JP2022013163A - Information processor, information processing method, program, medicine feeder, exhaust gas processor and exhaust gas processing method - Google Patents

Abstract

To predict the amount of sour gas contained in exhaust gas after prescribed time.SOLUTION: An information processor includes a control section predicting the concentration or substance quantity of sour gas in exhaust gas containing sour gas discharged from a waste incineration furnace burning waste. The control section acquires a measured value of the concentration or substance quantity of sour gas, stores it in a storage section as a sour gas measured value, acquires, from the waste incineration furnace, the information concerning the operation in the waste incineration furnace and stores it in the storage section as process data, predicts the concentration or substance quantity of sour gas after prescribed prediction time from prescribed time on the basis of the sour gas measured value and the process data at the prescribed time read out from the storage section and outputs a concentration predicted value.SELECTED DRAWING: Figure 4

Description

The present invention relates to an information processing device, an information processing method, a program, a drug supply device, an exhaust gas treatment device, and an exhaust gas treatment method.

Conventionally, a device for appropriately controlling the amount of substance of acid gas contained in the exhaust gas discharged from a waste incinerator has been proposed. For example, Patent Document 1 discloses a technique for reducing fluctuations in hydrogen chloride (HCl) concentration and the like in the exhaust gas after treatment to reduce the amount of desalting agent used.

In the technique described in Patent Document 1, specifically, in a method of neutralizing and removing acid gas in exhaust gas from a waste incinerator by blowing a chemical such as slaked lime, a bug along the flow direction of exhaust gas. Feed-forward control (FF control) based on the measured values of acid gas densitometers such as the HCl laser meter installed on the upstream side of the filter, and feedback control by other acid gas densitometers installed on the downstream side of the bag filter (FF control). The supply amount of the drug is determined in combination with FB control). In the technique described in Patent Document 1, by using an acid gas concentration meter on the upstream side of the exhaust gas treatment unit such as a bag filter, as compared with the case where only the acid gas concentration meter on the downstream side of the exhaust gas treatment unit is used. Therefore, a sudden change in the acid gas concentration in the exhaust gas before being treated by the exhaust gas treatment unit can be detected at an early stage, and the supply amount of the chemical can be reduced.

Japanese Unexamined Patent Publication No. 2006-07758

However, while the amount of acid gas contained in the exhaust gas of the waste incinerator fluctuates greatly, the chemical used for removing the acid gas takes time to react with the acid gas. Therefore, when the amount of acid gas on the upstream side of the exhaust gas treatment unit suddenly rises, the amount of chemical supply (hereinafter referred to as the chemical supply amount) is changed after the amount of acid gas on the inflow side of the exhaust gas treatment unit rises. However, the increase in acid gas exceeds the reaction between the drug and acid gas, and the concentration and amount of acid gas on the downstream side of the exhaust gas treatment section (hereinafter collectively referred to as acid gas concentration) increases. It ends up. In this case, it is necessary to greatly increase the amount of the drug supplied in order to suppress the increase in the acid gas concentration, and excessive supply of the drug results in wasteful consumption of the drug. Therefore, there has been a demand for a technique for reducing the consumption of a drug by predicting the concentration of the acid gas contained in the exhaust gas and controlling the supply amount of the drug to be cut out based on the predicted acid gas concentration.

The present invention has been made in view of the above, and an object thereof is an information processing apparatus capable of predicting the acid gas concentration contained in exhaust gas, an information processing method, and a program, and a drug based on the predicted acid gas concentration. It is an object of the present invention to provide a chemical supply device, an exhaust gas treatment device, and an exhaust gas treatment method capable of controlling the supply amount and reducing the chemical supply amount of the chemical used for exhaust gas treatment.

In order to solve the above-mentioned problems and achieve the object, the information processing apparatus according to one aspect of the present invention comprises the acid gas in the exhaust gas containing the acid gas discharged from the waste incinerator that incinerates the waste. An information processing device provided with a control unit for predicting a concentration or a substance amount, wherein the control unit acquires a measured value of the acid gas concentration or the substance amount and stores it in a storage unit as an acid gas measured value. Information related to the operation of the waste incinerator is acquired from the waste incinerator, stored as process data in the storage unit, and read from the storage unit, the acid gas measurement value at a predetermined time point and the process. Based on the data, the concentration or amount of the acid gas is predicted after a predetermined prediction time from the predetermined time point, and the predicted concentration value is output.

In the above invention, the information processing apparatus according to one aspect of the present invention acquires the acid gas measurement value and the process data at a predetermined time point from the storage unit as input parameters, and the control unit acquires the acid gas measurement value and the process data at the predetermined time point as input parameters. The acid gas measurement value and the process data read from the above are input to the predictive learning model, and the concentration predicted value is output as an output parameter. Input / output data using the measured value and the process data as input parameters for learning, and the acid gas measured value and the acid gas measured value after the elapse of the predicted time from the predetermined time point at which the process data was acquired as the learning output parameter. It is a learning model generated by machine learning using a set.

In the above invention, the information processing apparatus according to one aspect of the present invention is the acid gas contained in the exhaust gas before the exhaust gas treatment is executed in the exhaust gas treatment unit that executes the exhaust gas treatment for the exhaust gas. Predict concentration or amount of substance.

In the above invention, the information processing apparatus according to one aspect of the present invention includes a grate for moving the waste and a steam generating unit for generating steam, and the process data is the exhaust gas. Temperature, oxygen concentration, NO _x concentration, and flow rate, volume and bulk density in the waste, velocity in the grate, and air pressure under the grate, and pressure and temperature at the outlet of the steam generator. Contains at least one physical quantity selected from.

In the above invention, the information processing apparatus according to one aspect of the present invention includes an image pickup unit in which the waste incinerator captures an image of a region containing the waste in the waste incinerator, and the process data is obtained. It includes a feature amount obtained from at least one of the combustion image data indicating the combustion state of the flame captured by the imaging unit and the transmission image data indicating the state in which the flame is transmitted based on the thermal image information.

In the above invention, the information processing apparatus according to one aspect of the present invention includes a steam generating unit in which the waste incinerator generates steam, and the process data is information on the presence or absence of a soot blow operation in the steam generating unit. including.

In the information processing apparatus according to one aspect of the present invention, the acid gas is hydrogen chloride gas in the above invention.

The information processing method according to one aspect of the present invention includes information processing including a control unit for predicting the concentration or amount of the acid gas in the exhaust gas including the acid gas discharged from the waste incinerator that incinerates the waste. In the information processing method executed by the apparatus, the control unit acquires the measured value of the acid gas concentration or the amount of the substance and stores it in the storage unit as the acid gas measured value, and from the waste incinerator, the said Information related to the operation of the waste incinerator is acquired and stored as process data in the storage unit, and based on the acid gas measurement value and the process data at a predetermined time point read from the storage unit, from the predetermined time point. Predicts the concentration or amount of the acid gas after a predetermined prediction time, and outputs the predicted concentration value.

