CN111578290B - Automatic garbage scheduling method for garbage pool of garbage incineration plant based on big data - Google Patents
Automatic garbage scheduling method for garbage pool of garbage incineration plant based on big data Download PDFInfo
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- 239000010813 municipal solid waste Substances 0.000 title claims abstract description 213
- 238000000034 method Methods 0.000 title claims abstract description 25
- 239000000463 material Substances 0.000 claims abstract description 7
- 238000004056 waste incineration Methods 0.000 claims abstract description 4
- 238000000855 fermentation Methods 0.000 claims description 58
- 230000004151 fermentation Effects 0.000 claims description 58
- 238000006243 chemical reaction Methods 0.000 claims description 31
- 238000004422 calculation algorithm Methods 0.000 claims description 20
- 238000003860 storage Methods 0.000 claims description 11
- 230000008595 infiltration Effects 0.000 claims description 6
- 238000001764 infiltration Methods 0.000 claims description 6
- 238000002485 combustion reaction Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 2
- 238000004140 cleaning Methods 0.000 abstract description 12
- 238000005457 optimization Methods 0.000 abstract description 2
- 239000002699 waste material Substances 0.000 abstract 1
- 238000004891 communication Methods 0.000 description 2
- 238000009795 derivation Methods 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 238000003756 stirring Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 230000001186 cumulative effect Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005325 percolation Methods 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
- F23G5/50—Control or safety arrangements
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G5/00—Incineration of waste; Incinerator constructions; Details, accessories or control therefor
- F23G5/44—Details; Accessories
- F23G5/442—Waste feed arrangements
- F23G5/444—Waste feed arrangements for solid waste
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Abstract
A garbage incineration plant garbage pool garbage automatic scheduling method based on big data comprises the steps of firstly, numbering a feeding door, a garbage area, a furnace inlet, a garbage grab bucket, garbage hanger coordinates and a leachate diversion port of a garbage furnace; the second step: presetting data, collecting data and presetting a threshold value, and the third step: the control system automatically compares the acquired data with a preset threshold value; the fourth step: the garbage grab bucket dispatches the garbage in the garbage pool; the fifth step: and optimizing and adjusting the data to finally obtain the scheduling method suitable for the garbage pool. The uncovering, bottom cleaning, turning, material grabbing and furnace entering and leachate removal are all automatic operation, the control system is accurately controlled by preset data and collected data due to big data and continuous adjustment and optimization, and the problems that in the existing waste incineration process, data in a waste pool cannot be obtained, the uncovering and bottom cleaning can only be carried out manually and empirically, so that the resulting waste incineration is insufficient and the environment is secondarily polluted are solved.
Description
Technical Field
The invention belongs to the field of data application, and relates to a garbage pool garbage automatic scheduling method of a garbage incineration plant based on big data.
Background
The garbage pool management in the garbage incineration plant comprises the steps of feeding, fermenting, stirring, moving, charging, discharging percolate and the like of garbage. Whether the garbage is sufficiently combusted in the furnace is mainly related to several main factors, namely the fermentation degree of the garbage in the grab bucket, the frequency of the grab bucket and the amount of the garbage in the grab bucket. If each scheduling activity in the garbage pool is reasonably arranged, the combustion of the incinerator is stable, and the pollution is minimum. If the reasonable scheduling is lacked, the working condition of the incinerator fluctuates and the slagging is large. At present, various work executions are relatively mechanical and are generally executed according to personal experience of workers, and randomness is high. Even if there is a management request, the request is relatively rigid and rough, and the worker cannot be guided to work specifically. The staff cannot dynamically acquire the feed inlet information, including the position of the feed inlet and the congestion situation, and only communication between the staff and the staff is achieved through observation, so that the communication mode has time difference. The garbage can not move timely, so that a feed port can be blocked; secondly, the fermentation time can be shortened by stirring and mixing the new garbage and the old garbage, and the garbage with low fermentation degree can be prevented from entering the furnace by immediately lifting the top and cleaning the bottom. When a plurality of boilers need to continuously feed, the grab bucket operators can only grab buckets according to experience, and the accumulated amount of the garbage entering the boiler is large, the garbage is empty or partially fed, and the garbage cannot be fully combusted; the amount of the garbage entering the furnace is small, and the incineration efficiency is low; and the timely derivation of the percolate is favorable for improving the garbage fermentation condition, particularly in the south with more rainy seasons, and the water content of the garbage is high. However, the staff cannot predict the frequency with which the percolate is discharged, which has the least influence on the fermentation, and generally the percolate is treated after a certain height. Such a processing manner is comparatively delayed.
