CN110579367A - Fault self-diagnosis system and method for drying bed - Google Patents
Fault self-diagnosis system and method for drying bed Download PDFInfo
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Abstract
the invention provides a fault diagnosis system and a fault diagnosis method for a drying bed, wherein the diagnosis system comprises a data acquisition module, a data analysis module and a fault diagnosis processing module; the data acquisition module is respectively in communication connection with the data analysis module and the fault diagnosis processing module; the data analysis module is also in communication connection with the fault diagnosis processing module; the data acquisition module is used for acquiring the operating parameters of the drying bed and transmitting the operating parameters to the data analysis module and the fault diagnosis processing module; the data analysis module is used for analyzing the operation parameters and establishing a drying bed system model according to the operation parameters; the method comprises the following steps that a dry bed system model establishes a fault diagnosis model according to a given alarm limit value; the fault diagnosis processing module is used for carrying out fault diagnosis according to the operation parameters and the fault diagnosis model, determining a fault reason and outputting a fault processing method; the scheme provided by the invention can effectively avoid the reduction of the treatment capacity of the wastewater treatment system caused by the fault of the drying bed, and ensure the safe and stable operation of the drying bed system.
Description
Technical Field
the invention belongs to the technical field of fault self-diagnosis of a drying bed, and particularly relates to a fault diagnosis system and method of the drying bed.
background
In the existing desulfurization wastewater zero-discharge system, the fluidization condition of a drying bed can be gradually worsened due to the change of the operation condition of the drying bed in the continuous operation process, which is mainly reflected in the change of a bed temperature difference value of the drying bed and an outlet flue gas temperature difference value and a differential pressure of the drying bed, and the temperature difference value and the differential pressure value can change in real time along with the change of operation parameters, so that great troubles are brought to fault judgment of operators, the operation condition of the drying bed can not be timely relieved by taking measures until the drying bed collapses, and great obstacles are caused to the safe and stable operation of a wastewater drying system. Therefore, a system capable of automatically diagnosing the operation state of the drying bed and providing a processing method according to the change of the operation condition is established, and the system has important significance for improving the operation safety and stability of the drying bed.
based on the technical problems of the drying bed in the desulfurization wastewater zero-discharge system, no related solution is provided; there is therefore a pressing need to find effective solutions to the above problems.
Disclosure of Invention
The invention aims to provide a fault diagnosis system and method of a drying bed aiming at the defects in the prior art, and aims to solve the problems that the existing drying bed is unstable in operation and cannot timely solve the fault.
The invention provides a fault diagnosis system of a drying bed, which comprises a data acquisition module, a data analysis module and a fault diagnosis processing module, wherein the data acquisition module is used for acquiring data; the data acquisition module is respectively in communication connection with the data analysis module and the fault diagnosis processing module; the data analysis module is also in communication connection with the fault diagnosis processing module; the data acquisition module is used for acquiring the operating parameters of the drying bed and transmitting the operating parameters to the data analysis module and the fault diagnosis processing module; the data analysis module is used for analyzing the operation parameters and establishing a drying bed system model according to the operation parameters; the method comprises the following steps that a dry bed system model establishes a fault diagnosis model according to a given alarm limit value; and the fault diagnosis processing module is used for carrying out fault diagnosis according to the operation parameters and the fault diagnosis model, determining a fault reason and outputting a fault processing method.
Further, the data acquisition module comprises a measuring instrument and a DCS system; the measuring instrument comprises a thermometer, a flowmeter and a pressure transmitter of the dry bed system; the thermometer is used for detecting the bed temperature of the drying bed, the outlet flue gas temperature of the drying bed and the inlet flue gas temperature of the drying bed; the flowmeter is used for detecting the flue gas flow, the cold air flow and the slurry spraying amount at the inlet of the drying bed; the pressure transmitter is used for detecting the differential pressure of the drying bed.
Further, the drying bed system model takes the selected drying bed filling amount, unit load, drying bed inlet flue gas flow, drying bed inlet flue gas temperature, cold air volume and guniting amount as input amounts of the identification model; and selecting the difference value between the bed temperature of the drying bed and the outlet flue gas temperature of the drying bed and the differential pressure of the drying bed as the output quantity of the identification model.
furthermore, 3-5 different load working conditions of 50% -100% of the full load of the unit can be selected as the unit load; and/or 3-5 different flow working conditions from the lowest flue gas flow to the full air flow can be selected for the flue gas flow at the inlet of the drying bed; and/or the bed temperature of the drying bed fluctuates within +/-15 ℃ of the set temperature value; and/or selecting 3-5 different slurry spraying amount working conditions from the lowest slurry spraying amount to the designed slurry spraying amount according to the slurry spraying amount.