The program according to one aspect of the present invention is an information processing apparatus provided with a control unit for predicting the concentration or amount of the acid gas in the exhaust gas containing the acid gas discharged from the waste incinerator that incinerates the waste. , The measured value of the acid gas concentration or the amount of substance is acquired and stored in the storage unit as the acid gas measured value, and the information related to the operation in the waste incinerator is acquired from the waste incinerator and the process. The concentration or amount of the acid gas after a predetermined predicted time from the predetermined time point is determined based on the acid gas measurement value at a predetermined time point and the process data read from the storage unit as data. Predict and output the predicted concentration value.

The chemical supply device according to one aspect of the present invention is the exhaust gas treatment unit before the exhaust gas treatment is executed by the exhaust gas treatment unit that executes the exhaust gas treatment on the exhaust gas containing the acidic gas discharged from the waste incinerator that incinerates the waste. A drug supply device that supplies a drug to the exhaust gas, instructing the drug supply unit that supplies the drug to the exhaust gas before the exhaust gas treatment is executed and the drug supply unit the supply amount of the drug. The drug supply control unit includes a drug supply control unit that outputs a supply amount control value, and the drug supply control unit acquires a concentration predicted value output from the information processing apparatus according to the above invention, stores it in a storage unit, and stores the drug supply control unit. The concentration predicted value is acquired from the storage unit, and the supply amount control value is derived based on the concentration predicted value.

The exhaust gas treatment device according to one aspect of the present invention is an exhaust gas treatment device that performs exhaust gas treatment on exhaust gas containing acidic gas discharged from a waste incinerator that incinerates waste, and is a flue gas of the exhaust gas. The exhaust gas treatment unit provided in the above, the drug supply unit that supplies the drug to the upstream side along the flow direction of the exhaust gas in the exhaust gas treatment unit, and the supply that instructs the drug supply unit to supply the drug. The drug supply control unit includes a drug supply control unit that outputs a quantity control value, and the drug supply control unit acquires a concentration predicted value output from the information processing apparatus according to the above invention, stores it in a storage unit, and stores the storage unit. The concentration predicted value is acquired from the unit, and the supply amount control value is derived based on the concentration predicted value.

The exhaust gas treatment method according to one aspect of the present invention is an exhaust gas treatment method for executing exhaust gas treatment for exhaust gas containing acidic gas discharged from a waste incinerator that incinerates waste, and is a flue gas of the exhaust gas. From the exhaust gas treatment step performed in the exhaust gas treatment section provided in the above and the drug supply section configured to be able to supply the drug, the drug is supplied to the upstream side of the exhaust gas treatment section along the flow direction of the exhaust gas. The drug supply control step includes a step and a drug supply control step in which the drug supply control unit outputs a supply amount control value instructing the drug supply amount to the drug supply unit, and the drug supply control step includes the drug supply. The control unit acquires the concentration predicted value output from the information processing apparatus according to one aspect of the above invention and stores it in the storage unit, acquires the concentration predicted value from the storage unit, and based on the concentration predicted value. The step of deriving the supply amount control value is included.

According to the information processing device, the information processing method, the program, the drug supply device, the exhaust gas treatment device, and the exhaust gas treatment method according to the present invention, the acid gas concentration contained in the exhaust gas is predicted and based on the predicted acid gas concentration. Since the amount of chemicals supplied can be controlled, it is possible to reduce the amount of chemicals supplied for the exhaust gas treatment.

FIG. 1 is an overall configuration diagram schematically showing a configuration of an exhaust gas treatment facility to which an information processing apparatus according to an embodiment of the present invention is applied. FIG. 2 is an overall configuration diagram schematically showing an incinerator in an exhaust gas treatment facility according to an embodiment of the present invention. FIG. 3 is a block diagram showing an example of a configuration of a system including an information processing apparatus according to an embodiment of the present invention. FIG. 4 is a diagram for explaining a drug supply control method according to an embodiment of the present invention.

Hereinafter, an embodiment of the present invention will be described with reference to the drawings. In all the drawings of the following embodiment, the same or corresponding parts are designated by the same reference numerals. Further, the present invention is not limited to one embodiment described below.

(Exhaust gas treatment equipment)
FIG. 1 is a diagram showing an example of a configuration of an exhaust gas treatment facility to which a drug supply control method as an information processing method according to an embodiment of the present invention is applied. As shown in FIG. 1, the waste treatment facility 1 includes an incinerator 100, exhaust gas ducts 130 and 150, a dust collector 140, and a chimney 160.

The untreated exhaust gas discharged from the incinerator 100 passes through the exhaust gas duct 130 and is supplied to the dust collector 140. A supply port 131 for supplying chemicals such as calcium hydroxide (Ca (OH) ₂ ) (slaked lime) and baking soda (NaHCO ₃ ) is provided in front of the dust collector 140 in the exhaust gas duct 130. The chemicals supplied to the front stage of the dust collector 140 through the supply port 131 form a layer on the surface of the filter of the dust collector 140, and hydrogen chloride (HCl), sulfur dioxide (SO ₂ ), or trioxide in the exhaust gas. It reacts with sulfur (SO ₃ ) and produces reaction products. Examples of reaction formulas in which reaction products are produced are given in the following chemical reaction formulas (1-1) to (3). The production of reaction products is not limited to the following chemical reactions.
Ca (OH) ₂ + HCl → CaClOH + H ₂ O …… (1-1)
CaClOH + HCl → CaCl ₂ + H ₂ O …… (1-2)
Ca (OH) ₂ + SO ₂ → CaSO ₃ + H ₂ O …… (2-1)
2CaSO ₃ + O ₂ → 2CaSO ₄ …… (2-2)
Ca (OH) ₂ + SO ₃ → CaSO ₄ + H ₂ O …… (3)

These reaction products are collected and processed together with other dust in the dust collector 140 as an exhaust gas treatment unit that performs an exhaust gas treatment step. The treated exhaust gas from which hydrogen chloride and the like have been removed passes through the exhaust gas duct 150 and is discharged to the outside of the system from the chimney 160.

The waste treatment facility 1 further includes a drug supply control device 32, a drug supply unit 33, an upstream acid gas concentration meter 34, a downstream acid gas concentration meter 35, and a gas concentration prediction device 40. The waste treatment facility 1 may not be provided with the gas concentration prediction device 40. Further, the drug supply control device 32 and the drug supply unit 33 configure the drug supply device according to the present embodiment.

