CN112304657A - Method for dividing key easy-scaling groups of air preheater and monitoring heat exchange efficiency state - Google Patents
Method for dividing key easy-scaling groups of air preheater and monitoring heat exchange efficiency state Download PDFInfo
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Abstract
A method for dividing key scaling-prone groups of an air preheater and monitoring the heat exchange efficiency state comprises the following steps: establishing a key scaling-prone group division evaluation standard of an air preheater in an in-service heating furnace waste heat recovery system; selecting a detection point on the surface of the air preheater pipeline, and installing an integrated wireless temperature collector; constructing a wireless monitoring network for the operation heat exchange efficiency condition of a key easy-scaling air preheater group; building an online monitoring system platform; after real-time operation heat exchange efficiency data are obtained, drawing an isomorphic moving average index diagram of the heat exchange efficiency of the key easy-scaling air preheater; according to the different and same moving average index diagram of the heat exchange efficiency of the key air preheater easy to scale, the heat exchange efficiency state monitoring, scale cleaning early warning and scale cleaning effects of the air preheater are achieved. The invention has the advantages of simple and reasonable dividing program, convenient use, stable use and high working efficiency, reduces the safe operation and maintenance cost and realizes the long-period operation of the air preheater of the heating furnace.
Description
Technical Field
The invention relates to a method for monitoring the state of a key easy-scaling group of an air preheater for a heating furnace. In particular to a method for dividing key easy-scaling groups of an air preheater in a heating furnace waste heat recovery system and monitoring the heat exchange efficiency state.
Background
The petrochemical industry is a high-energy-consumption industry, and little improvement in any production process can bring huge economic benefits. The air preheater of the heating furnace is one of the common devices in petrochemical production, not only serves as a widely-used device for ensuring the normal operation of a specific process flow, but also is an important device for developing and utilizing industrial secondary energy and realizing waste heat recovery.
Furnace air preheaters that are put into operation can foul on heat transfer surfaces after a period of operation, thereby affecting flow and heat transfer. Meanwhile, the dirt often corrodes the heat transfer surface, and the service life of the air preheater of the heating furnace is seriously influenced. Therefore, the key easy-scaling group division is carried out on the heating furnace air preheater, the heat exchange efficiency condition of the key easy-scaling heating furnace air preheater is monitored, the scaling condition of the heating furnace air preheater is judged based on the change of the heat exchange efficiency, and a worker is reminded to take corresponding measures in time.
At the present stage, each process flow in a general petrochemical plant is provided with a flow monitoring device, flow data are stored in a real-time database, but heating furnace air preheaters are basically not subjected to temperature monitoring, and a small part of the heating furnace air preheaters are provided with field thermometers, but most of the detection is inaccurate. Therefore, the conditions for monitoring the operating state of the air preheater of the heating furnace and for warning the cleaning are not provided. To date, there is no complete system and method for monitoring the operating state of key scaling-prone groups of air preheaters of large petrochemical plant heating furnaces.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method for dividing key easy-scaling groups of an air preheater and monitoring the heat exchange efficiency state, which can determine and monitor the air preheater groups in a waste heat recovery system of a key easy-scaling heating furnace more intuitively and simply.
The technical scheme adopted by the invention is as follows: a method for dividing key scaling-prone groups of an air preheater and monitoring the heat exchange efficiency state comprises the following steps:
1) establishing a key scaling-prone group division evaluation standard of an air preheater in a waste heat recovery system of an in-service heating furnace, dividing key scaling-prone groups of the air preheater, and monitoring the operation heat exchange efficiency state of the key scaling-prone air preheater and performing scale cleaning early warning management and control according to a division result;
2) selecting a detection point on the surface of an air preheater pipeline, and installing an integrated wireless temperature collector on a flue gas inlet pipeline and a flue gas outlet pipeline of the air preheater which are easy to scale;
3) constructing a wireless monitoring network for the operation heat exchange efficiency condition of a key easy-scaling air preheater group;
4) establishing an online monitoring system platform, wherein the online monitoring system platform comprises an air preheater heat exchange efficiency state database, and performing key easy-scaling air preheater group division, wherein the key easy-scaling air preheater runs in real time to calculate heat exchange efficiency performance, inquire data and display;
5) after real-time operation heat exchange efficiency data are obtained, drawing a dissimilarity moving average index diagram of the heat exchange efficiency of the key easy-scaling air preheater by adopting a dissimilarity moving average method;
6) according to the different and same moving average index diagram of the heat exchange efficiency of the key easy-scaling air preheater, the current cleaning and scaling states of the tube bundle of the air preheater and the development and change trend of the heat exchange efficiency of the air preheater caused by the dispersion and aggregation of the short-term average index EDIF and the medium-and-long-term average index EDEA average line are represented, and the heat exchange efficiency state monitoring, scale removal early warning and scale removal effects of the air preheater are realized.
The method for dividing key easy-scaling groups of the air preheater and monitoring the heat exchange efficiency state comprises the steps of compiling a key easy-scaling group dividing program of the air preheater of the in-service heating furnace, dividing the key easy-scaling groups of the air preheater of the in-service heating furnace, determining the key easy-scaling groups of the air preheater of the heating furnace, which need to be subjected to operation state monitoring and cleaning prediction, according to an evaluation result, monitoring the heat exchange efficiency state of the air preheater of the heating furnace through a built wireless monitoring system network for the heat exchange efficiency operation state of the key easy-scaling groups of the air preheater of the heating furnace, combining a monitoring strategy based on an isomorphic moving average method, judging the scaling state of the air preheater of the heating furnace according to the change trend of the heat exchange efficiency. The method has the following advantages:
1. through the important degree of analysis heating furnace air heater production, the scale deposit mechanism of analysis heating furnace air heater to and carry out statistical analysis to the heating furnace air heater snaking number of times, formed the key easy scale deposit of heating furnace air heater group and divided the procedure, this division procedure is succinct reasonable, convenient to use.
