System and method for controlling operation of recovery boiler to reduce fouling

Abstract

To reduce a fouling rate in a recovery boiler system.SOLUTION: An analytical computing device receives boiler operating information including a fouling rate measured by a fouling sensor, which is a weight sensor configured to generate a value indicating a weight of a heat exchange element of a boiler, and boiler operating parameters; performs a regression analysis to determine at least one correlation to minimize the fouling rate; and transmits at least one adjusted boiler input parameter to a boiler controller.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a computer-implemented method for reducing fouling rates in recovery boiler systems, and to a system configured to perform such a method. Summary of the Invention [Means for solving the problem]

[0002]

[0003] In some aspects, a system is provided that includes a boiler, a fouling sensor, a boiler controller device, and an analytics computing device. The fouling sensor is associated with a component of the boiler. The analytics computing device includes at least one processor and a computer-readable medium. The computer-readable medium has computer-executable instructions stored thereon that, when executed by the at least one processor, cause the analytics computing device to perform actions including receiving boiler operating information over a period of time, the boiler operating information including boiler operating parameters and a fouling rate over the period of time, performing a regression analysis to determine at least one correlation between the boiler operating parameters and the fouling rate, adjusting at least one boiler input parameter based on the at least one correlation to minimize the fouling rate, and transmitting the at least one adjusted boiler input parameter to the boiler controller device for implementation.

[0003]

[0004] In some aspects, a computer-implemented method for reducing a fouling rate in a recovery boiler system is provided. A computing device receives boiler operating information over a period of time. The boiler operating information includes boiler operating parameters and a fouling rate over the period of time. The boiler operating parameters include one or more boiler input parameters. The computing device performs a regression analysis to determine at least one correlation between the boiler operating parameters and the fouling rate. The computing device adjusts the at least one boiler input parameter based on the at least one correlation to minimize the fouling rate.

[0004]

[0005] In some aspects, a non-transitory computer-readable medium is provided having computer-executable instructions stored thereon that, when executed by one or more processors of a computing device, cause the computing device to perform actions including receiving, by the computing device, boiler operating information over a period of time, the boiler operating information including boiler operating parameters and a fouling rate over the period of time, the boiler operating parameters including one or more boiler input parameters, performing, by the computing device, a regression analysis to determine at least one correlation between the boiler operating parameters and the fouling rate, and adjusting, by the computing device, the at least one boiler input parameter based on the at least one correlation to minimize the fouling rate.

[0005]

[0006] To easily identify the description of any particular element or function, the most significant digit(s) of the reference number refers to the figure number in which the element is first introduced. [Brief explanation of the drawings]

[0006] [Figure 1]

[0007] FIG. 1 illustrates components of one non-limiting example embodiment of a kraft black liquor recovery boiler system according to various aspects of the present disclosure. [Figure 2]

[0008] 1 illustrates how a recovery boiler is mounted in a steel support structure according to various aspects of the present disclosure. [Figure 3]

[0009] FIG. 1 illustrates some of the components of an independently suspended superheater system within a boiler according to various aspects of the present disclosure. [Figure 4]

[0010] FIG. 2 is a block diagram illustrating one non-limiting example embodiment of computing device components of a recovery boiler system according to various aspects of the present disclosure. [Figure 5]

[0011] 3 is a flow chart illustrating one non-limiting example embodiment of a method for minimizing fouling rates in a recovery boiler system according to various aspects of the present disclosure. [Figure 6]

[0012] FIG. 1 is a block diagram illustrating one non-limiting example embodiment of a computing device suitable for use as a computing device in connection with aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0007]

[0013] In the papermaking process, chemical pulping produces black liquor as a by-product, which contains nearly all of the inorganic cooking chemicals along with lignin and other organic materials separated from wood during pulping in the digester. The black liquor is burned in a recovery boiler. The two main functions of a recovery boiler are to recover the inorganic cooking chemicals used during the pulping process and to utilize the chemical energy in the organic portion of the black liquor to generate steam for the paper mill. The twin objectives of recovering both chemicals and energy make the design and operation of a recovery boiler very complex.

[0008]

[0014] In kraft recovery boilers, a superheater is located within the upper furnace to extract heat from the furnace gases through radiation and convection. Saturated steam enters the superheater section, and superheated steam exits at a controlled temperature. The superheater is constructed with an array of tube panels. The superheater surface is continually fouled by ash being carried out of the furnace chamber. The amount of black liquor that can be burned in a kraft recovery boiler is often limited by the rate and extent of fouling on the superheater surface. This fouling reduces the heat absorbed from liquor combustion, resulting in lower exit steam temperatures from the superheater and higher gas temperatures entering the boiler. The boiler is shut down for cleaning when the exit steam temperature is too low for downstream use or when the temperature entering the boiler bank exceeds the melting temperature of deposits, resulting in gas-side plugging of the boiler bank. Kraft recovery boilers are particularly prone to superheater fouling problems due to the high ash content of the fuel (typically greater than 35%) and the low melting temperature of the ash.

[0009]

[0015] There are three conventional methods for removing deposits from superheaters in kraft recovery boilers, listed in order of increasing downtime required and decreasing frequency: 1) soot blowing, 2) chill-and-blow, and 3) water washing.

