Information processing device, information processing method, and program

Abstract

To more accurately grasp a state of waste on a fire grate on the basis of thermal image data obtained by imaging inside of an incinerator.SOLUTION: An information processing device includes a control section with hardware. The control section acquires image data generated from thermal image information in which a region including waste in a waste incinerator with a fire grate for moving the waste is imaged, acquires process data on the waste incinerator, derives a present amount of the waste present on the fire grate, a supply amount of the waste supplied onto the fire grate and a temperature of the waste on the basis of at least one of the acquired image data and the acquired process data, inputs the acquired process data and the derived present amount of the waste on the fire grate, the derived supply amount of the waste supplied onto the fire grate and the derived temperature of the waste to a moisture evaporation model constructed beforehand to derive a moisture evaporation amount from the waste, and derives a ratio of moisture included in the waste present on the fire grate on the basis of the derived moisture evaporation amount to estimate a moisture amount included in the waste.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Conventionally, in order to improve the operating efficiency of stoker-type incinerators, methods have been proposed for measuring or estimating the state of waste present on the fire grates inside incinerators such as stoker-type incinerators that incinerate waste.

[0003] Patent Document 1 discloses a technique for estimating the amount of garbage on the grate by using the pressure loss that occurs when the combustion air blown from below the grate passes through the garbage. Patent Document 2 discloses a technique for calculating the amount of garbage accumulated in an incinerator by using an energy balance equation for the entire incinerator derived from the flow rate and air temperature of the combustion air. Patent Document 3 discloses a technique for estimating the amount of garbage by taking a thermal image of the garbage in the incinerator and detecting the boundary line between the garbage and the wall inside the incinerator. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 3030614 [Patent Document 2] Patent No. 3023080 [Patent Document 3] Patent No. 6472035 Summary of the Invention [Problem to be solved by the invention]

[0005] However, in the above-mentioned conventional technology, it is difficult to accurately derive the state of the waste, such as the amount of waste on the grate and the ratio of the moisture content to the volatile matter content, etc. Therefore, there is a need for a technology that can grasp the state of the waste on the grate more accurately based on thermal imaging data captured inside a waste incinerator and measurement data related to the incinerator.

[0006] The present invention has been made in consideration of the above, and its object is to provide an information processing device, an information processing method, and a program that can more accurately grasp the state of waste on the grate based on thermal imaging data captured inside a waste incinerator. [Means for solving the problem]

[0007] In order to solve the above-mentioned problems and achieve the object, an information processing device according to one embodiment of the present invention includes a control unit having hardware, and the control unit acquires image data generated from thermal image information in which an area containing waste in a waste incinerator equipped with a grate for moving the waste is captured, acquires process data in the waste incinerator, and derives the amount of waste present on the grate, the supply amount of the waste supplied to the grate, and the temperature of the waste based on at least one of the acquired image data and the acquired process data, inputs the acquired process data and the derived amount of waste present on the grate, the supply amount of the waste supplied to the grate, and the temperature of the waste into a moisture evaporation model constructed in advance to derive the amount of moisture evaporated from the waste, and derives the ratio of moisture contained in the waste present on the grate based on the derived amount of moisture evaporation, thereby estimating the amount of moisture contained in the waste.

[0008] In one aspect of the information processing device of the present invention, in the above invention, the waste incinerator is configured to be able to supply combustion air to the grate, and the control unit uses a model as the moisture evaporation model that derives the amount of moisture evaporation from the waste as the sum of the amount of moisture evaporation due to thermal radiation in the waste incinerator and the amount of moisture evaporation due to the ventilation of combustion air supplied to the grate.

[0009] In one aspect of the information processing device of the present invention, in the above invention, the control unit inputs the acquired process data, the derived amount of waste present on the grate, the derived amount of waste supplied to the grate, and the temperature of the waste into a pre-constructed volatile matter release model to derive the amount of volatile matter released from the waste, and based on the derived amount of water evaporation and the amount of volatile matter released, derives the ratio of the amount of moisture and the amount of volatile matter contained in the waste present on the grate to estimate the state of the waste.

[0010] In an information processing device according to one embodiment of the present invention, in the above invention, the control unit inputs the acquired process data, the derived amount of waste present on the grate, the derived amount of waste supplied onto the grate, and the temperature of the waste into a pre-constructed fixed carbon combustion model to derive the amount of fixed carbon combustion in the waste, and based on the derived amount of water evaporation, amount of volatile matter released, and amount of fixed carbon combustion, derives the ratio of the amount of moisture, amount of volatile matter, and amount of fixed carbon contained in the waste present on the grate to estimate the state of the waste.

[0011] In an information processing device according to one aspect of the present invention, in the above invention, the control unit corrects state variables when estimating the state of the waste from the amount of water evaporation at a specified time by data assimilation processing using a Kalman filter.

[0012] In one aspect of the information processing device of the present invention, in the above invention, the control unit virtually divides the waste on the grate into a plurality of regions at least along the direction in which the waste is transported, and derives the amount of waste present on the grate, the amount of waste moved, and the temperature of the waste for each of the plurality of regions based on the acquired image data, inputs the acquired process data and the derived amount of waste present on the grate, the amount of waste moved, and the temperature of the waste into the moisture evaporation model to derive the amount of moisture evaporation from the waste for each region, and derives the ratio of moisture contained in the waste present on the grate for each region based on the derived amount of moisture evaporation for each region, thereby estimating the amount of moisture contained in the waste for each region.

[0013] An information processing method according to one embodiment of the present invention is an information processing method executed by an information processing device having a control unit with hardware, in which the control unit acquires image data generated from thermal image information in which an area containing waste in a waste incinerator having a grate for moving the waste is imaged, acquires process data for the waste incinerator, derives the amount of waste present on the grate, the supply amount of the waste supplied to the grate, and the temperature of the waste based on at least one of the acquired image data and the acquired process data, inputs the acquired process data and the derived amount of waste present on the grate, the supply amount of the waste supplied to the grate, and the temperature of the waste into a moisture evaporation model constructed in advance to derive the amount of moisture evaporated from the waste, and derives the ratio of moisture contained in the waste present on the grate based on the derived amount of moisture evaporation, thereby estimating the amount of moisture contained in the waste.

[0014] In one aspect of the information processing method of the present invention, in the above invention, the waste incinerator is configured to be able to supply combustion air to the grate, and the control unit uses a model as the moisture evaporation model that derives the amount of moisture evaporation from the waste as the sum of the amount of moisture evaporation due to thermal radiation in the waste incinerator and the amount of moisture evaporation due to the ventilation of combustion air supplied to the grate.

[0015] In an information processing method according to one embodiment of the present invention, in the above invention, the control unit inputs the acquired process data, the derived amount of waste present on the grate, the derived amount of waste supplied to the grate, and the temperature of the waste into a pre-constructed volatile matter release model to derive the amount of volatile matter released from the waste, and based on the derived amount of water evaporation and the amount of volatile matter released, derives the ratio of the amount of moisture to the amount of volatile matter contained in the waste present on the grate to estimate the state of the waste.

[0016] In one aspect of the information processing method of the present invention, in the above invention, the acquired process data, the derived amount of waste present on the grate, the derived amount of waste supplied to the grate, and the temperature of the waste are input into a pre-constructed fixed carbon combustion model to derive the amount of fixed carbon combustion in the waste, and based on the derived amount of water evaporation, amount of volatile matter released, and amount of fixed carbon combustion, derive the ratio of the amount of water, amount of volatile matter, and amount of fixed carbon contained in the waste present on the grate to estimate the state of the waste.

[0017] In an information processing method according to one aspect of the present invention, in the above invention, the control unit corrects state variables when estimating the state of the waste from the amount of water evaporation at a specified time by data assimilation processing using a Kalman filter.

[0018] In an information processing method according to one aspect of the present invention, in the above invention, the control unit virtually divides the waste on the grate into a plurality of regions at least along the direction in which the waste is transported, and derives the amount of waste present on the grate, the amount of waste moved, and the temperature of the waste for each of the plurality of regions based on the acquired image data, inputs the acquired process data and the derived amount of waste present on the grate, the amount of waste moved, and the temperature of the waste into the moisture evaporation model to derive the amount of moisture evaporation from the waste for each region, and derives the ratio of moisture contained in the waste present on the grate for each region based on the derived amount of moisture evaporation for each region, thereby estimating the amount of moisture contained in the waste for each region.

[0019] A program according to one embodiment of the present invention causes a control unit having hardware to acquire image data generated from thermal image information in which an area containing waste in a waste incinerator equipped with a grate for moving the waste is captured, acquire process data for the waste incinerator, derive the amount of waste present on the grate, the supply amount of the waste supplied to the grate, and the temperature of the waste based on at least one of the acquired image data and the acquired process data, input the acquired process data and the derived amount of waste present on the grate, the supply amount of the waste supplied to the grate, and the temperature of the waste into a moisture evaporation model constructed in advance to derive the amount of moisture evaporated from the waste, and derive the ratio of moisture contained in the waste present on the grate based on the derived amount of moisture evaporation, thereby estimating the amount of moisture contained in the waste. Effect of the Invention

[0020] According to the information processing device, information processing method, and program of the present invention, it is possible to more accurately grasp the state of waste on the grate based on thermal imaging data captured inside a waste incinerator and acquired process data. [Brief description of the drawings]

[0021] [Figure 1] FIG. 1 is an overall configuration diagram showing a schematic diagram of a waste incineration facility to which a waste state estimating device according to an embodiment of the present invention is applied. [Diagram 2] FIG. 2 is a side view showing waste, a portion where the waste is fed onto a fire grate, and an imaging section in an incinerator according to an embodiment of the present invention. [Diagram 3] FIG. 3 is a block diagram showing the configuration of a combustion control device according to one embodiment of the present invention. [Figure 4] FIG. 4 is a block diagram showing the configuration of a waste state estimating device in a management system according to an embodiment of the present invention. [Diagram 5] FIG. 5 is a diagram showing an example of transmission image data of waste being burned, captured by the imaging section according to one embodiment of the present invention. [Figure 6] FIG. 6 is a diagram showing an example in which a longitudinal section of waste is set on boundary image data in which a boundary line is set on transmission image data captured by the imaging section according to an embodiment of the present invention. [Figure 7] FIG. 7 is a flow chart illustrating a waste treatment method according to one embodiment of the present invention. [Figure 8] FIG. 8 is a flow chart showing details of the calculation step of the waste reaction model in step ST4 of FIG. 7 in the waste treatment method according to one embodiment of the present invention. [Figure 9] FIG. 9 is a diagram for explaining the division areas and settings of waste on a grate in a waste incinerator according to an embodiment of the present invention. [Figure 10] FIG. 10 is a graph showing derived values ​​of waste condition for each divided area on the grate in a waste incinerator according to one embodiment of the present invention. [Figure 11] FIG. 11 is a graph showing the derived values ​​of the amount of water evaporation from the waste state for each divided area on the grate in a waste incinerator according to one embodiment of the present invention. [Figure 12]FIG. 12 is a graph showing derived devolatilization rates for waste conditions for each of the grate segments in a waste incinerator according to one embodiment of the present invention. [Figure 13] FIG. 13 is a graph showing the total amount of waste on the grate, the amount of waste dropped onto the grate, and the state of the waste in each region in a waste incinerator according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In all the drawings of the embodiment, the same or corresponding parts are denoted by the same reference numerals. Furthermore, the present invention is not limited to the embodiment described below.

