CN112348920B - Method for constructing dynamic characteristic thermodynamic diagram of circulating fluidized bed boiler based on data driving - Google Patents
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- 238000010586 diagram Methods 0.000 title claims abstract description 26
- 238000000034 method Methods 0.000 title claims description 12
- 238000004458 analytical method Methods 0.000 claims abstract description 43
- 238000010276 construction Methods 0.000 claims abstract description 10
- 239000011159 matrix material Substances 0.000 claims abstract description 10
- 230000008020 evaporation Effects 0.000 claims abstract description 5
- 238000001704 evaporation Methods 0.000 claims abstract description 5
- 238000009499 grossing Methods 0.000 claims abstract description 4
- 239000003245 coal Substances 0.000 claims description 21
- 239000002893 slag Substances 0.000 claims description 16
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 12
- 239000007789 gas Substances 0.000 claims description 11
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 9
- 239000001301 oxygen Substances 0.000 claims description 9
- 229910052760 oxygen Inorganic materials 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000007599 discharging Methods 0.000 claims description 5
- 230000004931 aggregating effect Effects 0.000 claims description 3
- 238000004220 aggregation Methods 0.000 claims description 3
- 230000002776 aggregation Effects 0.000 claims description 3
- 239000003517 fume Substances 0.000 claims description 3
- 238000011217 control strategy Methods 0.000 abstract description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000010206 sensitivity analysis Methods 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000005338 heat storage Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000011056 performance test Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
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- G—PHYSICS
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/20—Drawing from basic elements, e.g. lines or circles
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Abstract
The invention provides a thermodynamic diagram construction method of dynamic characteristics of a circulating fluidized bed boiler based on data driving, which comprises the steps of selecting data corresponding to analysis factors as selected data; smoothing all selected data; detecting and extracting a steady-state working condition section limited by a threshold value based on the quantitative change of the trend to obtain the steady-state working condition section; the selected data corresponding to the analysis factors in the time interval of the steady-state working condition period are aggregated, and the aggregated analysis factor data are obtained: dividing a load section by 5% -10% of the maximum continuous evaporation capacity width of the boiler; clustering all steady-state working conditions of the boundary state marks in each charge section into a working condition cluster, and calculating a correlation coefficient among analysis factors in each working condition cluster; and constructing a correlation coefficient matrix, namely, a thermodynamic diagram. The construction method can clearly and accurately display the correlation characteristics among the factors in the thermodynamic diagram, and can more accurately guide the selection and analysis of the control strategy and the related modeling work on the input quantity of the system.
Description
Technical Field
The invention belongs to the field of circulating fluidized bed boilers, relates to dynamic characteristic thermodynamic diagrams, and in particular relates to a method for constructing dynamic characteristic thermodynamic diagrams of a circulating fluidized bed boiler based on data driving.
Background
The factors influencing the dynamic characteristics of the boiler in the actual operation process of the circulating fluidized bed boiler are numerous, wherein the factors comprise partial environment temperature, load rate, coal quality and other uncontrollable operation environment factors, and exhaust gas oxygen content, air distribution mode and other controllable operation parameters. There are complex coupling relations among many factors, and some universities and electric scientific institutions have studied the energy efficiency sensitivity analysis of the coal motor unit. But most of them are in simulation stage and have certain application in actual optimization projects. If the power supply coal consumption is selected as a measurement standard on a large coal-fired unit, an energy consumption analysis model based on a support vector machine is established, the sensitivity coefficient of each operation characteristic parameter of different load areas to the power supply coal consumption is calculated, different regulation and control measures are adopted according to the difference of the sensitivity coefficient under different loads, but a single target such as boiler efficiency is usually determined in the analysis process, then a certain amount of influencing factors are selected, the correlation characteristics between each selected factor and the target are analyzed, but in practice, complex coupling relation exists between each factor, and when the dominant influencing factor of a certain target is determined by the sensitivity analysis, the independence of the factor on the target correlation coefficient needs to be determined, and the factor needs to be continuously used as the target for correlation analysis with other factors.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a thermodynamic diagram construction method of dynamic characteristics of a circulating fluidized bed boiler based on data driving, so as to solve the technical problem of insufficient thermodynamic diagram accuracy of the dynamic characteristics in the prior art.