[0010]

[0016] Sootblowing is the process of blowing ash deposits off superheaters using a blast of steam from nozzles called sootblowers. Sootblowing occurs virtually continuously during normal boiler operation, with different sootblowers turned on at different times. Because 5–10% of the boiler's steam is typically used for sootblowing, sootblowing reduces boiler efficiency. Each sootblowing operation reduces some of the ash deposits in the immediate vicinity, but the ash deposits nevertheless continue to grow over time. As the deposits grow, sootblowing becomes progressively less effective, resulting in reduced heat transfer.

[0011]

[0017] When the ash deposits reach a certain threshold where soot blowing becomes ineffective with a significant reduction in boiler efficiency, the deposits undergo a second cleaning process called "chill and blow" (also called "dry cleaning" because no water is used). The soot deposits are removed by a soot blowing process, which typically requires a partial or complete interruption of fuel combustion in the boiler for 4 to 12 hours, but not a complete boiler shutdown. During this time, the soot blower operates continuously to loosen the deposits from the superheater section and drop them onto the boiler floor. This process may be performed monthly, but the frequency can be reduced if soot blowing is performed optimally (on an optimal schedule and in an optimal sequence). Like soot blowing, the chill-and-blow process reduces some of the ash deposits in the immediate vicinity, but the ash deposits nevertheless continue to grow over time. As the deposits grow, the chill-and-blow process becomes less and less effective and must be performed more frequently.

[0012]

[0018] The third cleaning process, water washing, typically necessitates a complete boiler shutdown for two days, causing a significant loss of pulping capacity in the mill. In a heavily fouled recovery boiler, water washing may be required every four months, but if the chill-and-blow process is activated in a timely manner (i.e., before large deposits form in the boiler bank section), shutdowns and water washings can be avoided for a year or more.

[0013]

[0019] Since each of these cleaning processes reduces the efficiency of the boiler or involves boiler shutdown, it is clearly desirable to minimize the time spent during the cleaning processes. What is desired is an effective technique for regulating the operation of the boiler. Presumably, this is accomplished so that boiler fouling is minimized, thereby reducing the time spent or the amount of parasitic energy used in performing one or more of these cleaning processes.

[0014]

[0020] FIG. 1 diagrammatically illustrates the components of a typical kraft black liquor recovery boiler system 100. Black liquor is a by-product of chemical pulping in the papermaking process. The initial consistency of "weak black liquor" is approximately 15%. It is concentrated to combustion conditions (65% to 85% dry solids) in an evaporator 118 and then burned in a recovery boiler 106.

[0015]

[0021] The boiler 106 has a furnace section or "furnace 122," where black liquor is burned, and a convection heat transfer section 104, with an intermediate bullnose 128. Combustion converts the black liquor's organic material into gaseous products in a series of processes including drying, liquefaction (pyrolysis, molecular decomposition), and char burning / gasification. A portion of the organic matter is converted to solid carbon particles called char. While some char burns in flight, most of the char combustion occurs on a char bed 108 covering the floor of the furnace 122. As the carbon in the char is gasified or burned, inorganic compounds in the char are released and form a molten salt mixture called smelt, which flows to the bottom of the char bed 108 and is continuously tapped out of the furnace 122 through a smelt spout 110. The exhaust gases pass through an induced draft fan 138, are filtered through an electrostatic precipitator 136, and exit through the stack 102.

[0016]

[0022] The vertical walls 124 of the furnace are lined with vertically aligned wall tubes 126, and water is evaporated through the wall tubes 126 using the heat of the furnace 122. The furnace 122 has a primary level air port 112, a secondary level air port 114, and a tertiary level air port 120 for introducing combustion air at three different elevation levels. Black liquor is sprayed into the furnace 122 from a black liquor gun 116.

[0017]

[0023] The convection heat transfer section 104 includes: 1) an economizer 134 where the feedwater is heated to just below its boiling point; 2) a boiler bank 132 (or "steam generating bank") where, together with the wall tubes 126, the water is evaporated into steam; and 3) a steam generating bank 132 where the steam temperature is increased from the saturation temperature to the final superheat temperature. A series of parallel flow elements are used with intermediate headers to provide superheated steam, such as a superheater system 130, which houses three or more sets of tube banks (heat traps) that sequentially and incrementally heat the feedwater to superheat steam.

[0018]

[0024] FIG. 2 diagrammatically illustrates how the recovery boiler 106 is attached to a steel support structure 208, showing only the boiler's exterior and components of current interest. The entire recovery boiler 106 is suspended centrally from the steel support structure 208 by boiler hanger rods 202. The boiler hanger rods 202 are connected between the roof 206 of the boiler 106 and overhead beams 210 of the steel support structure 208. Another set of hanger rods (hereinafter referred to as "superheater hanger rods" or simply "hanger rods 212") suspends only the superheater system 130; that is, the superheater system 130 is suspended independently from the rest of the boiler 106. The outdoor area between the boiler roof 206 and the overhead beams 210 is referred to as the tower house 204.

[0019]

[0025] 3 diagrammatically illustrates some of the components of the superheater system 130 that are independently suspended within the boiler 106. The superheater system 130 in this embodiment has three superheater platens 310, 312, 314. While three superheaters are shown, it is within the scope of the present invention to incorporate more superheaters as needed. For clarity, the following discussion will describe or be in terms of the configuration of superheater platen 310, with the understanding that the configuration of superheater platen 312 and superheater platen 314 is the same.