2. The wireless monitoring system network for the heat exchange efficiency of the key easy-scaling group of the heating furnace air preheater is built, the monitoring system is flexible in configuration and stable in data transmission, the physical range of the heating furnace air preheater group can be expanded at any time, the use is stable, and the working efficiency is high.
3. By adopting an isogeny moving average method, dynamically drawing a heat exchange efficiency operation isogeny moving average index map of the heating furnace air preheater, judging the heat exchange efficiency state of the heating furnace air preheater more intuitively and simply, monitoring the heat exchange efficiency state of the key heating furnace air preheater easy to scale, judging the scaling state of the heating furnace air preheater according to the change trend of the heat exchange efficiency, reminding workers to take corresponding measures in time, guiding the heating furnace air preheater to operate efficiently, reducing the safe operation maintenance cost, and realizing the long-period operation of the heating furnace air preheater.
Drawings
FIG. 1 is a block flow diagram of a method for partitioning key fouling-prone groups of an air preheater and monitoring the state of heat exchange efficiency according to the present invention;
FIG. 2 is a block diagram of a real-time monitoring system for the operation status of a key scaling-prone heating furnace air preheater group of a large petrochemical plant;
FIG. 3 is a schematic diagram showing the acquisition of process parameters related to the heat exchange efficiency of an air preheater of a key scaling-prone heating furnace of a petrochemical plant;
FIG. 4 is a schematic diagram of the operation monitoring index of the heat exchange efficiency of the air preheater of the key easy-scaling heating furnace.
Detailed Description
The method for dividing key scaling-prone groups of the air preheater and monitoring the heat exchange efficiency state is described in detail below by combining the embodiment and the attached drawings.
The invention discloses a method for dividing key scaling-prone groups of an air preheater and monitoring the heat exchange efficiency state, which is a method for applying a real-time monitoring system for the heat exchange efficiency operation state of the air preheater of a key scaling-prone heating furnace of a large petrochemical device as shown in figures 1 and 2. The method mainly comprises the following steps that the operation condition monitoring result of the key easy-scaling heating furnace air preheater is mainly influenced by two factors, namely a system factor and a random factor, in the operation process of the heating furnace air preheater, the stability and the normality of the operation state are mainly concerned, if a large variable value system influence factor or a random influence factor exists in the operation process, the average value and the standard deviation of the measurement result are subjected to abnormal fluctuation, and the operation state of the heating furnace air preheater can be considered to be unstable. Mathematically, the operation process of the air preheater of the heating furnace is considered to be stable if the overall distribution parameters (mean and standard deviation) of the heat exchange efficiency test result data of the air preheater of the heating furnace are basically kept unchanged or are within the allowable range. If the distribution parameters exceed the allowable range, the reason of deviation should be analyzed, and measures are taken in time to adjust the operation state of the air preheater of the heating furnace.
In FIG. 2, 4 integrated wireless temperature collectors are included, wherein the four integrated wireless temperature collectors are arranged on a tube side inlet pipeline, a tube side outlet pipeline and a shell side inlet pipeline and a shell side outlet pipeline of a tested heating furnace air preheater 7-15; the wireless repeaters 4, 5 and 6 for expanding transmission distance, the intelligent wireless gateway 1 (model 1420A2A3A4) for receiving the data uploaded by the integrated wireless temperature collector, and the control system 2 and the factory real-time database system 3 which are connected with the intelligent wireless gateway 1 are installed.
As shown in FIG. 1, the method for dividing key easy-scaling groups of the air preheater and monitoring the heat exchange efficiency state comprises the following steps:
1) establishing a key scaling-prone group division evaluation standard of an air preheater in a waste heat recovery system of an in-service heating furnace, dividing key scaling-prone groups of the air preheater, and monitoring the operation heat exchange efficiency state of the key scaling-prone air preheater and performing scale cleaning early warning management and control according to a division result;
the key scaling-prone group division evaluation standard of the air preheater in the in-service heating furnace waste heat recovery system is as follows:
(1.1) determining four influencing factors of the key scaling susceptibility index of the air preheater: the production importance of the air preheater, the scaling condition of the air preheater, the historical scale cleaning times of the air preheater and the scale cleaning difficulty of the air preheater;
(1.2) determining the weight of four influencing factors of the key scaling-prone index of the air preheater by applying an analytic hierarchy process, wherein the four influencing factors comprise:
the air preheater production importance weight b1 was 0.16; the air preheater fouling status weight b2 was 0.41; the weight b3 of the historical scale removal times of the air preheater is 0.19; the weight b4 of the scale cleaning difficulty degree of the air preheater is 0.24;
(1.3) determining a key scaling degree scoring standard of the heat exchange efficiency of the air preheater; the method comprises the following steps:
(1.3.1) scoring according to the production importance of the air preheater:
after the air preheater breaks down, the heating furnace stops running, or more than two sets of related production devices abnormally fluctuate for 4 minutes;
after the air preheater breaks down, the heating furnace continues to operate, but the temperature of the material heating outlet of the heating furnace fluctuates by 3 minutes;
the product quality and the process operation are not influenced after the air preheater breaks down, but hot smoke and air series flow are caused, so that the heat efficiency reduction value of the heating furnace is more than 2 percent and is 2 minutes;
after the air preheater breaks down, the product quality and the process operation are not influenced, but hot smoke and air series flow are caused, so that the heat efficiency reduction value of the heating furnace is less than or equal to 2 percent and is 1 minute;
(1.3.2) scoring the fouling condition of the air preheater:
the proportion of the sediment covering the heat exchange wall surface in the last time of maintenance is more than 20 percent and is 5 minutes;
the proportion of the sediment covering the heat exchange wall surface during the last maintenance is 10-20 percent and is 4 minutes;
the proportion of the sediment covering the heat exchange wall surface during the last maintenance is 2% -10%, and is 3 minutes;
the proportion of the sediment covering the heat exchange wall surface in the last maintenance is less than 2 percent, which is 2 minutes;
the wall surface is clean and has no covering, and the score is 1;
(1.3.3) grading according to the historical scale cleaning times of the air preheater:
the scale cleaning is carried out for more than 6 times and 5 minutes regularly every four years;
the scale is regularly cleaned for 4-6 times every four years, and the cleaning time is 4 minutes;
the scale is regularly cleaned for 2-4 times every four years, and the cleaning time is 3 minutes;
the scale is cleaned for 1 time every four years, and the scale is 2 minutes;
no scale cleaning is needed every four years, and the scale cleaning rate is 1 minute;
(1.3.4) grading the scale cleaning difficulty of the air preheater:
the scale removal and shutdown time of the air preheater is more than or equal to 6 days and is 4 minutes;
the scale removal and shutdown time of the air preheater is less than 6 days and more than or equal to 3 days, and is 3 minutes;
the scale removal and shutdown time of the air preheater is less than 3 days and is 2 minutes;
the air preheater can carry out online snaking, is 1 minute.