In order to solve the technical problems, the invention adopts the following technical scheme:
a dynamic characteristic thermodynamic diagram construction method of a circulating fluidized bed boiler based on data driving is carried out according to the following steps:
step one, data selection:
the method comprises the steps of selecting main steam pressure sp, main steam temperature st, main steam flow sf, hearth outlet negative pressure np, hearth upper differential pressure dp, air chamber pressure wpo, a secondary air ratio q12, exhaust gas oxygen content o, exhaust gas temperature sm t, secondary air machine outlet temperature w2t, slag cooler frequency lz, coal feeding quantity c, slag discharging ratio hf, separator temperature difference tc and boiler relative efficiency eta as analysis factors;
selecting data corresponding to analysis factors as selected data;
step two, clustering and extracting steady-state working condition segments of the circulating fluidized bed boiler:
step 201, smoothing all selected data;
step 202, detecting and extracting a steady-state working condition section based on the limit of a trend quantitative change threshold value to obtain the steady-state working condition section;
the limit constraint conditions of the trend quantitative change threshold are as follows:
the difference between the extreme values of the main steam pressure is less than 2% of the average value;
the extreme value difference of the main steam flow is less than 3% of the mean value;
the extreme value difference of the coal feeding amount is less than 3% of the average value;
the bed temperature extreme value difference is less than 1% of the average value;
the extreme value difference of the bed pressure is less than 2% of the average value;
the extreme difference of the oxygen content of the exhaust fume is less than 5% of the mean value;
the continuous time length of the data is more than 10min and less than 60min;
step 203, aggregating the selected data corresponding to the analysis factors in the time interval of the steady-state working condition period obtained in step 202, wherein single data repeatedly participate in multi-segment aggregation, and obtaining aggregated analysis factor data:
204, dividing a load zone by 5% -10% of the maximum continuous evaporation capacity width of the boiler according to the change of the boundary state mark parameter main steam flow; clustering all steady-state working conditions of the boundary state marks in each charging section into a working condition cluster, wherein all aggregated analysis factor data corresponding to all steady-state working conditions of the boundary state marks in each charging section are analysis factor data corresponding to the working condition cluster;
step three, thermodynamic diagram construction for representing dynamic characteristics of the circulating fluidized bed boiler:
step 301, calculating correlation coefficients among analysis factors in each working condition cluster by adopting pearson correlation based on analysis factor data corresponding to each working condition cluster;
step 302, constructing a correlation coefficient matrix;
constructing a correlation coefficient matrix corresponding to each working condition cluster according to the correlation coefficients among the analysis factors in each working condition cluster obtained in the step 301;
step 303, the correlation coefficient matrix data parameter and the color parameter are utilized to represent the correlation degree of the analysis factors, namely the dynamic characteristic thermodynamic diagram of the circulating fluidized bed boiler.
The invention also has the following technical characteristics:
in the first step, the specific process of data selection comprises the following steps:
step 101, selecting coal feeding quantity, water feeding flow, water feeding temperature, water feeding pressure, main steam flow, main steam temperature and main steam pressure to calculate operation parameters of relative efficiency of the boiler;
the calculation method of the relative efficiency of the boiler is the ratio eta of the difference between the total steam enthalpy value and the total feed water enthalpy value and the coal feeding amount;
step 102, selecting a feedback ratio of primary air quantity and secondary air quantity as a secondary air ratio q12;
step 103, selecting the ratio of the frequency of the slag cooler to the coal feeding amount as a slag discharging ratio hf;
104, taking the difference value between the outlet temperature of the hearth and the return temperature as a separator temperature difference tc;
step 105, selecting main steam pressure sp, main steam temperature st, main steam flow sf, hearth outlet negative pressure np, hearth upper differential pressure dp, plenum pressure wpo, primary secondary air ratio q12, exhaust gas oxygen content o, exhaust gas temperature smt, secondary air outlet temperature w2t, slag cooler frequency lz, coal feed amount c, slag discharge ratio hf, separator temperature difference tc and boiler relative efficiency eta as analysis factors.
In the first step, the time period for selecting the data is 60-90 days.
Compared with the prior art, the invention has the following technical effects:
firstly, selecting operation parameters capable of representing the dynamic characteristics of a boiler, then converting the operation parameters into influencing factors, and eliminating the influence of heat storage change of the boiler on the dynamic characteristics among the factors through characteristic working condition treatment. The construction method can clearly and accurately display the correlation characteristics among the factors in the thermodynamic diagram, and can more accurately guide the selection and analysis of the control strategy and the related modeling work on the input quantity of the system.
And (II) the invention more intuitively guides technicians to analyze the correlation among multiple factors through a graphic visual display mode.
The invention can analyze the full working condition of the actual operation of the boiler, reduce the influence of the operation characteristic of the boiler along with the change of the working condition, and can be applied to the optimization of the actual production process.
The invention is based on the analysis of the boiler operation history data, and avoids the extra huge workload brought by online performance test adjustment.