Further, the data analysis module establishes the drying bed system model through self-adaptive control, fuzzy control and neural network control; the dry bed system model includes a plurality of input volumes and a plurality of output volumes.
Furthermore, the alarm limit value of the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed is set to be 5 ℃ ~ 15 ℃, and/or the alarm limit value of the differential pressure of the drying bed is set to be 300pa ~ 500 pa.
further, the fault diagnosis processing module determines the fault reason and outputs a fault processing method according to the real-time operation parameters and the fault diagnosis model of the drying bed acquired by the data acquisition module.
Correspondingly, the invention also provides a fault self-diagnosis method of the drying bed, which is applied to the fault diagnosis system of the drying bed; the method also comprises the following steps:
S1: adding a given amount of filler into the drying bed, selecting various load working conditions between 50% and 100% of the full load of the unit, and normally operating the drying bed; adjusting the flue gas flow at the inlet of the drying bed under each fixed load working condition, adjusting the spraying amount under various working conditions between the minimum flue gas flow and the full air flow, and ensuring that the bed temperature of the drying bed changes within +/-15 ℃ of a set value; selecting various working conditions between the minimum slurry spraying amount and the designed slurry spraying amount; recording the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the differential pressure of the drying bed in real time under each working condition;
S2: the data acquisition module transmits the historical data of each operating parameter in the step S1 to the data analysis module and the fault diagnosis processing module; the data analysis module establishes a drying bed system model according to the operation parameters;
S3: the output value of the drying bed system model is a theoretical operation value; setting a difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and an alarm limit value of the differential pressure of the drying bed, and combining the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the alarm limit value of the differential pressure of the drying bed with a theoretical operation value to obtain a normal operation interval;
s4: the data acquisition module acquires the operation parameters of the drying bed in real time, and inputs the filling amount of the drying bed, the unit load, the flue gas flow at the inlet of the drying bed, the flue gas temperature at the inlet of the drying bed, the cold air volume and the guniting volume into the system model of the drying bed to obtain a model output value;
S5: the fault diagnosis processing module analyzes and confirms the fault reason according to the model input value and reminds an operator to increase and change the operation mode; the set values of the operating parameters can be directly changed in the automatic operating mode of the drying bed.
Further, the step S5 specifically includes:
S51: judging whether the slurry spraying amount is between the lowest slurry spraying amount and the highest slurry spraying amount, if the slurry spraying amount exceeds the interval between the lowest slurry spraying amount and the highest slurry spraying amount, adjusting the corresponding set value of the slurry spraying amount, and alarming to remind an operator; the interval between the lowest slurry spraying amount and the highest slurry spraying amount is 0.4t/h to 1 t/h;
s52: judging whether the flue gas flow at the inlet of the drying bed is larger than the lowest flue gas flow, if so, adjusting a corresponding set value and alarming to remind an operator; the minimum flue gas flow is 5000m3/h；
S53: judging whether the inlet flue gas temperature of the drying bed is higher than the lowest flue gas temperature, if so, adjusting a corresponding set value and alarming to remind an operator; the lowest flue gas temperature is 260 ℃;
S54, judging whether the temperature difference value of the drying bed reaches an alarm limit value setting interval, if so, automatically adjusting the washing time and the washing interval and alarming to remind an operator, wherein the alarm limit value setting interval of the temperature difference value of the drying bed is 5 ℃ ~ 15 ℃;
And S55, judging that the alarm limit value of the differential pressure of the drying bed is set to be 300pa ~ 500pa, if the alarm limit value is reached, automatically adjusting the washing time and the washing interval, and alarming to remind an operator.
further, in step S3, the alarm limit of the difference between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed is set to 5 ℃ ~ 15 ℃, and/or the alarm limit of the differential pressure of the drying bed can be set to 300pa ~ 500 pa.
according to the scheme provided by the invention, the fault condition of the drying bed is timely found through the self-diagnosis system and a solution is given, so that the abnormal working state of the drying bed is timely solved, the self-repair of the wastewater drying system is realized, the stable running condition is maintained, the reduction of the treatment capacity of the wastewater treatment system caused by the fault of the drying bed is effectively avoided, and the safe and stable running of the drying bed system is ensured.
drawings
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The invention will be further explained with reference to the drawings, in which:
FIG. 1 is a schematic diagram of a fault diagnosis system of a desiccant bed according to the present invention;
FIG. 2 is a flow chart of a method for fault self-diagnosis of a dryer bed according to the present invention;
FIG. 3 is a schematic diagram of a desiccant bed system according to the present invention.