(1.4) establishing a calculation of a key scaling tendency index of the air preheater and a dividing standard of a key scaling tendency group of the air preheater, wherein:
(1.4.1) the key scaling tendency index K of the air preheater is comprehensively calculated according to the following formula:
k-b 1 × production importance + b2 × fouling status + b3 × number of cleanings + b4 × ease of cleanings
Wherein b1 is 0.16, b2 is 0.41, b3 is 0.19, b4 is 0.24, which are respectively the weight of production importance, the weight of scaling condition, the weight of scale cleaning times and the weight of scale cleaning difficulty degree;
(1.4.2) air preheater key fouling susceptibility group division criteria are as follows:
when the key easy-scaling degree index K is 3.8-4.6, the scaling degree grade is A, namely the key easy-scaling equipment;
when the key easy-scaling degree index K is 3.7-2.7, the scaling degree grade is B, namely the important easy-scaling equipment;
when the key easy-scaling degree index K is 1-2.6, the scaling degree grade is C, and the equipment is common equipment.
2) Selecting a detection point on the surface of an air preheater pipeline, and installing an integrated wireless temperature collector on a flue gas inlet pipeline and a flue gas outlet pipeline of the air preheater which are easy to scale; wherein the content of the first and second substances,
the distance between the integrated wireless temperature collector installed on the air inlet pipeline of the air preheater and the air inlet of the air preheater is less than or equal to 1 meter, the distance between the integrated wireless temperature collector installed on the air outlet pipeline of the air preheater and the air outlet of the air preheater is greater than or equal to 3 meters, the distance between the integrated wireless temperature collector installed on the flue gas inlet pipeline of the air preheater and the flue gas inlet of the air preheater is less than or equal to 1 meter, and the distance between the integrated wireless temperature collector installed on the flue gas outlet pipeline of the air preheater and the flue gas outlet of the air preheater is greater than or equal to 3 meters. The integrated wireless temperature collector installed on the selected detection point on the surface of the air preheater pipeline can adopt the integrated wireless temperature collector with the model number of 648DX1D1I5W produced by Rossimont.
As shown in fig. 3, the flue gas inlet and the flue gas outlet of the air preheater of a heating furnace, and the air inlet and the air outlet of the air preheater are respectively provided with an integrated wireless temperature collector 18-21 for collecting the flue gas inlet temperature, the flue gas outlet temperature, the air inlet temperature and the air outlet temperature of the air preheater 17 of the heating furnace; according to the process flow, an air flow data acquisition instrument 22 is found on the side of the furnace inlet air pipeline of the heating furnace 16, and an air flow data acquisition instrument 23 is found on the side of the furnace outlet flue gas pipeline of the heating furnace 16.
3) Constructing a wireless monitoring network for the operation heat exchange efficiency condition of a key easy-scaling air preheater group; the method comprises the following steps: the installation positions and the number of the wireless repeaters are determined according to the number of the key easy-scaling air preheater groups and the distance between each air preheater and the intelligent wireless gateway, so that temperature data acquired by the temperature sensors in the integrated wireless temperature acquisition devices are transmitted to the intelligent wireless gateway by using a wireless communication method, and the intelligent wireless gateway is used for receiving the temperature data sent by more than one integrated wireless temperature acquisition devices and communicating with an upper PC.