The drug supply control device 32 controls the amount of the drug supplied to the supply port 131 provided in the front stage of the dust collector 140 by controlling the drug supply unit 33. The upstream acid gas concentration meter 34 is provided on the upstream side of the dust collector 140 along the flow direction of the exhaust gas. The upstream acid gas concentration meter 34 is configured to be capable of measuring the acid gas concentration in the exhaust gas before treatment in the exhaust gas duct 130 in the previous stage of the dust collector 140. The downstream acid gas concentration meter 35 is provided on the downstream side of the dust collector 140 along the flow direction of the exhaust gas. The downstream acid gas concentration meter 35 is configured to be capable of measuring the acid gas concentration in the treated exhaust gas in the exhaust gas duct 150 at the subsequent stage of the dust collector 140. The downstream acid gas concentration meter 35 may be provided near the chimney 160 or its inlet.

Various process measurement values (hereinafter referred to as process data) in the incinerator 100 are input to the gas concentration prediction device 40. The gas concentration predictor 40 is a measured value of the acid gas concentration before exhaust gas treatment (hereinafter referred to as acid gas concentration before treatment) from the upstream acid gas concentration meter 34 as the acid gas measurement value, and from the downstream acid gas concentration meter 35. The measured values of the acid gas concentration after the exhaust gas treatment (hereinafter referred to as the acid gas concentration after the treatment) are input. The amount of substance of acid gas may be used instead of the concentration of acid gas, and in the following description, the acid gas concentration and the amount of substance of acid gas are collectively referred to as "acid gas concentration".

The gas concentration predictor 40 predicts the pre-treatment acid gas concentration after a predetermined prediction time from the present based on the current measured values of various process data, the pre-treatment acid gas concentration, and the post-treatment acid gas concentration. The predicted value (hereinafter referred to as the predicted concentration value) can be derived. The predicted time is selected to be longer than the time until the change in the amount of the drug supplied affects the acid gas concentration after the treatment, and specifically in the present embodiment, for example, in the range of 15 seconds or more and 5 minutes or less, the present embodiment. In, for example, it is selected in 1 minute. The gas concentration prediction device 40 can output the derived concentration prediction value to the drug supply control device 32.

The drug supply control device 32 derives the supply amount of the drug to be supplied to the front stage of the dust collector 140 based on the concentration prediction value input from the gas concentration prediction device 40. The drug supply control device 32 outputs information on the supply amount of the derived drug (hereinafter, supply amount control value) to the drug supply unit 33. The drug supply unit 33 performs the drug supply step by supplying the amount of the drug based on the input supply amount control value to the front stage of the dust collector 140 through the supply port 131.

(Waste incinerator)
Next, the incinerator 100 as a waste incinerator will be described. FIG. 2 is an overall configuration diagram schematically showing an incinerator in a waste treatment facility according to an embodiment of the present invention. As shown in FIG. 2, the incinerator 100 includes a furnace 101 in which waste is burned, a waste input port 102 for charging waste, and a boiler 109. The boiler 109 as a steam generating unit includes a heat exchanger 109a and a steam drum 109b installed on the downstream side of the furnace outlet 107 of the furnace 101.

The waste input from the waste input port 102 is conveyed to the grate 104 by the waste supply device 103. The reciprocating motion of the grate 104 causes the waste to be agitated and moved. The waste on the grate 104 is burned while being dried by blowing combustion air supplied from the combustion air blower 106 into the air box below the grate 104 to generate exhaust gas and ash. The generated ash falls through the ash drop port 105 and is discharged to the outside of the furnace 101.

The total amount of combustion air supplied from under the grate 104 to the inside of the furnace 101 is adjusted by a combustion air damper 114 provided in the immediate vicinity of the combustion air blower 106 as a push-in blower. The flow rate of the combustion air supplied to each air box is adjusted by the subgrate combustion air dampers 114a, 114b, 114c, 114d provided in the pipes that supply the combustion air to each air box, respectively. To. In other words, the sub-grate combustion air dampers 114a to 114d adjust the ratio of the flow rate of the combustion air supplied to each air box. In FIG. 1, four air boxes are divided under the grate 104 along the waste transport direction, and combustion air is supplied through each air box. However, the combustion air under the grate is used. The number of dampers 114a to 114d and the number of air boxes is not necessarily limited to four, and can be appropriately changed according to the scale and purpose of the grate incinerator.

Secondary air is blown into the furnace 101 by the secondary air blower 111 as a secondary blower from the secondary air blowing port 110 provided on the furnace wall. When the secondary air is blown into the furnace 101, the unburned components in the combustion gas are further burned, and the excessive rise in the temperature of the furnace wall is suppressed. The flow rate of the secondary air supplied from the secondary air inlet 110 into the furnace 101 is adjusted by the secondary air damper 115 provided in the immediate vicinity of the secondary air blower 111.

Along the direction of transporting waste in the grate 104, the combustible gas generated in the waste drying process and the main combustion process on the upstream side and the combustion exhaust gas generated in the post-combustion process on the downstream side are the furnace of the furnace 101. It merges at the gas mixing section provided on the outlet 107 side. The combustible gas and the combustion exhaust gas merged in the gas mixing section are stirred and mixed again, and then secondary combustion is performed by supplying air for secondary combustion. The boiler 109 is installed on the downstream side along the waste transport direction with respect to the portion where the secondary combustion is performed (hereinafter, the secondary combustion portion). The combustion gas subjected to the secondary combustion is exhausted from the incinerator 100 through the exhaust gas duct 130 after the heat energy is recovered by the heat exchanger 109a of the boiler 109.

In the furnace 101, an intermediate ceiling 116 is provided at an upper position along the height direction of the furnace 101. The gas flowing in the furnace 101 is divided into a gas containing a large amount of combustible gas generated in the waste drying process and the main combustion process on the upstream side and a combustion exhaust gas generated in the post-combustion process on the downstream side by the intermediate ceiling 116. , Can be divided and discharged. Specifically, the combustion exhaust gas flows through the flue below the intermediate ceiling 116 (main flue), while the gas containing a large amount of combustible gas flows through the flue above the intermediate ceiling 116 (secondary flue). .. The merging of the combustion exhaust gas and the gas containing a large amount of combustible gas in the gas mixing section further promotes the stirring and mixing of the gas in the gas mixing section. As a result, the combustion in the secondary combustion section becomes more stable, the generation of dioxins in the combustion process can be suppressed, and the generation of unburned waste can be suppressed. The intermediate ceiling 116 may not be provided in the furnace 101.

Thermometers as sensors for measuring the gas temperature in the furnace 101 are provided at a plurality of positions in the furnace 101. Specifically, a combustion chamber gas thermometer 117 is provided at an intermediate position between the grate 104 and the secondary air inlet 110 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 position in the middle of the furnace outlet 107 along the height direction of the furnace 101. A furnace outlet gas thermometer 121 for measuring the combustion control temperature is provided at a position on the downstream side of the furnace outlet 107 along the height direction of the furnace 101. The measured values of the temperature 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 process data. As a combustion process measurement value including, it is transmitted to the combustion control device 31 and stored in the storage unit 312 (see FIG. 3).