[0023] First, in describing the embodiments of the present invention, in order to deepen understanding of the present invention, the inventor will explain the intensive study conducted by the present inventor to solve the above-mentioned problems. First, the inventor extracted the problems in the above-mentioned conventional technology when studying the state of waste. That is, according to the study by the present inventor, the technology described in Patent Document 1 has a problem that, even if the amount of waste can be estimated, information on the state of the waste cannot be obtained. Furthermore, the technology described in Patent Document 2 has a problem that there is no means for directly measuring the amount of retained waste, and although the amount of retained waste can be derived by calculation, there is a problem that the accuracy of the derived value of the retained amount is likely to be insufficient. Furthermore, the technology described in Patent Document 3 has a problem that, even if the amount of waste can be estimated, no information on the state of the waste cannot be obtained.

[0024] Therefore, the inventors of the present invention have conducted extensive research and have come up with the idea of ​​deriving various conditions related to the waste inside the incinerator (hereinafter collectively referred to as "conditions of the waste") using thermal imaging data obtained by capturing images of the inside of the incinerator and process data related to the incinerator. Specifically, the inventors have devised a method for solving the problems in the prior art described above by using the following configuration.

[0025] That is, first, a theoretical model is constructed including the supply of waste on the grate in the incinerator, the movement of the waste on the grate, the evaporation of moisture from the waste, the thermal decomposition of the waste, and the combustion of the pyrolysis products generated by the thermal decomposition. Second, thermal image data of the grate in the incinerator is acquired, and the amount of waste supplied to the grate, the temperature of the waste, and the amount of waste are derived to acquire process data on the grate. Third, the temperature of each part in the incinerator, the flow rate of gas, and the heat absorption of the steam boiler are measured to acquire process data of the incinerator. Fourth, a state space model is constructed using the constructed waste reaction model, the acquired process data on the grate, and the process data inside the incinerator, and a data assimilation technique using a Kalman filter is used to execute an estimation process of the state of the waste, estimating the amount of waste, the moisture ratio of the waste, the combustible ratio of the waste, and the heat value of the waste at each of the multiple divided positions on the grate. Furthermore, fifthly, the estimation process of the state of the waste is executed immediately (in real time), and the combustion in the incinerator is controlled based on the output estimated value.

[0026] The present inventor also conducted a separate study and came up with a method for deriving the amount of waste on the grate of an incinerator based on thermal imaging data. That is, according to the knowledge of the present inventor, in a stoker-type incinerator (hereinafter referred to as a grate-type incinerator), the waste that is dropped from the supply port by a step wall and supplied is burned while being moved by the grate. Therefore, the cross-sectional shape of the waste deposited on the grate can be approximated by a simple closed curve (also called a single closed curve or a Jordan curve) having vertices at the intersection of the step wall and the grate, the top point of the waste, and the combustion point of the waste on the grate, respectively, that is, a triangle, a right-angled triangle, or a closed curve connecting three vertices. In this specification, various triangles and simple closed curves connecting three vertices are called three-vertex closed curves. On the other hand, the distribution shape of the waste can be accurately estimated by detecting the boundary line of the outer edge of the waste deposited on the grate by image signal processing such as deep learning and applying a model of the closed curve. As a result, the present inventor has devised a method for deriving the amount of waste by detecting the boundary line of the waste on the grate. The embodiment described below has been devised based on the inventor's extensive studies.

[0027] (Waste treatment system) Fig. 1 is an overall configuration diagram showing a waste incineration facility as an incineration facility to which a waste state estimation device according to an embodiment of the present invention is applied. As shown in Fig. 1, a waste treatment system 1 according to an embodiment has a combustion control device 30 and a waste state estimation device 40 that can communicate with each other via a network 2. The combustion control device 30 is configured to be able to control a waste incinerator 100 as a predetermined facility.

[0028] The network 2 is composed of an Internet line network, a mobile phone line network, etc. The network 2 is, for example, a public communication network such as the Internet, and may include other communication networks such as a WAN (Wide Area Network), a telephone communication network such as a mobile phone, and a wireless communication network such as Wi-Fi. The data transmitted and received in the communication between the combustion control device 30 and the waste state estimation device 40 may include an operation management index that is important for the operation of the waste incinerator 100. In this case, in consideration of the security of the transmitted and received data, the communication line between the combustion control device 30 and the waste state estimation device 40 can be a dedicated line or a VPN line. The combustion control device 30 and the waste state estimation device 40 may be configured as an integrated unit, and the combustion control device 30 and the waste state estimation device 40 may be installed in the same facility as the waste incinerator 100 or in a different facility. When the waste incinerator 100, the combustion control device 30, and the waste state estimation device 40 are installed in different facilities, various information and various data are communicated via the network 2.

[0029] (Waste incinerator) 1, a waste incinerator 100, such as a grate-type garbage incinerator, includes a furnace 101 in which waste material is burned, a waste inlet 102 into which the waste material is fed, and a boiler 109. The boiler 109 includes a heat exchanger 109a and a steam drum 109b disposed downstream of a furnace outlet 107 of the furnace 101.

[0030] Waste fed through the waste inlet 102 is transported to the grate 104 by a waste feeder 103. The grate 104 moves back and forth to agitate and move the waste. The waste on the grate 104 is burned while being dried by blowing in combustion air, which is a combustion gas supplied by a combustion air blower 106 into a wind box below the grate 104, to generate exhaust gas and ash. The generated ash falls through an ash drop port 105 (see FIG. 9) and is discharged outside the furnace 101.

[0031] The total amount of combustion air supplied to the inside of the furnace 101 from under the grate 104 is adjusted by the combustion air damper 114 provided immediately adjacent to the combustion air blower 106. The flow rate of the combustion air supplied to each wind box is adjusted by the under-grate combustion air dampers 114a, 114b, 114c, and 114d provided on the piping that supplies the combustion air to each wind box. That is, the ratio of the flow rate of the combustion air supplied to each wind box is adjusted by the under-grate combustion air dampers 114a to 114d. In FIG. 1, the area under the grate 104 is divided into four wind boxes along the waste transport direction, and the combustion air is supplied through each wind box, but the number of under-grate combustion air dampers 114a to 114d and wind boxes is not necessarily limited to four, and can be changed appropriately depending on the size and purpose of the waste incinerator.

[0032] Furthermore, for example, a combustion air temperature damper 126a connected in series and a combustion air temperature damper 126b connected in parallel are connected to the combustion air damper 114. The temperature of the combustion air supplied from below the fire grate 104 to the inside of the furnace 101 is adjusted by these combustion air temperature dampers 126a and 126b.

[0033] Cooling air is blown into the furnace 101 by a cooling air blower 111 from a cooling air blowing port 110 provided on the furnace wall or ceiling of the furnace 101. By blowing the cooling air into the furnace 101, unburned components in the combustion gas are further burned and the temperature of the furnace wall is prevented from rising excessively. The flow rate of the cooling air supplied into the furnace 101 from the cooling air blowing port 110 is adjusted by a cooling air damper 115 provided immediately adjacent to the cooling air blower 111. An exhaust gas recirculation air damper 128 is provided on the ceiling of the furnace 101, for adjusting the flow rate of the exhaust gas and the combustion air when the exhaust gas from the outlet of the exhaust gas treatment device (not shown) is mixed with the combustion air by a recirculation blower 127 and recirculated into the furnace 101. The exhaust gas recirculation air damper 128 enables low-air ratio combustion to suppress the generation of NOx during combustion.

[0034] Along the waste transport direction in the grate 104, combustible gas generated in the waste drying process and main combustion process on the upstream side and combustion exhaust gas generated in the post-combustion process on the downstream side join in a gas mixing section provided on the furnace outlet 107 side of the furnace 101. The combustible gas and combustion exhaust gas that join in the gas mixing section are stirred and mixed again, and then secondary combustion is performed by supplying secondary combustion air. The boiler 109 is installed downstream in the waste transport direction from the section where secondary combustion is performed (hereinafter, secondary combustion section). The combustion gas that has undergone secondary combustion has its thermal energy recovered by a heat exchanger 109a of the boiler 109, and is then exhausted to the outside from a chimney 108.

[0035] In the furnace 101, an intermediate ceiling 116 is provided at an upper position along the height direction of the furnace 101. The intermediate ceiling 116 separates the gas flowing in the furnace 101 into gas containing a large amount of combustible gas generated in the waste drying process and the main combustion process on the upstream side, and combustion exhaust gas generated in the post-combustion process on the downstream side, and discharges the separated gases. Specifically, the combustion exhaust gas flows through a flue (main flue) below the intermediate ceiling 116, while the gas containing a large amount of combustible gas flows through a flue (sub-flue) above the intermediate ceiling 116. The combustion exhaust gas and the gas containing a large amount of combustible gas join together in the gas mixing section, which further promotes the stirring and mixing of the gas in the gas mixing section. This makes the combustion in the secondary combustion section more stable, suppresses the generation of dioxins in the combustion process, and suppresses the generation of unburned waste. The furnace 101 may be configured without the intermediate ceiling 116.

[0036] Thermometers serving as sensors for measuring the gas temperature in the furnace 101 are provided at multiple positions in the furnace 101. Specifically, a combustion chamber gas thermometer 117 is provided at an intermediate position between the fire grate 104 and the cooling air inlet 110 along the height direction of the furnace 101.

[0037] Along the height direction of the furnace 101, a main flue gas thermometer 118 is provided at a position below the furnace outlet 107. Along the height direction of the furnace 101, a furnace outlet lower gas thermometer 119 is provided at a lower position of the furnace outlet 107. Along the height direction of the furnace 101, a furnace outlet middle gas thermometer 120 is provided at a middle position of the furnace outlet 107. Along the height direction of the furnace 101, a furnace outlet gas thermometer 121 for measuring a combustion control temperature is provided at a downstream position of the furnace outlet 107. The temperature measurement values ​​measured by the combustion chamber gas thermometer 117, the main flue gas thermometer 118, the furnace outlet lower gas thermometer 119, the furnace outlet middle gas thermometer 120, and the furnace outlet gas thermometer 121 are stored in the memory unit 34 (see FIG. 3) of the combustion control device 30 as combustion process measurement values. The data of the temperature measurement values ​​stored in the memory unit 34 may be transmitted from the combustion control device 30 to the waste state estimation device 40 as measurement data.