4) Establishing an online monitoring system platform, wherein the online monitoring system platform comprises an air preheater heat exchange efficiency state database, and performing key easy-scaling air preheater group division, wherein the key easy-scaling air preheater runs in real time to calculate heat exchange efficiency performance, inquire data and display; the method comprises the following steps:
(4.1) establishing an air preheater heat exchange efficiency database
Establishing an air preheater heat exchange efficiency database for storing structural parameters of the air preheater, operating state parameters of a heating furnace where the air preheater is located, scaling conditions in air preheater maintenance data, historical scale cleaning times of the air preheater, position information and scale cleaning difficulty degree information of the air preheater, and key scaling group division results of the air preheater, the intelligent wireless gateway transmits the key easy-scaling air preheater smoke inlet pipeline medium temperature, the smoke outlet pipeline medium temperature, the air preheater air inlet pipeline medium temperature and the real-time monitoring data of the air outlet pipeline medium temperature to an upper PC, extracts the related air preheater smoke and air flow from the distributed control system, the processing load parameter of the heating furnace where the air preheater is located, the enthalpy value of the air at each temperature and the enthalpy value of the smoke at each temperature;
(4.2) dividing key easy-scaling air preheater groups according to the key easy-scaling group division evaluation standard of the air preheater in the in-service heating furnace waste heat recovery system;
(4.3) calculating the performance of the heat exchange efficiency of the key easy-scaling air preheater in real time, wherein the calculation formula is as follows:
Φ＝(Gcp)minΔtmin
Φmax＝(Gcp)min×(t1i-t2i)
in the formula:
eta is the heat exchange efficiency of the air preheater in unit percent;
phi is the actual heat exchange heat load of the air preheater, and the unit is W;
Φmaxthe maximum theoretical heat exchange heat load of the air preheater is W;
g is the mass flow of two fluids of air and flue gas in the air preheater, and the unit is kg/s;
cpthe average specific heat capacity of two fluids of air and smoke in the air preheater is expressed by a unit J/(kg ℃);
(Gcp)minthe heat capacity of the air preheater is smaller than that of the air and flue gas in the air preheater, and the unit is W/DEG C;
Δtminthe medium temperature difference of an inlet pipeline and an outlet pipeline of fluid with smaller heat capacity in air and flue gas in the air preheater is unit;
t1ifor the smoke in air preheatersInlet pipe medium temperature of gas, unit ℃;
t2iis the inlet duct medium temperature of the air in the air preheater in units of deg.c.
5) After real-time operation heat exchange efficiency data are obtained, drawing a dissimilarity moving average index diagram of the heat exchange efficiency of the key easy-scaling air preheater by adopting a dissimilarity moving average method;
in order to determine the actual operation condition of the air preheater of the monitored heating furnace, the working condition of the normal operation of the air preheater is selected to measure basic data, the measurement comprises measuring the medium temperature data of a flue gas inlet pipeline of the air preheater, the medium temperature data of a flue gas outlet pipeline, the medium temperature data of the air inlet pipeline, the temperature data of an air outlet pipeline, the air flow data and the flue gas flow data at the zero time every day after the normal operation of the air preheater of the heating furnace, and calculating the heat exchange efficiency eta of the air preheater based on each measurement timei(ii) a Calculating the heat exchange efficiency eta of each measurement moment under the normal operation condition of the air preheateri12 days of
Calculating the heat exchange efficiency eta of each measurement moment under the normal operation condition of the air preheateri26 days of
Calculating the weighted average value of the heat exchange efficiency of 12 days under the normal operation condition of the air preheater
And 26 day weighted average
The heat exchange efficiency short-term average index EDIF (i) to form a heat exchange efficiency short-term average index change trend line; calculating the average index EDEA (i) of 9 cycles of EDIF (i) to form a trend line of the change of the average index of the heat exchange efficiency in a long term; calculating the heat exchange efficiency sliding average index EMACD (i) of the air preheater to form an EMACD histogram, wherein the zero axis of the histogram isThe above is a positive energy column, and below zero is a negative energy column. The method specifically comprises the following steps:
(5.1) calculating the weighted average value of the air preheater in the normal operation condition for 12 days
And a weighted average of 26 days
After the monitored air preheater is overhauled for each time, selecting data of the air preheater after 12 days of stable operation as a data sampling initial point, taking a sampling period every 24 hours, collecting medium temperature data of an air inlet pipeline of the air preheater, medium temperature data of an air outlet pipeline, medium temperature data of a smoke inlet pipeline, medium temperature data of a smoke outlet pipeline, air flow data and smoke flow data, calculating the heat exchange efficiency of each sampling period according to a heat exchange efficiency formula of the air preheater, and calculating the heat exchange efficiency eta of each sampling period according to the heat exchange efficiency eta of each sampling periodiComputing
And
in the formula: eta1The value of the heat exchange efficiency is the value of the 1 st sampling period; etaiThe value of the heat exchange efficiency of the ith sampling period is;
the heat exchange efficiency of the air preheater is an initial average value;
the weighted average value of the heat exchange efficiency of the air preheater on the ith 12 days is obtained;
the weighted average value of the ith 26 days of the heat exchange efficiency of the air preheater is obtained; etai-1(12)The weighted average value of the heat exchange efficiency of the air preheater for the i-1 th 12 days is obtained; etai-1(26)The weighted average value of the heat exchange efficiency of the air preheater for the i-1 th 26 days is obtained;
(5.2) determining the short-term average index EDIF (i) of the heat exchange efficiency of the ith sampling period under the normal operation working condition by the following formula:
(5.3) determining the heat exchange efficiency medium-long term average index EDEA (i) of the ith sampling period under the normal operation condition through the following formula:
EDEA(i)＝0.2×EDIF(i)+0.8×EDEA(i-1)i＝1......n
(5.4) determining the heat exchange efficiency moving average index EMACD (i) of the air preheater in the ith sampling period under the normal operation condition by the following formula:
EMACD(i)＝2×(EDIF(i)-EDEA(i))i＝1......n
(5.5) taking the sampling period as an abscissa, taking the value range of the ordinate as (-1,2), and falling EDIF (i) and EDEA (i) values of each sampling period on a coordinate system to form a short-term average index change trend line of the heat exchange efficiency and a long-term average index change trend line of the heat exchange efficiency, forming an EMACD column diagram by using the point values of the EMACD (i) falling on the coordinate system, and finally forming a different and same moving average index diagram containing the heat exchange efficiency of the key scaling-prone air preheater consisting of two lines and one column.
