Method and system for detecting and evaluating efficiency of wall-mounted gas boiler

Abstract

The invention belongs to the technical field of fuel gas wall-hanging stove efficiency evaluation, and particularly relates to a fuel gas wall-hanging stove efficiency detection evaluation method and system.The method comprises the steps that a condensation type wall-hanging stove is started and made to operate under the variable load condition, and first and second thermal parameters and energy consumption operation parameters are synchronously collected in real time; and according to the first thermal parameter, obtaining a preliminary real-time efficiency index, judging the stability of the preliminary real-time efficiency index, determining a preliminary evaluation efficiency index, identifying a smoke exhaust abnormal point according to the second thermal parameter, carrying out statistics on a smoke exhaust abnormal index, finally correcting the preliminary evaluation efficiency index through the smoke exhaust abnormal index, and outputting a final efficiency index. According to the method, the adaptation to the real operation scene of the wall-hanging stove is realized, the preliminary evaluation efficiency index is corrected in combination with the smoke exhaust abnormity, so that the final evaluation result can truly reflect the actual efficiency level of the wall-hanging stove, and on the other hand, a clear direction is provided for tracing and processing subsequent efficiency abnormity.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of gas wall-hanging stove efficiency evaluation, and in particular, relates to a gas wall-hanging stove efficiency detection and evaluation method and system. BACKGROUND

[0002] The gas wall-hanging stove is used for hot water supply or heating, and its efficiency level is directly related to the utilization efficiency of gas energy and the use cost of users, so in order to protect the user experience of the gas wall-hanging stove, the efficiency of the gas wall-hanging stove needs to be detected and evaluated.

[0003] The existing gas wall-hanging stove efficiency detection generally performs efficiency test and evaluation under the rated load condition, without considering the influence of the dynamic change of the load on the efficiency stability in actual use.

[0004] Secondly, the current efficiency evaluation of the gas wall-hanging stove is basically to compare and calculate the detected parameters reflecting the efficiency condition with the fixed threshold value, so as to output the final evaluation result, without judging the stability of the evaluation result at different times, that is, without considering the influence of the difference of the results at different times on the final result, resulting in a large error of the final evaluation result and insufficient representation.

[0005] At the same time, the traditional efficiency detection is usually performed under the steady state to give a thermal efficiency value, without considering the reflection of the transient state in the actual combustion process of the gas wall-hanging stove, so as to fail to capture the abnormal combustion condition and reflect the health condition, thereby possibly leading to that the given thermal efficiency value is based on the evaluation result under the healthy and steady state, with a large error and deviating from the actual situation, and on the other hand, failing to provide a clear direction for the subsequent tracing and processing of the efficiency abnormality. SUMMARY

[0006] In view of this, in order to solve the above problems, a gas wall-hanging stove efficiency detection and evaluation method is proposed.

[0007] The purpose of the present application can be achieved by the following technical scheme: the present application provides a gas wall-hanging stove efficiency detection and evaluation method, which comprises: starting the condensing wall-hanging stove to make it run under variable load conditions, and synchronously collecting first thermal parameters, second thermal parameters and energy consumption operation parameters in real time.

[0008] The real-time actual thermal efficiency and the real-time condensing heat recovery efficiency are calculated based on the first thermal parameters and the second thermal parameters respectively, and the real-time energy consumption operation efficiency is calculated based on the energy consumption operation parameters.

[0009] The real-time actual thermal efficiency, the real-time condensing heat recovery efficiency and the real-time energy consumption operation efficiency are linearly weighted and calculated to output a real-time preliminary efficiency index, the stability of the efficiency index is judged, and a preliminary evaluation efficiency index is determined based on the judgment result.

[0010] According to the second thermal parameter, the dynamic change rate of the exhaust smoke parameter is calculated in real time, the exhaust smoke abnormal point is identified through cluster analysis, and the exhaust smoke abnormal index is counted based on the frequency and amplitude of the exhaust smoke abnormal point.

[0011] The preliminary evaluation efficiency index is corrected by the exhaust smoke abnormal index, and the final efficiency index is output.

[0012] Compared with the prior art, the beneficial effects of the present application are as follows: (1) The present application collects the first thermal parameter, the second thermal parameter and the dynamic energy consumption parameter under the condition of variable load, so as to accurately capture the performance of intermittent heating and low load heat preservation in actual scenes, so that the evaluation result is more in line with the real use demand of the user.

[0013] (2) The present application judges the stability according to the combination of fluctuation amplitude and deviation proportion, and outputs the final preliminary evaluation efficiency index, so that the preliminary evaluation efficiency index is more reliable, and the final efficiency index after correction is more accurate.

