WO2022034738A1 - 異常診断装置及びガス化システム - Google Patents
異常診断装置及びガス化システム Download PDFInfo
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- WO2022034738A1 WO2022034738A1 PCT/JP2021/022734 JP2021022734W WO2022034738A1 WO 2022034738 A1 WO2022034738 A1 WO 2022034738A1 JP 2021022734 W JP2021022734 W JP 2021022734W WO 2022034738 A1 WO2022034738 A1 WO 2022034738A1
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- gasification system
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- 230000005856 abnormality Effects 0.000 title claims description 54
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
Definitions
- the present invention relates to an abnormality diagnostic device and a gasification system.
- Patent Document 1 discloses an abnormality diagnosis method and an abnormality diagnosis system.
- the abnormality diagnosis method in Patent Document 1 measures a model creation step for creating a simulation model of a monitored object, an operation start step for starting the operation of the monitored object, and an internal state quantity in the operating state of the monitored object.
- a measurement step that extracts the measured value
- a prediction step that inputs the same control input value as the operating state of the monitored object into the simulation model, and calculates the predicted value of the internal state amount of the monitored object, and the measured value and prediction.
- It includes a Maharanobis distance calculation step for calculating the Maharanobis distance from the difference from the value, and an abnormality diagnosis step for diagnosing whether or not the operating state of the monitored object is abnormal based on the Maharanobis distance.
- Patent Document 2 discloses a simulation device and a simulation method.
- the simulation device in Patent Document 2 is a simulation device that predicts the operating state of an actual process, and the adjustment parameters of the simulation model set in the synchronization of the operating state by the tracking simulator device are set under the operating conditions obtained from the actual plant.
- a parameter storage unit that accumulates in association with the information in the above, a process simulator unit that predicts the operating state using a simulation model based on the operating conditions of the prediction target, and an adjustment parameter setting unit that dynamically sets the adjustment parameters of the simulation model.
- the adjustment parameter setting unit obtains the adjustment parameter associated with the information of the operation condition similar to the operation condition to be predicted from the parameter storage unit, and sets the adjustment parameter of the simulation model based on this adjustment parameter. It is something to do.
- this gasification system produces a gaseous fuel (gasification gas) such as methane gas as a product by gasifying a solid fuel (raw material) such as biomass by thermal decomposition and reduction reaction. It is known that the operational stability of such a gasification system is affected by the water content of the raw material, the gasification temperature, and the like. In a gasification system, in order to stably generate gasified gas, it is extremely important to optimally set operating parameters according to the raw material.
- each operation amount of the gasification system is controlled by using well-known PID control (proportional / integral / differential control), and the operating parameters are preset limit values (upper limit value and upper limit value). If it deviates from the lower limit value), it is determined that the operating state of the gasification system has reached an abnormal state, and an alarm is output. Therefore, the conventional gasification system has a problem that the operation abnormality of the gasification system cannot be predicted in advance.
- PID control proportional / integral / differential control
- the operating parameters are preset limit values (upper limit value and upper limit value). If it deviates from the lower limit value), it is determined that the operating state of the gasification system has reached an abnormal state, and an alarm is output. Therefore, the conventional gasification system has a problem that the operation abnormality of the gasification system cannot be predicted in advance.
- the present invention has been made in view of the above circumstances, and an object of the present invention is to predict in advance an operation abnormality of a gasification system.
- the gasification system is abnormal based on the correlation between a specific process value in the gasification system and a specific component concentration in the gasification gas generated by the gasification system. It is provided with an evaluation means for evaluating whether or not there is a tendency toward gasification, and a notification means for notifying the evaluation result of the evaluation means to the outside.
- the evaluation means may include a temperature predicting means for obtaining a predicted value of the process value and a concentration predicting means for obtaining a predicted value of the component concentration, and the difference between the predicted value and the measured value of the process value and the said. Whether the gasification system tends to be abnormal by comparing the distance evaluation index given by the difference between the predicted value of the component concentration and the measured value with the distance evaluation index obtained at the normal time of the gasification system. You may evaluate whether or not.
- the temperature predicting means may obtain a predicted value of the process value using the physical model of the gasification system.
- the concentration predicting means may obtain a predicted value of the component concentration using a trained model of the gasification system.
- the evaluation means may evaluate whether or not the gasification system tends to be abnormal when the predicted value of the component concentration differs from the measured value of the component concentration by a predetermined amount or more.