6) According to the dissimilarity moving average index graph of the heat exchange efficiency of the key easy-scaling air preheater shown in the figure 4, the current cleaning and scaling states of the tube bundle of the air preheater and the development and change trend of the heat exchange efficiency of the air preheater caused by the dispersion and aggregation of the short-term average index EDIF and the medium-term average index EDEA average line are represented, so that the heat exchange efficiency state monitoring, scale cleaning early warning and scale cleaning effects of the air preheater are realized; the method comprises the following steps:
(6.1) when the short-term average index EDIF and the medium-term average index EDEA are both greater than 0, on the different and same moving average index graph of the heat exchange efficiency of the key easy-scaling air preheater, the short-term average index EDIF and the medium-term average index EDEA are both above the zero line and are kept to stably move along the direction of the horizontal axis, and in the heat exchange efficiency sliding average index EMACD histogram, a positive energy column above the zero line, the short-term average index EDIF and the medium-term average index EDEA are continuously increased in the same direction, which indicates that the heat exchange efficiency is good and the operation is stable, so that the current stable state can be;
(6.2) when the short-term average index EDIF and the medium-term average index EDEA are both greater than 0, on a key scaling-prone air preheater heat exchange efficiency dissimilarity moving average index graph, the short-term average index EDIF and the medium-term average index EDEA are both above a zero line and both move downwards, particularly when the medium-term average index EDEA passes through the short-term average index EDIF and continues above the EDIF, and a negative energy column below the zero line in a heat exchange efficiency sliding average index EMACD histogram is continuously increased in the same direction as the short-term average index EDIF and the medium-term average index EDEA, which shows that the heat exchange efficiency condition is poor, scaling exists on a tube bundle, a first heat exchange efficiency reduction early warning point is arranged at the intersection of the short-term average index EDIF and the medium-term average index EDEA, and the flow rate is increased under the condition that production is not affected, so that deposits; when the two lines both fall below a zero line, the short-term average index EDIF and the medium-term average index EDEA are both smaller than 0, namely the short-term average index EDIF and the medium-term average index EDEA are both below the zero line and are represented on a heat exchange efficiency different moving average index graph of the key scaling-prone air preheater, and a negative energy column in a heat exchange efficiency sliding average index EMACD histogram is continuously increased in the same direction as the short-term average index EDIF and the medium-term average index EDEA, and is a second heat exchange efficiency falling early warning point, a scale cleaning valve is opened, and scale cleaning is performed on the tube bundle;
(6.3) when the short-term average index EDIF and the medium-term average index EDEA are both less than 0, namely on the key easy-scaling air preheater heat exchange efficiency isokinetic moving average index graph, the short-term average index EDIF and the medium-term average index EDEA are both below a zero line, but move upwards, particularly when the short-term average index EDIF passes through the medium-term average index EDEA and continues above the medium-term average index EDEA, and a negative energy column below the zero line in the heat exchange efficiency sliding average index EMACD histogram is continuously increased in the same direction as the short-term average index EDIF and the medium-term average index EDEA, the scale cleaning effect is obvious, the scale cleaning amount is increased for preventing the heat exchange efficiency from rebounding until the heat exchange efficiency returns to a normal state.
Claims (9)
1. A method for dividing key scaling-prone groups of an air preheater and monitoring the heat exchange efficiency state is characterized by comprising the following steps:
1) establishing a key scaling-prone group division evaluation standard of an air preheater in a waste heat recovery system of an in-service heating furnace, dividing key scaling-prone groups of the air preheater, and monitoring the operation heat exchange efficiency state of the key scaling-prone air preheater and performing scale cleaning early warning management and control according to a division result;
2) selecting a detection point on the surface of an air preheater pipeline, and installing an integrated wireless temperature collector on a flue gas inlet pipeline and a flue gas outlet pipeline of the air preheater which are easy to scale;
3) constructing a wireless monitoring network for the operation heat exchange efficiency condition of a key easy-scaling air preheater group;
4) establishing an online monitoring system platform, wherein the online monitoring system platform comprises an air preheater heat exchange efficiency state database, and performing key easy-scaling air preheater group division, wherein the key easy-scaling air preheater runs in real time to calculate heat exchange efficiency performance, inquire data and display;
5) after real-time operation heat exchange efficiency data are obtained, drawing a dissimilarity moving average index diagram of the heat exchange efficiency of the key easy-scaling air preheater by adopting a dissimilarity moving average method;
6) according to the different and same moving average index diagram of the heat exchange efficiency of the key easy-scaling air preheater, the current cleaning and scaling states of the tube bundle of the air preheater and the development and change trend of the heat exchange efficiency of the air preheater caused by the dispersion and aggregation of the short-term average index EDIF and the medium-and-long-term average index EDEA average line are represented, and the heat exchange efficiency state monitoring, scale removal early warning and scale removal effects of the air preheater are realized.
2. The method for dividing key scaling-prone groups of an air preheater and monitoring the state of heat exchange efficiency of the air preheater according to claim 1, wherein the evaluation criteria for dividing the key scaling-prone groups of the air preheater in the in-service heating furnace waste heat recovery system in the step 1) are as follows:
(1.1) determining four influencing factors of the key scaling susceptibility index of the air preheater: the production importance of the air preheater, the scaling condition of the air preheater, the historical scale cleaning times of the air preheater and the scale cleaning difficulty of the air preheater;
(1.2) determining the weight of four influencing factors of the key scaling-prone index of the air preheater by applying an analytic hierarchy process, wherein the four influencing factors comprise:
the air preheater production importance weight b1 was 0.16; the air preheater fouling status weight b2 was 0.41; the weight b3 of the historical scale removal times of the air preheater is 0.19; the weight b4 of the scale cleaning difficulty degree of the air preheater is 0.24;
(1.3) determining a key scaling degree scoring standard of the heat exchange efficiency of the air preheater;
and (1.4) establishing calculation of a key scaling tendency index of the air preheater and a key scaling tendency group division standard of the air preheater.