The boiler 109 is provided with a boiler outlet oxygen concentration meter 122 for measuring the concentration of oxygen (O ₂ ) in the exhaust gas on the outlet side. At the inlet of the exhaust gas duct 130, a gas densitometer 123 for measuring the concentrations of carbon monoxide (CO) and nitrogen oxides (NO _x ) in the exhaust gas is provided. An exhaust gas flow meter 124 for measuring the amount of exhaust gas is provided on the outlet side of the boiler 109. The measured values of the gas concentration and the flow rate measured by the boiler outlet oxygen concentration meter 122, the gas concentration meter 123, and the exhaust gas flow meter 124 are stored in the storage unit 312 of the combustion control device 31 as process data. Further, the boiler 109 is provided with a steam flow meter 125 for measuring the amount of steam generated in the boiler 109. The measured value of the steam amount of the boiler 109 measured by the steam flow meter 125 is stored in the storage unit 312 of the combustion control device 31 as process data.

An imaging unit 126 is provided on the downstream side of the furnace 101 in the direction of transporting waste. The image pickup unit 126 includes, for example, a flame transmission camera composed of an infrared camera and an image processing unit for processing captured image data. The image pickup unit 126 may be arranged outside the furnace in the vicinity of the monitoring window provided on the furnace wall, or may have a water-cooled structure and may be arranged inside the furnace 101. The waste falls on the grate 104 from the waste supply unit 112 at the portion of the step wall 113. The waste that has fallen on the grate 104 is moved forward on the image pickup unit 126 side while being agitated by the reciprocating motion accompanying the back-and-forth movement of the grate 104.

The imaging unit 126 may have a transmission imaging unit that can acquire thermographic information of waste on the grate 104 as thermal image information. Here, the wavelength of the infrared rays emitted from the waste is different from the wavelength of the infrared rays emitted from the hot gas and the flame in the space. Therefore, in the image pickup unit 126, by appropriately selecting the infrared wavelength to be measured, it is possible to obtain thermal image information corresponding to the temperature distribution of the waste layer even if a flame is present in the measurement field of view. Further, the measurement range in the furnace length direction by the image pickup unit 126 can be set, and the thermal image information of the waste layer on the grate 104 at the position upstream from the combustion region (upstream from the flame) can be obtained. The thermal image information can be treated as video data in a state where the flame is transmitted, that is, as a plurality of transmitted image data.

The combustion control device 31 can generate process data such as the fall area, fall height, and burnout point position of the waste based on the acquired transmission image data. The combustion control device 31 can derive process data such as the average temperature, region area, and temperature center of gravity of the waste before supply based on the transmission image data. The combustion control device 31 includes an average temperature, a region area, and a temperature center of the step wall 113, an average temperature of waste on the grate 104, a region area, and a temperature center, an average temperature of the grate 104, a region area, and a temperature. Process data such as the center of gravity can be derived. Further, the combustion control device 31 can derive process data such as the layered mesh temperature and the equally divided mesh temperature in the acquired transmission image data. Derivation of these process data can be performed using an image processing learning model related to image processing.

Further, the imaging unit 126 may further include a combustion image imaging unit that captures a combustion state of waste on the grate 104, that is, a flame. By capturing a combustion image by the combustion image imaging unit of the imaging unit 126, it is possible to quantify the combustion state based on the combustion image and generate combustion quantified data as a feature amount. The generation of combustion quantified data can be performed using a predetermined combustion image learning model. The combustion quantified data is stored in the storage unit 312 of the combustion control device 31 as process data.

(Exhaust gas treatment system)
Next, an exhaust gas treatment system as an exhaust gas treatment device for deriving the supply amount of the chemicals supplied to the exhaust gas in the waste treatment facility 1 described above will be described. FIG. 3 is a block diagram showing an example of the configuration of an exhaust gas treatment system including an information processing apparatus according to an embodiment of the present invention.

As shown in FIG. 3, the exhaust gas treatment system that executes the exhaust gas treatment method includes a control device group 30 and a gas concentration prediction device 40 in the waste treatment facility 1. The control device group 30 includes a combustion control device 31 and a drug supply control device 32. The exhaust gas treatment system may further have a learning server 50 independent of the waste treatment facility 1. In this case, the waste treatment facility 1 provided with the gas concentration prediction device 40 and the learning server 50 are connected via the network 2.

In the waste treatment facility 1, the control device group 30 and the gas concentration prediction device 40 are connected to each other via the network 2. The network 2 includes, for example, a private line, a public communication network such as the Internet, for example, a LAN (Local Area Network), a WAN (Wide Area Network), a telephone communication network such as a mobile phone, a public line, a VPN (Virtual Private Network), or the like. Consists of one or more combinations.

The gas concentration prediction device 40 may be connected to the network 2 independently of the waste treatment facility 1, or the gas concentration prediction device 40 and the control device group 30 may be installed in separate facilities. .. When the gas concentration prediction device 40 and the control device group 30 are installed in separate facilities, various information and various data are communicated via the above-mentioned network 2. Further, the gas concentration prediction device 40 and the learning server 50 may be integrally configured.

The combustion control device 31 in the control device group 30 of the waste treatment facility 1 includes a control unit 311 and a storage unit 312. It should be noted that an operation amount adjusting unit for performing combustion control may be further provided. The control unit 311 as a combustion control unit is specifically a processor such as a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an FPGA (Field-Programmable Gate Array), and a RAM (Random Access Memory) or ROM (Random Access Memory). It is equipped with a main memory unit (none of which is shown) such as Read Only Memory). The storage unit 312 includes volatile memory such as RAM, non-volatile memory such as ROM, EPROM (Erasable Programmable ROM), hard disk drive (HDD, Hard Disk Drive), solid state drive (SSD, Solid State Drive), and removable media. It is composed of a storage medium selected from the above. The removable media is, for example, a USB (Universal Serial Bus) memory or a disc recording medium such as a CD (Compact Disc), a DVD (Digital Versatile Disc), or a BD (Blu-ray (registered trademark) Disc). be. Further, the storage unit 312 may be configured by using a computer-readable recording medium such as a memory card that can be mounted from the outside.

The storage unit 312 can store an operating system (OS), various programs, various tables, various databases, and the like for executing the operation of the combustion control device 31. Here, the various programs also include an information processing program that realizes processing based on a learning model such as the above-mentioned combustion image learning model or image processing learning model, or a trained model. That is, the various programs include an automatic judgment processing program that realizes judgment processing using a combustion image learning model or an image processing learning model that can execute a predetermined judgment from the combustion image captured by the combustion image imaging unit. You may be. These various programs can also be recorded on a computer-readable recording medium such as an HDD, SSD, flash memory, CD-ROM, DVD-ROM, or flexible disk and widely distributed.

The combustion control device 31 controls the operation amount of each operation end based on a predetermined operation amount relational expression. The operation amount of the operation end is, for example, an operation amount such as a waste supply device feed speed for adjusting the waste supply speed of waste and a grate feed speed for adjusting the movement speed of waste. The combustion control device 31 controls the amount of combustion air and the amount of secondary air, if necessary, based on the manipulated variable relational expression.