- the process value may be the gasification temperature, and the component concentration may be the methane concentration.
- Another aspect of the present invention is a gasification system, which comprises the above-mentioned abnormality diagnostic device.
- This two-tower gasification furnace T includes a gasification furnace 1, a combustion furnace 2, a first cyclone 3 and a second cyclone 4 as main components, and gas fuel (gas) from a predetermined raw material N input from the outside. Gasification) is manufactured.
- gasification furnace T corresponds to the gasification system according to the present invention.
- the raw material N in this embodiment is a solid fuel such as coal or biomass.
- the above-mentioned coal is low-grade coal such as lignite and subbituminous coal in addition to general coal.
- the biomass is, for example, woody biomass such as thinned wood, or resource crop-based biomass such as sugar cane.
- Such raw material N is charged into the two-tower gasification furnace T in a state where the particle size is adjusted to a predetermined particle size.
- the gasification furnace 1 is a pyrolysis furnace that generates gasification gas by pyrolyzing and reducing the above-mentioned raw material N. ..
- the gasification furnace 1 forms a gasification chamber Rg including an internal space having a predetermined capacity. Further, as shown in the figure, the gasification furnace 1 includes a raw material input port 1a, a heat medium receiving port 1b, a bubble fluidized bed 1c, a first discharge port 1d, and a second discharge port 1e.
- the raw material charging port 1a is an opening for charging the raw material N into the gasification chamber Rg, and is provided on the side of the gasification furnace 1 as shown in the figure. That is, the raw material input port 1a is provided at a position where the raw material can be dropped onto the bubble fluidized bed 1c formed at the bottom of the gasification chamber Rg, and the raw material N input from the outside is placed in the bubble fluidized bed 1c. Drop it up.
- the heat medium receiving port 1b is an opening for receiving the high-temperature granular heat medium P (heat medium) flowing in from the first cyclone 3 into the gasification chamber Rg, and is the upper part of the gasification furnace 1 and in the horizontal direction as shown in the figure. It is provided at one end of the above. That is, the heat medium receiving port 1b allows the high-temperature granular heat medium P or the like flowing from the first cyclone 3 to flow into the gasification chamber Rg from above and one end.
- the granular heat medium P is a granular (solid) heat medium having a predetermined particle size, and is, for example, sand having a predetermined particle size.
- the bubble fluidized bed 1c is formed over the entire bottom of the gasification chamber Rg, and the raw material N, the granular heat medium P, and the like are fluidized by the steam J injected from the bottom to the top.
- the bottom of the gasification chamber Rg is provided with a wind box that restricts the passage of the raw material N, the granular heat medium P, and the like and allows the steam J to pass through.
- the raw material N and the granular heat medium P located on such a wind box are fluidized using steam J.
- a pyrolysis gas is generated by thermally decomposing the raw material N using a high-temperature granular heat medium P as a heat source, and the pyrolysis gas is generated by steam J.
- a gas component such as gasification gas G is generated.
- solid components such as char (thermally decomposed char) and tar are generated by the thermal decomposition of the raw material N.
- the pyrolysis char is a substance containing carbon (C) as a main component and can function as a fuel.
- the first discharge port 1d is provided on the side of the gasification furnace 1 as shown in the figure, and is an opening that mainly discharges the solid component and the granular heat medium P to the combustion furnace 2. That is, the first discharge port 1d is provided on the side portion of the gasification furnace 1 to selectively discharge the solid component and the granular heat medium P having a specific gravity larger than that of the gas component to the combustion furnace 2.
- the second discharge port 1e is an opening provided in the upper part of the gasification furnace 1 as shown in the figure, and mainly contains a gas component such as gasification gas G as a second. Discharge to cyclone 4. That is, the second discharge port 1e is provided in the upper part of the gasification furnace 1 to selectively discharge a gas component such as gasification gas G having a specific gravity smaller than that of the solid component to the second cyclone 4.
- the gas component contains a small amount of combustion ash (solid) having a relatively small specific gravity.
- the raw material input port 1a and the heat medium receiving port 1b described above are arranged at relatively close positions as shown in the figure. Further, although the first discharge port 1d and the second discharge port 1e described above are arranged at relatively close positions as shown in the figure, they are arranged at positions sufficiently separated from the raw material input port 1a and the heat medium receiving port 1b. Has been done. Such a separation arrangement between the raw material input port 1a and the heat medium receiving port 1b and the first discharge port 1d and the second discharge port 1e is for ensuring a sufficient reaction distance in the gasification chamber Rg.