3. The method for dividing the key scaling-prone group of the air preheater and monitoring the heat exchange efficiency state according to claim 2, wherein the step (1.3) of establishing the key scaling-prone degree scoring standard of the heat exchange efficiency of the air preheater comprises:
(1.3.1) scoring according to the production importance of the air preheater:
after the air preheater breaks down, the heating furnace stops running, or more than two sets of related production devices abnormally fluctuate for 4 minutes;
after the air preheater breaks down, the heating furnace continues to operate, but the temperature of the material heating outlet of the heating furnace fluctuates by 3 minutes;
the product quality and the process operation are not influenced after the air preheater breaks down, but hot smoke and air series flow are caused, so that the heat efficiency reduction value of the heating furnace is more than 2 percent and is 2 minutes;
after the air preheater breaks down, the product quality and the process operation are not influenced, but hot smoke and air series flow are caused, so that the heat efficiency reduction value of the heating furnace is less than or equal to 2 percent and is 1 minute;
(1.3.2) scoring the fouling condition of the air preheater:
the proportion of the sediment covering the heat exchange wall surface in the last time of maintenance is more than 20 percent and is 5 minutes;
the proportion of the sediment covering the heat exchange wall surface during the last maintenance is 10-20 percent and is 4 minutes;
the proportion of the sediment covering the heat exchange wall surface during the last maintenance is 2% -10%, and is 3 minutes;
the proportion of the sediment covering the heat exchange wall surface in the last maintenance is less than 2 percent, which is 2 minutes;
the wall surface is clean and has no covering, and the score is 1;
(1.3.3) grading according to the historical scale cleaning times of the air preheater:
the scale cleaning is carried out for more than 6 times and 5 minutes regularly every four years;
the scale is regularly cleaned for 4-6 times every four years, and the cleaning time is 4 minutes;
the scale is regularly cleaned for 2-4 times every four years, and the cleaning time is 3 minutes;
the scale is cleaned for 1 time every four years, and the scale is 2 minutes;
no scale cleaning is needed every four years, and the scale cleaning rate is 1 minute;
(1.3.4) grading the scale cleaning difficulty of the air preheater:
the scale removal and shutdown time of the air preheater is more than or equal to 6 days and is 4 minutes;
the scale removal and shutdown time of the air preheater is less than 6 days and more than or equal to 3 days, and is 3 minutes;
the scale removal and shutdown time of the air preheater is less than 3 days and is 2 minutes;
the air preheater can carry out online snaking, is 1 minute.
4. A method for dividing key scaling-prone groups of an air preheater and monitoring the state of heat exchange efficiency according to claim 2, wherein the following steps (1.4):
(1.4.1) the key scaling tendency index K of the air preheater is comprehensively calculated according to the following formula:
k-b 1 × production importance + b2 × fouling status + b3 × number of cleanings + b4 × ease of cleanings
Wherein b1 is 0.16, b2 is 0.41, b3 is 0.19, b4 is 0.24, which are respectively the weight of production importance, the weight of scaling condition, the weight of scale cleaning times and the weight of scale cleaning difficulty degree;
(1.4.2) air preheater key fouling susceptibility group division criteria are as follows:
when the key easy-scaling degree index K is 3.8-4.6, the scaling degree grade is A, namely the key easy-scaling equipment;
when the key easy-scaling degree index K is 3.7-2.7, the scaling degree grade is B, namely the important easy-scaling equipment;
when the key easy-scaling degree index K is 1-2.6, the scaling degree grade is C, and the equipment is common equipment.
5. The method for dividing key scaling-prone groups of an air preheater and monitoring the state of heat exchange efficiency of the air preheater according to claim 1, wherein in the step 2):
the distance between the integrated wireless temperature collector installed on the air inlet pipeline of the air preheater and the air inlet of the air preheater is less than or equal to 1 meter, the distance between the integrated wireless temperature collector installed on the air outlet pipeline of the air preheater and the air outlet of the air preheater is greater than or equal to 3 meters, the distance between the integrated wireless temperature collector installed on the flue gas inlet pipeline of the air preheater and the flue gas inlet of the air preheater is less than or equal to 1 meter, and the distance between the integrated wireless temperature collector installed on the flue gas outlet pipeline of the air preheater and the flue gas outlet of the air preheater is greater than or equal to 3 meters.
6. The method for dividing the key easy-to-scale groups of the air preheater and monitoring the heat exchange efficiency state of the air preheater according to claim 1, wherein the step 3) of constructing the wireless monitoring network for the operation heat exchange efficiency condition of the key easy-to-scale air preheater groups comprises the following steps: the installation positions and the number of the wireless repeaters are determined according to the number of the key easy-scaling air preheater groups and the distance between each air preheater and the intelligent wireless gateway, so that temperature data acquired by the temperature sensors in the integrated wireless temperature acquisition devices are transmitted to the intelligent wireless gateway by using a wireless communication method, and the intelligent wireless gateway is used for receiving the temperature data sent by more than one integrated wireless temperature acquisition devices and communicating with an upper PC.