Drawings
FIG. 1 is a thermodynamic diagram of the dynamic characteristics of a circulating fluidized bed boiler corresponding to a working condition cluster of 260t/h to 270 t/h.
FIG. 2 is a thermodynamic diagram of the dynamic characteristics of the circulating fluidized bed boiler corresponding to the working condition clusters of 270t/h to 280 t/h.
FIG. 3 is a thermodynamic diagram of the dynamic characteristics of the circulating fluidized bed boiler corresponding to the working condition clusters of 280t/h to 290 t/h.
FIG. 4 is a thermodynamic diagram of the dynamic characteristics of the circulating fluidized bed boiler corresponding to the working condition clusters of 290t/h to 300 t/h.
The following examples illustrate the invention in further detail.
Detailed Description
The following specific embodiments of the present invention are given according to the above technical solutions, and it should be noted that the present invention is not limited to the following specific embodiments, and all equivalent changes made on the basis of the technical solutions of the present application fall within the protection scope of the present invention.
Examples:
in the embodiment, a circulating fluidized bed boiler is configured in a self-provided thermal power plant of a certain chemical enterprise, the rated evaporation capacity is 300t/h, the rated steam pressure is 9.8MPa, the rated steam temperature is 540 ℃, and the single steam drum is horizontally arranged, single hearth, natural circulation and all-steel arrangement are adopted.
The embodiment provides a thermodynamic diagram construction method of dynamic characteristics of a circulating fluidized bed boiler based on data driving, which comprises the following steps:
step one, data selection:
the specific process of data selection comprises the following steps:
step 101, selecting coal feeding quantity, water feeding flow, water feeding temperature, water feeding pressure, main steam flow, main steam temperature and main steam pressure to calculate operation parameters of relative efficiency of the boiler;
the calculation method of the relative efficiency of the boiler is the ratio eta of the difference between the total steam enthalpy value and the total feed water enthalpy value and the coal feeding amount;
step 102, selecting a feedback ratio of primary air quantity and secondary air quantity as a secondary air ratio q12;
step 103, selecting the ratio of the frequency of the slag cooler to the coal feeding amount as a slag discharging ratio hf;
104, taking the difference value between the outlet temperature of the hearth and the return temperature as a separator temperature difference tc;
step 105, selecting main steam pressure sp, main steam temperature st, main steam flow sf, hearth outlet negative pressure np, hearth upper differential pressure dp, plenum pressure wpo, primary secondary air ratio q12, exhaust gas oxygen content o, exhaust gas temperature smt, secondary air outlet temperature w2t, slag cooler frequency lz, coal feed amount c, slag discharge ratio hf, separator temperature difference tc and boiler relative efficiency eta as analysis factors.
Selecting data corresponding to analysis factors as selected data;
in this embodiment, continuous operation history data of the unit is selected, the data selection frequency interval is 5 seconds, the data is stored in a CSV file format, and the time period for selecting the data is 60 days.
Step two, clustering and extracting steady-state working condition segments of the circulating fluidized bed boiler:
step 201, smoothing all selected data;
step 202, detecting and extracting a steady-state working condition section based on the limit of a trend quantitative change threshold value to obtain the steady-state working condition section;
the limit constraint conditions of the trend quantitative change threshold are as follows:
the difference between the extreme values of the main steam pressure is less than 2% of the average value;
the extreme value difference of the main steam flow is less than 3% of the mean value;
the extreme value difference of the coal feeding amount is less than 3% of the average value;
the bed temperature extreme value difference is less than 1% of the average value;
the extreme value difference of the bed pressure is less than 2% of the average value;
the extreme difference of the oxygen content of the exhaust fume is less than 5% of the mean value;
the continuous time length of the data is more than 10min and less than 60min;
in this embodiment, 1593 stable conditions are obtained in total in the selected time period.
Step 203, aggregating the selected data corresponding to the analysis factors in the time interval of the steady-state working condition period obtained in step 202, wherein single data repeatedly participate in multi-segment aggregation, and obtaining aggregated analysis factor data:
in this embodiment, the aggregated analysis factor data is stored in a CSV file format.
Step 204, dividing a load section by 10t/h evaporation amount width according to the change of the boundary state mark parameter main steam flow; clustering all steady-state working conditions of the boundary state marks in each charging section into a working condition cluster, wherein all aggregated analysis factor data corresponding to all steady-state working conditions of the boundary state marks in each charging section are analysis factor data corresponding to the working condition cluster;
in the embodiment, the boiler load is operated at 250 t/h-300 t/h in a selected time period, wherein the stable working condition section in the working condition cluster of 250 t/h-260 t/h is 39 sections, the stable working condition section in the working condition cluster of 260 t/h-270 t/h is 189 sections, the stable working condition section in the working condition cluster of 270 t/h-280 t/h is 461 sections, the stable working condition section in the working condition cluster of 280 t/h-290 t/h is 538 sections, the stable working condition section in the working condition cluster of 290 t/h-300 t/h is 366 sections, the data section in the working condition cluster of 250 t/h-260 t/h is less, the working condition is not commonly used, the data quantity is insufficient, and the working condition cluster is ignored.