[0020]

[0026] The superheater platens 310 typically have 20 to 50 platens 306. Steam enters the platens 306 through a manifold called an inlet header 308, is superheated within the platens, and exits the platens as superheated steam through another manifold called an outlet header 304. The platens 306 are suspended from the inlet headers 308 and the outlet headers 304, which are themselves suspended from the overhead beam 210 (FIG. 2) by hanger rods 212. Typically, 10 to 20 hanger rods 212 are equally spaced along the length of each inlet header 308 and outlet header 304 and secured below the headers and above the overhead beam 210 by conventional means, such as welding, as described below. The superheater system 130 typically has 20 hanger rods 212: 10 hanger rods for the inlet headers 308 and 10 hanger rods for the outlet headers 304. Each hanger rod has a threaded top around which a tension nut is turned to adjust the tension in the rod, which is typically adjusted after every 1-3 washes to maintain uniform (balanced) tension among all hanger rods 212 of a single superheater platen 310.

[0021]

[0027] When cleaned (immediately after a thorough water rinse), each superheater platen 310 typically weighs 5000 kg and each superheater hanger rod typically withstands a load of 5000 kg. Subsequently, just before the next water rinse is required, deposits (fouling) add an additional weight of typically 2000 kg to each superheater platen 310, which results in an additional load of typically 2000 kg on each hanger rod, resulting in a load of typically 5.0 x 10 -5 This results in an additional strain of cm / cm, which can be measured by commonly available methods such as with strain gauges 302.

[0022]

[0028] The strain (after zeroing off the strain read immediately after the previous water wash) summed for all hanger rods 212 suspending the superheater platens 310 is proportional to the weight of the load on that superheater. Each additional kg of load typically results in an additional strain of 2.0×10 cm / cm, which can be measured by a strain sensor such as strain gauge 302. Therefore, the weight of the load on each superheater platen 310 is The amount can be determined directly by measuring the strain on its corresponding hanger rod 212 .

[0023]

[0029] A typical system for determining pile weight for a single superheater platen 310 might include 20 strain gauges affixed to each of the superheater's 20 hanger rods 212, a computer with data acquisition capabilities (not shown) connected to the 60 strain gauges, and a computer program. Under program control, the computer periodically (typically every minute) records strain measurements from the 20 strain gauges (from each superheater platen 310, 312, 314), calculates the sum of the strain measurements, subtracts the sum of the strain measurements taken immediately after the previous washdown, and then multiplies the result by a calibration factor to obtain the current pile weight.

[0024]

[0030] In mathematical form, the formula is:

[0031] Sediment weight = (total of current strain gauge readings - total of strain gauge readings immediately after the previous water wash) x calibration factor

[0032] or equivalently stated as follows:

[0025]

[0033] Sediment weight = (ΣSt-ΣSo)×C

[0034] however,

[0035] ΣSt = Sum of strain gauge measurements at any time t

[0036] ΣSo = sum of strain gauge measurements immediately after the previous water wash considered at time zero

[0037] C = calibration constant for converting strain to weight

[0038] The strain gauges 302 allow for the determination of the weight of the superheater platen 310, which can be converted to the amount of fouling on the superheater platen 310; however, it is desirable to minimize the fouling rate in order to extend the intervals between which dry cleaning and / or water washing are performed. The relationship between various boiler operating parameters and fouling rate is complex, and therefore simple manual tuning of the boiler to minimize fouling is ineffective. What is desired is a technique for determining the complex relationship between boiler operating parameters and fouling rate in order to determine boiler input parameters that minimize the fouling rate.

[0026]

[0039] 4 is a block diagram illustrating one non-limiting example embodiment of computing device components of a recovery boiler system according to various aspects of the present disclosure. As shown, the recovery boiler system can include a boiler controller device 402 and an analytics computing device 404. The boiler controller device 402 and the analytics computing device 404 can be used to determine boiler input parameters that minimize fouling rates and to implement those input parameters during operation of the recovery boiler system 100.

[0027]

[0040] In some embodiments, the boiler controller device 402 is a computing device that electrically controls one or more components of the recovery boiler system 100. In some embodiments, the boiler controller device 402 may include an ASIC, an FPGA, or another customized computing device to control the components of the recovery boiler system 100. In some embodiments, the boiler controller device 402 may include a computing device, such as a desktop computing device, a laptop computing device, a server computing device, a mobile computing device, or any other type of computing device. In some embodiments, two or more computing devices may be used to collectively provide the functionality described as part of the boiler controller device 402.

[0028]

[0041] As shown, the boiler controller device 402 includes at least one processor 406, a network interface 410, a boiler component interface 414, and a computer-readable medium 416. In some embodiments, the network interface 410 may include any suitable communication technology for communicating with the analytical computing device 404, including, but not limited to, wired communication technology (including, but not limited to, Ethernet, USB, and Firewire), wireless communication technology (including, but not limited to, 2G, 3G, 4G, 5G, LTE, Bluetooth, ZigBee, Wi-Fi, and WiMAX), or a combination thereof. In some embodiments, the boiler component interface 414 communicatively couples the boiler controller device 402 to one or more adjustable components of the recovery boiler system 100, including, but not limited to, the black liquor gun 116, the evaporator 118, the primary level airport 112, the secondary level airport 114, and the tertiary level airport 120.