[0038] The boiler 109 is provided with a boiler outlet oxygen concentration meter 122 for measuring the concentration of oxygen (O2) in the exhaust gas on the outlet side. x ) is provided. An exhaust gas flowmeter 124 for measuring the amount of exhaust gas is provided in the pipe connecting the outlet of the boiler 109 and the chimney 108. The measurement values ​​of the gas concentration and flow rate measured by the boiler outlet oxygen concentration meter 122, the gas concentration meter 123, and the exhaust gas flowmeter 124 are stored in the memory unit 34 of the combustion control device 30 as combustion process measurement values. The combustion process measurement values ​​are also simply referred to as measurement values.

[0039] An imaging unit 125 is provided downstream in the waste transport direction in the furnace 101. The imaging unit 125 is configured to include a flame transmission camera, for example, an infrared camera, and an image processing unit that processes the captured image data. The imaging unit 125 captures an image of the burning state of the waste on the grate 104, and stores the transmitted image data, which is thermal image data generated from the captured thermal image information, in the memory unit 34 of the combustion control device 30. Furthermore, the imaging unit 125 may capture an image of the burning state of the waste on the grate 104, and store the captured transmitted image data in, for example, the captured image database 421 (see FIG. 4) in the memory unit 42 of the waste state estimation device 40.

[0040] FIG. 2 is a side view showing the installation state of the imaging unit 125. In this embodiment, the imaging unit 125 is installed at a position that is approximately directly opposite the waste supply unit 112 and the step wall 113, as shown in FIG. 2. The installation of the imaging unit 125 is not limited to a position that is approximately directly opposite the waste supply unit 112 and the step wall 113. The installation position of the imaging unit 125 can be various positions as long as it can capture an image of at least the boundary portion between the waste on the grate 52 and other objects, here the step wall 113 and the grate 104. The imaging unit 125 may be disposed outside the furnace near a window provided in the furnace wall 101a, or may be disposed inside the furnace 101 with a water-cooling structure. As shown in FIG. 2, the pre-supply waste 51 in the waste 50 falls from the waste supply unit 112 onto the grate 104 at the step wall 113. The waste 50 that has fallen onto the grate 104, that is, waste on the grate 52, is moved forward toward the imaging unit 125 while being stirred by the reciprocating motion that accompanies the back and forth movement of the grate 104.

[0041] (Combustion control device) Fig. 3 is a block diagram showing the configuration of the combustion control device 30. As shown in Fig. 3, the combustion control device 30 includes a calculation control unit 31, an operation amount reference value adjustment unit 32, an operation amount reference value correction unit 33, a storage unit 34, an operation amount adjustment unit 35, and a communication unit 36. Specifically, the calculation control unit 31, the operation amount reference value adjustment unit 32, the operation amount reference value correction unit 33, and the operation amount adjustment unit 35 include a processor such as a central processing unit (CPU), a digital signal processor (DSP), or a field-programmable gate array (FPGA) having hardware, and a main storage unit such as a random access memory (RAM) or a read only memory (ROM) (none of which are shown).

[0042] The storage unit 34 is composed of a storage medium selected from a volatile memory such as a RAM, a non-volatile memory such as a ROM, an erasable programmable ROM (EPROM), a hard disk drive (HDD, Hard Disk Drive), and a removable medium. The removable medium is, for example, a universal serial bus (USB) memory, or a disk recording medium such as a compact disc (CD), a digital versatile disc (DVD), or a Blu-ray (registered trademark) disc (BD). The storage unit 34 may also be composed of a computer-readable recording medium such as an externally mountable memory card.

[0043] The storage unit 34 can store an operating system (OS), various programs, various tables, various databases, and the like for executing the operation of the combustion control device 30. Here, the various programs include an information processing program that realizes processing based on a model such as the learning model or the learned model according to this embodiment. These various programs can also be recorded on a computer-readable recording medium such as a hard disk, a flash memory, a CD-ROM, a DVD-ROM, or a flexible disk and widely distributed. The storage unit 34 has a set value database 341 that stores the incineration amount set value and the evaporation amount set value input from the outside as information, and a measurement value database 342 that stores the process measurement value (also called process data) related to combustion acquired from the waste incinerator 100 as information. The storage unit 34 may be provided in another server that can communicate via various networks.

[0044] The combustion control device 30 controls the combustion air volume, the cooling air volume, the waste feeder feed rate, and the grate feed rate as the manipulated variables of the respective manipulated variables based on a predetermined manipulated variable reference value setting relational expression. The combustion control device 30 also controls the waste feeder feed rate and the grate feed rate to stop or operate. The manipulated variable reference value setting relational expression is a relational expression between the waste incineration volume set value or the waste quality set value and the manipulated variable reference value (target value of the manipulated variable), and includes a control parameter as a correction coefficient. The control parameter is adjusted by the manipulated variable reference value adjustment unit 32 so as to match the waste incineration volume set value and the waste quality set value. When at least one of the waste incineration volume set value and the waste quality set value is changed, the adjusted control parameter is changed by the manipulated variable reference value adjustment unit 32 in accordance with the changed set value. The preset manipulated variable reference value is corrected by changing the control parameter.

[0045] The calculation control unit 31 executes various controls and calculations. Specifically, for example, the calculation control unit 31 can derive the amount of evaporation per hour caused by the combustion of waste in the waste incinerator 100 during a predetermined period, for example, one day (24 hours), as the evaporation amount setting value. In addition, when the calculation control unit 31 functions as, for example, a waste calculation unit, it can calculate the waste quality (lower heating value of waste) according to the waste incineration amount setting value. The operation amount reference value adjustment unit 32 can adjust the operation amount reference value by adjusting the control parameters included in the operation amount reference value setting relational expression. The operation amount reference value correction unit 33 can correct the operation amount reference value adjusted by the operation amount reference value adjustment unit 32 based on a predetermined control algorithm (PID control, fuzzy calculation, etc.). Note that data referred to by the calculation control unit 31, the operation amount reference value adjustment unit 32, and the operation amount reference value correction unit 33 are readably stored in the storage unit 34. The memory unit 34 stores predetermined operation quantity reference value setting relational expressions and control algorithms, daily evaporation amount setting values ​​and incineration amount setting values ​​transmitted from the waste state estimation device 40, and combustion process measurement values ​​transmitted from the waste incinerator 100 and acquired as combustion state quantities within the furnace 101.

[0046] The manipulated variable adjustment unit 35 adjusts the manipulated variable of each manipulated variable so as to follow the manipulated variable reference value. Specifically, the manipulated variable adjustment unit 35 has a combustion air amount adjustment unit 351, an air amount ratio adjustment unit 352, a cooling air amount adjustment unit 353, a waste feeder feed rate adjustment unit 354, a grate feed rate adjustment unit 355, a combustion air temperature adjustment unit 356, and an exhaust gas recirculation air flow rate adjustment unit 357.

[0047] The combustion air amount adjusting unit 351 adjusts the amount of operation so that the amount of combustion air follows the operation amount reference value corrected by the operation amount reference value correcting unit 33 (hereinafter, the corrected operation amount reference value). The air amount ratio adjusting unit 352 controls each of the under-grate combustion air dampers 114a to 114d to adjust the mutual ratio of the flow rates in each wind box. The cooling air amount adjusting unit 353 adjusts the amount of operation so that the amount of cooling air follows the corrected operation amount reference value. Here, the combustion air amount and the cooling air amount are adjusted by controlling the opening degree of each of the combustion air damper 114, the under-grate combustion air dampers 114a to 114d, and the cooling air damper 115. The waste feeder feed rate adjusting unit 354 adjusts the amount of operation so that the waste feeder feed rate follows the corrected operation amount reference value. The grate feed rate adjusting unit 355 adjusts the amount of operation so that the grate feed rate follows the corrected operation amount reference value. The combustion air temperature adjusting unit 356 controls the combustion air temperature dampers 126a and 126b so that the temperature of the combustion air follows the corrected manipulated variable reference value. The exhaust gas recirculation air flow rate adjusting unit 357 controls the exhaust gas recirculation air damper 128 so that the flow rates of the exhaust gas and air to be recirculated follow the corrected manipulated variable reference value. When the manipulated variable reference value correcting unit 33 has not corrected the manipulated variable reference value, the manipulated variable adjusting unit 35 adjusts each manipulated variable based on the uncorrected manipulated variable reference value.

[0048] The communication unit 36 ​​is, for example, a LAN (Local Area Network) interface board or a wireless communication circuit for wireless communication. The LAN interface board or the wireless communication circuit is connected to a network 2 such as the Internet, which is a public communication network. The communication unit 36 ​​is connected to the network 2 and is configured to be able to communicate with the waste state estimation device 40, other devices, and servers.

[0049] (Waste status estimation device) FIG. 4 is a block diagram showing a schematic configuration of the waste state estimation device 40. As shown in FIG. 4, the waste state estimation device 40, which is a device for estimating the state of waste, has a general computer configuration capable of communicating via a network 2. The waste state estimation device 40 includes a control unit 41, a storage unit 42, a communication unit 43, and an input / output unit 44. The control unit 41, the storage unit 42, and the communication unit 43 are physically and functionally similar to the calculation control unit 31, the storage unit 34, and the communication unit 36 ​​described above. The waste state estimation device 40 functions as an information processing device that derives the state of the waste 50. The waste state estimation device 40 further functions as a waste 50 volume estimation device that derives or estimates the volume of the waste 50, and a combustion point position measurement device that can measure the position of the combustion point (also called the burnout point).

[0050] First, the input / output unit 44 as an output means displays images of the waste 50 in the furnace 101 on a display monitor consisting of, for example, an organic EL panel or a liquid crystal display panel, displays characters and figures on the screen of a touch panel display, and outputs voice from a speaker, under the control of the control unit 41. The input / output unit 44 as an input means is configured using a user interface such as a keyboard, input buttons, levers, a touch panel for manual input superimposed on a display such as a liquid crystal display, or a microphone for voice recognition. The input / output unit 44 is configured so that a user can input predetermined information to the control unit 41 by operating the input / output unit 44. That is, the input / output unit 44 is configured, for example, by a touch panel keyboard incorporated inside a keyboard or display unit to detect touch operations on the display panel, or a voice input device that enables calls between the outside and the like. The input / output unit 44 may be configured as an output unit and an input unit separately.

[0051] The control unit 41 can realize a function that meets a predetermined purpose by loading a program stored in the storage unit 42 into a working area of ​​the main storage unit and executing the program, and controlling each component unit through the execution of the program. In this embodiment, the control unit 41 executes the functions of the boundary generation unit 411, the combustion calculation unit 412, and the learning unit 413 by executing the program stored in the storage unit 42. Specifically, for example, the control unit 41 executes the function of the boundary generation unit 411 by reading a boundary discrimination learning model 423, which is a program, from the storage unit 42. In addition, the control unit 41 executes the function of the combustion calculation unit 412 by reading a volume calculation program from the storage unit 42. Details of the functions of the boundary generation unit 411, the combustion calculation unit 412, and the learning unit 413 will be described later.

