SL. In this configuration, the environmental data 50 can be obtained by a temperature sensor and flow rate sensor that are pre-installed on the specific location SL, or by a temperature sensor and flow rate sensor that are retrofitted to the specific location SL. The type of waste heat-containing fluid 70 can be estimated from the flow velocity obtained from the flow rate data and the representative temperature extracted from the temperature data. This makes it easy to obtain waste heat source information 81.

[0158] In this embodiment, the environmental data 50 includes visible light image data 53 and thermal image data 54 of a specific location SL captured by an environmental camera 5B, and the waste heat source information generation module 32 includes an image analysis module 32A that performs predetermined image analysis on the visible light image data 53 and thermal image data 54, and a waste heat source inference module 32B that infers waste heat source information 81 according to a pre-created processing rule by inputting the visible light image data 53 and thermal image data 54 that have undergone predetermined image analysis. In this configuration, the environmental data 50 can be obtained by a visible light camera and an infrared camera capable of taking pictures of a specific location SL at predetermined time intervals. The waste heat source information generation module 32 is configured to include an image analysis module 32A and a waste heat source inference module 32B, and takes the visible light image data 53 and thermal image data 54 that have undergone predetermined image analysis as input and outputs waste heat source information 81 by image analysis. This makes it possible to obtain waste heat source information 81 from a position away from the specific location SL, even when it is difficult to install environmental sensors 5A such as temperature sensors or flow rate sensors.

[0159] In this embodiment, the knowledge information 80 includes equipment information 83 relating to heat recovery machinery and equipment 90 applicable to heat recovery, and the waste heat source diagnostic system 1 further includes a machinery and equipment presentation module 37 that, when the heat recovery discrimination module 33 determines that heat recovery is possible, extracts and presents at least one type of heat recovery machinery and equipment 90 used in the example of the knowledge information 80 that formed the basis of the discrimination. In this configuration, when the heat recovery discrimination module 33 determines that heat recovery is possible based on the existence of similar examples, the machinery and equipment presentation module 37 extracts and presents the heat recovery machinery and equipment 90 used in similar examples. This makes it possible to determine whether to implement equipment modification, equipment addition, or equipment replacement when adopting heat recovery.

[0160] In this embodiment, the waste heat source diagnostic system 1 further includes an existing equipment database 38 in which existing heat supply machinery and equipment 91 are registered as industrial equipment 2. The machinery and equipment presentation module 37 compares the heat recovery machinery and equipment 90 with the existing equipment database 38 and presents the heat supply machinery and equipment 91 if a heat supply machinery and equipment 91 that matches the heat recovery machinery and equipment 90 exists. In this configuration, by presenting a heat supply machinery and equipment 91 that matches the heat recovery machinery and equipment 90 from among the existing heat supply machinery and equipment 91, it becomes possible to determine the feasibility of heat recovery through equipment modification.

[0161] In this embodiment, the waste heat source diagnostic system 1 further includes an uninstalled equipment database 39 in which uninstalled heat supply machinery and equipment 91 are registered as industrial equipment 2. The machinery and equipment presentation module 37 compares the heat recovery machinery and equipment 90 with the uninstalled equipment database 39 and presents the heat supply machinery and equipment 91 if a heat supply machinery and equipment 91 that matches the heat recovery machinery and equipment 90 exists. In this configuration, by presenting a heat supply machinery and equipment 91 that matches the heat recovery machinery and equipment 90 from among the uninstalled heat supply machinery and equipment 91, it becomes possible to determine the feasibility of heat recovery through the addition or replacement of equipment.

[0162] In this embodiment, the waste heat source diagnostic system 1 further comprises a model management database 40 in which virtual models 71 that simulate the operation of heat supply machinery and equipment 91 are registered, and a cost reduction prediction module 41 that uses the virtual model 71 corresponding to the heat supply machinery and equipment 91 presented by the machinery and equipment presentation module 37 to predict the amount of reduction in at least one of fuel costs and electricity costs that can be expected from heat recovery. In this configuration, the cost reduction prediction module 41 selects the virtual model 71 corresponding to the heat supply machinery and equipment 91 presented by the machinery and equipment presentation module 37 from the model management database 40, uses this virtual model 71 to simulate the amount of heat transfer medium generated by heat recovery, and predicts the amount of reduction in running costs when the heat transfer medium generated by heat recovery is utilized. This makes it possible to estimate the amortization period of the equipment costs required for equipment modification, equipment addition, or equipment replacement. Therefore, by concretely demonstrating the economic usefulness of heat recovery, it becomes easier for equipment users considering equipment introduction to determine whether or not heat recovery is feasible.