[0029]

[0042] As shown, the computer-readable medium 416 includes logic that, in response to execution by the at least one processor 406, causes the boiler controller device 402 to provide an information reporting engine 426 and an input control engine 428. In some aspects, the information reporting engine 426 receives information from one or more components of the recovery boiler system 100 and transmits the information to the analytics computing device 404. In some aspects, the input control engine 428 receives instructions from the analytics computing device 404 and adjusts adjustable components of the recovery boiler system 100 based on the instructions.

[0030]

[0043] In some aspects, analytics computing device 404 may include a computing device, such as a desktop computing device, a laptop computing device, a mobile computing device, a server computing device, one or more computing devices of a cloud computing system, or any other type of computing device. In some aspects, two or more computing devices may be used to collectively provide the functionality described as part of analytics computing device 404.

[0031]

[0044] As shown, the analytics computing device 404 includes at least one processor 408, a network interface 412, and a computer-readable medium 418. In some aspects, the network interface 412 may include any suitable communication technology for communicating with the network interface 410 of the boiler controller device 402.

[0032]

[0045] As shown, the computer-readable medium 418 includes logic that, in response to execution by at least one processor 408, causes the analytics computing device 404 to provide an information collection engine 420, an analytics engine 422, and an input adjustment engine 424. In some aspects, the information collection engine 420 receives information from at least an information reporting engine 426 of the boiler controller device 402. In some aspects, the analytics engine 422 analyzes the information collected by the information reporting engine 426 to determine correlations between various boiler operating parameters and fouling rates. In some aspects, the input adjustment engine 424 uses the correlations determined by the analytics engine 422 to determine adjustments to one or more boiler input parameters and sends those adjustments to the boiler controller device 402 for implementation. Further details of the actions performed by each of these components are provided below.

[0033]

[0046] "Computer-readable medium" refers to any technology-implementing removable or non-removable device capable of storing, in volatile or non-volatile fashion, information to be read by a processor of a computing device, including, but not limited to, hard drives, flash memory, solid-state drives, random access memory, This includes access memory (RAM), read-only memory (ROM), CD-ROM, DVD, or other disk storage, magnetic cassette, magnetic tape, and magnetic disk storage.

[0034]

[0047] An "engine" refers to logic embodied in hardware or software instructions that may be written in a programming language, such as C, C++, COBOL, JAVA™, PHP, Perl, HTML, CSS, JavaScript, VBScript, ASPX, Microsoft.NET™, Go, Python, and / or the like. An engine may be compiled into an executable program or written in an interpreted programming language. Software engines may be callable from other engines or from themselves. Generally, engines described herein refer to logic modules that may be merged with other engines or divided into sub-engines. An engine may be implemented by logic stored on any type of computer-readable medium or computer storage device and stored and executed by one or more general-purpose computers, thus creating the engine or a special-purpose computer configured to provide its functionality. An engine may be implemented by logic programmed into an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or another hardware device.

[0035]

[0048] 5 is a flow chart illustrating one non-limiting example embodiment of a method for minimizing the fouling rate of a recovery boiler system according to various aspects of the present disclosure. In method 500, at least one correlation between a boiler operating parameter and a fouling rate is determined such that the operation of the boiler can be automatically adjusted to minimize the fouling rate.

[0036]

[0049] From a start block, the method 500 proceeds to block 502, where the recovery boiler system 100 is operated by the boiler controller device 402 according to one or more boiler input parameters. In some embodiments, the boiler input parameters can include any controllable aspect of operating the recovery boiler system 100. In some embodiments, the chemical composition of the black liquor can be an example of a boiler input parameter. For example, the chloride content of the black liquor can affect the fouling rate. Therefore, chloride levels can be mitigated by reducing the ash recovered from the electrostatic precipitator 136 or by utilizing various techniques to selectively remove chlorides from this ash and then recycle the clean ash into thin black liquor. In some embodiments, the type of constituent chemicals can be varied to reduce the amount of chlorides in the black liquor. In some embodiments, the technique used to atomize the black liquor can be another example of a boiler input parameter. For example, the black liquor gun 116 can be adjustable, with the liquor gun configured to spray black liquor into the boiler 106 at different flow rates and / or with different droplet sizes.

[0037]

[0050] In some embodiments, the technique used to introduce air into the boiler may be another example of a boiler input parameter. For example, settings may be adjusted to vary the amount of air passed by at least one of primary-level air ports 112, secondary-level air ports 114, and / or tertiary-level air ports 120 and / or to use primary-level air ports 112, secondary-level air ports 114, and / or tertiary-level air ports 120 to vary the air pressure at one or more locations within boiler 106.