[0052] The storage unit 42 has the same functional and physical configuration as the above-mentioned storage unit 34, and is composed of a storage medium selected from a volatile memory such as a RAM, a non-volatile memory such as a ROM, an EPROM, a HDD, and a removable medium. The removable medium is, for example, a USB memory or a disk recording medium such as a CD, a DVD, or a BD. The storage unit 42 may also be composed of a computer-readable recording medium such as an externally mountable memory card.

[0053] The storage unit 42 can store an OS, various programs, various tables, various databases, and the like for executing the operation of the waste state estimation device 40. Here, the various programs include an information processing program for realizing control using the learning model or the learned model according to this embodiment. The storage unit 42 may be provided in another server that can communicate via various networks, or may be provided in the combustion control device 30.

[0054] Specifically, the storage unit 42 stores a captured image database 421, a combustion information database 422, a boundary discrimination learning model 423, and a waste reaction model 424. The database (DB) described in this embodiment is constructed by a program of a database management system (DBMS) executed by the above-mentioned processor managing the data stored in the storage unit 42. The captured image database 421 and the combustion information database 422 are, for example, relational databases (RDB). The databases stored in the storage unit 42 are not limited to the above databases.

[0055] The captured image database 421 stores searchable captured image data of the inside of the furnace 101, such as transmission image data captured by the imaging unit 125 and boundary image data generated by the boundary generation unit 411. The combustion information database 422 stores searchable various data including various process data that are sensor values ​​measured by various sensors in the waste treatment system 1, for example, combustion information including process measurement values ​​related to the combustion of the waste 50 on the grate 104. The captured image database 421 and the combustion information database 422 can be configured from big data or the like. In this case, the captured image database 421 and the combustion information database 422 can also be stored in a storage unit of another server accessible via the network 2.

[0056] The boundary discrimination learning model 423 is an updateable model including at least one learning model. When the learning model is not updated, it is stored in the storage unit 42 as a learned model. The boundary discrimination learning model 423 may include a combustion state learning model that is a learning model capable of executing a process of extracting a combustion region based on image data inside the furnace 101, such as transmission image data and boundary image data. In addition, instead of the boundary discrimination learning model 423, a rule-based information processing program that executes a predetermined information processing on input data and is created without learning or the like may be used. Furthermore, an automatic judgment processing program that realizes a judgment process using a combustion image learning model that can execute a predetermined judgment from the data of the combustion image of the luminous flame itself captured by the imaging unit 125 may be included. These various programs can be recorded on computer-readable recording media such as hard disks, flash memories, CD-ROMs, DVD-ROMs, and flexible disks and widely distributed.

[0057] The waste reaction model 424 is a model that employs data assimilation technology. The waste reaction model 424 is constructed based on a predetermined relational expression. Note that the following relational expression is merely an example, and is not limited to the following relational expression. In this embodiment, the waste reaction model 424 is a model related to the waste 52 on the grate 104. Specifically, the waste reaction model 424 is configured to include at least one model among a relational expression related to the amount of evaporation of moisture in the waste 52 on the grate (hereinafter, moisture evaporation model), a relational expression related to the amount of volatile matter released by pyrolysis (hereinafter, volatile matter release model), and a relational expression related to the amount of combustion of fixed carbon (hereinafter, fixed carbon combustion model).

[0058] (Water evaporation model) The moisture evaporation model according to this embodiment is a relational expression of the amount of moisture evaporated from the waste on the grate 52 per unit time (moisture evaporation amount (kg / s)). From various experiments conducted by the present inventor, it was found that the evaporation of moisture from the waste on the grate 52 is dominated by drying due to heating and drying due to ventilation. In other words, it was found that the evaporation of moisture from the waste on the grate 52 is dominated by the evaporation of moisture caused by radiant heat and the evaporation of moisture caused by the combustion air supplied to the waste on the grate 52 from below the grate 104. Therefore, as the moisture evaporation model according to this embodiment, the amount of moisture evaporated from the waste on the grate 52 per unit time (kg / s) is adopted as the amount of moisture evaporated based on the sum of the amount of moisture evaporated by radiant heat and the amount of moisture evaporated by the combustion air ventilation, as shown in the following formula (1). Amount of water evaporated from waste per unit time (kg / s) = (amount of water evaporation due to radiant heat) + (amount of water evaporation due to ventilation of combustion air)……(1)

[0059] (Amount of water evaporated by thermal radiation per unit time) The amount of water evaporated per unit time (kg / s) due to radiant heat from the waste on the grate 52 can be expressed by the following formula (2). Note that if the temperature of the waste reaches the water evaporation temperature and the amount of heat received exceeds the amount of heat required to evaporate the water contained in the waste on the grate 52, the amount of water evaporated will be equal to the amount of latent heat equivalent to the amount of direct heat. (Amount of water evaporated by radiant heat per unit time) = q / Q ev (kg / s) = S φ ε σ T f 4 / Q ev …(2) Where, q (kW): heat flow rate of waste received, Q ev (J / kg): latent heat of vaporization of water, S(m 2 ): Representative area, φ (dimensionless): View factor, ε (dimensionless): Emissivity, σ(W / (m 2 ·K 4 ))=5.67×10 -8 : Stefan-Boltzmann constant, T f(K): Representative flame temperature.

[0060] (Amount of water evaporated by ventilation of combustion air per unit time) The amount of water evaporation (kg / s) per unit time caused by the passage of combustion air through the waste 52 on the grate can be expressed by the following formula (3). (Amount of water evaporated by ventilation of combustion air per unit time) =G m ·(H w -H)·(1-e -ζ )(kg / s)…(3) (Note that ζ=hG a Z S a / (G m C H )) Here, G m (kg / s): Air flow rate, H w (kg / kg′(water vapor amount / dry air)): Saturation absolute humidity of combustion air, H(kg / kg′): Absolute humidity of combustion air, hGa(W / (m 3 s) ): heat transfer capacity coefficient, Z(m): height of waste layer, S a (m 2 ): cross-sectional area of ​​the waste layer, C H (J / (kg K)): Specific heat capacity.

[0061] From the above, the relational expression of the amount of water evaporated from waste per unit time (kg / s) according to this embodiment, that is, the water evaporation model, can employ the following relational expression (4). Amount of water evaporated from waste per unit time (kg / s) = (amount of water evaporation due to radiant heat) + (amount of water evaporation due to ventilation of combustion air) = S φ ε σ T f 4 / Q ev +G m ·(H w -H)·(1-e -ζ )……(4)

[0062] (Volatile release model) The volatile matter release model according to this embodiment is a relational expression of the amount of volatile matter released per unit time (kg / s) due to pyrolysis that starts at the stage where evaporation of moisture in the waste on the grate 52 is almost completed. From various experiments conducted by the present inventor, it was found that the empirical formula (5) below holds for the amount of volatile matter released from the waste on the grate 52. Therefore, as the volatile matter release model according to this embodiment, the relational expression of the amount of volatile matter released per unit time (kg / s) from the waste on the grate 52 shown in the following formula (5) is adopted. In this specification, "volatile matter" means a combustible gas generated by heating the waste (garbage), and includes, for example, carbon monoxide (CO) and methane (CH4) as components. (Amount of volatile matter released from waste per unit time) = A T n ·exp(-E / (R·T))·W……(5) Here, A(s -1 ): frequency factor, E(J / kmol): activation energy, T(K): temperature of the waste 52 on the grate, R(kJ / (mol·K)): general gas constant, W(kg): amount of volatile matter remaining in the waste 52 on the grate. Furthermore, according to an experiment conducted by the present inventor, in a given furnace 101, A( / s)=3.96×10 2 ( / s), n = 0, E (J / kmol) = 6.31 × 10 7 (J / kmol). That is, when the above-mentioned formula (5) is adopted, it is possible to change the values ​​of the frequency factor A, the activation energy E, and the influence degree (multiplier n) of the temperature of the waste on the grate 52 in accordance with the waste incinerator 100 in each waste treatment system 1. Furthermore, since the flame is generated mainly by pyrolysis gas released by the pyrolysis of the waste on the grate 52, it is possible to derive the state of the flame in the furnace 101 based on the amount of volatile matter released obtained by formula (5).

[0063] (Fixed carbon combustion model) The fixed carbon combustion model according to this embodiment is a relational expression for the amount of fixed carbon burned per unit time (kg / s) contained in the waste on the grate 52. Through various experiments conducted by the present inventor, it was found that the empirical expression (6) below holds for the amount of fixed carbon burned per unit time contained in the waste on the grate 52. Therefore, as the fixed carbon combustion model according to this embodiment, the relational expression for the amount of fixed carbon burned per unit time (kg / s) contained in the waste on the grate 52 shown in the following expression (6) is adopted. In this specification, "fixed carbon" refers to a combustible solid generated by heating waste (garbage), and includes, for example, carbon (C) as a component. (Amount of fixed carbon burned from waste per unit time) =A P O2 n exp(-E / (R T)) W c ……(6) Here, A(s -1 ): frequency factor, P O2 (atm): partial pressure of oxygen, E (kJ / kmol): activation energy, T (K): temperature of waste 52 on the grate, R (kJ / (mol K)): universal gas constant, W c (kg): The mass of carbon remaining in the waste 52 on the grate. Furthermore, according to an experiment conducted by the present inventor, in a given furnace 101, A( / s)=1.36×10 6 ( / s), n = 0.68, and E (J / kmol) = 130 (kJ / kmol). In other words, when the above formula (5) is adopted, the frequency factor A, activation energy E, oxygen partial pressure P O2 It is possible to change the value of the influence (multiplier n).

[0064] In this embodiment, when the waste reaction model 424 is composed of, for example, only a moisture evaporation model, it is possible to derive the amount of moisture evaporated from the waste on the grate 52 by the waste reaction model 424. This makes it possible to construct a state space model relating to the waste state, and to estimate the amount of moisture contained in the waste on the grate 52. By being able to estimate the amount of moisture contained in the waste on the grate 52, it becomes possible to adjust the amount of air supplied to the waste drying process on the grate 104, particularly on the upstream side.

[0065] In addition, in this embodiment, when the waste reaction model 424 is composed of only a volatile matter release model, for example, the amount of volatile matter released can be derived by the waste reaction model 424. In this case, the waste 52 on the grate from which the moisture has evaporated is thermally decomposed, volatile matter is released, and the waste 52 is burned as a flame. By deriving the amount of volatile matter released, a state space model regarding the waste state can be constructed, and the amount of volatile matter contained in the waste 52 on the grate can be estimated. By being able to estimate the mass of volatile matter contained in the waste 52 on the grate, it is possible to adjust the amount of combustible gas generated in the waste drying process and main combustion process on the upstream side, and the amount of combustion exhaust gas generated in the post-combustion process on the downstream side.

[0066] Furthermore, in this embodiment, when the waste reaction model 424 is composed of, for example, only a fixed carbon combustion model, it is possible to derive the amount of fixed carbon combustion contained in the waste on the grate 52 by the waste reaction model 424. This makes it possible to construct a state space model regarding the state of the waste, and to estimate the mass of fixed carbon contained in the waste on the grate 52. By being able to estimate the mass of fixed carbon contained in the waste on the grate 52, it becomes possible to perform combustion control necessary for ash carbonation on the downstream side.