Disclosure of Invention
1. The technical problem to be solved is as follows:
in the existing waste incineration, all work execution is relatively mechanical, and is generally executed according to personal experience of workers, so that the randomness is strong. Even if there is a management request, the request is relatively rigid and rough, and the worker cannot be guided to work specifically.
2. The technical scheme is as follows:
in order to solve the problems, the invention provides a garbage automatic scheduling method of a garbage pool of a garbage incineration plant based on big data, which comprises the following steps of dividing garbage areas into 4 areas, namely an area A, an area B, an area C and an area D, wherein the area A is a feeding area, the area B is a fermentation area, the area C is a standby combustion area, the area D is a combustion area, and the garbage areas are divided into 4 layers which are respectively 1 layer, 2 layers, 3 layers and 4 layers: firstly, numbering a feeding door, a garbage area, a furnace inlet, a garbage grab bucket, a garbage hanger coordinate and a percolate diversion port of a garbage furnace; the second step is that: presetting data, collecting data, calculating a fermentation value of each layer of each garbage area, inputting the collected data and the fermentation value of each layer of each area into a control system, and presetting a threshold value, and the third step: the control system automatically compares the acquired data with a preset threshold value; the fourth step: the control system dispatches the garbage in the garbage pool through the garbage grab bucket according to the comparison result; the fifth step: observing whether the working condition of the boiler is stable under dispatching, if the working condition of the boiler is deviated, entering a second step, recalculating the fermentation value of each layer of each area and resetting a threshold value; if the working condition of the boiler is stable, the algorithm is proper, and finally a scheduling method suitable for the garbage pool is obtained, the preset data are the garbage input amount, the height of a feed port of the garbage pool, the range of coordinates of a garbage hanger and the area of a percolate guide opening, and the data in the collected data comprise garbage fermentation information, information of a garbage area, percolate information and garbage feeding height; the garbage dispatching calculation comprises a feed inlet algorithm, a top-removing and bottom-cleaning algorithm and a dispatching, grabbing and charging algorithm, and the garbage dispatching of the garbage pool comprises dispatching and charging, dispatching and top-removing, bottom-cleaning, turning, dispatching, grabbing and charging and dispatching a percolate flow guide port.
The data of the garbage input amount is from the average input amount of the garbage in the recent period, and the recent period is 5 days to 1 year.
The regional garbage fermentation information passes through the fermentation value of each region and each layer of the fermentation algorithm, and the fermentation value algorithm is as follows: the fermentation value of each layer of each region = the heat value of garbage entering the pool 0-10% + the storage time equivalent 70-90% + the percolate equivalent 10-30% + the state equivalent 0-10% + the layer state equivalent 0-10%; the conversion value of the heat value of the garbage entering the tank is 0-1, the mapping relation between the heat value r of the garbage entering the tank and the conversion value z is set, the direct proportion is related, the conversion value is 0 when the conversion value is smaller than a certain value and is 1 when the conversion value is larger than the certain value, the storage time conversion value is 0-1, the conversion value of 5 days is 1 when the storage time is zero days and is 0 when the storage time is zero days, the conversion value of the percolate is 0-1, the conversion value z of the percolate is negatively related to the generation amount of the percolate, the conversion value is smaller and higher than the certain amount when the percolate is more, the conversion value is 0 when the storage time is 0, the zone state conversion value is 0-1, the conversion value of the feeding zone is 0, the conversion value of the fermentation zone is 0.8, the conversion value of the combustion zone is 1, the conversion value of the zone state is 0-1, the top layer is 0.3, the fermentation layer is 1, the bottom layer is 0, and the fermentation value is 0, and the algorithm of the fermentation value is carried out in the control system and is stored.
The information of the garbage area also comprises whether the area has garbage or not and is the highest layer or not, and the information is transmitted to the control system. Whether the garbage is in the highest layer or not is obtained through infrared scanning.
The percolate information obtains the height and the flow rate of percolate from the percolate guide opening.
The threshold value comprises a fermentation value threshold value, a percolate height and a feed inlet height.
The control system collects fermentation values of garbage on each layer of each area of the garbage pool, compares the fermentation value of the highest layer with the garbage in each area with a uncovering threshold value, if the fermentation value is smaller than the uncovering threshold value, the control system controls the garbage grab bucket to uncover the highest layer of the garbage area, compares the fermentation value of the lowest layer without the garbage on the upper layer of each area with a bottom clearing threshold value, and if the fermentation value is smaller than the bottom clearing threshold value, the control system controls the garbage grab bucket to clear the bottom of the lowest layer without the garbage in the area.