- the raw material N and the granular heat medium P charged into the gasification chamber Rg are transported from one end to the other while being fluidized by steam J. Then, in the gasification furnace 1, the gasification gas G is generated by the progress of the thermal decomposition reaction of the raw material N and the reduction reaction of the thermal decomposition gas during such transportation.
- the combustion furnace 2 is a heating furnace that heats the granular heat medium P by burning the pyrolysis char flowing from the gasification furnace 1, and the internal space thereof forms the combustion chamber Rb.
- the combustion furnace 2 generates high-temperature combustion gas and combustion ash by combustion of the pyrolysis char, and uses this combustion gas as a heat source to heat the granular heat medium P flowing from the gasification furnace 1.
- a combustion furnace 2 includes an inlet 2a, a circulating fluidized bed 2b, and an outlet 2c.
- the receiving port 2a is an opening for receiving the solid component from the gasification furnace 1, and is provided on the side of the combustion furnace 2 as shown in the figure. That is, the receiving port 2a is provided at a position where the granular heat medium P can be dropped on the circulating fluidized bed 2b formed at the bottom of the combustion chamber Rb, and the solid component, that is, the granular material received from the gasification furnace 1 is provided. The heat medium P and the pyrolysis char are dropped onto the circulating fluidized bed 2b.
- the circulating fluidized bed 2b is formed over the entire bottom of the combustion chamber Rb, and the granular heat medium P and the pyrolysis char are fluidized by the air A injected from the bottom to the top.
- the bottom of the combustion chamber Rb is provided with a plurality of air diffusers that blow air A upward.
- the granular heat medium P and the pyrolysis char located on the air diffuser are fluidized, and the pyrolysis char is burned by acting on the pyrolysis char using air A as an oxidant. ..
- combustion chamber Rb provided with such a circulating fluidized bed 2b, high-temperature combustion gas is generated by burning the pyrolysis char in the presence of air A. Further, in the combustion chamber Rb, the granular heat medium P is heated by exchanging heat with the granular heat medium P by the high-temperature combustion gas. In such a combustion chamber Rb, the combustion gas and the combustion ash become an ascending flow and flow from the lower part to the upper part, and the granular heat medium P is blown up from the lower part to the upper part by the ascending flow.
- the discharge port 2c is an opening for discharging the combustion gas, combustion ash, and granular heat medium P toward the first cyclone 3, and is provided in the upper part of the combustion furnace 2 as shown in the figure. That is, the discharge port 2c is provided in the upper part of the combustion furnace 2 to discharge the granular heat medium P heated to a sufficiently high temperature to the first cyclone 3 together with the combustion gas and the combustion ash.
- the first cyclone 3 is a solid air separation device that separates the combustion gas flowing from the combustion furnace 2 and the granular heat medium P into solid air.
- the first cyclone 3 takes in the combustion gas and the granular heat medium P from the side to form a downward swirling flow, and separates the combustion gas, the combustion ash, and the granular heat medium P by utilizing the difference in specific gravity.
- Such a first cyclone 3 includes a first discharge port 3a and a second discharge port 3b.
- the first discharge port 3a is an opening for discharging the combustion ash and the granular heat medium P, which are solid components, toward the gasification furnace 1, and is provided at the bottom (lower part) of the first cyclone 3 as shown in the figure. .. Since the first discharge port 3a is provided at the bottom of the first cyclone 3, the combustion ash and the granular heat medium P having a relatively large specific gravity among the combustion gas and the granular heat medium P are discharged.
- the second discharge port 3b is an opening for discharging the combustion gas to the outside, and is provided at the center of the first cyclone 3 in the horizontal direction as shown in the figure. Since the second discharge port 3b is provided at the center of the first cyclone 3 in the horizontal direction, the combustion gas (gas) having a relatively small specific gravity is discharged to the outside.
- the second cyclone 4 is a solid air separation device that separates gas components such as gasified gas G flowing in from the second discharge port 1e of the gasification furnace 1 and combustion ash.
- the second cyclone 4 takes in the gas component and the combustion ash from the side to form a downward swirling flow, and separates the gas component and the combustion ash by utilizing the difference in specific gravity.