[0038]

[0051] In block 504, a cleaning cycle of the recovery boiler system 100 is initiated and completed. In some embodiments, the cleaning cycle of block 504 is performed during operation of the recovery boiler system 100. As described above, the boiler 10 A cleaning method available during operation of the recovery boiler system 106 is sootblowing. Sootblowing can be performed by multiple sootblowers that may not all be active at one time. Thus, a sootblowing "cleaning cycle" includes a sufficient amount of time such that all of the sootblowers are activated at least once, and the entire boiler 106 is cleaned at least once. By allowing a complete cleaning cycle to be completed, sufficient information is gathered to compensate for any short-term anomalies in detected fouling rates due to unequal effectiveness of individual sootblowers. In some embodiments, two or more cleaning cycles of the recovery boiler system 100 may be completed in block 504 while the recovery boiler system 100 is operating.

[0039]

[0052] In block 506, during operation and cleaning of the recovery boiler system 100, the information reporting engine 426 of the boiler controller device 402 transmits boiler operating parameters to the information gathering engine 420 of the analytical computing device 404. The period of time over which the transmission of boiler operating parameters occurs includes at least the cleaning cycle described in block 504. In some aspects, this period of time may include several weeks or months.

[0040]

[0053] In some embodiments, the boiler operating parameters may include boiler input parameters. In some embodiments, the boiler operating parameters may also include other information related to the operation of the recovery boiler system 100, including, but not limited to, the temperature of the boiler 106 at various locations, the amount of black liquor processed by the recovery boiler system 100, the pressure drop across heat transfer surfaces, and / or the operating load on the induced draft fan 138. In some embodiments, the boiler operating parameters may include weight information generated by at least one strain gauge 302. In some embodiments, the boiler operating parameters may be provided as one or more time series of boiler operating parameter values.

[0041]

[0054] In block 508, during operation and cleaning of the recovery boiler system 100, the information gathering engine 420 collects a time series of fouling value values. In some embodiments, the information gathering engine 420 can extract weight information received within the boiler operating parameters and determine a time series of fouling value values ​​by subtracting from each weight value the tare weight of the element suspended by the at least one strain gauge 302. In block 510, the analytics engine 422 of the analytics computing device 404 determines a fouling rate based on the time series of fouling value values. In some embodiments, the fouling rate can be determined for each step of the time series so that the change in fouling rate over time can be determined.

[0042]

[0055] In block 512, the analysis engine 422 performs a regression analysis on the boiler input parameters and the fouling rate. In some embodiments, the regression analysis may be configured to detect a correlation between a change in the boiler input parameter and a change in the fouling rate. In some embodiments, the regression analysis may detect a correlation between a single boiler input parameter and a change in the fouling rate. In some embodiments, the regression analysis may detect a correlation between a combination of two or more boiler input parameters and a change in the fouling rate. In some embodiments, the regression analysis may also detect a correlation between one or more boiler operating parameters other than the boiler input parameters and a change in the fouling rate, and / or may determine additional correlations between those boiler operating parameters and the boiler input parameters. For example, the regression analysis may detect a correlation between the boiler operating temperature and the fouling rate, and an additional correlation between the liquid gun setting and the boiler operating temperature.

[0043]

[0056] Any suitable analysis may be performed, including but not limited to classification and regression tree (CART) analysis. Recursive analysis may also be used. In some embodiments, CART analysis recursively partitions observations in a matched dataset, which includes a categorical (in the case of a classification tree) or continuous (in the case of a regression tree) dependent (response) variable and one or more independent (explanatory) variables, into progressively smaller groups. Each partition may be a binary partition. During each recursion, partitions for each explanatory variable are examined, and the partition that maximizes the homogeneity of the two resulting groups with respect to the dependent variable is chosen. When examining boiler input parameters and fouling rates, one non-limiting approach is to partition the boiler's behavior into "low fouling" and "high fouling" times, and then develop a CART classification tree using the boiler input parameters to create homogeneous groups that separate low fouling states from high fouling states. The range of the boiler input parameters that promotes low fouling states may then be selected as the control range.

[0044]

[0057] In block 514, the input adjustment engine 424 of the analytics computing device 404 determines adjusted boiler input parameters based on the results of the regression analysis. For example, the input adjustment engine 424 can use the correlation between liquid gun settings and fouling rates determined by the regression analysis to determine adjustments to liquid gun settings. As another example, the input adjustment engine 424 can use the correlation between settings for one or more air ports and fouling rates to determine adjustments to one or more air ports. As yet another example, the input adjustment engine 424 can use the correlation between black liquor chemistry and fouling rates to determine adjustments to chemistry. As yet another example, the input adjustment engine 424 can use the correlation between combined boiler input parameters and fouling rates to determine combined optimal settings or combined optimal settings where one boiler input parameter (such as chemistry) is held constant and determine adjusted boiler input parameters based on the combined optimal settings.

[0045]

[0058] In block 516, the input adjustment engine 424 causes the adjusted boiler input parameters to be used by the recovery boiler system 100 to minimize fouling. In some embodiments, the input adjustment engine 424 can cause the adjusted boiler input parameters to be automatically implemented by the recovery boiler system 100. For example, the input adjustment engine 424 can send the adjusted boiler input parameters to an input control engine 428 of the boiler controller device 402, which can automatically adjust the boiler input parameters to minimize fouling. In some embodiments, such adjustment of the boiler input parameters can include sending a command to an actuator for the black liquor gun 116 or one or more air ports to change settings for the black liquor gun 116 or one or more air ports. In some embodiments, such adjustment of the boiler input parameters can include sending a command to an actuator for a valve that controls the amount of precipitator ash purged or sent to the recovery boiler ash cleaning system to reduce chloride levels. In some embodiments, instead of the adjusted boiler input parameters being automatically implemented, the input adjustment engine 424 may indicate the adjusted boiler input parameters to an operator, who can generate instructions to change the settings of components of the recovery boiler system 100 to adjust the boiler input parameters as indicated.