7. The method for dividing key scaling-prone groups of an air preheater and monitoring the state of heat exchange efficiency of the air preheater according to claim 1, wherein the step 4) comprises the following steps:
(4.1) establishing an air preheater heat exchange efficiency database
Establishing an air preheater heat exchange efficiency database for storing structural parameters of the air preheater, operating state parameters of a heating furnace where the air preheater is located, scaling conditions in air preheater maintenance data, historical scale cleaning times of the air preheater, position information and scale cleaning difficulty degree information of the air preheater, and key scaling group division results of the air preheater, the intelligent wireless gateway transmits the key easy-scaling air preheater smoke inlet pipeline medium temperature, the smoke outlet pipeline medium temperature, the air preheater air inlet pipeline medium temperature and the real-time monitoring data of the air outlet pipeline medium temperature to an upper PC, extracts the related air preheater smoke and air flow from the distributed control system, the processing load parameter of the heating furnace where the air preheater is located, the enthalpy value of the air at each temperature and the enthalpy value of the smoke at each temperature;
(4.2) dividing key easy-scaling air preheater groups according to the key easy-scaling group division evaluation standard of the air preheater in the in-service heating furnace waste heat recovery system;
(4.3) calculating the performance of the heat exchange efficiency of the key easy-scaling air preheater in real time, wherein the calculation formula is as follows:
Φ＝(Gcp)minΔtmin
Φmax＝(Gcp)min×(t1i-t2i)
in the formula:
eta is the heat exchange efficiency of the air preheater in unit percent;
phi is the actual heat exchange heat load of the air preheater, and the unit is W;
Φmaxthe maximum theoretical heat exchange heat load of the air preheater is W;
g is the mass flow of two fluids of air and flue gas in the air preheater, and the unit is kg/s;
cpthe average specific heat capacity of two fluids of air and smoke in the air preheater is expressed by a unit J/(kg ℃);
(Gcp)minthe heat capacity of the air preheater is small in two fluids of air and flue gas, and the unit is W/DEG C;
Δtminthe medium temperature difference of an inlet pipeline and an outlet pipeline of fluid with small heat capacity in air and flue gas in the air preheater is unit;
t1ithe temperature is the inlet pipeline medium temperature of the flue gas in the air preheater, and the unit is;
t2iis the inlet duct medium temperature of the air in the air preheater in units of deg.c.
8. A method for dividing key scaling-prone groups of an air preheater and monitoring the state of heat exchange efficiency according to claim 1, wherein the step 5) comprises the following steps:
(5.1) calculation ofWeighted average of 12 days under normal operating conditions of air preheater
And a weighted average of 26 days
After the monitored air preheater is overhauled for each time, selecting data of the air preheater after 12 days of stable operation as a data sampling initial point, taking a sampling period every 24 hours, collecting medium temperature data of an air inlet pipeline of the air preheater, medium temperature data of an air outlet pipeline, medium temperature data of a smoke inlet pipeline, medium temperature data of a smoke outlet pipeline, air flow data and smoke flow data, calculating the heat exchange efficiency of each sampling period according to a heat exchange efficiency formula of the air preheater, and calculating the heat exchange efficiency eta of each sampling period according to the heat exchange efficiency eta of each sampling periodiComputing
And
in the formula: eta1The value of the heat exchange efficiency is the value of the 1 st sampling period; etaiThe value of the heat exchange efficiency of the ith sampling period is;
the heat exchange efficiency of the air preheater is an initial average value;
the weighted average value of the heat exchange efficiency of the air preheater on the ith 12 days is obtained;
the weighted average value of the ith 26 days of the heat exchange efficiency of the air preheater is obtained; etai-1(12)The weighted average value of the heat exchange efficiency of the air preheater for the i-1 th 12 days is obtained; etai-1(26)The weighted average value of the heat exchange efficiency of the air preheater for the i-1 th 26 days is obtained;
(5.2) determining the short-term average index EDIF (i) of the heat exchange efficiency of the ith sampling period under the normal operation working condition by the following formula:
(5.3) determining the heat exchange efficiency medium-long term average index EDEA (i) of the ith sampling period under the normal operation condition through the following formula:
EDEA(i)＝0.2×EDIF(i)+0.8×EDEA(i-1)i＝1......n
(5.4) determining the heat exchange efficiency moving average index EMACD (i) of the air preheater in the ith sampling period under the normal operation condition by the following formula:
EMACD(i)＝2×(EDIF(i)-EDEA(i))i＝1......n
(5.5) taking the sampling period as an abscissa, taking the value range of the ordinate as (-1,2), and falling EDIF (i) and EDEA (i) values of each sampling period on a coordinate system to form a short-term average index change trend line of the heat exchange efficiency and a long-term average index change trend line of the heat exchange efficiency, forming an EMACD column diagram by using the point values of the EMACD (i) falling on the coordinate system, and finally forming a different and same moving average index diagram containing the heat exchange efficiency of the key scaling-prone air preheater consisting of two lines and one column.