- Such a second cyclone 4 includes a discharge valve 4a and a discharge port 4b.
- the discharge valve 4a is an on-off valve that discharges combustion ash, which is a solid component, to the outside, and is provided at the bottom (lower part) of the second cyclone 4 as shown in the figure. Since the discharge valve 4a is provided at the bottom of the second cyclone 4, the combustion ash having a specific gravity larger than that of the gas component is selectively discharged.
- the discharge port 4b is an opening for discharging a gas component such as gasification gas G to the outside, and is provided at the center of the second cyclone 4 in the horizontal direction as shown in the figure. Since the discharge port 4b is provided at the center of the second cyclone 4 in the horizontal direction, the gas component having a relatively small specific gravity is discharged to the outside.
- the gasification furnace 1 In gasification chamber Rg
- a gas component containing gasification gas G is generated from the raw material N.
- the combustion ash which is a solid impurity is selectively removed.
- the gasification gas G containing some gas impurities is supplied to the outside as a product of the two-tower gasification furnace T.
- various operation amounts are adjusted by a system control device (not shown). That is, in the two-tower gasification furnace T, the supply amount of steam J in the bubble flow layer 1c (steam flow rate), the flow velocity of steam J (steam flow rate) and the layer temperature (gasification temperature), and the air A in the circulating flow layer 2b.
- Various sensors (not shown) for detecting various process amounts such as the supply amount (air flow rate) of the gas are provided.
- the system control device operates the two-tower gasifier T stably by PID controlling the operation amounts such as steam flow rate, steam flow rate, gasification temperature and air flow rate based on the detected values (controlled amounts) of these various sensors.
- the abnormality diagnosis device D diagnoses the above-mentioned two-tower gasification furnace T, and includes a storage device 5, an operation device 6, and an arithmetic unit 7 as shown in the figure.
- This abnormality diagnosis device D is incidentally provided to the two-tower gasification furnace T as ancillary equipment to assist the system control device.
- the storage device 5 is a non-volatile storage device such as a hard disk, and stores at least the trained model 5a and the physical model 5b. Further, the storage device 5 stores an abnormality diagnosis program as one of the application programs executed by the operation device 6. Such a storage device 5 provides the operation device 6 with a learned model 5a, a physical model 5b, and an abnormality diagnosis program based on a read instruction input from the operation device 6.
- the trained model 5a includes a database (teacher database) in which a large number of teacher data showing the relationship between a specific process value in the normal state of the two-tower gasifier T and a specific component concentration in the gasified gas G are registered. ing.
- This trained model 5a is a mathematical model (mathematical model) obtained by machine learning the teacher data, and when an actually measured value of a process value is input (designated), a predicted value of a specific component concentration corresponding to the actually measured value is input (designated). Is output.
- a trained model 5a for example, when the measured values of the steam flow rate, the steam flow rate, the gasification temperature and the air flow rate, and the composition of the raw material N (raw material composition) are input, the component concentration of the characteristic corresponding to these measured values is input. As a result, the predicted value of the concentration (methane concentration) of the methane gas (CH4), which is the main component of the gasification gas G, is output. This methane concentration corresponds to the specific component concentration in the present invention.
- the physical model 5b is a mathematical model (mathematical model) that simulates the behavior of the two-tower gasifier T under normal conditions.
- the physical model 5b outputs the predicted value of the process value different from the specific process value for the two-tower gasifier T in the normal state.
- the gasification temperature corresponding to the composition is output. This gasification temperature corresponds to the specific process value in the present invention.
- the gasification temperature which is a specific process value, that is, the layer temperature of the bubble fluidized bed 1c is a physical quantity having a relatively good correlation with the methane concentration of the gasification gas G, which is a specific component concentration.
- the abnormality diagnosis device D pays attention to such a correlation between the gasification temperature and the methane concentration, and evaluates the cooperation of the two-tower gasification furnace T in a metric space based on the correlation. By doing so, the tendency of gasification is identified.
- the operation device 6 is an input device operated by the user of the abnormality diagnosis device D, and is a pointing device such as a keyboard and / or a mouse.
- the user causes the abnormality diagnosis device D to start the abnormality diagnosis process based on the abnormality diagnosis program by inputting various operation instructions to the operation device 6.