The control system collects the height of the garbage feeding and the height of the garbage pool feeding port, if the height of the garbage feeding port is larger than the height of the garbage pool feeding port in the area A, the control system controls the garbage grab bucket to move the garbage in the right adjacent area B, and if the highest layer of the area B has the garbage, the control system firstly controls the garbage grab bucket to move the garbage in the highest layer of the area B in the area C, and the rest is done in the same way.
The leachate diversion port is connected with the infiltration tank through a pump, the control system collects the flow rate of leachate, and calculates the height of the leachate through the speed of the leachate and the time divided by the area of the leachate diversion port, the control system compares the calculated height with the preset height of the leachate, and if the calculated height is larger than the preset height of the leachate, the control system controls the pump to be connected and discharges the infiltration port into the infiltration tank from the diversion port.
The preset data also comprises the uppermost garbage turning frequency of each region of the garbage pool, and the turning frequency is set according to the combination of historical data and personal experience.
3. Has the advantages that:
the method provided by the invention has the advantage that the fermentation sufficiency in each area in the garbage pool is accurately judged by the computer under the condition of big data. The water content in the regional garbage, the optimum frequency of uncovering and cleaning the top and the bottom and the optimum position of grabbing materials can be judged. The method can also guide the optimal feeding hole of the unloading personnel, guide the working personnel how to uncover, clear the bottom and turn the garbage in the garbage pool, so that the garbage can be fermented more fully, the heat value of the garbage entering the furnace is high and stable, and guide the working personnel how to grab the material and enter the furnace mouth, thereby ensuring the stability of the garbage entering the furnace of each boiler. Guide the staff in time to derive filtration liquid, prevent that filtration liquid accumulational overuse from influencing the fermentation of rubbish, all are automatic going on moreover.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
FIG. 2 is a top view of the garbage pool of the present invention.
Fig. 3 is a garbage pool area division and numbering diagram in the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings.
A garbage incineration plant garbage pool garbage automatic scheduling method based on big data comprises the steps of firstly, numbering a feeding door, a garbage area, a furnace inlet, a garbage grab bucket, garbage hanger coordinates and a leachate diversion port of a garbage furnace; the second step is that: presetting data, collecting data, calculating a fermentation value of each layer of each garbage area, inputting the collected data and the fermentation value of each layer of each area into a control system, and presetting a threshold value, and the third step: the control system automatically compares the acquired data with a preset threshold value; the fourth step: the control system dispatches the garbage in the garbage pool through the garbage grab bucket according to the comparison result; the fifth step: observing whether the working condition of the boiler is stable under dispatching, if the working condition of the boiler is deviated, entering a second step, recalculating the fermentation value of each layer of each area and resetting a threshold value; and if the working condition of the boiler is stable, the algorithm is proper, and finally the scheduling method suitable for the garbage pool is obtained.
As shown in fig. 1, the preset and collected data in the second step mainly includes the garbage input amount, garbage fermentation information and leachate information, the garbage scheduling algorithm of the control system is used for performing automatic scheduling feeding, uncovering, bottom cleaning, material grabbing and furnace entering and leachate diversion port diversion, and meanwhile, the garbage scheduling algorithm is continuously optimized in practical application, and finally, a suitable automatic scheduling method is obtained.
Examples
As shown in fig. 2, the number of the feeding gate is J, three feeding gates are provided, i.e., J1, J2 and J3, the furnace inlet is provided as R, two furnace inlets are provided, i.e., R1 and R2, and the coordinates of the garbage crane are as follows: the abscissa is between 0 and 50 meters, the ordinate is between 0 and 20 meters, the number of the percolate guide opening is S, four percolate guide openings are arranged at four corners of the garbage pool respectively, the four percolate guide openings are S1, S2, S3 and S4, a pump is arranged at the guide openings, and the pump is controlled by a control system.
As shown in fig. 3, the garbage area is divided into 4 areas, namely an area a, an area B, an area C and an area D, wherein the area a is a feeding area, the area B is a fermentation area, the area C is a preparation burning area, the area D is a burning area, and the garbage area is divided into 4 layers, namely 1 layer, 2 layers, 3 layers and 4 layers.
The preset data comprises the garbage input amount, the height of a garbage pool feeding hole, the range of a garbage hanging coordinate and the area of a percolate guiding opening, and the data in the collected data comprises garbage fermentation information, garbage area information, percolate information and garbage feeding height.
The garbage input amount is preset data, the garbage input amount is calculated according to an average value of 5 days to 1 year, the average value of 5 days is taken as an example, and the algorithm is as follows: average garbage input = garbage day cumulative value ÷ days.