[0067] (Derivation of ash content) In addition, in this embodiment, when the waste reaction model 424 is composed of a moisture evaporation model, a volatile matter release model, and a fixed carbon combustion model, the amount of moisture evaporation, the amount of volatile matter release, and the amount of fixed carbon combustion can be derived by the waste reaction model 424. This makes it possible to construct a state space model regarding the state of the waste, and to estimate the mass of moisture, volatile matter, and fixed carbon in the waste on the grate 52. If the mass and volume of the waste on the grate 52 can be derived by other methods, the mass of the ash can be derived by subtracting the mass of the moisture, volatile matter, and fixed carbon from the mass of the waste on the grate 52. The ash falls through the ash drop port 105 and is discharged to the outside of the furnace 101. That is, an ash content model can be constructed as a state space model that can derive the mass of ash from the amount of ash that falls from the ash drop port 105, using the waste reaction model 424, a model that derives the mass of the waste on the grate 52, and a state space model that can derive the mass of ash.

[0068] Next, in order to derive the volume and mass of the waste 52 on the grate, it is necessary to perform a boundary identification process to distinguish the waste 50 on the grate 104 from other areas. Therefore, before describing the method for deriving the volume and mass of the waste 52 on the grate, the boundary identification process method will be described below.

[0069] (Boundary discrimination learning model) First, a boundary discrimination learning model 423 stored in the storage unit 42 of the waste state estimation device 40 and a method for generating the same will be described. Fig. 5 is a diagram showing an example of transmission image data of waste being burned, captured by the imaging unit 125 of this embodiment. Fig. 6 is a diagram showing an example of boundary image data in which a boundary line is generated for the transmission image data captured by the imaging unit 125 of this embodiment.

[0070] As shown in FIG. 5, the imaging unit 125 images the waste 51 before being supplied onto the waste supply unit 112 and the grate 104, the step wall 113, the grate 104, the waste 52 on the grate 104, and the furnace wall 101a in the furnace 101 while transmitting the flame, and outputs the images as transmission image data. As shown in FIG. 6, the boundary identification learning model 423 executes a process for generating a boundary line 531 for the boundary between the waste 50 and other objects for the transmission image data captured by the imaging unit 125. In the example shown in FIG. 6, the boundary line 531 is drawn on the boundary between the waste 52 on the grate and the step wall 113, the furnace wall 101a, and the grate 104. By drawing the boundary line 531, the boundary image data can define the outer edge of the waste 52 on the grate that exists on the grate 104.

[0071] The data used for generating the boundary discrimination learning model 423 are the transmission image data captured by the imaging unit 125 and the processed image data (hereinafter, boundary image data) in which the boundary is identified in the transmission image data and the above-mentioned boundary line 531 is drawn. The number of the transmission image data and the boundary image data is preferably, for example, 100 or more. That is, the boundary image data used for generation is image data in which the boundary line 531 is drawn by the worker for each boundary between the waste 50 and the waste supply unit 112, the step wall 113, the furnace wall 101a, and the grate 104 in the transmission image data. As the input / output data set for generating the boundary discrimination learning model 423, the transmission image data is used as the learning input parameter, and the boundary image data is used as the learning output parameter. The learning unit 413 of the control unit 41 generates the boundary discrimination learning model 423 by deep learning using a hierarchical convolutional neural network (hierarchical CNN) such as U-Net, for example, using the above-mentioned learning input parameter and learning output parameter as teacher data. The control unit 41 generates boundary image data from the transparent image data based on the contents learned by the learning unit 413. In addition, the learning unit 413 appropriately updates the boundary discrimination learning model 423 using the input transparent image data and boundary image data obtained by an operator correcting or drawing a boundary.

[0072] In addition, when the boundary identification learning model 423 includes a combustion state learning model, the input / output data set used for generating the combustion state learning model is the input parameter for learning, which is transmitted image data or boundary image data, and the output parameter for learning, which is extracted image data of a predetermined combustion state.

[0073] That is, the learning input parameters of the combustion state learning model are at least one of the transmission image data captured by the imaging unit 125 and the boundary image data generated by the boundary generating unit 411 based on the boundary identification learning model 423. The learning output parameters used for generating the combustion state learning model are extracted image data in which the boundary between the waste on the grate 52 and other areas, and the boundary between the waste on the grate 52 whose combustion temperature is equal to or higher than a predetermined temperature and other areas including the waste on the grate 52 whose combustion temperature is lower than the predetermined temperature are drawn on the transmission image data or the boundary image data by an operator. The imaging unit 125 equipped with a thermal imaging camera or the like can output transmission image data based on the temperature distribution of the waste 50. In this case, the output transmission image data can be output as image data in which the brightness is increased as the temperature is higher and the brightness is decreased as the temperature is lower. This makes it possible to generate extracted image data by extracting the waste on the grate 52 from the transmission image data and extracting a high-temperature area with a temperature equal to or higher than a predetermined temperature in the extracted waste on the grate 52 as a combustion area. In this way, for transmission image data in which the temperature distribution can be grasped from the brightness, extracted image data in which the waste 52 on the grate and the combustion area are extracted may be used as boundary image data.

[0074] The number of each of the transmission image data, boundary image data, and extracted image data used in learning is preferably, for example, 100 or more. The learning unit 413 of the control unit 41 generates a combustion state learning model by machine learning such as deep learning using a neural network, using the above-mentioned learning input parameters and learning output parameters as teacher data. The control unit 41 generates extracted image data from the transmission image data or boundary image data based on the content learned by the learning unit 413. In addition, the learning unit 413 can appropriately update the combustion state learning model using the input transmission image data or boundary image data, and extracted image data obtained by an operator correcting or drawing a boundary.

[0075] (Waste status estimation method) Next, a waste state estimation method executed by the waste state estimation device 40 of the waste treatment system 1 configured as above will be described. In the waste state estimation method, the volume and mass of the waste 52 on the grate can be derived. FIGS. 7 and 8 are flow charts for explaining the waste state estimation method according to this embodiment. In the following description, FIGS. 5 and 6 will also be referred to as appropriate. In this embodiment, step ST1 is processing performed by the imaging unit 125 in the furnace 101, and steps ST2 to ST5 and ST11 to ST15 are processing performed by the waste state estimation device 40.

[0076] As shown in FIG. 7, in step ST1, the imaging unit 125 images the inside of the furnace 101. The imaging unit 125 images the situation inside the furnace 101 within the field of view as an image through which a flame is transmitted. Specifically, as shown in FIG. 5, the imaging unit 125 images the pre-supply waste 51, the step wall 113, the waste on the grate 52, the grate 104, and the furnace wall 101a in the waste supply unit 112 as a state in which a luminous flame is transmitted. Note that it is not necessary to image the pre-supply waste 51. The imaging unit 125 transmits the captured transmission image data to the control unit 41 through the input / output unit 44 of the waste state estimation device 40. The control unit 41 stores the received transmission image data in the captured image database 421 of the storage unit 42.

[0077] As shown in FIG. 6, the imaging unit 125 has a measurement field of view that extends, for example, in the vertical direction (height direction: z direction) of the furnace 101, the left-right direction (furnace width direction: x direction), and the front-rear direction (transport direction: y direction) on the grate 104. In this embodiment, the field of view of the imaging unit 125 includes at least the waste supply unit 112, the step wall 113, the grate 104, and the furnace wall 101a. The furnace wall 101a included in the field of view of the imaging unit 125 restricts the outward movement, i.e., the spread, of the waste 50 in the left-right direction. Note that the field of view of the imaging unit 125 only needs to have a field of view that can image the boundary portion between the waste 52 on the grate present on the grate 104 and the furnace wall 101a, the grate 104, and the step wall 113. In addition, it is preferable that the imaging unit 125 can image the waste 50 transported to the waste supply unit 112. This allows the waste 50 falling at the position of the step wall 113 to be imaged.

[0078] The combustion calculation unit 412 of the waste state estimation device 40 sets the coordinates of the transport direction (y direction) of the grate 104 with respect to the position x in the left-right direction (x direction) of the lower end of the step wall 113, i.e., the intersection of the step wall 113 and the grate 104. That is, in the two-dimensional screen of the captured image data, the coordinates (x, y) are set with respect to the upper surface of the grate 104. Here, the x direction and the y direction as the predetermined axes are usually perpendicular to each other, but are not necessarily limited to being perpendicular. In addition, the z direction is set in the up-down direction (height direction) of the furnace 101 with respect to the plane set by the x direction and the y direction. Here, the z direction and the y direction are usually perpendicular to each other, but are not necessarily limited to being perpendicular. Similarly, the z direction and the x direction are usually perpendicular to each other, but are not necessarily limited to being perpendicular. With the above settings, three-dimensional coordinates (x, y, z) can be set with respect to the two-dimensional screen of the captured image data. This allows the combustion calculation unit 412 to determine the pile height of the waste 50 near the step wall 113 on a two-dimensional screen of the captured image data using a z-coordinate corresponding to the x-coordinate, and also to determine the downstream end along the transport direction on the grate 104 using a y-coordinate corresponding to the x-coordinate.

[0079] 7 and proceeds to step ST2, where the boundary generation unit 411 of the waste state estimation device 40 reads the boundary discrimination learning model 423 and determines the boundaries between the waste 50 and the waste supply unit 112, the step wall 113, the furnace wall 101a, and the grate 104 based on the transmission image data (see FIG. 5) acquired from the imaging unit 125. The boundary generation unit 411 may also use a rule-based image discrimination algorithm to mutually discriminate between the waste 50, the waste supply unit 112, the step wall 113, the furnace wall 101a, and the grate 104 and determine the boundaries therebetween.

[0080] Next, the boundary generation unit 411 draws a boundary line 531 for the boundary between the waste 50 and other objects, specifically, for each boundary between the waste 50 and the waste supply unit 112, the step wall 113, the furnace wall 101a, and the grate 104, in the transmission image data. As a result, as shown in FIG. 6, for example, the boundary generation unit 411 draws a boundary line 531 for the boundary between the step wall 113, the grate 104, and the furnace wall 101a and the waste 52 on the grate in the transmission image data. In other words, the boundary generation unit 411 draws the boundary line 531 so as to surround the outer edge of the waste 52 on the grate. As described above, the boundary generation unit 411 generates boundary image data in which the boundary line 531 is drawn in the transmission image data. The boundary generation unit 411 outputs the generated boundary image data to the combustion calculation unit 412.

[0081] Next, the process proceeds to step ST3, and the control unit 41 of the waste state estimation device 40 derives the volume of the waste 52 on the grate from the partial volume. That is, first, the combustion calculation unit 412 calculates the height of the layer of the waste 52 on the grate (hereinafter, the waste layer height z). Specifically, the combustion calculation unit 412 of the waste state estimation device 40 calculates the waste layer height z based on the boundary portion between the step wall 113 and the waste 52 on the grate on the boundary line 531. Here, the boundary portion between the step wall 113 and the waste 52 on the grate on the boundary line 531 is uneven. The combustion calculation unit 412 derives the height coordinate z0 of the boundary line 531 corresponding to an arbitrary position coordinate x0 in the x direction along the intersection portion between the grate 104 and the step wall 113 that is preset in the boundary image data.