The storage unit 312 stores the data referred to by the control unit 311. The storage unit 312 stores the above-mentioned various process data acquired as a predetermined operation amount relational expression, a control algorithm, a preset incinerator amount set value, and a combustion state amount in the furnace 101. There is.

The drug supply control device 32 in the waste treatment facility 1 includes a control unit 321, a storage unit 322, and a communication unit 323. The control unit 321 has the same configuration as the control unit 311 described above functionally and physically, and has a processor such as a CPU, DSP, FPGA, and a main storage unit such as RAM and ROM (none of which is shown). ).

The storage unit 322 has the same configuration as the storage unit 312 described above functionally and physically, and has a volatile memory such as RAM, a non-volatile memory such as ROM, an EPROM, an HDD, an SSD, a removable medium, and the like. Consists of storage media selected from. The storage unit 322 can store the operation of the drug supply control device 32, that is, the OS for executing the drug supply control process, various programs, various databases, and the like. Specifically, the storage unit 322 stores a program for controlling the drug supply unit 33, a program for calculating the drug supply amount, and a drug supply amount control value.

The control unit 321 loads the program stored in the storage unit 322 into the work area of the main storage unit and executes it, and controls each component or the like through the execution of the program to realize a function suitable for a predetermined purpose. can. In the present embodiment, the control unit 321 executes the function of the drug amount calculation unit 324 by executing the program stored in the storage unit 322. Specifically, for example, the control unit 321 functions as a drug amount calculation unit 324 by reading a program for calculating the drug amount from the storage unit 322, and the current pre-treatment acid gas concentration and post-treatment acid gas concentration, and prediction. The amount of the drug to be supplied to the exhaust gas duct 130 is derived from at least one piece of information on the predicted concentration value after time.

The communication unit 323 in the drug supply control device 32 is composed of, for example, a LAN (Local Area Network) interface board, a wireless communication circuit for wireless communication, and the like. The communication unit 323 is connected to the network 2. The communication unit 323 connected to the network 2 is configured to be able to communicate with the gas concentration prediction device 40 and the learning server 50. The combustion control device 31 and the communication unit 323 may be communicable, and the combustion control device 31 may be connected to the network 2 via the communication unit 323.

(Gas concentration predictor)
The gas concentration prediction device 40 as an information processing device includes a control unit 41, a storage unit 42, an input unit 43, an output unit 44, and a communication unit 45. The gas concentration prediction device 40 calculates the pretreatment acid gas concentration in the exhaust gas duct 130 after the prediction time, that is, the concentration prediction value. The control unit 41, the storage unit 42, and the communication unit 45 have the same configurations as the control unit 311, 321, the storage unit 312, 322, and the communication unit 323 described above, respectively, functionally and physically.

The storage unit 42 can store an OS, various programs, various tables, various databases, etc. for executing the operation of the gas concentration prediction device 40. Here, the various programs include an information processing program that realizes processing using the predictive learning model according to the present embodiment. The storage unit 42 may be provided in another server such as the learning server 50 capable of communicating via the network 2, or may be provided in the combustion control device 31 or the drug supply control device 32.

Specifically, the storage unit 42 stores a predictive learning model 421, a gas concentration database (gas concentration DB) 422, and a process data database (process data DB) 423. The predictive learning model 421 includes at least one learning model. The predictive learning model 421 is an updatable model. If the learning model is not updated, it is stored in the storage unit 42 as a predictive learning model. These various programs can also be recorded on a computer-readable recording medium such as SSD, HDD, flash memory, CD-ROM, DVD-ROM, and flexible disk and widely distributed. The gas concentration DB 422 is composed of data on the concentrations of various gases flowing in the exhaust gas ducts 130 and 150, particularly acid gas. The gas concentration DB 422 stores data of the pre-treatment acid gas concentration and the post-treatment acid gas concentration associated with the date and time information in chronological order. The process data DB 423 is composed of various process data measured and acquired at various places in the incinerator 100 described above.

The control unit 41 loads the program stored in the storage unit 42 into the work area of the main storage unit and executes it, and controls each component or the like through the execution of the program to realize a function that meets a predetermined purpose. can. In the present embodiment, the control unit 41 can execute the functions of the prediction unit 411 and the learning unit 412 by executing the program stored in the storage unit 42. The function of the learning unit 412 may not be provided. Specifically, for example, the control unit 41 executes the function of the prediction unit 411 by reading the prediction learning model 421 which is a program from the storage unit 42. The details of the functions of the prediction unit 411 and the learning unit 412 will be described later.

The input unit 43 as an input means uses a user interface such as a keyboard, input buttons, levers, a touch panel for manual input provided superimposed on a display such as a liquid crystal display, or a microphone for voice recognition. It is composed of. By operating the input unit 43, a user or the like can input predetermined information to the control unit 41. The output unit 44 as an output means is configured so that predetermined information can be notified to the outside. The output unit 44 displays an image of waste in the furnace 101 on the display monitor, displays characters and figures on the screen of the touch panel display, and outputs sound from the speaker according to the control by the control unit 41. Or something. The input / output unit 43 and the output unit 44 may be integrated to form an input / output unit, and the input / output unit may be composed of a touch panel display, a speaker microphone, or the like.

(Predictive learning model)
Here, the predictive learning model 421 stored in the storage unit 42 and its generation method will be described. The predictive learning model 421 is based on the pretreatment acid gas concentration measured by the upstream acid gas concentration meter 34 from the past to the present, various process data described above, combustion image data, and transmission image data as explanatory variables. The input parameters are the characteristic amount indicating the combustion state of the derived waste and the presence or absence of soot blow operation. The post-treatment acid gas concentration may be included in the input parameters. Further, the process data may include data consisting of physical quantities selected from the volume and bulk density of waste, in addition to the process data such as various gas temperatures and air flow rates described above. Specifically, the process data includes exhaust gas temperature, oxygen concentration in exhaust gas, NO _x concentration in exhaust gas, exhaust gas flow rate, waste volume, waste bulk density, grate speed, subgrate air pressure, and boiler 109 overheater. It can contain data selected from physical quantities such as outlet temperature and pressure. The prediction learning model 421 uses the acid gas concentration or the acid gas amount as the output parameter as the objective variable after the prediction time from the present. The acid gas is typically hydrogen chloride gas (HCl), but may be another acid gas. The "present" in the predictive learning model 421 can be paraphrased as "arbitrary time".