[0046]

[0059] The method 500 then proceeds to an end block and ends.

[0060] 6 is a block diagram illustrating aspects of an exemplary computing device 600 suitable for use as a computing device of the present disclosure. While several different types of computing devices are described above, the exemplary computing device 600 illustrates various elements common to many different types of computing devices. While FIG. 6 is described with reference to a computing device implemented as a network device, the following description also applies to a server, personal computer, or other device that may be used to implement some aspects of the present disclosure. The computing device 600 may be applicable to a variety of devices, including computers, mobile phones, smartphones, tablet computers, embedded computing devices, and other devices. Some aspects of the computing device may be implemented in or include an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other customized device. Those skilled in the art will also recognize that the computing device 600 may be any one of any number of currently available or further developed devices.

[0047]

[0061] In its most basic configuration, computing device 600 includes at least one processor 602 and a system memory 604 connected by a communications bus 606. Depending on the exact configuration and device type, system memory 604 may be volatile or non-volatile memory, such as read-only memory (“ROM”), random access memory (“RAM”), EEPROM, flash memory, or similar memory technologies. Those skilled in the art will recognize that system memory 604 typically stores data and / or program modules that are immediately accessible to and / or presently being operated on by processor 602. In this regard, processor 602 can act as the computational center of computing device 600 by assisting in the execution of instructions.

[0048]

[0062] As further shown in FIG. 6 , computing device 600 may include a network interface 610 comprising one or more components for communicating with other devices over a network. Aspects of the present disclosure may access basic services utilizing network interface 610 to communicate using a common network protocol. Network interface 610 may also include a wireless network interface configured to communicate via one or more wireless communication protocols, e.g., Wi-Fi, 2G, 3G, LTE, WiMAX, Bluetooth, Bluetooth low energy, and / or the like. As will be appreciated by those skilled in the art, network interface 610 shown in FIG. 6 may represent one or more of the wireless or physical communication interfaces described and illustrated above with reference to particular components of computing device 600.

[0049]

[0063] In the exemplary embodiment shown in Figure 6, computing device 600 also includes storage medium 608. However, services may be accessed using computing devices that do not include means for persisting data to a local storage medium. Accordingly, storage medium 608 shown in Figure 6 is represented by a dashed line to indicate that storage medium 608 is optional. In any event, storage medium 608 may be removable or non-removable, volatile or non-volatile, implemented using any technology capable of storing information, such as, but not limited to, a hard drive, solid-state drive, CD-ROM, DVD, or other disk storage, magnetic cassette, magnetic tape, magnetic disk storage, and / or the like.

[0050]

[0064] Suitable implementations of a computing device including a processor 602, system memory 604, communications bus 606, storage medium 608, and network interface 610 are known and communicatively available. For simplicity of explanation and because they are not important to an understanding of the claimed subject matter, FIG. 6 does not show some of the typical components of many computing devices. In this regard, computing device 600 may include input devices, such as a keyboard, keypad, mouse, microphone, touch input device, touch screen, tablet, and / or the like. Such input devices may include radio frequency, infrared, serial, parallel, Bluetooth, The computing device 600 may be connected to the computing device 600 by a wired or wireless connection, including ethernet, Bluetooth Low Energy, USB, or other suitable connection protocols using a wireless or physical connection. Similarly, the computing device 600 may also include output devices, such as a display, speakers, printer, etc. Because these devices are well known in the art, they are not further shown or described herein.

[0051]

[0065] In the foregoing description, numerous specific details are set forth to provide a thorough understanding of each aspect. However, those skilled in the art will understand that the techniques described herein may be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations have not been shown or described in detail to avoid obscuring certain aspects.

[0052]

[0066] The order in which some or all of the processing blocks appear in each process should not be considered limiting. Rather, one skilled in the art having the benefit of this disclosure will understand that some of the processing blocks may be performed in various orders not shown, or may even be performed in parallel.

[0053]

[0067] The above description of illustrated embodiments of the present invention, including what is described in the Abstract, is not intended to be exhaustive or to limit the invention to the precise form disclosed. For illustrative purposes, specific embodiments of, and examples for, the present invention have been described herein; however, various modifications are possible within the scope of the present invention, as those skilled in the art will recognize.

[0054]

[0068] These modifications can be made to the invention in light of the above detailed description. The terms used in the following claims should not be construed to limit the invention to the specific embodiments disclosed therein. Rather, the scope of the invention is to be determined entirely by the following claims, which are to be construed in accordance with established doctrines of claim interpretation.