- the arithmetic unit 7 is an information processing unit mainly composed of a CPU (Central Processing Unit), and is a two-tower gasifier T (gasification system) by executing an abnormality diagnosis program read from the storage device 5 on the CPU. Make an abnormality diagnosis. Further, the arithmetic unit 7 notifies the outside of the diagnosis result, that is, whether or not the two-tower gasifier T has an abnormal tendency.
- a CPU Central Processing Unit
- T gasification system
- the arithmetic unit 7 has a trained model 5a and a physical model 5b read from the storage device 5 in addition to the abnormality diagnosis program, and specific process values acquired from the system control device, that is, raw material composition and steam.
- An abnormality diagnosis of the two-tower gasification furnace T is performed based on the flow rate, steam flow rate, gasification temperature, and air flow rate.
- the arithmetic unit 7 also updates the learned model 5a stored in the storage device 5. That is, when the arithmetic unit 7 determines that the two-tower gasification furnace T is normal based on the above-mentioned various process values, the measured values of the raw material composition, steam flow rate, steam flow rate, gasification temperature and air flow rate, and methane.
- the trained model 5a is updated by incorporating the data showing the relationship with the calculated concentration value into the trained model 5a as new teaching data.
- Such a storage device 5, an operation device 6, and a calculation device 7 are used for the gasification temperature (specific process value) in the two-tower gasification furnace T and the gasification gas G output from the two-tower gasification furnace T. It constitutes an evaluation means for evaluating whether or not the two-tower gasifier T is heading toward an abnormal tendency based on the correlation with the methane concentration (specific component concentration). Further, the arithmetic unit 7 corresponds to a notifying means for notifying the evaluation result of the evaluation means to the outside.
- the arithmetic unit 7 starts the abnormality diagnosis process of the two-tower type gasifier T based on the abnormality diagnosis program.
- the arithmetic unit 7 first acquires the measured values of the raw material composition, steam flow rate, steam flow rate, gasification temperature, and air flow rate from the system control device (step S1).
- the arithmetic unit 7 analyzes the methane concentration based on the measured value of such a process value, and acquires the analyzed value as the measured value Cr of the methane concentration (step S2).
- Acquisition of such measured value Cr (analyzed value) of methane concentration is, for example, past actual data showing the relationship between a specific process value (raw material composition, steam flow rate, steam flow rate, gasification temperature and air flow rate) and methane concentration. It is done based on.
- the arithmetic unit 7 inputs the raw material composition, steam flow rate, steam flow rate, gasification temperature, and air flow rate acquired in step S1 into the trained model 5a acquired from the storage device 5, thereby methane after a predetermined time.
- the predicted value Ce of the concentration is acquired (step S3).
- the learned model 5a of the arithmetic unit 7 and the storage device 5 constitutes a concentration predicting means for obtaining a predicted value Ce of the methane concentration.
- the arithmetic unit 7 determines whether or not the predicted value Ce is extremely fluctuating with respect to the methane concentration in the two-tower gasifier T in the normal state with respect to the past normal value (step S4). .. That is, the arithmetic unit 7 determines that the predicted value Ce is extremely fluctuating with respect to the past normal value when the predicted value Ce of the methane concentration exceeds the concentration threshold value Cth, and the predicted value Ce of the methane concentration If does not exceed the concentration threshold Cth, it is determined that the predicted value Ce does not fluctuate extremely. That is, the concentration threshold value Cth is a limit value in the range that the past normal value can take.
- step S4 determines whether the predicted value Ce shows a change exceeding the concentration threshold value Cth.
- the arithmetic unit 7 sets the predicted value Te of the gasification temperature to the physical model 5b. Obtained from (step S5).
- the physical model 5b of the arithmetic unit 7 and the storage device 5 constitutes a temperature predicting means for obtaining a predicted value Te of the gasification temperature (process value).
- the arithmetic apparatus 7 determines the raw material composition, steam flow rate, steam flow rate, and air flow rate excluding the gasification temperature among the measured values of the raw material composition, steam flow rate, steam flow rate, gasification temperature, and air flow rate acquired in step S1.
- the gasification temperature corresponding to the raw material composition, steam flow rate, steam flow rate and air flow rate is acquired from the physical model 5b as the predicted value Te of the gasification temperature.