[0014] (3) The present application identifies the exhaust smoke abnormal point through cluster analysis, and obtains the exhaust smoke abnormal index based on the abnormal frequency and deviation amplitude, and finally obtains the thermal efficiency value, which considers the reflection of transient state in the actual combustion process of the gas wall-hanging stove, and also captures the abnormal combustion condition of the gas wall-hanging stove, and reflects its health condition, so that the evaluation result is in line with the actual situation, and on the other hand, it can provide a clear direction for the subsequent tracing and processing of efficiency abnormality. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0016] Figure 1 It is the overall implementation flowchart of the present application.

[0017] Figure 2 It is the determination flowchart of the preliminary evaluation efficiency index of the present application.

[0018] Figure 3 It is the identification flowchart of the exhaust smoke abnormal point of the present application.

[0019] Figure 4 It is the overall implementation flowchart of the present application. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0021] The present application is based on the actual use process simulation of the condensing wall-mounted boiler to construct a detection and evaluation scene, and specific embodiments are analyzed around the scene. Specifically, refer to Figure 1 The present application provides a gas wall-mounted boiler efficiency detection and evaluation method, which comprises the following steps: S1, starting the condensing wall-mounted boiler to run under variable load conditions, and synchronously collecting first thermal parameters, second thermal parameters and energy consumption operation parameters in real time.

[0022] The condensing wall-mounted boiler is usually used for household heating and domestic hot water supply. The energy-saving effect of the condensing wall-mounted boiler is closely related to the operation load. If it is run under fixed load, either the condensation is insufficient due to too high flue gas temperature, or the latent heat recovery is insufficient due to unstable combustion, which cannot reflect its energy-saving characteristics. Therefore, the condensing wall-mounted boiler is run under variable load conditions.

[0023] In order to make the condensing wall-mounted boiler run under variable load conditions, the load conditions can be changed by power supply control, and the wall-mounted boiler needs to be confirmed to be in normal working state before operation. The specific operation process of changing the load conditions is as follows: in the starting state, first, reset the condensing wall-mounted boiler according to the reset setting of the technical manual of the condensing wall-mounted boiler, obtain the rated power of the condensing wall-mounted boiler from the technical manual, take the rated power as the highest load, i.e. the reference load, take the 30th percentile of the rated power as the lowest load, take the 60th percentile of the rated power as the medium load, take the medium load and the lowest load as the fluctuating load, switch by random insertion, set the random insertion time and switching frequency of the fluctuating load based on the total running time of the wall-mounted boiler, and switch the load based on the random insertion time and switching frequency.

[0024] It should be noted that the random insertion time and switching frequency of the fluctuating load are executed in the following manner: the insertion time needs to avoid the device startup time, the running time of the reference load accounts for not less than 80th percentile of the total running time, the cumulative running time accounts for not more than 20th percentile of the total running time, to ensure that the load fluctuates smoothly and avoids unstable operation caused by frequent switching in a short time, and after each fluctuating load operation ends, the reference load is switched back immediately until the next random insertion time triggers.

[0025] Exemplarily, assuming that the total length of a single operation of the condensing wall-mounted boiler is set to 120 minutes, the operation time length ratio of the reference load is greater than or equal to 96 minutes, the cumulative operation time length ratio of the fluctuation load is less than or equal to 24 minutes, the first 10 minutes after the device is started is the reference load stable operation period, the time of inserting the fluctuation load needs to avoid this period, the single operation time length of the medium load is 5-8 minutes, the single operation time length of the minimum load is 3-5 minutes, after the start buffer period ends, the insertion time is randomly generated by the power control system, and a specific example is as follows: the medium load is started at the 15th minute and continuously operated for 5 minutes, the minimum load is started at the 38th minute and continuously operated for 4 minutes, the minimum load is started at the 62nd minute and continuously operated for 3 minutes, and the medium load is started at the 95th minute and continuously operated for 6 minutes, so as to ensure that the number of switching times of the fluctuation load in the total length of a single operation is less than or equal to 6 times. The specific setting of the random insertion time and the switching frequency of the above fluctuation load is only a preferred embodiment of the present application, and is not a limitation on the technical solution.

[0026] Specifically, the collection process of each feature parameter includes: collecting the water inlet temperature and the water outlet temperature in real time through temperature sensors arranged at the water inlet and the water outlet of the wall-mounted boiler respectively, and collecting the water flow in real time through a water flow sensor arranged at the water inlet.

[0027] The water inlet temperature, the water outlet temperature, the water flow, the gas flow, and the corresponding collection time points and collection positions form the first thermal parameter.