The calculation formula is expressed as: LP = (L1+ L2+ L3+ L4+ L5) ÷ 5.
The height of the feed inlet of the garbage pool is also fixed, the data is also preset, the range of coordinates of the garbage crane is limited by the length and the width of the garbage pool, the data is also preset, and the area of the percolate guide opening is fixed, so the data is also preset.
The preset data also comprises the uppermost garbage turning frequency of each region of the garbage pool, and the turning frequency is set according to the combination of historical data and personal experience. Such as two turns a day with 12 hours intervals. The turning frequency and the interval time are set by combining historical data and experienced workers in the past, and can be adjusted and optimized in the later period according to whether the working condition of the boiler is stable or not
The collected information is mainly garbage fermentation information, and particularly fermentation values of each layer in each garbage area can be judged to uncover and clear the top.
The method is characterized in that the fermentation value of each layer of each region = 10% of the heat value of garbage entering a pool, 70% of the storage time, 20% of the percolate, 5% of the state of the region and 5% of the state of the layer are preset, the proportion of each part can be adjusted and optimized in the later period according to whether the working condition of a boiler is stable or not, the algorithm is performed in a control system, the fermentation value of each layer of each region is calculated and then stored in the control system, and the control system calculates once every interval of time.
And (4) obtaining a value according to a fermentation algorithm according to the garbage fermentation condition of the garbage area, wherein the higher the value is, the better the garbage fermentation degree is.
And when the uncovering area is not necessarily the 4 th layer of a certain garbage area, for example, B3, the 3 rd layer of the B area, but the 4 th layer of the B area has no garbage, then B3 is also the uncovering area, the control system calculates that the fermentation value of B3 is lower than 0.8, then the uncovering area B3 needs to be uncovered, and the control system sends an instruction to the garbage grab bucket to control the garbage grab bucket to be uncovered above B3.
And for whether bottom cleaning is required or not, setting the threshold value of the fermentation value to be 0.8, and adjusting and optimizing the threshold value according to whether the working condition of the boiler is stable or not at the later stage, wherein the bottom cleaning layer is the 1 st layer of a certain garbage area, and no garbage exists above the 1 st layer, the control system calculates that the fermentation value of the bottom cleaning layer of the certain garbage area is lower than 0.8, so that the bottom cleaning layer of the certain coming and coming area needs to be cleaned, and sends an instruction to the garbage grab bucket to control the garbage grab bucket to clean the bottom cleaning layer.
The driver drives the car and gets into the feed inlet, with in-car rubbish pour into the pond, to the algorithm of rubbish feed inlet, rubbish feed inlet = the rubbish feed inlet that the feed gate number corresponds, and rubbish height is greater than rubbish pond feed inlet under the rubbish feed inlet, control system sends the scheduling request, control rubbish grab bucket moves the regional rubbish that A4 district moved to B3 district through rubbish regional information whether have rubbish, whether the highest layer is judged, if B4 has rubbish, the highest layer, then control system control rubbish grab bucket moves B4 layer rubbish earlier to C district, so on and so on, until at least B4 layer does not have rubbish.
The height of the percolate can not exceed the early warning height, the speed of the percolate is multiplied by the time divided by the area of a percolate flow guide port to be smaller than the height of the percolate, if the height is exceeded within the prediction time t, the control system sends out a percolate derivation instruction before the time t and controls the pump to work, and the percolate is discharged to the percolation pool after the time t reaches the rated height.