[0055]

[0069] Generally, the present invention provides a method for manufacturing a semiconductor device comprising:

[0070] a boiler controller device; and an analytics computing device including at least one processor and a computer-readable medium, the computer-readable medium responsive to execution by the at least one processor, for receiving, to the analytics computing device, boiler operating information over a period of time, the boiler operating information including boiler operating parameters and a fouling rate over the period of time, the boiler operating parameters including one or more boiler input parameters; performing a regression analysis to determine at least one correlation between the boiler operating parameters and the fouling rate; adjusting the at least one boiler input parameter based on the at least one correlation to minimize the fouling rate; and selecting the at least one adjusted boiler input parameter for implementation. and / or preferably, the boiler includes a heat exchange element and the fouling sensor is associated with the heat exchange element, and / or preferably, the fouling sensor is a weight sensor configured to generate a value indicative of a weight of the heat exchange element, and / or preferably, receiving the fouling rate over the time period includes receiving a time series of fouling value values ​​and determining the fouling rate based on the time series of fouling value values, and / or preferably, performing a regression analysis to determine at least one correlation between the boiler operating parameter and the fouling rate includes performing a CART analysis on the boiler operating information, and / or preferably. , and further comprising one or more soot blowers configured to operate according to a cycle, wherein receiving boiler operational information over a period of time comprises receiving boiler operational information over a period of time comprising at least one complete cycle; and / or preferably further comprising one or more valves configured to control an amount of precipitator ash purged or sent to an ash cleaning system to affect chloride levels, and one or more actuators configured to control the one or more valves, wherein the at least one boiler input parameter comprises a valve setting, and sending the at least one adjusted boiler input parameter to the boiler controller device for implementation comprises sending the valve setting to the one or more actuators, the one or more actuators configured to adjust the one or more valves based on the valve setting ... The boiler may further include a liquid gun, wherein the at least one boiler input parameter includes a liquid gun setting, and sending the at least one adjusted boiler input parameter to the boiler controller device for implementation includes sending the liquid gun setting to the boiler controller device, the boiler controller device being configured to change operation of the one or more liquid guns based on the liquid gun setting; and / or preferably, the boiler may further include one or more air ports, wherein the at least one boiler input parameter includes a setting for one or more air ports, and sending the at least one adjusted boiler input parameter to the boiler controller device for implementation includes sending the adjusted setting for the one or more air ports to the boiler controller device, the boiler controller device being configured to change operation of the one or more air ports based on the adjusted setting for the one or more air ports.

[0056]

[0071] 1. A computer-implemented method for reducing a fouling rate in a recovery boiler system, the method comprising: receiving, by a computing device, boiler operating information over a period of time, the boiler operating information including boiler operating parameters and a fouling rate over the period of time, the boiler operating parameters including one or more boiler input parameters; performing a regression analysis by the computing device to determine at least one correlation between the boiler operating parameters and the fouling rate; and causing the computing device to adjust the at least one boiler input parameter based on the at least one correlation to minimize the fouling rate; and / or preferably, receiving the fouling rate over the period of time includes: receiving, by the computing device, a time series of fouling amount values; and determining the fouling rate based on the time series of fouling amount values; and / or preferably, and / or preferably, wherein the step of receiving a time series of fouling values ​​comprises receiving a time series of fouling values ​​from a weight sensor configured to weigh the heat exchange element, and / or preferably, the step of performing a regression analysis to determine at least one correlation between the boiler operating parameter and the fouling rate comprises performing a CART analysis on the boiler operating information, and / or preferably, the recovery boiler system includes one or more sootblowers configured to operate according to a cycle, and wherein receiving boiler operating information over said period comprises receiving boiler operating information over a period comprising at least one complete cycle, and / or preferably, the step of adjusting at least one boiler input parameter based on the at least one correlation to minimize the fouling rate comprises at least one of adjusting boiler input chemistry, adjusting liquid gun settings, and adjusting settings for one or more air ports.

[0057]

[0072] In response to execution by one or more processors of the computing device, the computing device receives boiler operating information over a period of time. and / or preferably, receiving the fouling rate over the time period comprises receiving a time series of values ​​of fouling amount, and adjusting the fouling rate over the time period based on the time series of values ​​of fouling amount. and / or preferably, performing a regression analysis to determine at least one correlation between the boiler operating parameter and the fouling rate comprises performing a CART analysis on the boiler operating information, and / or preferably, the recovery boiler system includes one or more sootblowers configured to operate according to a cycle, and receiving boiler operating information over a period of time comprises receiving boiler operating information over a period of time comprising at least one complete cycle, and / or preferably, adjusting at least one boiler input parameter based on the at least one correlation to minimize the fouling rate comprises at least one of adjusting boiler input chemistry, adjusting liquid gun settings, and adjusting settings for one or more air ports.

Claims

1. 1. A system comprising: Boiler and a fouling sensor associated with a component of the boiler; a boiler controller device; 1. An analytics computing device comprising: at least one processor; and a computer-readable medium having stored thereon computer-executable instructions, the computer-executable instructions, in response to execution by the at least one processor, causing the analytics computing device to: receiving boiler operating information over a period of time, the boiler operating information including boiler operating parameters and a fouling rate over the period of time, the boiler operating parameters including one or more boiler input parameters; performing a regression analysis to determine at least one correlation between the boiler operating parameter and the fouling rate; adjusting at least one boiler input parameter based on the at least one correlation to minimize the fouling rate; transmitting the at least one adjusted boiler input parameter to the boiler controller device for implementation; an analytical computing device that performs an action including A system comprising:

2. The system of claim 1 , wherein the boiler includes a heat exchange element, and the fouling sensor is associated with the heat exchange element.