Step three, thermodynamic diagram construction for representing dynamic characteristics of the circulating fluidized bed boiler:
step 301, calculating correlation coefficients among analysis factors in each working condition cluster by adopting pearson correlation based on analysis factor data corresponding to each working condition cluster;
it should be noted that, the calculation formula of the pearson correlation in the present invention is:
wherein: e is a mathematical expectation and X and Y are each two factors for analysis.
The calculation results range from-1 to 1. -1 represents a negative correlation and 1-to-1 represents a positive correlation. The pearson correlation is actually measured as whether the two random variables are increasing and decreasing. If two random variables are sampled simultaneously, when one gets a larger value and the other is larger, and when one is smaller, the other is smaller, the correlation is positive, the calculated correlation is close to 1, and conversely, the calculated correlation is close to-1.
Step 302, constructing a correlation coefficient matrix;
constructing a correlation coefficient matrix corresponding to each working condition cluster according to the correlation coefficients among the analysis factors in each working condition cluster obtained in the step 301;
step 303, the correlation coefficient matrix data parameter and the color parameter are utilized to represent the correlation degree of the analysis factors, namely the dynamic characteristic thermodynamic diagram of the circulating fluidized bed boiler. The thermodynamic diagrams of dynamic characteristics of the circulating fluidized bed boiler obtained in this example are specifically shown in fig. 1 to 4.
Claims (3)
1. The dynamic characteristic thermodynamic diagram construction method of the circulating fluidized bed boiler based on data driving is characterized by comprising the following steps of:
step one, data selection:
the method comprises the steps of selecting main steam pressure sp, main steam temperature st, main steam flow sf, hearth outlet negative pressure np, hearth upper differential pressure dp, air chamber pressure wpo, a secondary air ratio q12, exhaust gas oxygen content o, exhaust gas temperature sm t, secondary air machine outlet temperature w2t, slag cooler frequency lz, coal feeding quantity c, slag discharging ratio hf, separator temperature difference tc and boiler relative efficiency eta as analysis factors;
selecting data corresponding to analysis factors as selected data;
step two, clustering and extracting steady-state working condition segments of the circulating fluidized bed boiler:
step 201, smoothing all selected data;
step 202, detecting and extracting a steady-state working condition section based on the limit of a trend quantitative change threshold value to obtain the steady-state working condition section;
the limit constraint conditions of the trend quantitative change threshold are as follows:
the difference between the extreme values of the main steam pressure is less than 2% of the average value;
the extreme value difference of the main steam flow is less than 3% of the mean value;
the extreme value difference of the coal feeding amount is less than 3% of the average value;
the bed temperature extreme value difference is less than 1% of the average value;
the extreme value difference of the bed pressure is less than 2% of the average value;
the extreme difference of the oxygen content of the exhaust fume is less than 5% of the mean value;
the continuous time length of the data is more than 10min and less than 60min;
step 203, aggregating the selected data corresponding to the analysis factors in the time interval of the steady-state working condition period obtained in step 202, wherein single data repeatedly participate in multi-segment aggregation, and obtaining aggregated analysis factor data:
204, dividing a load zone by 5% -10% of the maximum continuous evaporation capacity width of the boiler according to the change of the boundary state mark parameter main steam flow; clustering all steady-state working conditions of the boundary state marks in each charging section into a working condition cluster, wherein all aggregated analysis factor data corresponding to all steady-state working conditions of the boundary state marks in each charging section are analysis factor data corresponding to the working condition cluster;
step three, thermodynamic diagram construction for representing dynamic characteristics of the circulating fluidized bed boiler:
step 301, calculating correlation coefficients among analysis factors in each working condition cluster by adopting pearson correlation based on analysis factor data corresponding to each working condition cluster;
step 302, constructing a correlation coefficient matrix;
constructing a correlation coefficient matrix corresponding to each working condition cluster according to the correlation coefficients among the analysis factors in each working condition cluster obtained in the step 301;
step 303, the correlation coefficient matrix data parameter and the color parameter are utilized to represent the correlation degree of the analysis factors, namely the dynamic characteristic thermodynamic diagram of the circulating fluidized bed boiler.