In the figure: 1. drying the bed; 11. a drying bed outlet flue; 12. a drying bed inlet flue; 2. a slurry supply flowmeter; 3. a hot air blower; 4. a cold air blower.
Detailed Description
it should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
As shown in fig. 1, the present invention provides a fault diagnosis system for a drying bed, which includes a data acquisition module, a data analysis module and a fault diagnosis processing module; the data acquisition module is respectively in communication connection with the data analysis module and the fault diagnosis processing module; the data analysis module is also in communication connection with the fault diagnosis processing module; the data acquisition module is used for acquiring the operating parameters of the drying bed and transmitting the operating parameters to the data analysis module and the fault diagnosis processing module; the data analysis module is used for analyzing the operation parameters and establishing a drying bed system model according to the operation parameters; the method comprises the following steps that a dry bed system model establishes a fault diagnosis model according to a given alarm limit value; the fault diagnosis processing module is used for carrying out fault diagnosis according to the operation parameters and the fault diagnosis model, determining a fault reason and outputting a fault processing method; by adopting the scheme, an operator can find faults in the operation of the drying bed in time and take measures in time to relieve the operation condition of the drying bed, so that the operation of the drying bed system is safer and more stable.
Preferably, in combination with the above scheme, as shown in fig. 1 to fig. 3, in this embodiment, the data acquisition module includes a measurement instrument and a DCS system; the measuring instrument comprises a thermometer, a flowmeter and a pressure transmitter of the dry bed system; the thermometer is used for detecting the bed temperature of the drying bed, the outlet flue gas temperature of the drying bed and the inlet flue gas temperature of the drying bed; the flowmeter is used for detecting the flue gas flow, the cold air flow and the slurry spraying amount at the inlet of the drying bed; the pressure transmitter is used for detecting the differential pressure of the drying bed; the amount of the filling material of the drying bed is the amount weighed before the seasoning is added into the drying bed, and the load of the unit is provided by the self detection and communication of the main unit; as shown in fig. 3, the drying bed system includes a drying bed 1, a slurry supply flow meter 2, a hot air blower 3, and a cold air blower 4; the pulp supply flowmeter 2 is arranged on the side surface of the drying bed and used for measuring the pulp supply amount; the flow meters are respectively arranged in the drying bed, the outlet flue of the drying bed and the inlet flue of the drying bed.
preferably, with reference to the above scheme, as shown in fig. 1, in this embodiment, the drying bed system model takes the selected amount of the filler of the drying bed, the unit load, the flue gas flow rate at the inlet of the drying bed, the flue gas temperature at the inlet of the drying bed, the cold air volume and the guniting volume as the input amount of the identification model; selecting the difference value between the bed temperature of the drying bed and the outlet flue gas temperature of the drying bed and the differential pressure of the drying bed as the output quantity of the identification model; wherein, the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed is the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed.
Preferably, in combination with the above scheme, as shown in fig. 1, in this embodiment, 3 to 5 different load conditions between 50% and 100% of the full load of the unit can be selected for the unit load; further, 3-5 different flow working conditions from the lowest flow to the full flow can be selected for the flue gas flow at the inlet of the drying bed; further, the bed temperature of the drying bed fluctuates within +/-15 ℃ of the set temperature value; further, the slurry spraying amount can be selected from 3-5 working conditions with different slurry spraying amounts between the lowest slurry spraying amount and the designed slurry spraying amount.
Preferably, in combination with the above scheme, as shown in fig. 1, in this embodiment, the data analysis module establishes a dry bed system model through adaptive control, fuzzy control, and neural network control; the dry bed system model includes multiple inputs and multiple outputs, which facilitate inputs and outputs.