[0028] The exhaust gas temperature, the exhaust gas pressure, and the volume fraction of oxygen in the exhaust gas are collected in real time through a temperature sensor, a micro pressure difference sensor, and an oxygen sensor arranged at the exhaust gas pipeline of the wall-mounted boiler.

[0029] The exhaust gas condensate flow is collected in real time through a micro flow sensor arranged at the water outlet of the collection disc of the wall-mounted boiler, and the exhaust gas temperature, the exhaust gas pressure, the volume fraction of oxygen in the exhaust gas, and the exhaust gas condensate flow, and the corresponding collection time points and positions form the second thermal parameter.

[0030] The power consumption is collected in real time through a single-phase electric energy metering module connected in series at the corresponding power supply inlet end of the wall-mounted boiler, the gas consumption is calculated according to the gas flow, and the gas consumption, the power consumption, and the corresponding collection time points and collection positions together form the energy consumption operation parameter.

[0031] It should be noted that the above-mentioned gas consumption is calculated based on the instantaneous gas flow through time accumulation, and can be automatically outputted by a sensor with a built-in accumulation function or calculated through external discrete integration to obtain the gas consumption.

[0032] S2, calculate real-time actual thermal efficiency and real-time condensing heat recovery efficiency based on the first thermal parameter and the second thermal parameter respectively, and calculate real-time energy consumption operation efficiency based on energy consumption operation parameters.

[0033] Specifically, the calculation process of the real-time condensing heat recovery efficiency includes: based on the real-time gas flow, the volume fraction of oxygen in the exhaust gas and the exhaust gas pressure, the real-time flue gas dew point temperature is calculated, and the latent heat of vaporization of water at the dew point temperature is retrieved.

[0034] It should be noted that the above-mentioned real-time flue gas dew point temperature Based on the Antoine equation, the real-time flue gas dew point temperature The calculation formula is: , wherein A, B and C are constants of the Antoine equation, wherein in the working condition of taking natural gas as fuel, the value of A is 6.1, the value of B is 7.6, the unit is Celsius, and the value of C is 240.7, the unit is Celsius. is the real-time exhaust gas pressure. is the volume fraction of oxygen in the standard dry air, which is 0.2. is the volume fraction of oxygen in the real-time exhaust gas. is the conversion coefficient, which is 100. is the molar volume of ideal gas under standard state, which is 22.4 liters per mole under standard state. characterizes the deviation of the oxygen consumption degree from the air excess state in the natural gas combustion process. characterizes the total exhaust gas pressure correction based on the combustion oxygen consumption state. characterizes the proportional relationship between the volume of oxygen per mole of flue gas under standard state and the volume fraction of oxygen in the exhaust gas. characterizes the partial pressure of water vapor in the flue gas.

[0035] Based on the real-time flue gas condensate flow, the product of the flue gas condensate flow and the corresponding latent heat of vaporization is taken as the real-time condensing latent heat of condensing recovery.

[0036] Based on the real-time gas flow, the low-grade heat value corresponding to the gas flow is extracted, and the product of the gas flow and the low-grade heat value of the gas is taken as the real-time total heat input of the gas.

[0037] Wherein, the above-mentioned low-grade heat value of the gas is obtained through the manual provided by the gas supplier.

[0038] The ratio of the real-time condensing latent heat to the real-time total heat input of the gas is taken as the real-time condensing heat recovery efficiency.

[0039] Specifically, the calculation process of the real-time actual thermal efficiency comprises: based on the real-time collected water inlet temperature, water outlet temperature and water flow, and in combination with the specific heat capacity of the water, a real-time total output heat of the water is calculated, and a ratio of the total output heat of the water to a real-time total input heat of the gas is taken as a real-time reference thermal efficiency.

[0040] It should be noted that the real-time total output heat of the water is calculated by the following formula: , wherein, is the specific heat capacity of the water. is a real-time water flow, is a real-time water inlet temperature, is a real-time water outlet temperature, is a temperature change amount of the water, characterizes the heat absorbed or released by unit mass of the water when the temperature changes.

[0041] When the flue gas dew point temperature is greater than the condensation critical exhaust gas temperature threshold, if the exhaust gas temperature is greater than the flue gas dew point temperature, the conversion coefficient is assigned as 0.

[0042] It should be noted that the condensation critical exhaust gas temperature threshold refers to the lowest exhaust gas temperature critical value at which the flue gas can start to form stable condensation in the condensing wall-hanging stove exhaust system, and the condensation critical exhaust gas temperature threshold is obtained according to the factory specification of the condensing wall-hanging stove. For example, the value range of the condensation critical exhaust gas temperature threshold is 45℃~55℃.