- the arithmetic unit 7 calculates the difference vector Vc regarding the methane concentration by using the measured value Cr of the methane concentration acquired in step S2 and the predicted value Ce of the methane concentration calculated in step S3 (step S6). That is, the arithmetic unit 7 calculates the difference vector Vc by calculating the difference between the actually measured value Cr and the predicted value Ce.
- the arithmetic unit 7 calculates the difference vector Vt regarding the gasification temperature by using the measured value Tr of the gasification temperature acquired in step S1 and the predicted value Te of the gasification temperature calculated in step S5 (step S6). ). That is, the arithmetic unit 7 calculates the difference vector Vt by calculating the difference between the actually measured value Tr and the predicted value Te.
- the arithmetic unit 7 calculates the Mahalanobis distance M using the difference vector Vc of the methane concentration calculated in step S6 and the difference vector Vt of the gasification temperature calculated in step S7 (step S8).
- the Mahalanobis distance M is an amount given by the difference between the measured value Tr and the predicted value Te of the gasification temperature and the difference between the measured value Cr and the predicted value Ce of the methane concentration.
- Such a Mahalanobis distance M corresponds to the distance evaluation index of the present invention.
- This Mahalanobis distance M is well known as a statistical distance concept based on the correlation between multiple variables. Further, in the above-mentioned Patent Document 1, the Mahalanobis distance, which is a concept similar to the Mahalanobis distance M, is described in detail. For these reasons, the details of the method for calculating the Mahalanobis distance M will be omitted here, but the Mahalanobis distance M is calculated by using the covariance matrix related to the teacher data used for learning the trained model 5a.
- the arithmetic unit 7 determines whether or not the two-tower gasifier T reaches an abnormal state after a predetermined time by comparing the Mahalanobis distance M calculated this time with the predetermined distance threshold value Mth. (Step S9).
- the distance threshold value Mth is a limit value of the Mahalanobis distance M set based on the past Mahalanobis distance in the normal state of the two-tower gasifier T.
- the arithmetic unit 7 outputs an alarm when the determination in step S9 is "Yes", that is, when the Mahalanobis distance M exceeds the distance threshold value Mth (step S10).
- This alarm is output to an output device such as a display device provided separately and / or a system control device.
- the user of the abnormality diagnosis device D and / and the operator of the two-tower gasifier T can hear the alarm output by the abnormality diagnosis device D before the two-tower gasifier T actually becomes abnormal. It is possible to recognize the tendency of the tower gasifier T to become abnormal.
- step S4 the arithmetic unit 7 repeats the abnormality diagnosis process in steps S1 to S10. That is, the arithmetic unit 7 sequentially acquires the Mahalanobis distance M as time-series data as shown in FIG. 4 by repeating the abnormality diagnosis process at predetermined time intervals based on a preset time schedule. Then, the arithmetic unit 7 sequentially compares the Mahalanobis distance M calculated at each cycle time with the distance threshold value Mth to determine whether or not the two-tower gasifier T reaches an abnormal state in a plurality of cycle times. Monitor over.
- step S11 the arithmetic unit 7 updates the teacher database in the trained model 5a (step S11). That is, in this case, since the two-tower gasifier T is in a normal state, the various process values acquired in step S1 and the measured value Cr of the methane concentration acquired in step S2 are the two-tower gasifier T. It is a state quantity indicating a normal state. Therefore, the above-mentioned process value and the measured value Cr of the methane concentration sufficiently satisfy the eligibility as new teacher data.
- the arithmetic unit 7 in the present embodiment registers the measured values Cr of the various process values and the measured values Cr of the methane concentration described above as new teacher data in the teacher database of the storage device 5.
- the teacher database is updated by such new registration of teacher data.
- machine learning is further enhanced by such an update of the teacher database.
- step S4 when the determination in step S4 is "No", the arithmetic unit 7 in the present embodiment starts the abnormality diagnosis process in the next cycle time without performing the subsequent processes in steps S5 to S11. Therefore, according to the abnormality diagnosis device D according to the present embodiment, it is possible to reduce the calculation load of the calculation device 7 by the amount that the processing of steps S5 to S11 can be omitted.
- the layer temperature (gasification temperature) of the bubble fluidized bed 1c is set to a specific process value
- the methane concentration of the gasification gas G is set to a specific component concentration
- the present invention is limited to this. Not done.