Preferably, in combination with the above solutions, as shown in fig. 1, in this embodiment, the alarm limit values of the temperature difference and the differential pressure are set according to the operation experience, specifically, the alarm limit value of the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed is set to be 5 ℃, ~ 15 ℃, and can be generally set to be 7 ℃, 9 ℃, 12 ℃ or 14 ℃, and further, the alarm limit value of the differential pressure of the drying bed is set to be 300pa, ~ 500pa, and can be generally set to be 330pa, 380pa, 420pa, 470pa or 500 pa.
preferably, with reference to the above scheme, as shown in fig. 1, in this embodiment, the fault diagnosis processing module determines a fault cause and outputs a fault processing method according to the real-time operation parameters and the fault diagnosis model of the drying bed acquired by the data acquisition module; where a pattern can be established based on historical parameters and a diagnostic method can be obtained based on existing data input.
Correspondingly, in combination with the above solution, as shown in fig. 2, the present invention further provides a fault self-diagnosis method for a drying bed, which is applied to the fault diagnosis system for a drying bed; the method also comprises the following steps:
S1: adding a given amount of filler into the drying bed, selecting 3-5 load working conditions between 50% and 100% of the full load of the unit, and normally operating the drying bed, wherein the unit load generally needs 50% to normally operate, and the normal operation range is 50% to 100%; adjusting the flue gas flow at the inlet of the drying bed under each fixed load working condition, adjusting the spraying amount under 3-5 working conditions between the minimum flue gas flow and the full air flow, and ensuring that the bed temperature of the drying bed changes within +/-15 ℃ of a set value; selecting 3-5 working conditions with the minimum spraying amount to the designed spraying amount; recording the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the differential pressure of the drying bed in real time under each working condition; wherein the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed is the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed; according to the scheme, 3-5 working conditions are adopted, and the selected working conditions are considered to cover the whole operating working condition range; the specific implementation process comprises the following steps:
assuming that the full load of a unit is 1000MW, according to 3 working condition tests, three load working conditions of 500MW, 750MW and 1000MW can be selected, under any working condition, assuming that the lowest flue gas flow at the inlet of a drying bed is 5000Nm3/h and the full air quantity is 10000m3/h, 5000Nm3/h, 7500Nm3/h and 10000Nm3/h can be selected, assuming that the bed temperature set value of the drying bed is 130 ℃, adjusting the slurry spraying quantity under each flue gas flow to ensure that the bed temperature of the drying bed is changed within the set value of 115-145 ℃, changing at least three slurry supply quantities, after the 3 flue gas flow tests are finished, repeating the next load working condition to continue the test until the 3 load working condition tests are finished; the above are a way for the practical implementation of the invention, and specifically, the method can comprise the same operation of four working condition tests or five working condition tests;
S2: the data acquisition module transmits the historical data of each operating parameter in the step S1 to the data analysis module and the fault diagnosis processing module; the data analysis module establishes a drying bed system model according to the operation parameters, and can obtain output values of the model, namely a drying bed temperature, an outlet flue gas temperature difference value and a drying bed differential pressure value when input quantities such as a drying bed filling quantity, a unit load, a drying bed inlet flue gas flow, a drying bed inlet flue gas temperature, a cold air flow rate, a slurry spraying quantity and the like are given according to the drying bed system model;
S3, setting the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the alarm limit value of the differential pressure of the drying bed, and combining the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the alarm limit value of the differential pressure of the drying bed with the theoretical operation value to obtain a normal operation interval, specifically, setting the alarm limit value of the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed to be 5 ℃ ~ 15 ℃ and setting the alarm limit value of the differential pressure to be 300pa ~ 500 pa;
S4: the data acquisition module acquires the operation parameters of the drying bed in real time, and inputs the filling amount of the drying bed, the unit load, the flue gas flow at the inlet of the drying bed, the flue gas temperature at the inlet of the drying bed, the cold air volume and the guniting amount into the system model of the drying bed to obtain a model output value; the method comprises the following steps of obtaining a bed temperature of a drying bed, a difference value of a flue gas temperature at an outlet of the drying bed and a theoretical operation value of a differential pressure of the drying bed, and performing fault diagnosis by combining a fault diagnosis model;
s5: the fault diagnosis processing module analyzes and confirms the fault reason according to the model input value and reminds an operator to increase and change the operation mode; the set value of the operation parameter can be directly changed in the automatic operation mode of the drying bed; the specific implementation process comprises the following steps:
s51: judging whether the slurry spraying amount is between the lowest slurry spraying amount and the highest slurry spraying amount, if the slurry spraying amount exceeds the interval between the lowest slurry spraying amount and the highest slurry spraying amount, adjusting the corresponding set value of the slurry spraying amount, and alarming to remind an operator; the interval between the lowest slurry spraying amount and the highest slurry spraying amount is 0.4t/h to 1 t/h;
S52: judging whether the flue gas flow at the inlet of the drying bed is larger than the lowest flue gas flow, if so, adjusting a corresponding set value and alarming to remind an operator; the lowest flue gas flow is 5000m 3/h;
S53: judging whether the inlet flue gas temperature of the drying bed is higher than the lowest flue gas temperature, if so, adjusting a corresponding set value and alarming to remind an operator; the lowest flue gas temperature is 260 ℃;
S54, judging whether the temperature difference value of the drying bed reaches an alarm limit value setting interval or not, if so, automatically adjusting the washing time and the washing interval and alarming to remind an operator, wherein the operator can further adjust and optimize the temperature difference value, and the alarm limit value setting interval of the temperature difference value between the bed temperature of the drying bed and the temperature of the flue gas at the outlet of the drying bed is 5 ℃ ~ 15 ℃;
And S55, judging that the alarm limit value of the differential pressure of the drying bed is set to be 300pa ~ 500pa, if the alarm limit value is reached, automatically adjusting the washing time and the washing interval and alarming to remind an operator, wherein the operator can further adjust and optimize.