The data used to generate the predictive learning model 421 is, for example, waste derived based on pretreatment acid gas concentration, various process data, combustion image data and transmission image data from the past to the present. Features that indicate the combustion state, and the presence or absence of soot blow operation. Each of these data is preferably based on, for example, operation data for the past one week or more and one month or less, and in the present embodiment, it is based on, for example, two weeks of operation data, but is not limited. That is, as the input / output data set for generating the predictive learning model 421, as the input parameters for learning, the acid gas concentration before treatment, the various process data described above, and the burning state of waste from the past to a predetermined time point. Data such as the feature amount indicating the above and the presence / absence of soot blow operation are used, and the pretreatment acid gas concentration after the predicted time has elapsed from a predetermined time point is used as the learning output parameter. Further, in order to better learn a certain abnormal state, the data may be processed by a method such as oversampling for a specific state.

The learning unit 412 of the control unit 41 uses the above-mentioned learning input parameters and learning output parameters as teacher data, and is a predictive learning model 421 of regression analysis by machine learning such as deep learning using a neural network. To generate. The control unit 41 is at least one selected from the group of pretreatment acid gas concentration, various process data, feature amount indicating the combustion state of waste, and the presence / absence of soot blow operation based on the content learned by the learning unit 412. The pretreatment acid gas concentration after the predicted time elapses is derived from the type parameters. Further, the learning unit 412 appropriately updates the prediction learning model 421 using the above-mentioned input parameters at a predetermined time point and the pretreatment acid gas concentration measured by the upstream acid gas concentration meter 34 after the predicted time has elapsed from the predetermined time point. do.

(Learning server)
The learning server 50 as an information processing device includes a control unit 51, a storage unit 52, an input unit 53, an output unit 54, and a communication unit 55. The learning server 50 generates a predictive learning model 521 similar to the predictive learning model 421 described above. The control unit 51, the storage unit 52, the input unit 53, the output unit 54, and the communication unit 55 are functionally and physically the above-mentioned control units 311, 321, 41, storage units 312, 322, 42, and inputs, respectively. It has the same configuration as the unit 43, the output unit 44, and the communication unit 323, 45.

The storage unit 52 can store an OS for executing the operation of the learning server 50, various programs, various tables, various databases, and the like. Here, the various programs include an information processing program that realizes processing using the predictive learning model according to the present embodiment. The storage unit 52 may be provided in another server capable of communicating via the network 2. Specifically, the storage unit 52 stores the predictive learning model 521 and the big data 522. The predictive learning model 521 includes a learning model similar to the predictive learning model 421 described above. Big data 522 includes past operation data in the waste treatment facility 1, that is, data such as pretreatment acid gas concentration, various process data, feature quantities indicating the combustion state of waste, and the presence or absence of soot blow operation. That is, the learning server 50 receives and acquires various operation data in the waste treatment facility 1 via the network 2, and stores the data as big data 522 in the storage unit 52.

In the present embodiment, the control unit 51 of the learning server 50 loads the program stored in the storage unit 52 into the work area of the main storage unit and executes the program, and controls each component unit and the like through the execution of the program for learning. The function of the unit 511 can be realized. The function of the learning unit 511 is the same as that of the learning unit 412 described above. The learning unit 511 of the control unit 51 generates and updates the predictive learning model 521 in the same manner as the above-mentioned generation method and update method of the predictive learning model 421 based on the past operation data included in the big data 522. Or something. The control unit 51 transmits the generated prediction learning model 521 to the gas concentration prediction device 40 through the network 2. The gas concentration prediction device 40 stores the received prediction learning model 521 as the prediction learning model 421 in the storage unit 42. This eliminates the need to generate the prediction learning model 421 in the gas concentration prediction device 40, so that the load on the control unit 41 can be reduced.

Further, it is also possible to realize the same function as the prediction unit 411 in the control unit 51 of the learning server 50. In this case, the storage unit 52 may store a program that realizes the function of the prediction unit 411. Thereby, in the learning server 50, the function executed by the gas concentration prediction device 40, that is, the derivation of the concentration prediction value can be realized. In other words, it is also possible to integrally configure the learning server 50 and the gas concentration prediction device 40, and transmit the information of the concentration prediction value derived from the learning server 50 to the waste treatment facility 1 via the network 2. Is. As a result, the processing load in the waste treatment facility 1 can be reduced.

(Drug supply control method)
Next, a drug supply control method for controlling the amount of the drug supplied to the exhaust gas duct 130 by using the gas concentration prediction device 40 described above will be described. FIG. 4 is a diagram for explaining a drug supply control method according to the present embodiment.

As shown in FIG. 4, first, at the start of operation, the characteristic amount of the combustion state, the information on the presence / absence of the soot blow operation, and various process data (hereinafter, various types) acquired by the combustion control device 31 during the operation of the incinerator 100. Process data (collectively referred to as process data) is transmitted from the combustion control device 31 to the gas concentration prediction device 40. The gas concentration prediction device 40 stores the acquired various process data in the process data DB 423 of the storage unit 42. Further, the measured value of the pretreatment acid gas concentration measured by the upstream acid gas concentration meter 34 is transmitted to the gas concentration prediction device 40 and stored in the gas concentration DB 422.

(Process data acquisition process)
In the gas concentration prediction device 40, the prediction unit 411 reads the program of the prediction learning model 421, and acquires various acquired process data and the measured value of the acid gas concentration before processing from the storage unit 42.

(Prediction processing of acid gas concentration before treatment)
The prediction unit 411 performs prediction processing for deriving a predicted value of the concentration of the pre-treatment acid gas after the prediction time based on the input various process data and the pre-treatment acid gas concentration. The control unit 41 of the gas concentration prediction device 40 outputs the information of the concentration predicted value after the prediction time to the drug supply control device 32 as the drug supply control unit.

(Drug amount calculation process)
When the control unit 321 of the drug supply control device 32 acquires the concentration prediction value from the gas concentration prediction device 40, the acquired concentration prediction value is stored in the storage unit 322. Further, the drug supply control device 32 acquires the measured value of the treated acid gas concentration from the downstream acid gas concentration meter 35 and stores it in the storage unit 322. Subsequently, the chemical amount calculation unit 324 calculates the chemical amount to be supplied to the exhaust gas duct 130 based on the concentration predicted value read from the storage unit 322. The drug amount calculation unit 324 may calculate the drug amount based on the predicted concentration value and the measured value of the acid gas concentration after treatment. The drug amount calculation unit 324 generates a supply amount control value for the drug amount to be supplied to the exhaust gas duct 130 based on the calculated value of the drug amount, and outputs the supply amount control value to the drug supply unit 33.

(Drug supply processing)
The drug supply unit 33 supplies an amount of drug based on the input supply amount control value to the exhaust gas duct 130 through the supply port 131. In the exhaust gas duct 130, the reactions of the reaction formulas (1) to (3) described above occur and the acid gas concentration is reduced.

(Acid gas concentration after treatment)
The acid gas concentration after the treatment is measured by the downstream acid gas concentration meter 35 with respect to the exhaust gas treated by the dust collector 140. The measured acid gas concentration after processing is supplied to the gas concentration prediction device 40 and stored in the gas concentration DB 422, while being supplied to the drug supply control device 32 and stored in the storage unit 322. Exhaust gas is purified by various treatments and released into the atmosphere. As a result, the drug supply control process is executed. The drug supply control process is repeatedly executed while the exhaust gas treatment continues.