[0082] Next, the combustion calculation unit 412 functions as a position measurement device of the combustion point, and performs position measurement of the combustion point, which is the front position of the waste on the grate 52 along the transport direction on the grate 104. That is, the front boundary line 531a of the boundary line 531 between the waste on the grate 52 and the grate 104 is the specific combustion point of the waste 50. Note that the specific combustion point of the waste 50 is usually uneven. The combustion calculation unit 412 derives the coordinate y0 of the front position of the boundary line 531a corresponding to an arbitrary position coordinate x0 in the x direction along the intersection of the grate 104 and the step wall 113, which is set in advance in the boundary image data. Note that the above-mentioned derivation process of the coordinates (y0, z0) is not limited to the above-mentioned order, and may be performed in parallel, in reverse order, or in any order.

[0083] Thereafter, combustion calculation unit 412 derives three points based on the derived coordinate z0 of the height of boundary line 531 corresponding to the position coordinate x0 in the x direction and the coordinate y0 of the position in front of boundary line 531a. Here, the three points at coordinate z0 of the height of boundary line 531 and coordinate y0 of the position in front of boundary line 531a corresponding to the position coordinate x0 in the x direction will be described.

[0084] That is, the combustion calculation unit 412 sets a predetermined position x0 in the x direction along the intersection of the step wall 113 and the grate 104 in the waste on the grate 52 on the grate 104 in the boundary image data as point A (x0,0,0). The combustion calculation unit 412 also sets a position of the waste on the grate 52 near the step wall 113 corresponding to point A in the boundary image data (the upper end of the boundary line 531) as point B (x0,0,z0). Furthermore, the combustion calculation unit 412 sets a combustion point (a position in front of the boundary line 531a) corresponding to point A in the boundary image data as point C (x0,y0,z0).

[0085] The combustion calculation unit 412 sets a three-vertex closed curve consisting of a simple closed curve connecting points A, B, and C in the boundary image data. The three-vertex closed curve ABC corresponds to a vertical section of the waste 52 on the grate 104. The vertical section, which is a predetermined section, is usually preferably a plane perpendicular to the x direction, but is not limited thereto. Here, for example, a triangle with sides AB, AC, and BC as straight lines is set as the three-vertex closed curve. Note that the angle of the apex angle A is usually 90°, but is not necessarily limited thereto. In addition, the side AC can be set based on the shape of the upper surface of the grate 104, and the side AB can be set based on the shape of the side surface of the step wall 113. In addition, the side BC may be set to a curve that rises upward (a curve that is convex upward) or a curve that is concave downward (a curve that is convex downward).

[0086] Furthermore, the combustion calculation unit 412 derives the area of ​​a three-vertex closed curve ABC, such as a triangle, whose vertices are points A, B, and C. The area S(x) of the three-vertex closed curve ABC changes along the x direction, and can be expressed by the following equation (7). Area of ​​3-vertex closed curve ABC = S(x) …(7)

[0087] The combustion calculation unit 412 performs the above-mentioned derivation of the points A, B, and C and the derivation of the area of ​​the three-vertex closed curve ABC at every predetermined interval Δx along the x direction. The predetermined interval Δx can be set to any width in the boundary image data. When the predetermined interval Δx is set to an interval equal to or less than the width of one pixel constituting the boundary image data, an interpolated image using any interpolation method, for example, a bicubic filter, can be used. In addition, in the boundary image data, which is two-dimensional data, the unit length in the x direction on the front side of the transport direction (y direction) of the grate 104 is larger than the unit length in the x direction of the intersection part of the step wall 113. That is, in the boundary image data, the width in the x direction is displayed so as to be larger along the y direction. In this case, the predetermined interval Δx may be set to one pixel along the x direction at the intersection part of the step wall 113 at the minimum, or may be one pixel along the x direction at the front side of the transport direction of the grate 104. In addition, one pixel in the captured image data or the boundary image data can be obtained by the optical system for capturing the image, and is, for example, about 1.1 cm to 10 cm.

[0088] Next, the combustion calculation unit 412 derives a partial infinitesimal volume ΔV of the waste on the grate 52 based on the area of ​​the three-vertex closed curve derived at a predetermined interval Δx along the x direction. That is, the combustion calculation unit 412 first sets a three-vertex closed curve, such as a right-angled triangle, by the height z0 (point B) of the boundary line 531 corresponding to the height of the waste on the grate 52, which corresponds to the horizontal position x0 (point A), and the position y0 (point C) in front of the boundary line 531a. On the other hand, the combustion calculation unit 412 sets a three-vertex closed curve by the height z1 of the boundary line 531, which corresponds to the horizontal position x1 in the x direction, and the position y1 in front of the boundary line 531a. Here, these three-vertex closed curves may be similar to each other or may have different shapes.

[0089] First, when the three-vertex closed curve ABC is a triangle and the three-vertex closed curve set corresponding to the horizontal position x1 is also a triangle, the partial volume ΔV can be derived by calculating the volume of the triangular pyramid shown in the following formula (8). Note that S(x) is the area of ​​the triangle corresponding to the horizontal position x.

[0090]

number

[0091] Based on equation (8), the volume V of the waste on the grate 52 piled up on the grate 104 can be derived by summing the partial volumes ΔV along the x direction over the entire width of the step wall 113, as shown in the following equation (9). This makes it possible to estimate the volume V of the waste on the grate 52 approximately using equations (8) and (9). V = Σ(total width of step wall 113) ΔV … (9)

[0092] Furthermore, regardless of whether a three-vertex closed curve consisting of horizontal position x0, height z0 corresponding to horizontal position x0, and front position y0 is similar to a three-vertex closed curve consisting of horizontal position x1, height z1 corresponding to horizontal position x1, and front position y1, the partial volume ΔV can generally be derived by the following formula (10). This is the same when three-vertex closed curves set at multiple arbitrary horizontal positions x are similar to each other or not. In addition, in formula (10), S(x) is the area of ​​the three-vertex closed curve corresponding to horizontal position x.

[0093]

number

[0094] Based on equation (10), the volume V of the waste on the grate 52 piled up on the grate 104 can be derived by integrating the partial volume ΔV over the entire width of the step wall 113 along the x direction, as shown in the following equation (11). This makes it possible to estimate the volume V of the waste on the grate 52 by approximation using equations (10) and (11). Note that L is the entire length of the width of the step wall 113. The combustion calculation unit 412 stores the derived estimated value of the volume V of the waste on the grate 52 in the combustion information database 422.

[0095]

number

[0096] Furthermore, by setting a three-vertex closed curve of the height z, which is the upper part of the boundary line 531, and the front position y, which is the lower part of the boundary line, the overall shape of the waste 52 on the grate can be approximated. This makes it possible to accurately estimate the distribution shape of the waste 50 on the grate 104. Data on the distribution shape of the waste 52 on the grate is stored in the combustion information database 422. Therefore, the control unit 41 reads out the derived estimated value of the volume V of the waste 52 on the grate and information on the estimated distribution shape of the waste 52 on the grate from the combustion information database 422 and transmits it to the combustion control device 30. In the combustion control device 30, the waste incinerator 100 can be controlled with high accuracy based on the acquired estimated value of the volume of the waste 52 on the grate and information on the estimated distribution shape. As described above, the combustion calculation unit 412 can estimate an approximate value of the volume V of the waste 52 on the grate.

[0097] (Modification) (First Modification) Next, a modification of the embodiment described above will be described. In a first modification, the three-vertex closed curve ABC may be an obtuse triangle with an apex angle A of the intersection between the step wall 113 and the grate 104, the angle θ being greater than 90°. Even in this case, the estimated value of the volume V of the waste on the grate 52 can be derived as an approximation from the area S(x) of the vertical cross section of the waste on the grate 52 corresponding to the horizontal position x of the step wall 113 by appropriately using the above-mentioned formulas (7) to (11).

[0098] (Second Modification) In the second modification, the three-vertex closed curve ABC may be a simple closed curve with an apex angle A at the intersection of the step wall 113 and the grate 104 of 90° and a side BC that is raised upward. Here, the side BC may be a curve along various upwardly convex functions, such as a curve along a part of an n-th order function (n is an integer of 2 or more) or a trigonometric function. The function along which the side BC is curved may be selected based on the properties of the waste 50. In this case, the estimated value of the volume V of the waste 52 on the grate can be derived as an approximate value from the area S(x) of the vertical cross section of the waste 52 on the grate corresponding to the horizontal position x of the step wall 113 by appropriately using the above-mentioned formulas (7) to (11).

[0099] (Third Modification) In the third modified example, the three-vertex closed curve ABC may be an acute triangle with an apex angle A of less than 90°, which is the intersection of the step wall 113 and the grate 104. Even in this case, the estimated value of the volume V of the waste on the grate 52 can be derived as an approximation from the area S(x) of the vertical cross section of the waste on the grate 52 corresponding to the horizontal position x of the step wall 113 by appropriately using the above-mentioned formulas (7) to (11).

[0100] (Fourth Modification) In the fourth modification, the three-vertex closed curve ABC is a three-vertex closed curve consisting of a simple closed curve with an apex angle A, which is the intersection between the step wall 113 and the grate 104, of 90° and a side BC that is bulging downward. Here, the side BC may be a curve along various downwardly convex functions, such as an exponential function, an inverse proportional function, an n-th order function (n is an integer of 2 or more), or a curve along a part of a trigonometric function. The function along which the side BC is curved may be selected based on the properties of the waste 50. In this case, the estimated value of the volume V of the waste 52 on the grate can be derived as an approximate value from the area S(x) of the vertical cross section of the waste 52 on the grate corresponding to the horizontal position x of the step wall 113 by appropriately using the above-mentioned formulas (7) to (11).

[0101] The above first to fourth modified examples can be combined as appropriate. That is, the angle θ between the side AB and the side AC can be applied to the second and fourth modified examples, and the curved shape of the side BC can be applied to the first and third modified examples.

[0102] In this manner, the volume of the waste 52 on the grate being transported on the grate 104 can be derived. Also, the volume of the waste 50 dropped and supplied from the waste 51 before being fed onto the grate 104 can be derived. In this manner, the mass of each part of the waste 52 on the grate can be derived from the volume of the waste 52 on the grate being transported and the waste 50 supplied onto the grate 104 from the waste 51 before being fed, and the specific gravity of each part calculated according to the surface temperature of the waste 52 on the grate obtained by the thermal imaging data. That is, the combustion calculation unit 412 multiplies the volume of the waste 52 on the grate in each part calculated by the specific gravity that can be estimated according to the observed surface temperature, thereby deriving the mass of the waste 52 on the grate for each part. For example, as described above, the waste 52 on the grate is divided into small parts by the longitudinal section, so that the control unit 41 can derive the individual mass of each divided part of the waste 52 on the grate.