s6: the steps S4 to S5 are repeated.
by adopting the scheme, the invention has the following technical effects:
According to the scheme provided by the invention, the fault condition of the drying bed is timely found through the self-diagnosis system and a solution is given, so that the abnormal working state of the drying bed is timely solved, the self-repair of the wastewater drying system is realized, the stable running condition is maintained, the reduction of the treatment capacity of the wastewater treatment system caused by the fault of the drying bed is effectively avoided, and the safe and stable running of the drying bed system is ensured.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way. Those skilled in the art can make numerous possible variations and modifications to the described embodiments, or modify equivalent embodiments, without departing from the scope of the invention. Therefore, any modification, equivalent change and modification made to the above embodiments according to the technology of the present invention are within the protection scope of the present invention, unless the content of the technical solution of the present invention is departed from.
Claims (10)
1. The fault diagnosis system of the drying bed is characterized by comprising a data acquisition module, a data analysis module and a fault diagnosis processing module; the data acquisition module is respectively in communication connection with the data analysis module and the fault diagnosis processing module; the data analysis module is also in communication connection with the fault diagnosis processing module;
The data acquisition module is used for acquiring the operating parameters of the drying bed and transmitting the operating parameters to the data analysis module and the fault diagnosis processing module;
The data analysis module is used for analyzing the operation parameters and establishing a drying bed system model according to the operation parameters; the method comprises the following steps that a dry bed system model establishes a fault diagnosis model according to a given alarm limit value;
and the fault diagnosis processing module is used for carrying out fault diagnosis according to the operation parameters and the fault diagnosis model, determining a fault reason and outputting a fault processing method.
2. the system of claim 1, wherein the data acquisition module comprises a measurement instrument and a DCS system; the measuring instrument comprises a thermometer, a flowmeter and a pressure transmitter; the thermometer is used for detecting the bed temperature of the drying bed, the outlet flue gas temperature of the drying bed and the inlet flue gas temperature of the drying bed; the flowmeter is used for detecting the flue gas flow, the cold air flow and the slurry spraying amount at the inlet of the drying bed; the pressure transmitter is used for detecting the differential pressure of the drying bed.
3. the system for diagnosing the faults of the drying bed according to claim 1, wherein the drying bed system model takes the selected amount of the filler of the drying bed, the unit load, the flow rate of flue gas at the inlet of the drying bed, the temperature of flue gas at the inlet of the drying bed, the cold air volume and the guniting volume as input quantities of an identification model; and selecting the difference value between the bed temperature of the drying bed and the outlet flue gas temperature of the drying bed and the differential pressure of the drying bed as the output quantity of the identification model.
4. the system for diagnosing the fault of the drying bed according to claim 3, wherein the unit load can be selected from 3-5 different load working conditions between 50% and 100% of the full load of the unit; and/or 3-5 different flow working conditions from the lowest flow of flue gas to the full flow of flue gas at the inlet of the drying bed can be selected; and/or the bed temperature of the drying bed fluctuates within +/-15 ℃ of the set temperature value; and/or selecting 3-5 different working conditions from the lowest slurry spraying amount to the designed slurry spraying amount according to the slurry spraying amount.