[0163] In one embodiment, the waste heat source diagnostic method is performed by a computer 10 and diagnoses whether or not heat can be recovered from a waste heat source generated in an industrial facility 2. The method includes: generating waste heat source information 81, which includes at least the type of waste heat-containing fluid 70, its representative temperature, and its calorific value, using time-series environmental data 50 acquired for a specific location SL of the industrial facility 2; acquiring heat transfer medium information 82 from a heat transfer medium information database 35 in which heat transfer medium information 82 relating to the heat transfer medium consumed by the industrial facility 2 to be diagnosed is registered; and determining whether or not heat can be recovered from the waste heat-containing fluid 70 by comparing the waste heat source information 81 and the heat transfer medium information 82 with a case study database 34 in which heat recovery cases are accumulated as knowledge information 80.

[0164] In this configuration, the computer 10 takes acquired time-series environmental data 50 as input and outputs waste heat source information 81, including the type of waste heat-containing fluid 70, its representative temperature, and its heat generation amount, through heat calculations according to a predetermined formula and inference processing using a trained learning model. The computer 10 compares the waste heat source information 81 and heat transfer medium information 82 with the case study database 34 and determines whether there are similar cases with the same set of waste heat source information 81 and heat transfer medium information 82. For example, if a similar case exists, the computer 10 determines that heat recovery is possible, and if no similar case exists, it determines that heat recovery is not possible. This makes it possible to quickly find waste heat sources from which heat can be recovered.

[0165] [7] Other embodiments In the embodiments described above, the recovery of thermal energy from a high-temperature waste heat-containing fluid 70 was explained, but heat recovery in this specification is not limited to the recovery of thermal energy. Cold energy may also be recovered from a low-temperature waste heat-containing fluid 70.

[0166] [8] Contribution to the United Nations-led Sustainable Development Goals (SDGs) The waste heat source diagnostic system described in this disclosure can collect a wide range of environmental data from industrial facilities and can be used to quickly identify unused waste heat sources from which heat can be recovered. As a result, by realizing heat recovery from such waste heat sources, it is possible to improve the energy efficiency of business establishments, including factories, reduce carbon dioxide emissions, and contribute to achieving Sustainable Development Goals (SDGs) Goal 7, "Affordable and Clean Energy," and Goal 13, "Take urgent action to combat climate change and its impacts." [Explanation of Symbols]

[0167] 1…Waste heat source diagnostic system, 2…Industrial equipment, 3…Business establishment, 3A…First business establishment, 3B…Second business establishment, 3C…Third business establishment, 4…Factory, 4A…First factory, 4B…Second factory, 5…Environmental data acquisition equipment, 5A…Environmental sensor, 5B…Environmental camera, 6…Information processing device, 7…Data collection terminal, 8…Communication network, 10…Computer, 11…Processor, 12…Storage device, 13…Communication interface, 14…Input / output interface, 31…Information processing module, 32…Waste heat source information generation module, 32A…Image analysis module, 32B…Waste heat source inference module, 33…Heat recovery discrimination module, 34…Case study database, 35…Heat transfer medium information database, 36…Information storage platform, 37…Machinery and equipment presentation module, 38…Existing equipment database, 39…Uninstalled equipment database, 40…Model management database, 41…Cost reduction prediction module, 4 2...UI provision module, 45...User terminal, 50...Environmental data, 51...Temperature data, 52...Flow rate data, 53...Visible image data, 54...Thermal image data, 61...Controller, 61A...Microcomputer, 61B...Programmable logic controller, 62...Edge computer, 63...Gateway, 64...Guest computer, 65...Host computer, 70...Waste heat-containing fluid, 71...Virtual model, 80...Knowledge information, 81...Waste heat source information, 82...Heat transfer medium information, 83...Equipment information, 90...Heat recovery machinery and equipment, 91...Heat supply machinery and equipment, 100...Application program, 101...Hot water boiler, 102...Cooling tower, 103,104...Water source heat pump, 105...Air compressor, 106...Air source heat pump, 107...Steam boiler, 108...Flash steam generator, MS...Mesh, OP...Opening, SL...Specific location.