[0103] Next, the process proceeds to step ST4 shown in Fig. 7. In step ST4, the waste reaction model 424 is read and calculations are performed to derive the state of the waste of the waste on the grate 52 in the furnace 101. Fig. 8 is a flow chart showing the details of the calculation step of the waste reaction model in step ST4. Fig. 9 is a diagram for explaining the division and setting of the region of the waste on the grate 52 in the furnace 101 according to this embodiment.

[0104] As shown in FIG. 9, the waste on the grate 52 is divided into a number of N (N is a natural number) regions in the conveying direction (front-back direction: y direction) in the furnace 101. In the example shown in FIG. 9, the waste on the grate 52 is divided into 18 regions along the conveying direction (N=18), but this is not limited to this. In addition, the waste on the grate 52 is set to one region in the left-right direction (furnace width direction: x direction), that is, it is set not to be divided in the left-right direction, but it is also possible to divide it into a plurality of regions as in the case of deriving the volume of the waste on the grate 52 described above. The numbers (i: 1 to N) in FIG. 9 correspond to each divided region (first region, second region, third region, ..., i-th region, ..., N-th region).

[0105] The state of the waste can be defined for each waste on the grate 52 present in each of the i-th regions shown in Fig. 9. Here, the state of the waste is at least one of the content rates of the moisture content contained in the waste on the grate 52, the volatile matter content of the pyrolysis gas that can be released from the waste on the grate 52, and the fixed carbon content contained in the waste on the grate 52. The content rate of ash as a residue after combustion of the waste on the grate 52 may also be included. In addition, it is preferable to adopt the respective content rates of the moisture content, volatile matter content, fixed carbon content, and ash content contained in the waste on the grate 52 as the state of the waste.

[0106] In the state shown in Fig. 9, first, waste is pushed out by a waste supplying device 103 such as a pusher and dropped onto a grate 104 for supply. The waste 52 on the grate is moved by the grate 104. Due to the movement of the grate 104, the waste 52 on the grate moves to the ash discharge side, and the ash is discharged from an ash drop port 105. In addition, combustion air is supplied to the grate 104 from below.

[0107] First, as shown in FIG. 9, for the waste 50 (waste on the grate 52) on the grate 104 in the furnace 101, a number of divided regions are set in advance for calculation, and a number of region numbers are set, and then calculation of the waste reaction model 424 is started.

[0108] As shown in FIG. 8, in step ST11, the combustion calculation unit 412 sets the state of the waste at time (t-1). Specifically, as the state of the waste, the content ratio of the moisture content, the volatile matter content, the fixed carbon content, and the distribution amount, which are the state of the waste, and the waste mass (or volume) are set for the waste 52 on the grate in each of the first to Nth regions. That is, the state and amount of the waste are obtained for each region (first to Nth regions) on the grate 104. When performing the initial calculation process, the initial value of the state of the waste in the first to Nth regions can be set based on a probable value. In addition, the amount of waste in each region (first to Nth regions) on the grate 104 can be derived based on at least one of the thermal imaging data obtained by imaging the inside of the waste incinerator 100 and the process data, which are sensor values ​​measured by various sensors.

[0109] Next, the process proceeds to step ST12, where the combustion calculation unit 412 derives the state of the waste at time t. That is, the combustion calculation unit 412 applies a waste reaction model (moisture evaporation model) to each of the first to Nth regions to derive the amount of moisture evaporation from the waste 52 on the grate. Next, the combustion calculation unit 412 applies a waste reaction model (volatile matter release model) to each of the first to Nth regions where moisture evaporation has been completed to derive the amount of volatile matter release. Furthermore, the combustion calculation unit 412 applies a waste reaction model (fixed carbon combustion model) to each of the first to Nth regions to derive the amount of fixed carbon combustion.

[0110] Next, the process proceeds to step ST13, where the combustion calculation unit 412 derives the movement state of the waste 52 on the grate at time t. That is, the waste 51 before supply is dropped and supplied onto the grate 104 by the waste supply device 103. In this case, the combustion calculation unit 412 adds the mass of the waste 50 at the position where the waste 50 is supplied (for example, the first to third regions). The position and mass where the waste 50 is dropped and supplied can be derived by the combustion calculation unit 412 from the thermal imaging data based on the above-mentioned method for deriving the volume of the waste 50. In addition, the position and mass where the waste 50 is dropped and supplied may be derived by the combustion calculation unit 412 from the process data. Next, as the movement amount of the waste 52 on the grate, a calculation is performed assuming that a part of the waste 52 on the grate in the i-th region (i=1 to N-1) moves to the (i+1)-th region. A part of the waste 52 on the grate present in the N-th region is discharged as ash through the ash drop port 105.

[0111] Next, the process proceeds to step ST14, where the combustion calculation unit 412 adjusts and corrects the state parameters (state variables) of the waste based on the observed values ​​(observed variables) at time t. Here, as an example of the observed values ​​used for the waste reaction and data assimilation technology, the process data may include the temperature and pressure in the furnace 101 and other parts, the gas flow rates of various gases, and the component concentrations of each gas. The process data may further include the blower temperature, pressure, and flow rate of each part, as well as the grate speed v, the speed (pusher speed) of the waste supply device 103, the amount of water vapor evaporated, the amount of waste 50 processed, and the amount of heat generated. The process data is not necessarily limited to the above-mentioned examples.

[0112] Here, in this embodiment, the observed variables can be the amount of waste 52 on the grate in each region (first region to Nth region) on the grate 104, obtained from the thermal imaging data captured by the imaging unit 125, the distribution of surface temperature, and the sensible heat of the combustion gas at the furnace outlet 107 measured by the furnace outlet gas thermometer 121. The amount of waste 52 on the grate includes the concepts of mass and volume, and may mean at least one of mass and volume. Furthermore, the combustion calculation unit 412 can derive the supply amount of waste 52 on the grate to each region on the grate 104. The moving speed of the waste 52 on the grate used here can be derived by the combustion calculation unit 412 from the grate speed v of the grate 104.

[0113] The combustion calculation unit 412 calculates the surface temperature T of the waste on the grate 52 in each of the first to Nth regions based on the state of the flame formed in the furnace 101 due to the release of volatile matter from the waste on the grate 52. s The temperature of the waste 52 on the grate in each of the first to Nth regions can be calculated based on the surface temperature T s and the grate temperature T measurable at the grate 104 g The temperature of the waste 52 on the grate can be calculated, for example, from the following formula (12), but is not limited to the formula (12). Temperature of waste 52 on the grate = (surface temperature T s +Grate temperature T g ) / 2 …(12)

[0114] Specifically, in step ST14, the combustion calculation unit 412 constructs a state space model based on the waste reaction model 424 described above in order to estimate the state of the waste. That is, as state variables of the state of the waste, the mass (weight) and the mixture ratio (proportion) of the moisture content, the volatile content, the fixed carbon content, and the ash content of the waste 52 on the grate in each of the first to Nth regions are adopted. Note that the mass and moisture content of the waste 52 on the grate in each of the first to Nth regions may be adopted as state variables of the state of the waste. Similarly, the mass and volatile content of the waste 52 on the grate in each of the first to Nth regions may be adopted as state variables of the waste state. Furthermore, the mass and fixed carbon content of the waste 52 on the grate in each of the first to Nth regions may be adopted as state variables of the waste state. Note that the ash content is derived as the remainder with respect to the moisture content, volatile content, and fixed carbon content in the state of the waste.

[0115] In this embodiment, as a method for estimating state variables in the constructed state space model, an infinite impulse response filter is adopted that can estimate quantities that change continuously over time, here the position of the waste on the grate 52 and the mass of each component contained therein, from observations with discrete errors. Here, it is preferable to adopt, for example, a Kalman filter as the infinite impulse response filter, and in this embodiment, a UKF (Unscented Kalman Filter) is applied as one of the nonlinear Kalman filters, but other methods may also be applied.

[0116] Specifically, the combustion calculation unit 412 estimates the values ​​of each state variable using data assimilation processing such as a Kalman filter so as to correct errors between the weight of waste, the distribution of volatile matter emission, and the amount of volatile matter emission in each of the first to Nth regions on the grate 104 obtained for the state variables at a certain time t and the respective observed values.

[0117] That is, the combustion calculation unit 412 matches the weight of the waste 52 on the grate 104, which is derived based on the thermal imaging data captured by the imaging unit 125 as an observed value, with the mass of the waste 52 on the grate 104, which is obtained based on the state variable model for the state variables at a certain time t, in each of the first to Nth regions on the grate 104. Also, the combustion calculation unit 412 matches the surface temperature T s The distribution of the sensible heat of the combustion gas at the outlet of the furnace 101 obtained as an observation value minus the sensible heat of the blowing air is made to match with the distribution of the volatile matter release amount obtained for the state variables at a certain time t. Furthermore, the combustion calculation unit 412 makes the value obtained by subtracting the sensible heat of the blowing air from the sensible heat of the combustion gas at the outlet of the furnace 101 obtained as an observation value proportional to the volatile matter release amount obtained for the state variables at a certain time t. This corrects the deviation of the state variables, which are parameters, and makes it possible to derive a more accurate state of the waste at time t in the state space model. Note that these processes for estimating the state of the waste can be performed instantly (in real time) while the furnace 101 is in operation.

[0118] Thereafter, the process proceeds to step ST15, where the state of the waste at time t is set to time t-1 in order to make the state of the waste at time t the initial state at the next time t+1. As a result, the combustion calculation unit 412 executes setting of the state of the waste at time (t-1) in step ST11.

[0119] After the process in step ST4, the process proceeds to step ST5 shown in Fig. 7, where the combustion calculation unit 412 outputs the proportions of moisture, volatile matter, fixed carbon, and ash in the waste. This completes the process of estimating the state of the waste in the waste on the grate 52 in the furnace 101. The flowcharts in Figs. 7 and 8 are repeatedly executed while the furnace 101 is operating.

[0120] Fig. 10 is a graph showing the state of the waste on the grate 104 at a certain time t derived as described above. In the example shown in Fig. 10, the area on the grate 104 is divided into 18 areas (N=18), and the amount of waste and the mixture ratio of moisture, volatile matter, fixed carbon, and ash in each of the first to eighteenth areas are shown. The graph shown in Fig. 10 changes in real time as the time t progresses.

[0121] 11 and 12 are graphs showing the amount of water evaporation and the amount of volatile matter discharged per unit time, respectively. Also, FIG. 13 is a graph showing the total amount of waste 52 on the grate in the waste incinerator 100, the amount of waste 50 dropped and supplied onto the grate 104, and the state of the waste in each area corresponding to FIG.