- the correlation changes depending on the behavior of the two-tower gasification furnace T. As long as it is a physical quantity to be used, a process value other than the gasification temperature may be used as a specific process value, and a component concentration other than the methane concentration may be used as a specific component concentration.
- the steam flow rate that is, the flow rate of the water vapor J supplied to the bubble fluidized bed 1c may be set as a specific process value corresponding to the methane concentration (specific component concentration).
- This steam flow rate is a process amount that has a correlation with the methane concentration (specific component concentration) as well as the gasification temperature.
- the gasification temperature instead of the layer temperature of the bubble fluidized bed 1c, the representative temperature of the gasification furnace 1, the upper temperature of the combustion furnace 2, the middle temperature of the combustion furnace 2, and the combustion furnace 2
- the outlet combustion exhaust gas temperature and the outlet methane gas temperature of the gas furnace 1 may be adopted.
- the component concentration hydrogen gas concentration, carbon dioxide concentration or carbon monoxide concentration may be adopted instead of the methane concentration.
- the two-tower gasification furnace T is adopted as the gasification system, but the present invention is not limited to this. That is, a gasification furnace other than the two-tower gasification furnace T may be adopted as the gasification system.
- a gasification furnace other than the two-tower gasification furnace T may be adopted as the gasification system.
- a fluidized bed type gasification system and a fixed bed type gasification system are known, but the present invention is adopted for both a fluidized bed type gasification system and a fixed bed type gasification system. be able to.
- the abnormality diagnosis device D is provided as an incidental device to the two-tower gasification furnace T, but the present invention is not limited to this.
- the abnormality diagnosis device D is arranged at a position separated from the two-tower type gasifier T, that is, the system control device, and the abnormality diagnosis device D and the system control device are connected to each other by using a communication line. Anomalous diagnosis of the formula gasifier T may be performed.
- the abnormality diagnosis of the plurality of two-tower gasifiers T can be performed in parallel (at the same time). It may be done in a time-divided manner. According to such an operation method of the abnormality diagnosis device D, it is possible to improve the operating efficiency of the abnormality diagnosis device D, and thus it is possible to reduce the cost related to the abnormality diagnosis.
- the Mahalanobis distance M is adopted as the distance evaluation index, but the present invention is not limited to this. That is, the abnormal tendency of the two-tower gasifier T may be evaluated using a distance evaluation index other than the Mahalanobis distance M.