Claims

1. A waste heat source diagnostic system that operates on a computer and diagnoses whether or not heat can be recovered from waste heat sources generated in industrial equipment, A database of case studies that compiles heat recovery examples as knowledge information, A heat transfer medium information database in which heat transfer medium information relating to the heat transfer medium consumed by the aforementioned industrial equipment to be diagnosed is registered, A waste heat source information generation module generates waste heat source information, including at least the type of waste heat-containing fluid, representative temperature, and heat generation amount, using time-series environmental data acquired for specific locations of the aforementioned industrial equipment. The system includes a heat recovery determination module that determines whether or not heat can be recovered from the waste heat-containing fluid by comparing the waste heat source information and the heat transfer medium information with the case study database. Waste heat source diagnostic system.

2. The aforementioned environmental data includes temperature data and flow rate data detected by environmental sensors installed at the specified location. The waste heat source diagnostic system according to claim 1.

3. The aforementioned environmental data includes visible image data and thermal image data of the specific location captured by the environmental camera. The aforementioned waste heat source information generation module is: An image analysis module that performs predetermined image analysis on the visible image data and the thermal image data, The system includes a waste heat source inference module that, upon inputting the visible image data and thermal image data that have undergone the aforementioned predetermined image analysis, infers the waste heat source information according to a pre-created processing rule, and The waste heat source diagnostic system according to claim 1.

4. The aforementioned knowledge information includes equipment information relating to heat recovery machinery and equipment applicable to heat recovery, If the heat recovery determination module determines that heat recovery is possible, the system further includes a machine and equipment presentation module that extracts and presents at least one type of heat recovery machine or equipment used in the example of the knowledge information that formed the basis of the determination. The waste heat source diagnostic system according to claim 1.

5. The aforementioned industrial equipment further includes an existing equipment database in which existing heat supply machinery and equipment are registered. The aforementioned machinery and equipment display module compares the heat recovery machinery and equipment with the existing equipment database, and if a heat supply machinery and equipment that matches the heat recovery machinery and equipment exists, it displays the heat supply machinery and equipment. The waste heat source diagnostic system according to claim 4.

6. The aforementioned industrial equipment further includes a database of uninstalled equipment in which heat supply machinery and equipment that have not yet been installed are registered. The aforementioned machinery and equipment display module compares the heat recovery machinery and equipment with the database of uninstalled equipment, and if a heat supply machinery and equipment that matches the heat recovery machinery and equipment exists, it displays the heat supply machinery and equipment. The waste heat source diagnostic system according to claim 4.

7. A model management database in which virtual models that simulate the operation of the aforementioned heat supply machinery and equipment are registered, The system further comprises a cost reduction prediction module that predicts the amount of reduction in at least one of fuel costs and electricity costs that can be expected from heat recovery, using the virtual model corresponding to the heat supply machinery and equipment presented by the machinery and equipment presentation module. The waste heat source diagnostic system according to claim 5 or claim 6.

8. A waste heat source diagnostic method, performed by computer, which diagnoses whether or not heat can be recovered from waste heat sources generated in industrial equipment, Using time-series environmental data acquired for specific locations of the aforementioned industrial equipment, waste heat source information is generated, including at least the type of waste heat-containing fluid, representative temperature, and calorific value. Obtain the heat transfer medium information from a heat transfer medium information database in which information on the heat transfer medium consumed by the industrial equipment to be diagnosed is registered. This includes determining whether heat recovery is possible from the waste heat-containing fluid by comparing the waste heat source information and the heat transfer medium information with a database of case studies that have been compiled as knowledge information on heat recovery cases. Methods for diagnosing waste heat sources.

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