[0043] If the exhaust gas temperature is less than or equal to the flue gas dew point temperature and greater than the condensation critical exhaust gas temperature threshold, the difference between the flue gas dew point temperature and the exhaust gas temperature and the difference between the flue gas dew point temperature and the condensation critical exhaust gas temperature threshold are calculated respectively, and the ratio of the two is taken as the conversion coefficient.

[0044] If the exhaust gas temperature is less than or equal to the condensation critical exhaust gas temperature threshold, the conversion coefficient is assigned as 1.

[0045] When the flue gas dew point temperature is less than or equal to the condensation critical exhaust gas temperature threshold, the conversion coefficient is assigned as 0.

[0046] The conversion coefficient is multiplied by the real-time condensation heat recovery efficiency to obtain a real-time conversion efficiency, and the sum of the real-time conversion efficiency and the real-time reference thermal efficiency is taken as the real-time actual thermal efficiency.

[0047] Specifically, the calculation process of the real-time energy consumption operation efficiency comprises: multiplying the real-time gas consumption and the low calorific value of the gas to obtain a real-time gas energy consumption, and adding the real-time gas energy consumption and the real-time power consumption to obtain a real-time total input energy consumption.

[0048] It should be noted that the above real-time gas energy consumption needs to be converted according to the conversion standard of electric energy and heat before being added to the real-time power consumption, such as 1 kilowatt-hour of electric energy being equal to 3.6 megajoules.

[0049] The ratio of the real-time total output heat of water to the real-time total input energy consumption is taken as the energy consumption operation efficiency.

[0050] S3, linearly weighting the real-time actual thermal efficiency, the real-time condensing heat recovery efficiency and the real-time energy consumption operation efficiency, outputting a real-time preliminary performance index, judging the stability of the performance index, and determining a preliminary evaluation performance index based on the judgment result.

[0051] The weights of the real-time actual thermal efficiency, the real-time condensing heat recovery efficiency and the real-time energy consumption operation efficiency are quantitatively determined based on the influence degree of each efficiency index on the performance core dimension of the condensing wall-hanging stove.

[0052] Specifically, the real-time actual thermal efficiency directly reflects the conversion ability of gas to heating heat, which is the basis of performance evaluation, so the weight of the real-time actual thermal efficiency is the highest, the real-time condensing heat recovery efficiency is the exclusive feature of the condensing stove, which quantifies the functional value of the latent heat recovery of flue gas of the equipment, so the weight of the real-time actual thermal efficiency is the second, and the influence degree of the real-time energy consumption operation efficiency on the total performance is less than the former two, so the weight of the real-time energy consumption operation efficiency is the lowest.

[0053] For example, the weight of the real-time actual thermal efficiency is 0.65, the weight of the real-time condensing heat recovery efficiency is 0.25, and the weight of the real-time energy consumption operation efficiency is 0.1.

[0054] Since the condensing wall-hanging stove presents dynamic fluctuations in the performance index under variable load working conditions, in order to distinguish between reasonable fluctuations under normal working conditions and disordered fluctuations or trend disorder under abnormal working conditions, and to avoid mixing of abnormal data due to direct output of the performance index, resulting in distorted results.

[0055] Therefore, the stability of the performance index needs to be judged to accurately determine the nature of the fluctuations and avoid misjudgment of normal fluctuations as abnormal or missing of real abnormal fluctuations.

[0056] In one specific embodiment, the judgment process of the stability of the performance index includes: taking time as the horizontal coordinate and the performance index as the vertical coordinate to construct a curve of the performance index changing with time.

[0057] Each peak point and the adjacent valley point is recorded as an extreme value pair, the difference between each peak point and the adjacent valley point is taken as the fluctuation amplitude of the corresponding extreme value pair, the mean value of the fluctuation amplitude is calculated and recorded as the average fluctuation amplitude, the number of fluctuation amplitudes exceeding the average fluctuation amplitude is recorded as the exceeding number, and the number of extreme value pairs whose fluctuation amplitudes do not exceed the average fluctuation amplitude is recorded as the non-exceeding number.

[0058] The curve of the performance index changing over time is segmented according to a preset time window, the slope of each curve segment and the slope of the curve are extracted.

[0059] The number of curve segments whose slope is inconsistent with the direction of the slope of the curve is counted, and the deviation proportion is obtained by comparing the number with the total number of curve segments.

[0060] When the following conditions are met, it is determined that the performance index is stable: the number of deviations is less than the number of non-deviations.

[0061] The deviation proportion is less than a preset proportion threshold.

[0062] On the contrary, it is determined that the performance index is not stable.