9. A method for dividing key scaling-prone groups of an air preheater and monitoring the state of heat exchange efficiency according to claim 1, wherein step 6) comprises:
(6.1) when the short-term average index EDIF and the medium-term average index EDEA are both greater than 0, on the different and same moving average index graph of the heat exchange efficiency of the key easy-scaling air preheater, the short-term average index EDIF and the medium-term average index EDEA are both above the zero line and are kept to stably move along the direction of the horizontal axis, and in the heat exchange efficiency sliding average index EMACD histogram, a positive energy column above the zero line, the short-term average index EDIF and the medium-term average index EDEA are continuously increased in the same direction, which indicates that the heat exchange efficiency is good and the operation is stable, so that the current stable state can be;
(6.2) when the short-term average index EDIF and the medium-term average index EDEA are both greater than 0, on a key scaling-prone air preheater heat exchange efficiency dissimilarity moving average index graph, the short-term average index EDIF and the medium-term average index EDEA are both above a zero line and both move downwards, particularly when the medium-term average index EDEA passes through the short-term average index EDIF and continues above the EDIF, and a negative energy column below the zero line in a heat exchange efficiency sliding average index EMACD histogram is continuously increased in the same direction as the short-term average index EDIF and the medium-term average index EDEA, which shows that the heat exchange efficiency condition is poor, scaling exists on a tube bundle, a first heat exchange efficiency reduction early warning point is arranged at the intersection of the short-term average index EDIF and the medium-term average index EDEA, and the flow rate is increased under the condition that production is not affected, so that deposits; when the two lines both fall below a zero line, the short-term average index EDIF and the medium-term average index EDEA are both smaller than 0, namely the short-term average index EDIF and the medium-term average index EDEA are both below the zero line and are represented on a heat exchange efficiency different moving average index graph of the key scaling-prone air preheater, and a negative energy column in a heat exchange efficiency sliding average index EMACD histogram is continuously increased in the same direction as the short-term average index EDIF and the medium-term average index EDEA, and is a second heat exchange efficiency falling early warning point, a scale cleaning valve is opened, and scale cleaning is performed on the tube bundle;
(6.3) when the short-term average index EDIF and the medium-term average index EDEA are both less than 0, namely on the key easy-scaling air preheater heat exchange efficiency isokinetic moving average index graph, the short-term average index EDIF and the medium-term average index EDEA are both below a zero line, but move upwards, particularly when the short-term average index EDIF passes through the medium-term average index EDEA and continues above the medium-term average index EDEA, and a negative energy column below the zero line in the heat exchange efficiency sliding average index EMACD histogram is continuously increased in the same direction as the short-term average index EDIF and the medium-term average index EDEA, the scale cleaning effect is obvious, the scale cleaning amount is increased for preventing the heat exchange efficiency from rebounding until the heat exchange efficiency returns to a normal state.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113432740A (en) * | 2021-06-25 | 2021-09-24 | 西安交通大学 | Wireless temperature measurement system for heat storage element in rotor of rotary air preheater |
| CN116196872A (en) * | 2023-04-04 | 2023-06-02 | 江西德盛精细化学品有限公司 | Environment-friendly color fixing agent preparation device and method |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060144057A1 (en) * | 2004-12-30 | 2006-07-06 | Industrial Technology Research Institute | Key performance index calculation and real-time condition monitoring methods for heat exchanger |
| CN103199628A (en) * | 2013-04-28 | 2013-07-10 | 国家电网公司 | Real-time power equipment monitoring system based on OSGA (Open Grid Service Architecture) grid technology |
| CN103604460A (en) * | 2013-11-29 | 2014-02-26 | 重庆市勘测院 | Building structure safety monitoring system |
| CN108871821A (en) * | 2017-10-25 | 2018-11-23 | 中国石油化工股份有限公司 | Based on mean value-moving range method air cooler energy efficiency state method of real-time |
| CN109086930A (en) * | 2018-07-27 | 2018-12-25 | 广东电网有限责任公司 | A kind of user power utilization behavior analysis method based on electric power K line chart and depth network |
| CN109813544A (en) * | 2019-03-26 | 2019-05-28 | 武汉众犇慧通科技有限公司 | A kind of rotating machinery Incipient Fault Diagnosis method and system based on on-line monitoring |
| CN110906171A (en) * | 2019-10-29 | 2020-03-24 | 中国石油化工股份有限公司 | Pipeline heat preservation condition monitoring and hierarchical control method based on dynamic envelope curve method |
| CN110942156A (en) * | 2019-10-29 | 2020-03-31 | 中国石油化工股份有限公司 | Heat exchanger group preventive maintenance method based on operation risk |
| CN110991692A (en) * | 2019-10-29 | 2020-04-10 | 中国石油化工股份有限公司 | Heat exchanger group operation condition monitoring, cleaning and early warning method based on dynamic envelope curve method |
| US20200116553A1 (en) * | 2018-10-12 | 2020-04-16 | Industrial Technology Research Institute | Health monitor method for an equipment and system thereof |
-
2020
- 2020-10-17 CN CN202011113805.9A patent/CN112304657A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060144057A1 (en) * | 2004-12-30 | 2006-07-06 | Industrial Technology Research Institute | Key performance index calculation and real-time condition monitoring methods for heat exchanger |
| CN103199628A (en) * | 2013-04-28 | 2013-07-10 | 国家电网公司 | Real-time power equipment monitoring system based on OSGA (Open Grid Service Architecture) grid technology |
| CN103604460A (en) * | 2013-11-29 | 2014-02-26 | 重庆市勘测院 | Building structure safety monitoring system |
| CN108871821A (en) * | 2017-10-25 | 2018-11-23 | 中国石油化工股份有限公司 | Based on mean value-moving range method air cooler energy efficiency state method of real-time |
| CN109086930A (en) * | 2018-07-27 | 2018-12-25 | 广东电网有限责任公司 | A kind of user power utilization behavior analysis method based on electric power K line chart and depth network |
| US20200116553A1 (en) * | 2018-10-12 | 2020-04-16 | Industrial Technology Research Institute | Health monitor method for an equipment and system thereof |
| CN109813544A (en) * | 2019-03-26 | 2019-05-28 | 武汉众犇慧通科技有限公司 | A kind of rotating machinery Incipient Fault Diagnosis method and system based on on-line monitoring |
| CN110906171A (en) * | 2019-10-29 | 2020-03-24 | 中国石油化工股份有限公司 | Pipeline heat preservation condition monitoring and hierarchical control method based on dynamic envelope curve method |
| CN110942156A (en) * | 2019-10-29 | 2020-03-31 | 中国石油化工股份有限公司 | Heat exchanger group preventive maintenance method based on operation risk |
| CN110991692A (en) * | 2019-10-29 | 2020-04-10 | 中国石油化工股份有限公司 | Heat exchanger group operation condition monitoring, cleaning and early warning method based on dynamic envelope curve method |
Non-Patent Citations (1)
| Title |
|---|
| 万然: "变电站在线监测及辅助设备监控***研究与应用", 《中国优秀博硕士学位论文全文数据库(硕士) 工程科技Ⅱ辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113432740A (en) * | 2021-06-25 | 2021-09-24 | 西安交通大学 | Wireless temperature measurement system for heat storage element in rotor of rotary air preheater |
| CN116196872A (en) * | 2023-04-04 | 2023-06-02 | 江西德盛精细化学品有限公司 | Environment-friendly color fixing agent preparation device and method |
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