3. The system of claim 2 , wherein the fouling sensor is a weight sensor configured to generate a value indicative of a weight of the heat exchange element.

4. Receiving the fouling rate over the time period includes: receiving a time series of fouling volume values; determining the fouling rate based on the time series of fouling values; The system of claim 1 , comprising:

5. 2. The system of claim 1, wherein performing the regression analysis to determine the at least one correlation between the boiler operating parameter and the fouling rate comprises performing a CART analysis on the boiler operating information.

6. 10. The system of claim 1, further comprising one or more sootblowers configured to operate according to a cycle, and wherein receiving boiler operating information over a period of time comprises receiving boiler operating information over a period of time comprising at least one complete cycle.

7. one or more valves configured to control the amount of precipitator ash purged or sent to the ash cleaning system to affect chloride levels; one or more actuators configured to control the one or more valves; Furthermore, the at least one boiler input parameter includes a valve setting; Sending the at least one adjusted boiler input parameter to the boiler controller device for implementation includes sending the valve setting to the one or more actuators. This includes believing in The system of claim 1 , wherein the one or more actuators are configured to adjust the one or more valves based on the valve settings.

8. 2. The system of claim 1, further comprising one or more liquid guns, wherein the at least one boiler input parameter includes a liquid gun setting, and wherein sending the at least one adjusted boiler input parameter to the boiler controller device for implementation includes sending the liquid gun setting to the boiler controller device, and the boiler controller device is configured to vary operation of the one or more liquid guns based on the liquid gun setting.

9. 10. The system of claim 1, further comprising one or more airports, wherein the at least one boiler input parameter includes settings for one or more airports, and wherein transmitting the at least one adjusted boiler input parameter to the boiler controller device for implementation includes transmitting the adjusted settings for one or more airports to the boiler controller device, and the boiler controller device is configured to vary operation of the one or more airports based on the adjusted settings for the one or more airports.

10. 1. A computer-implemented method for reducing fouling rates in a recovery boiler system, comprising: receiving, by a computing device, boiler operating information over a period of time, the boiler operating information including boiler operating parameters and fouling rates over the period of time, the boiler operating parameters including one or more boiler input parameters; performing, by the computing device, a regression analysis to determine at least one correlation between the boiler operating parameter and the fouling rate; causing the computing device to adjust at least one boiler input parameter based on the at least one correlation to minimize the fouling rate; 11. A computer-implemented method comprising:

11. receiving the fouling rate over the time period includes: receiving, by the computing device, a time series of fouling volume values; determining, by the computing device, the fouling rate based on the time series of fouling volume values; The computer-implemented method of claim 10, comprising:

12. The computer-implemented method of claim 11 , wherein receiving the time series of fouling values ​​comprises receiving the time series of fouling values ​​from a weight sensor configured to weigh a heat exchange element.

13. 11. The computer-implemented method of claim 10, wherein performing the regression analysis to determine the at least one correlation between the boiler operating parameter and the fouling rate comprises performing a CART analysis on the boiler operating information.

14. 11. The computer-implemented method of claim 10, wherein the recovery boiler system includes one or more sootblowers configured to operate according to a cycle, and wherein receiving boiler operating information over a period of time includes receiving boiler operating information over a period of time that includes at least one complete cycle.

15. 11. The computer-implemented method of claim 10, wherein adjusting the at least one boiler input parameter based on the at least one correlation to minimize the fouling rate comprises at least one of adjusting a boiler input chemistry, adjusting a liquid gun setting, and adjusting settings for one or more air ports.

16. A non-transitory computer-readable medium having stored thereon computer-executable instructions that, in response to execution by one or more processors of a computing device, cause the computing device to: receiving, by the computing device, boiler operating information over a period of time, the boiler operating information including boiler operating parameters and a fouling rate over the period of time, the boiler operating parameters including one or more boiler input parameters; performing, by the computing device, a regression analysis to determine at least one correlation between the boiler operating parameter and the fouling rate; adjusting, by the computing device, at least one boiler input parameter based on the at least one correlation to minimize the fouling rate; A non-transitory computer-readable medium for causing an action to be performed, including:

17. Receiving the fouling rate over the time period includes: receiving, by the computing device, a time series of fouling volume values; determining, by the computing device, the fouling rate based on the time series of fouling volume values; 17. The computer-readable medium of claim 16, comprising:

18. 17. The computer-readable medium of claim 16, wherein performing the regression analysis to determine the at least one correlation between the boiler operating parameter and the fouling rate comprises performing a CART analysis on the boiler operating information.

19. 17. The computer-readable medium of claim 16, wherein the recovery boiler system includes one or more sootblowers configured to operate according to a cycle, and receiving boiler operating information over a period of time includes receiving boiler operating information over a period of time that includes at least one complete cycle.

20. 17. The computer-readable medium of claim 16, wherein adjusting the at least one boiler input parameter based on the at least one correlation to minimize the fouling rate comprises at least one of adjusting a boiler input chemistry, adjusting a liquid gun setting, and adjusting settings for one or more air ports.

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