5. the system of claim 1, wherein the data analysis module builds the model of the dry bed system through adaptive control, fuzzy control, neural network control; the dry bed system model includes a plurality of input volumes and a plurality of output volumes.
6. the system of claim 3, wherein the alarm limit for the difference between the temperature of the desiccant bed and the temperature of the outlet flue gas of the desiccant bed is set to 5 ℃ ~ 15 ℃, and/or the alarm limit for the differential pressure of the desiccant bed is set to 300pa ~ 500 pa.
7. the system for diagnosing the faults of the drying bed according to claim 1, wherein the fault diagnosis processing module is used for determining a fault reason and outputting a fault processing method according to the real-time operation parameters of the drying bed and the fault diagnosis model acquired by the data acquisition module.
8. A fault self-diagnosis method of a drying bed, characterized by being applied to a fault diagnosis system of a drying bed according to any one of claims 1 to 7; the method also comprises the following steps:
s1: adding a given amount of filler into the drying bed, selecting 3-5 load working conditions between 50% and 100% of the full load of the unit, and normally operating the drying bed; adjusting the flue gas flow at the inlet of the drying bed under each fixed load working condition, adjusting the spraying amount under 3-5 working conditions between the minimum flue gas flow and the full air flow, and ensuring that the bed temperature of the drying bed changes within +/-15 ℃ of a set value; selecting 3-5 working conditions with the minimum spraying amount to the designed spraying amount; recording the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the differential pressure of the drying bed in real time under each working condition;
S2: the data acquisition module transmits the historical data of each operating parameter in the step S1 to the data analysis module and the fault diagnosis processing module; the data analysis module establishes a drying bed system model according to the operation parameters;
s3: the output value of the drying bed system model is a theoretical operation value; setting a difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and an alarm limit value of the differential pressure of the drying bed, and combining the difference value between the bed temperature of the drying bed and the flue gas temperature at the outlet of the drying bed and the alarm limit value of the differential pressure of the drying bed with a theoretical operation value to obtain a normal operation interval;
s4: the data acquisition module acquires the operation parameters of the drying bed in real time, and inputs the filling amount of the drying bed, the unit load, the flue gas flow at the inlet of the drying bed, the flue gas temperature at the inlet of the drying bed, the cold air volume and the guniting volume into the system model of the drying bed to obtain a model output value;
s5: the fault diagnosis processing module analyzes and confirms the fault reason according to the model input value and reminds an operator to increase and change the operation mode; the set values of the operating parameters can be directly changed in the automatic operating mode of the drying bed.
9. the method for fault self-diagnosis of a drying bed according to claim 8, wherein the step S5 further includes:
s51: judging whether the slurry spraying amount is between the lowest slurry spraying amount and the highest slurry spraying amount, if the slurry spraying amount exceeds the interval between the lowest slurry spraying amount and the highest slurry spraying amount, adjusting the corresponding set value of the slurry spraying amount, and alarming to remind an operator; the interval between the lowest slurry spraying amount and the highest slurry spraying amount is 0.4t/h to 1 t/h;
S52: judging whether the flue gas flow at the inlet of the drying bed is larger than the lowest flue gas flow, if so, adjusting a corresponding set value and alarming to remind an operator; the minimum flue gas flow is 5000m3/h；
s53: judging whether the inlet flue gas temperature of the drying bed is higher than the lowest flue gas temperature, if so, adjusting a corresponding set value and alarming to remind an operator; the lowest flue gas temperature is 260 ℃;
S54, judging whether the temperature difference value of the drying bed reaches an alarm limit value setting interval, if so, automatically adjusting the washing time and the washing interval and alarming to remind an operator, wherein the alarm limit value setting interval of the temperature difference value of the drying bed is 5 ℃ ~ 15 ℃;
and S55, judging that the alarm limit value of the differential pressure of the drying bed is set to be 300pa ~ 500pa, if the alarm limit value is reached, automatically adjusting the washing time and the washing interval, and alarming to remind an operator.