- a Air D Abnormality diagnosis device J Steam G Gasification gas N Raw material P Granular heat medium Rb Combustion chamber Rg Gasification chamber T Two-tower gasification furnace (gasification system) 1 Gasification furnace 1a Raw material input port 1b Heat medium inlet 1c Bubble fluidized bed 1d 1st discharge port 1e 2nd discharge port 2 Combustion furnace 2a Inlet 2b Circulation fluidized bed 2c Discharge port 3 1st cyclone 3a 1st discharge port 3b 2nd discharge port 4 2nd cyclone 4a discharge valve 4b discharge port 5 storage device 5a trained model 5b physical model 6 operation device 7 arithmetic unit
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Abstract
Description
最初に、図1を参照して本実施形態における二塔式ガス化炉Tについて説明する。この二塔式ガス化炉Tは、主な構成要素としてガス化炉1、燃焼炉2、第1サイクロン3及び第2サイクロン4を備え、外部から投入された所定の原料Nから気体燃料(ガス化ガス)を製造する。このような二塔式ガス化炉Tは、本発明に係るガス化システムに相当する。
(1)上記実施形態では、気泡流動層1cの層温(ガス化温度)を特定のプロセス値とし、またガス化ガスGのメタン濃度を特定の成分濃度としたが、本発明はこれに限定されない。二塔式ガス化炉T(ガス化システム)に関する入力値としての各種プロセス量及び出力値としてのガス化ガスGの各種成分濃度のうち、二塔式ガス化炉Tの挙動によって相関関係が変化する物理量であれば、ガス化温度以外のプロセス値を特定のプロセス値とし、メタン濃度以外の成分濃度を特定の成分濃度としてもよい。
D 異常診断装置
J 水蒸気
G ガス化ガス
N 原料
P 粒状熱媒
Rb 燃焼室
Rg ガス化室
T 二塔式ガス化炉(ガス化システム)
1 ガス化炉
1a 原料投入口
1b 熱媒受入口
1c 気泡流動層
1d 第1排出口
1e 第2排出口
2 燃焼炉
2a 受入口
2b 循環流動層
2c 排出口
3 第1サイクロン
3a 第1排出口
3b 第2排出口
4 第2サイクロン
4a 排出バルブ
4b 排出口
5 記憶装置
5a 学習済モデル
5b 物理モデル
6 操作装置
7 演算装置
Claims (7)
- ガス化システムにおける特定のプロセス値と前記ガス化システムで生成されるガス化ガスにおける特定の成分濃度との相関関係に基づいて前記ガス化システムが異常化傾向にあるか否かを評価する評価手段と、
該評価手段の評価結果を外部に報知する報知手段と
を備える異常診断装置。 - 前記評価手段は、前記プロセス値の予測値を求める温度予測手段と、前記成分濃度の予測値を求める濃度予測手段とを備え、前記プロセス値の予測値と実測値との差分及び前記成分濃度の予測値と実測値との差分とによって与えられる距離評価指数を前記ガス化システムの正常時に得られた前記距離評価指数と比較することにより、前記ガス化システムが異常化傾向にあるか否かを評価する請求項1記載の異常診断装置。
- 前記温度予測手段は、前記ガス化システムの物理モデルを用いて前記プロセス値の予測値を求める請求項2に記載の異常診断装置。
- 前記濃度予測手段は、前記ガス化システムの学習済モデルを用いて前記成分濃度の予測値を求める請求項2または3に記載の異常診断装置。
- 前記評価手段は、前記成分濃度の予測値が所定の濃度しきい値を超える場合に前記ガス化システムが異常化傾向にあるか否かを評価する請求項1~4のいずれか一項に記載の異常診断装置。
- 前記プロセス値はガス化温度であり、かつ、前記成分濃度はメタン濃度である請求項1~5のいずれか一項に記載の異常診断装置。
- 請求項1~6のいずれか一項に記載の異常診断装置を備えるガス化システム。
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH07260146A (ja) * | 1994-03-18 | 1995-10-13 | Hitachi Ltd | 流動層ボイラの異常検出方法及びその装置 |
JP2006170609A (ja) * | 2006-01-05 | 2006-06-29 | Ebara Corp | 固形廃棄物のガス化並びにガス化燃焼方法 |
JP2008101141A (ja) * | 2006-10-19 | 2008-05-01 | Nippon Steel Engineering Co Ltd | ガス化ガスの利用方法 |
JP2008308534A (ja) * | 2007-06-13 | 2008-12-25 | Nippon Steel Engineering Co Ltd | ガス化ガスの浄化方法及び浄化装置 |
CN102175345A (zh) * | 2011-01-06 | 2011-09-07 | 华东理工大学 | 多喷嘴对置式水煤浆气化炉炉膛温度的软测量方法 |
JP2014173572A (ja) * | 2013-03-12 | 2014-09-22 | Hitachi Ltd | 熱電可変型コジェネレーションシステム |
JP2019184079A (ja) * | 2018-04-02 | 2019-10-24 | 株式会社神戸製鋼所 | ガス化溶融炉プラントの排ガス制御装置、排ガス制御方法、及びプログラム |
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Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH07260146A (ja) * | 1994-03-18 | 1995-10-13 | Hitachi Ltd | 流動層ボイラの異常検出方法及びその装置 |
JP2006170609A (ja) * | 2006-01-05 | 2006-06-29 | Ebara Corp | 固形廃棄物のガス化並びにガス化燃焼方法 |
JP2008101141A (ja) * | 2006-10-19 | 2008-05-01 | Nippon Steel Engineering Co Ltd | ガス化ガスの利用方法 |
JP2008308534A (ja) * | 2007-06-13 | 2008-12-25 | Nippon Steel Engineering Co Ltd | ガス化ガスの浄化方法及び浄化装置 |
CN102175345A (zh) * | 2011-01-06 | 2011-09-07 | 华东理工大学 | 多喷嘴对置式水煤浆气化炉炉膛温度的软测量方法 |
JP2014173572A (ja) * | 2013-03-12 | 2014-09-22 | Hitachi Ltd | 熱電可変型コジェネレーションシステム |
JP2019184079A (ja) * | 2018-04-02 | 2019-10-24 | 株式会社神戸製鋼所 | ガス化溶融炉プラントの排ガス制御装置、排ガス制御方法、及びプログラム |
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