The embodiment shows that the top uncovering, bottom clearing, turning, material grabbing and feeding and leachate removal are all automatic operation, the control system is accurately controlled by preset data and collected data due to big data and continuous adjustment and optimization, and the problems that the data in a garbage pool cannot be obtained in the conventional garbage incineration process, the top uncovering and bottom clearing can only be carried out manually and empirically, so that the resultant garbage incineration is insufficient and the environment is secondarily polluted are solved.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. The utility model provides a waste incineration factory garbage pool automatic scheduling method based on big data, is divided into 4 regions with the rubbish region, is A district, B district, C district and D district respectively, wherein A district is the feeding district, and B district is the fermentation district, and C district is for preparing to burn the district, and D district is the burning zone, the rubbish region divide into 4 layers, is 1 layer, 2 layers, 3 layers, 4 layers respectively, includes the following step: firstly, numbering a feeding door, a garbage area, a furnace inlet, a garbage grab bucket, a garbage hanger coordinate and a percolate diversion port of a garbage furnace; the second step is that: presetting data, collecting data, calculating a fermentation value of each layer of each garbage area, inputting the collected data and the fermentation value of each layer of each area into a control system, and presetting a threshold value, wherein the third step is as follows: the control system automatically compares the acquired data with a preset threshold value; the fourth step: the control system dispatches the garbage in the garbage pool through the garbage grab bucket according to the comparison result; the fifth step: observing whether the working condition of the boiler is stable under dispatching, if the working condition of the boiler is deviated, entering a second step, recalculating the fermentation value of each layer of each area and resetting the threshold value; if the working condition of the boiler is stable, the algorithm is proper, and finally a scheduling method suitable for the garbage pool is obtained, the preset data are the garbage input amount, the height of a feed port of the garbage pool, the range of coordinates of a garbage hanger and the area of a percolate guide opening, and the data in the collected data comprise garbage fermentation information, information of a garbage area, percolate information and garbage feeding height; the garbage scheduling calculation comprises a feed inlet algorithm, a top uncovering algorithm, a bottom clearing algorithm and a scheduling, material grabbing and furnace entering algorithm, the garbage scheduling of the garbage pool comprises scheduling, feeding, scheduling, top uncovering, bottom clearing, turning, scheduling, material grabbing and furnace entering and scheduling of a percolate diversion port, and the fermentation value of each layer of each area = the heat value of the garbage entering pool 0-10% + the storage time reduced value 70-90% + the percolate reduced value 10-30% + the area state reduced value 0-10% + the layer state reduced value 0-10%; the conversion value of the heat value of the garbage entering the tank is 0-1, the mapping relation between the heat value r of the garbage entering the tank and the conversion value z is set, the conversion value is related in positive proportion, 0 is taken when the conversion value is smaller than a certain value and is 1 when the conversion value is larger than the certain value, the conversion value of the storage time is 0-1, 1 is taken when the storage time is 5 days and 0 is taken when the storage time is zero days, the conversion value of the percolate is 0-1, the conversion value of the percolate is negatively related to the generation amount of the percolate, the conversion value is smaller and higher than a certain amount, the conversion value is 0 when the percolate is more, the conversion value is 0 when the storage time is 0-1, the conversion value of the feeding area is 0, the conversion value of the fermentation area is 0.8, the conversion value of the spare combustion area is 1, the conversion value of the layer state is 0-1, the top layer is 0.3, the fermentation layer is 1, the bottom layer is 0, and the algorithm of the fermentation value is carried out in a control system and is stored in the control system.
2. The method of claim 1, wherein: the data of the garbage input amount is from the average input amount of the garbage in the recent period, and the recent period is 5 days to 1 year.
3. The method of claim 1, wherein: the information of the garbage area also comprises whether the area has garbage or not and is the highest layer or not, and the information is transmitted to the control system.
4. The method of claim 1, wherein: the leachate information obtains the leachate height and flow rate from the leachate diversion opening.
5. The method of any one of claims 1-4, wherein: the threshold value comprises a fermentation value threshold value, a percolate height and a feed inlet height.
6. The method of claim 5, wherein: the control system collects fermentation values of garbage on each layer of each region of the garbage pool, compares the fermentation value of the highest layer with garbage in each region with a uncovering threshold value, controls the garbage grab bucket to uncover the highest layer of the garbage region if the fermentation value is smaller than the uncovering threshold value, compares the fermentation value of the lowest layer without garbage on the upper layer of each region with a bottom clearing threshold value, and controls the garbage grab bucket to clear the bottom of the lowest layer without garbage in each region if the fermentation value is smaller than the bottom clearing threshold value.
7. The method of claim 5, wherein: the control system collects the height of the garbage feeding and the height of the garbage pool feeding port, if the height of the garbage feeding port is larger than the height of the garbage pool feeding port in the area A, the control system controls the garbage grab bucket to move the garbage in the right adjacent area B, and if the highest layer of the area B has the garbage, the control system firstly controls the garbage grab bucket to move the garbage in the highest layer of the area B in the area C, and the rest is done in the same way.
8. The method of claim 5, wherein: the leachate diversion port is connected with the infiltration tank through a pump, the control system collects the flow rate of leachate, and calculates the height of the leachate through the speed of the leachate and the time divided by the area of the leachate diversion port, the control system compares the calculated height with the preset height of the leachate, and if the calculated height is larger than the preset height of the leachate, the control system controls the pump to be connected and discharges the infiltration port into the infiltration tank from the diversion port.
9. The method of any one of claims 1-4 and 6-8, wherein: the preset data also comprises the uppermost garbage turning frequency of each region of the garbage pool, and the turning frequency is set according to the combination of historical data and personal experience.
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| CN111578290A (en) | 2020-08-25 |
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