10. the method for fault self-diagnosis of a dryer bed according to claim 8, wherein in the step S3, the alarm limit for the difference between the bed temperature of the dryer and the bed outlet flue gas temperature of the dryer may be set to 5 ℃ ~ 15 ℃, and/or the alarm limit for the differential pressure of the dryer may be set to 300pa ~ 500 pa.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101329582B (en) * | 2008-07-18 | 2010-06-02 | 东南大学 | Method for optimizing and diagnosing circulating fluid bed boiler combustion |
| CN101738435A (en) * | 2009-11-30 | 2010-06-16 | 浙江大学 | Dynamic fault diagnostic method of polymer aggregation in gas-solid fluidized bed reactor |
| CN101907685A (en) * | 2010-06-18 | 2010-12-08 | 华北电力大学 | Method for checking correctness of operating parameters of generator set capable of adapting to change of operating conditions |
| CN104459819A (en) * | 2014-10-31 | 2015-03-25 | 杭州杭锅电气科技有限公司 | Boiler coal interruption detecting device and method |
| CN104615122A (en) * | 2014-12-11 | 2015-05-13 | 深圳市永达电子股份有限公司 | Industrial control signal detection system and detection method |
| CN104697704A (en) * | 2015-03-13 | 2015-06-10 | 芜湖凯博实业股份有限公司 | Method for detecting discharge pressure faults of water chilling unit |
| CN107505927A (en) * | 2017-03-29 | 2017-12-22 | 华北电力大学 | CFB Boiler cigarette equipment fault monitoring method and device based on component |
| CN107944633A (en) * | 2017-12-07 | 2018-04-20 | 北京能源集团有限责任公司 | Alarm method and system based on model trend prediction |
| CN108636094A (en) * | 2018-07-12 | 2018-10-12 | 浙江大学 | A kind of accurate PREDICTIVE CONTROL in wet desulfurizing process and energy conserving system and method |
| CN108837698A (en) * | 2018-07-02 | 2018-11-20 | 大唐环境产业集团股份有限公司 | Based on advanced measuring instrumentss and the SCR denitration of advanced control algorithm spray ammonia optimization method and system |
| CN109205719A (en) * | 2018-09-28 | 2019-01-15 | 北京国电龙源环保工程有限公司 | Waste water zero discharge device drying system and its operation method |
| CN110298455A (en) * | 2019-06-28 | 2019-10-01 | 西安因联信息科技有限公司 | A kind of mechanical equipment fault intelligent early-warning method based on multivariable estimation prediction |
-
2019
- 2019-09-23 CN CN201910898638.4A patent/CN110579367A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101329582B (en) * | 2008-07-18 | 2010-06-02 | 东南大学 | Method for optimizing and diagnosing circulating fluid bed boiler combustion |
| CN101738435A (en) * | 2009-11-30 | 2010-06-16 | 浙江大学 | Dynamic fault diagnostic method of polymer aggregation in gas-solid fluidized bed reactor |
| CN101907685A (en) * | 2010-06-18 | 2010-12-08 | 华北电力大学 | Method for checking correctness of operating parameters of generator set capable of adapting to change of operating conditions |
| CN104459819A (en) * | 2014-10-31 | 2015-03-25 | 杭州杭锅电气科技有限公司 | Boiler coal interruption detecting device and method |
| CN104615122A (en) * | 2014-12-11 | 2015-05-13 | 深圳市永达电子股份有限公司 | Industrial control signal detection system and detection method |
| CN104697704A (en) * | 2015-03-13 | 2015-06-10 | 芜湖凯博实业股份有限公司 | Method for detecting discharge pressure faults of water chilling unit |
| CN107505927A (en) * | 2017-03-29 | 2017-12-22 | 华北电力大学 | CFB Boiler cigarette equipment fault monitoring method and device based on component |
| CN107944633A (en) * | 2017-12-07 | 2018-04-20 | 北京能源集团有限责任公司 | Alarm method and system based on model trend prediction |
| CN108837698A (en) * | 2018-07-02 | 2018-11-20 | 大唐环境产业集团股份有限公司 | Based on advanced measuring instrumentss and the SCR denitration of advanced control algorithm spray ammonia optimization method and system |
| CN108636094A (en) * | 2018-07-12 | 2018-10-12 | 浙江大学 | A kind of accurate PREDICTIVE CONTROL in wet desulfurizing process and energy conserving system and method |
| CN109205719A (en) * | 2018-09-28 | 2019-01-15 | 北京国电龙源环保工程有限公司 | Waste water zero discharge device drying system and its operation method |
| CN110298455A (en) * | 2019-06-28 | 2019-10-01 | 西安因联信息科技有限公司 | A kind of mechanical equipment fault intelligent early-warning method based on multivariable estimation prediction |
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