(Update of predictive learning model)
Further, in the drug supply control process executed as described above, various process data acquired from the combustion control device 31 are accumulated in the process data DB 423, and the measured values of the acid gas concentration before the treatment and the acid gas concentration after the treatment are measured. Is accumulated in the gas concentration DB422. The learning unit 412 in the control unit 41 of the gas concentration prediction device 40 can appropriately update the prediction learning model 421 using the accumulated various process data and the gas concentration as teacher data. The predictive learning model 421 may be updated at a frequency of each predetermined period, and the root mean square error (RSME) between the measured value of the acid gas concentration before treatment and the predicted concentration value is at the time of update. It may be performed at a certain ratio, for example, 30% or more larger than the RSME of.

Since acid gas is generated by the combustion of waste, it is considered that the acid gas concentration can be predicted if the combustion condition can be estimated and the change in the combustion condition can be predicted. However, due to the complexity of the combustion process, it has been difficult to predict the acid gas concentration. On the other hand, according to the above-described embodiment, the acid gas concentration is predicted by the gas concentration predictor 40 from various process data measured in the incinerator 100, and the drug is based on the predicted increase / decrease in the acid gas concentration. The supply amount can be adjusted. As a result, it is possible to reduce the amount of the drug supplied and suppress the excessive input of the drug as compared with the conventional case. In the present invention, it is possible to predict the acid gas concentration by making predictions from past process data using machine learning.

Although one embodiment of the present invention has been specifically described above, the present invention is not limited to the above-mentioned one embodiment, and various modifications based on the technical idea of the present invention are possible. For example, the numerical values given in the above-described embodiment are merely examples, and different numerical values may be used if necessary. The invention is not limited.

For example, in the above-described embodiment, the prediction learning model 421 is stored in the storage unit 42 of the gas concentration prediction device 40 provided in the waste treatment facility 1, but of another server capable of communicating through the network 2. It is also possible to store it in the storage unit. That is, it is also possible to store the prediction learning model 421 in a prediction server capable of communicating with the drug supply control device 32 via the network 2. In this case, the control unit of the prediction server acquires various input parameters such as process data from the above-mentioned combustion control device 31, gas densitometers 34, 35, etc. in response to the request from the drug supply control device 32. , The predicted concentration value after the predicted time is derived and transmitted to the drug supply control device 32. In other words, the control unit having the function of the prediction unit 411 may be provided in an information processing device separate from the waste treatment facility 1 capable of communicating via the network 2. Further, the prediction unit 411 and the learning unit 412 may be provided in different devices capable of communicating with each other via the network 2.

Further, for example, in the above-described embodiment, deep learning using a neural network in machine learning is used as an example of numerical prediction, but numerical prediction based on other methods may be performed. For example, the following three types of methods can be adopted. First, in time series prediction using a recurrent neural network, methods such as LSTM and GRU can be adopted. Second, supervised learning using reflexive machine learning can be adopted. Machine learning includes, for example, gradient boosting such as XGBOOST and LIGHTGBM, bagging such as random forest, regularized linear regression such as ELASTICNET regression, PLS regression, orthogonal matching tracking, support vector machine, decision tree, naive bays, k-nearest neighbor method. You may use the method such as. Further, an ensemble model combining these plurality of methods, stacking, and the like may be performed. When these methods are adopted, a feature amount obtained by processing sensor data into a form including time-series information may be used as an explanatory variable. There are a plurality of types of feature quantities depending on the window size, time delay, aggregate function, etc. For example, a three-minute moving average of acid gas concentration may be used as the feature quantity. Further, not only regression but also classification may be performed and the result may be used for regression, or semi-supervised learning may be used instead of supervised learning. Thirdly, a method based on statistical modeling, for example, a state space model such as an ARIMA model or a linear Gaussian state space model using a Kalman filter may be adopted.

Further, for example, in the above-described embodiment, an example in which a grate incinerator having a stepped wall is used as the incinerator has been described, but the incinerator is not necessarily limited to the grate incinerator.

(recoding media)
In one of the above embodiments, a program for causing the combustion control device 31, the drug supply control device 32, or the gas concentration prediction device 40 to execute these processing methods is provided by a device such as a computer or other machine or a wearable device (hereinafter, a computer or the like). ,) Can be recorded on a readable recording medium. By having a computer or the like read and execute the program of this recording medium, the computer or the like functions as a mobile control device. Here, a recording medium that can be read by a computer or the like is a non-temporary recording medium that can store information such as data and programs by electrical, magnetic, optical, mechanical, or chemical action and can be read from a computer or the like. Recording medium. Among such recording media, those that can be removed from a computer or the like include, for example, a memory such as a flexible disk, a magneto-optical disk, a CD-ROM, a CD-R / W, a DVD, a BD, a DAT, a magnetic tape, or a flash memory. There are cards and so on. Further, as a recording medium fixed to a computer or the like, there are a hard disk, a ROM, and the like. Further, the SSD can be used as a recording medium that can be removed from a computer or the like, or as a recording medium fixed to the computer or the like.

Further, the program to be executed by the combustion control device 31, the drug supply control device 32, and the gas concentration prediction device 40 according to the embodiment is stored on a computer connected to a network such as the Internet and downloaded via the network. It may be configured to provide.

(Other embodiments)
In one embodiment, the above-mentioned "part" can be read as "circuit" or the like. For example, the control unit can be read as a control circuit.

In the description of the drug supply control method in the present specification, the context of the treatment is clarified by using expressions such as "first", "after", and "continued", but in order to implement the present embodiment. The order of processing required for is not uniquely determined by those expressions. That is, the order of processing in the drug supply control method described in the present specification can be changed within a consistent range.

Further effects and variations can be easily derived by those skilled in the art. The broader aspects of the present disclosure are not limited to the particular details and representative embodiments described and described above. Thus, various modifications can be made without departing from the spirit or scope of the overall concept of the invention as defined by the attached claims and their equivalents.