2. The method for constructing thermodynamic diagrams of dynamic characteristics of circulating fluidized bed boiler based on data driving according to claim 1, wherein in the first step, the specific process of data selection comprises the following steps:
step 101, selecting coal feeding quantity, water feeding flow, water feeding temperature, water feeding pressure, main steam flow, main steam temperature and main steam pressure to calculate operation parameters of relative efficiency of the boiler;
the calculation method of the relative efficiency of the boiler is the ratio eta of the difference between the total steam enthalpy value and the total feed water enthalpy value and the coal feeding amount;
step 102, selecting a feedback ratio of primary air quantity and secondary air quantity as a secondary air ratio q12;
step 103, selecting the ratio of the frequency of the slag cooler to the coal feeding amount as a slag discharging ratio hf;
104, taking the difference value between the outlet temperature of the hearth and the return temperature as a separator temperature difference tc;
step 105, selecting main steam pressure sp, main steam temperature st, main steam flow sf, hearth outlet negative pressure np, hearth upper differential pressure dp, plenum pressure wpo, primary secondary air ratio q12, exhaust gas oxygen content o, exhaust gas temperature smt, secondary air outlet temperature w2t, slag cooler frequency lz, coal feed amount c, slag discharge ratio hf, separator temperature difference tc and boiler relative efficiency eta as analysis factors.
3. The method for constructing thermodynamic diagrams of dynamic characteristics of circulating fluidized bed boiler based on data driving according to claim 1, wherein in the first step, the time period for selecting data is 60-90 days.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015074575A1 (en) * | 2013-11-21 | 2015-05-28 | 北京国双科技有限公司 | Method and apparatus for obtaining three-dimensional thermodynamic diagram |
| WO2016145736A1 (en) * | 2015-03-18 | 2016-09-22 | 百度在线网络技术（北京）有限公司 | Method, apparatus and device for presenting thermodynamic chart and non-volatile computer storage medium |
| CN106407601A (en) * | 2016-10-18 | 2017-02-15 | 中国运载火箭技术研究院 | Aerodynamic characteristic data processing method based on data mining technology |
| WO2017050207A1 (en) * | 2015-09-21 | 2017-03-30 | 华北电力科学研究院有限责任公司 | Method for analyzing energy efficiency of generator set |
| CN107330543A (en) * | 2017-06-01 | 2017-11-07 | 华北电力大学 | A kind of coal consumption method for optimization analysis based on load characteristics clustering and Controlling UEP |
| CN107451346A (en) * | 2017-07-21 | 2017-12-08 | 国网浙江省电力公司绍兴供电公司 | A kind of grid operation situation model building method |
| CN109766950A (en) * | 2019-01-18 | 2019-05-17 | 东北大学 | A kind of industrial user's short-term load forecasting method based on form cluster and LightGBM |
| CN109861293A (en) * | 2019-03-29 | 2019-06-07 | 国网河南省电力公司经济技术研究院 | The appraisal procedure that photovoltaic uncertainty influences electric system small-signal stability |
-
2020
- 2020-10-30 CN CN202011189470.9A patent/CN112348920B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015074575A1 (en) * | 2013-11-21 | 2015-05-28 | 北京国双科技有限公司 | Method and apparatus for obtaining three-dimensional thermodynamic diagram |
| WO2016145736A1 (en) * | 2015-03-18 | 2016-09-22 | 百度在线网络技术（北京）有限公司 | Method, apparatus and device for presenting thermodynamic chart and non-volatile computer storage medium |
| WO2017050207A1 (en) * | 2015-09-21 | 2017-03-30 | 华北电力科学研究院有限责任公司 | Method for analyzing energy efficiency of generator set |
| CN106407601A (en) * | 2016-10-18 | 2017-02-15 | 中国运载火箭技术研究院 | Aerodynamic characteristic data processing method based on data mining technology |
| CN107330543A (en) * | 2017-06-01 | 2017-11-07 | 华北电力大学 | A kind of coal consumption method for optimization analysis based on load characteristics clustering and Controlling UEP |
| CN107451346A (en) * | 2017-07-21 | 2017-12-08 | 国网浙江省电力公司绍兴供电公司 | A kind of grid operation situation model building method |
| CN109766950A (en) * | 2019-01-18 | 2019-05-17 | 东北大学 | A kind of industrial user's short-term load forecasting method based on form cluster and LightGBM |
| CN109861293A (en) * | 2019-03-29 | 2019-06-07 | 国网河南省电力公司经济技术研究院 | The appraisal procedure that photovoltaic uncertainty influences electric system small-signal stability |
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