[0122] As shown in Fig. 10 and Fig. 11, the combustion calculation unit 412 can derive the ratio of the moisture amount of the waste shown in Fig. 10 based on the amount of moisture evaporation in each of the first to eighteenth regions shown in Fig. 11. Conversely, the combustion calculation unit 412 can derive the amount of moisture evaporation in each of the first to eighteenth regions shown in Fig. 11 by time-differentiating the ratio of the moisture amount of the waste shown in Fig. 10. Similarly, as shown in Fig. 10 and Fig. 12, the combustion calculation unit 412 can derive the ratio of the volatile matter emission amount of the waste shown in Fig. 10 based on the amount of volatile matter emission in each of the first to eighteenth regions shown in Fig. 12. Conversely, the combustion calculation unit 412 can derive the amount of volatile matter emission shown in Fig. 12 by time-differentiating the ratio of the volatile matter emission amount of the waste in each of the first to eighteenth regions shown in Fig. 10. 10 and 13, by measuring the total amount of waste 50 and the amount fed onto the grate 104, a graph of the state of the waste corresponding to FIG. 10 changes over time.

[0123] According to the embodiment described above, a state space model is constructed using the constructed waste reaction model, the acquired process data on the grate, and the process data inside the incinerator, and a data assimilation technique using a Kalman filter is used to estimate the amount of waste, the moisture percentage of the waste, the combustible percentage of the waste, and the heat value of the waste at each of the multiple divided positions on the grate. By performing a waste state estimation process, the furnace 101 can be controlled after more accurately grasping the state of the waste 50 inside the furnace 101, enabling more appropriate control.

[0124] (Recording medium) In the above-mentioned embodiment, a program capable of executing the processing method by the combustion control device 30 or the waste state estimation device 40 can be recorded on a computer or other machine or device (hereinafter referred to as a computer, etc.) or on a computer-readable recording medium. By making a computer, etc. read and execute the program from the recording medium, the computer functions as the waste state estimation device 40 or the combustion control device 30. Here, a computer-readable recording medium refers to a non-transient recording medium that stores information such as data and programs by electrical, magnetic, optical, mechanical, or chemical action and can be read from a computer, etc. Among such recording media, those that can be removed from a computer, etc. include, for example, a flexible disk, a magneto-optical disk, a CD-ROM, a CD-R / W, a DVD, a BD, a DAT, a magnetic tape, and a memory card such as a flash memory. In addition, a hard disk, a ROM, etc. are examples of recording media fixed to a computer, etc. Furthermore, an SSD can be used as a recording medium that can be removed from a computer, etc., and as a recording medium fixed to a computer, etc.

[0125] In addition, the programs executed by the combustion control device 30 and the waste state estimation device 40 according to one embodiment may be configured to be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network.

[0126] (Other embodiments) Furthermore, in the combustion control device 30 and the waste state estimation device 40 according to one embodiment, the above-mentioned "section" can be read as a "circuit" etc. For example, the communication section can be read as a communication circuit.

[0127] Further effects and modifications can be easily derived by those skilled in the art. The broader aspects of the present invention are not limited to the specific details and representative embodiments shown and described above. Therefore, various modifications are possible without departing from the spirit or scope of the general inventive concept defined by the appended claims and their equivalents. For example, the numerical values ​​and types of information given in the above embodiment are merely examples, and different numerical values ​​and types of information may be used as necessary, and the present invention is not limited by the description and drawings that form part of the disclosure of the present invention according to the above embodiment.

[0128] In the embodiment described above, the state of the waste is defined as the ratio of the amount of moisture, the amount of volatile matter, the amount of fixed carbon, and the amount of ash contained in the waste 50. However, it is also possible to set the state of the waste as the ratio of at least two amounts selected from the amount of moisture, the amount of volatile matter, the amount of fixed carbon, and the amount of ash.

[0129] For example, in the above-described embodiment, deep learning using a neural network is adopted as an example of machine learning, but machine learning based on other methods may be performed. For example, other supervised learning such as a support vector machine, a decision tree, a naive Bayes method, or a k-nearest neighbor method may be used. Also, semi-supervised learning may be used instead of supervised learning. [Explanation of symbols]

[0130] 1 Waste treatment system 2 Network 30 Combustion control device 31 Calculation control unit 32 Operation volume reference value adjustment section 33 Operation volume reference value correction unit 34,42 Storage part 35 Operation amount adjustment section 36,43 Communications Department 40 Waste status estimation device 41 Control section 44 Input / output section 50 Waste 51 Pre-supply waste 52 Grate waste 100 Waste incinerator 101 Furnace 101a Furnace wall 102 Waste Inlet 103 Waste supply device 104 Grate 105 Ash fall hole 106 Combustion air blower 107 Furnace outlet 108 Chimney 109 Boiler 109a heat exchanger 109b Steam drum 110 Cooling air inlet 111 Cooling air blower 112 Waste Supply Department 113 Step wall 114 Combustion air damper 114a, 114b, 114c, 114d Air dampers for under-grate combustion 115 Cooling air damper 116 Intermediate Ceiling 117 Combustion chamber gas thermometer 118 Main flue gas thermometer 119 Gas thermometer at bottom of furnace outlet 120 Gas thermometer at furnace outlet 121 Furnace outlet gas thermometer 122 Boiler outlet oxygen concentration meter 123 Gas concentration meter 124 Exhaust gas flow meter 125 Imaging unit 126a, 126b Combustion air temperature damper 127 Recirculation Blower 128 Exhaust gas recirculation air damper 341 Setting Value Database 342 Measurement Database 351 Combustion air volume adjustment section 352 Air volume ratio adjustment section 353 Cooling air volume adjustment unit 354 Waste feeder feed speed adjustment unit 355 Grate feed speed adjustment unit 356 Combustion air temperature adjustment unit 357 Exhaust gas recirculation air flow rate adjustment section 411 Boundary generator 412 Combustion Calculation Unit 413 Learning Department 421 Image Database 422 Combustion Information Database 423 Boundary Discrimination Learning Model 424 Waste reaction model 531,531a border

Claims

1. A control unit having hardware, The control unit is acquiring image data generated from thermal image information of an area containing waste in a waste incinerator having a grate through which waste is moved; Acquire process data for the waste incinerator; Deriving the amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste based on at least one of the acquired image data and the acquired process data; The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a moisture evaporation model constructed in advance to derive the amount of moisture evaporated from the waste; Based on the calculated amount of evaporated water, a ratio of water contained in the waste material present on the grate is calculated to estimate the amount of water contained in the waste material. Information processing device.

2. The waste incinerator is configured to be able to supply combustion air to the grate, The control unit uses, as the moisture evaporation model, a model that derives the amount of moisture evaporation from the waste as the sum of the amount of moisture evaporation due to thermal radiation in the waste incinerator and the amount of moisture evaporation due to ventilation of the combustion air supplied to the grate. The information processing device according to claim 1 .

3. The control unit is The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a pre-constructed volatile matter release model to derive the amount of volatile matter released from the waste; Based on the derived amount of water evaporation and the amount of volatile matter released, a ratio between the amount of water and the amount of volatile matter contained in the waste present on the grate is derived to estimate the state of the waste. The information processing device according to claim 1 .

4. The control unit is The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a fixed carbon combustion model constructed in advance to derive the amount of fixed carbon combustion in the waste; Based on the derived amounts of water evaporation, volatile matter emission, and fixed carbon combustion, a ratio of the amount of water, the amount of volatile matter, and the amount of fixed carbon contained in the waste present on the grate is derived to estimate the state of the waste. The information processing device according to claim 3 .

5. The control unit is A state variable used when estimating the state of the waste from the amount of water evaporation at a predetermined time is corrected by data assimilation processing using a Kalman filter. The information processing device according to claim 1 .

6. The control unit is The waste on the grate is virtually divided into a plurality of regions at least along a transport direction of the waste; Deriving the amount of the waste present on the grate, the amount of the waste moving, and the temperature of the waste for each of the plurality of regions based on the acquired image data; The acquired process data, the derived amount of the waste present on the grate, the movement amount of the waste, and the temperature of the waste are input into the moisture evaporation model to derive the amount of moisture evaporated from the waste for each region; Based on the amount of water evaporation derived for each area, a ratio of water contained in the waste present on the grate is derived for each area, and the amount of water contained in the waste for each area is estimated. The information processing device according to claim 1 .

7. An information processing method executed by an information processing device having a control unit having hardware, The control unit is acquiring image data generated from thermal image information of an area containing waste in a waste incinerator having a grate through which waste is moved; Acquire process data for the waste incinerator; Deriving the amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste based on at least one of the acquired image data and the acquired process data; The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a moisture evaporation model constructed in advance to derive the amount of moisture evaporated from the waste; Based on the calculated amount of evaporated water, a ratio of water contained in the waste material present on the grate is calculated to estimate the amount of water contained in the waste material. Information processing methods.

8. The waste incinerator is configured to be able to supply combustion air to the grate, The control unit uses, as the moisture evaporation model, a model that derives the amount of moisture evaporation from the waste as the sum of the amount of moisture evaporation due to thermal radiation in the waste incinerator and the amount of moisture evaporation due to ventilation of the combustion air supplied to the grate. The information processing method according to claim 7.

9. The control unit is The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a pre-constructed volatile matter release model to derive the amount of volatile matter released from the waste; Based on the derived amount of water evaporation and the amount of volatile matter released, a ratio between the amount of water and the amount of volatile matter contained in the waste present on the grate is derived to estimate the state of the waste. The information processing method according to claim 7.

10. The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a fixed carbon combustion model constructed in advance to derive the amount of fixed carbon combustion in the waste; Based on the derived amounts of water evaporation, volatile matter emission, and fixed carbon combustion, a ratio of the amount of water, the amount of volatile matter, and the amount of fixed carbon contained in the waste present on the grate is derived to estimate the state of the waste. The information processing method according to claim 9.

11. The control unit is A state variable used when estimating the state of the waste from the amount of water evaporation at a predetermined time is corrected by data assimilation processing using a Kalman filter. The information processing method according to claim 7.

12. The control unit is The waste on the grate is virtually divided into a plurality of regions at least along a transport direction of the waste; Deriving the amount of the waste present on the grate, the amount of the waste moving, and the temperature of the waste for each of the plurality of regions based on the acquired image data; The acquired process data, the derived amount of the waste present on the grate, the movement amount of the waste, and the temperature of the waste are input into the moisture evaporation model to derive the amount of moisture evaporated from the waste for each region; Based on the amount of water evaporation derived for each area, a ratio of water contained in the waste present on the grate is derived for each area, and the amount of water contained in the waste for each area is estimated. The information processing method according to claim 7.

13. A control unit having hardware, acquiring image data generated from thermal image information of an area containing waste in a waste incinerator having a grate through which waste is moved; Acquire process data for the waste incinerator; Deriving the amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste based on at least one of the acquired image data and the acquired process data; The acquired process data, the derived amount of the waste present on the grate, the amount of the waste supplied onto the grate, and the temperature of the waste are input into a moisture evaporation model constructed in advance to derive the amount of moisture evaporated from the waste; Based on the calculated amount of evaporated water, a ratio of water contained in the waste material present on the grate is calculated to estimate the amount of water contained in the waste material. A program to make that happen.

Images