1 Waste treatment facility 2 Network 30 Control device group 31 Combustion control device 32 Drug supply control device 33 Drug supply unit 34 Upstream acid gas concentration meter 35 Downstream acid gas concentration meter 40 Gas concentration prediction device 41, 51, 311, 321 Control unit 42, 52, 312,322 Storage unit 43,53 Input unit 44,54 Output unit 45,55,323 Communication unit 50 Learning server 100 Incinerator 101 Boiler 102 Waste input port 103 Waste supply device 104 Grate 105 Ash fall Port 106 Combustion air blower 107 Boiler outlet 109 Boiler 109a Heat exchanger 109b Steam drum 110 Secondary air blow port 111 Secondary air blower 112 Waste supply unit 113 Step wall 114 Combustion air damper 114a, 114b, 114c, 114d Fire Air damper for under-grid combustion 116 Intermediate ceiling 117 Combustion chamber gas thermometer 118 Main flue gas thermometer 119 Fuel outlet lower gas thermometer 120 Furnace outlet middle gas thermometer 121 Boiler outlet gas thermometer 122 Boiler outlet oxygen concentration meter 123 Gas Densitometer 124 Exhaust flow meter 125 Steam flow meter 126 Image pickup unit 130, 150 Exhaust gas duct 131 Supply port 140 Dust collector 160 Chimney 324 Chemical amount calculation unit 411 Prediction unit 421,511 Learning unit 421,521 Prediction learning model 422 Gas concentration DB
423 Process data DB
522 big data

Claims (12)

An information processing device equipped with a control unit that predicts the concentration or amount of substance of the acid gas in the exhaust gas including the acid gas discharged from the waste incinerator that incinerates the waste.
The control unit
The measured value of the concentration or the amount of substance of the acid gas is acquired and stored in the storage unit as the measured value of the acid gas.
Information related to the operation in the waste incinerator is acquired from the waste incinerator and stored as process data in the storage unit.
Based on the acid gas measurement value at a predetermined time point and the process data read from the storage unit, the acid gas concentration or the amount of substance after a predetermined prediction time is predicted from the predetermined time point, and the concentration predicted value is obtained. Information processing device to output. The control unit
The acid gas measurement value and the process data at a predetermined time point are acquired from the storage unit as input parameters, and the acid gas measurement value and the process data read from the storage unit are input to the prediction learning model.
The predicted concentration value is output as an output parameter,
The prediction learning model uses the measured value of the concentration or the amount of the acid gas and the process data as input parameters for learning in a predetermined period, and the prediction is performed from the predetermined time point when the acid gas measured value and the process data are acquired. The information processing apparatus according to claim 1, which is a learning model generated by machine learning using an input / output data set using the acid gas measurement value after a lapse of time as a learning output parameter. The information processing according to claim 1 or 2, wherein the exhaust gas treatment unit that executes the exhaust gas treatment on the exhaust gas predicts the concentration or the amount of the acid gas contained in the exhaust gas before the exhaust gas treatment is executed. Device. The waste incinerator comprises a grate for moving the waste and a steam generator for generating steam.
The process data includes temperature, oxygen concentration, NO _x concentration and flow rate in the exhaust gas, volume and bulk density in the waste, velocity in the grate, and subgrate air pressure, and steam generation. The information processing apparatus according to any one of claims 1 to 3, which comprises at least one kind of physical quantity selected from the pressure and temperature at the outlet of the unit. The waste incinerator includes an image pickup unit that images an area containing the waste in the waste incinerator.
The process data is a feature amount obtained from at least one of the combustion image data indicating the combustion state of the flame captured by the image pickup unit and the transmission image data indicating the state in which the flame is transmitted based on the thermal image information. The information processing apparatus according to any one of claims 1 to 4, which includes the information processing apparatus. The waste incinerator is provided with a steam generator that generates steam.
The information processing apparatus according to any one of claims 1 to 5, wherein the process data includes information on the presence or absence of a soot blow operation in the steam generating unit. The information processing apparatus according to any one of claims 1 to 6, wherein the acid gas is hydrogen chloride gas. An information processing method executed by an information processing apparatus equipped with a control unit for predicting the concentration or amount of substance of the acidic gas in the exhaust gas containing the acidic gas discharged from the waste incinerator that incinerates the waste.
The control unit
The measured value of the concentration or the amount of substance of the acid gas is acquired and stored in the storage unit as the measured value of the acid gas.
Information related to the operation in the waste incinerator is acquired from the waste incinerator and stored as process data in the storage unit.
Based on the acid gas measurement value at a predetermined time point read from the storage unit and the process data, the acid gas concentration or the amount of substance after a predetermined prediction time is predicted from the predetermined time point, and the concentration predicted value is output. Information processing method. An information processing device equipped with a control unit that predicts the concentration or amount of substance of the acid gas in the exhaust gas including the acid gas discharged from the waste incinerator that incinerates the waste.
The measured value of the concentration or the amount of substance of the acid gas is acquired and stored in the storage unit as the measured value of the acid gas.
Information related to the operation in the waste incinerator is acquired from the waste incinerator and stored as process data in the storage unit.
Based on the acid gas measurement value at a predetermined time point read from the storage unit and the process data, the concentration or substance amount of the acid gas after a predetermined prediction time from the predetermined time point is predicted, and the concentration prediction value is output. A program that lets you do what you do. A chemical supply device that supplies chemicals to the exhaust gas before the exhaust gas treatment is executed by the exhaust gas treatment unit that executes the exhaust gas treatment on the exhaust gas containing acid gas discharged from the waste incinerator. hand,
A drug supply unit that supplies chemicals to the exhaust gas before the exhaust gas treatment is executed, and
A drug supply control unit that outputs a supply amount control value that indicates the supply amount of the drug to the drug supply unit is provided.
The drug supply control unit is
The predicted concentration value output from the information processing apparatus according to any one of claims 1 to 7 is acquired, stored in the storage unit, and stored.
A drug supply device that acquires the concentration prediction value from the storage unit and derives the supply amount control value based on the concentration prediction value. An exhaust gas treatment device that performs exhaust gas treatment on exhaust gas containing acid gas discharged from a waste incinerator that incinerates waste.
The exhaust gas treatment unit provided in the flue of the exhaust gas and
A drug supply unit that supplies chemicals to the upstream side of the exhaust gas treatment unit along the flow direction of the exhaust gas,
A drug supply control unit that outputs a supply amount control value that indicates the supply amount of the drug to the drug supply unit is provided.
The drug supply control unit is
The predicted concentration value output from the information processing apparatus according to any one of claims 1 to 7 is acquired, stored in the storage unit, and stored.
An exhaust gas treatment device that acquires the concentration predicted value from the storage unit and derives the supply amount control value based on the concentration predicted value. It is an exhaust gas treatment method that executes exhaust gas treatment for exhaust gas containing acid gas discharged from a waste incinerator that incinerates waste.
The exhaust gas treatment process performed in the exhaust gas treatment section provided in the flue of the exhaust gas,
A drug supply process for supplying a drug from a drug supply unit configured to be able to supply the drug to the upstream side of the exhaust gas treatment unit along the flow direction of the exhaust gas.
The drug supply control unit includes a drug supply control step of outputting a supply amount control value instructing the drug supply unit to supply the drug.
The drug supply control step is
The drug supply control unit acquires the concentration predicted value output from the information processing apparatus according to any one of claims 1 to 7 and stores it in the storage unit, and acquires the concentration predicted value from the storage unit. A method for treating exhaust gas, which comprises a step of deriving the supply amount control value based on the predicted concentration value.

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