[0063] It should be noted that the above-mentioned preset proportion threshold is a quantitative critical value of the consistency of the time series trend of the performance index. When the deviation proportion is less than the preset proportion threshold, it indicates that the change trend of most curve segments is consistent with the overall curve trend, and the trend consistency of the time series data of the performance index meets the characteristic requirements of stable operation of the condensing wall-mounted boiler, that is, the trend is consistent. When the deviation proportion is greater than or equal to the preset proportion threshold, it indicates that more than a critical proportion of curve segments appear fluctuations in the opposite direction of the overall trend, and the trend disorder degree of the time series data of the performance index exceeds the acceptable range, that is, the trend is inconsistent. The preset proportion threshold is obtained from the factory technical manual of the condensing wall-mounted boiler, and the exemplary value range is 15% to 25%.

[0064] The present application determines through the two dimensions of fluctuation amplitude and deviation proportion, covering fluctuation distribution and trend consistency, and the trend determination focuses on the consistency of the slope of the curve segment and the slope of the curve, rather than only considering the overall curve slope. The frequency proportion of such local reverse can be quantified by the deviation proportion. When the deviation proportion exceeds the preset proportion threshold, it is accurately determined to be unstable, avoiding evaluation distortion caused by the overall trend covering local disorder. The concentration degree of local fluctuation is quantified by the fluctuation amplitude, the synergy of segmented trend and overall trend is represented by the deviation proportion, and the stability is determined by the combination of the two dimensions, so as to ensure that both disordered fluctuations and trend disorders are filtered.

[0065] By determining the stability through fluctuation amplitude and trend consistency, instantaneous large amplitude oscillation and other random abnormalities can be accurately removed, and performance indexes with persistent decay and local reverse fluctuations can also be removed. Finally, valid data is obtained, so that the preliminary evaluation of the performance index can truly reflect the long-term stable operation level of the wall-mounted boiler, providing a reliable basis for subsequent smoke anomaly correction.

[0066] Therefore, the final preliminary evaluation of the performance index is determined based on the comprehensive stability evaluation result.

[0067] Specifically, referring to Figure 2 As shown, the determination process of the preliminary evaluation performance index includes: when the performance index judgment result is stable, the maximum real-time preliminary performance index is taken as the preliminary evaluation performance index.

[0068] When the performance index judgment result is unstable, the real-time preliminary performance indexes are sorted according to time sequence to construct a performance index time sequence.

[0069] The performance indexes under each time window are obtained by intercepting the performance index time sequence based on a preset time window, and the performance index mean value under each time window is calculated.

[0070] Among them, the preset time window is 5 minutes as a preferred embodiment.

[0071] The performance index mean values under each time window are linearly weighted to obtain the preliminary evaluation performance index.

[0072] Since the condensing wall-hanging stove needs to go through the processes of preheating of the combustion system, temperature stabilization of the heat exchanger, load adaptation adjustment and the like after starting, the equipment running state corresponding to the later time window is closer to the long-term stable working condition, and the reliability and representativeness of the performance index mean value are stronger, so a higher weight can be given, so that the preliminary evaluation performance index is closer to the actual long-term running level of the equipment.

[0073] Further, all the time windows are sorted according to time sequence, and the ratio of the sorting sequence number to the total number of time windows is taken as the weight of the performance index mean value of the time window corresponding to the sequence number.

[0074] Based on the weight of the performance index mean value, the performance index mean values of the time windows under each sequence number are linearly weighted and summed to obtain a weighted sum, and the mean value of the weighted sum is taken as the preliminary evaluation performance index.

[0075] S4, the dynamic change rate of the flue gas emission parameter is calculated in real time according to the second thermal parameter, the flue gas emission abnormal point is identified through cluster analysis, and the flue gas emission abnormal index is counted based on the frequency and amplitude of the flue gas emission abnormal point.

[0076] Since the flue gas emission parameter is a direct representation of the combustion state and heat exchange efficiency of the condensing wall-hanging stove, when the combustion is sufficient, the flue gas emission temperature is stable near the dew point, and the oxygen content is maintained within a reasonable range, and when the combustion is insufficient, the heat exchanger is scaled, the fuel gas pressure fluctuates and the like, the flue gas emission parameter will change in a trend, at this time, the change trend of the parameter can be accurately quantified by calculating the dynamic change rate in real time, so as to adapt to the dynamic running characteristics of the condensing wall-hanging stove under variable load, avoid misjudgment of the static threshold, and avoid distortion of the abnormal evaluation.

[0077] The frequency of anomalies reflects how frequently they occur; a higher frequency indicates poorer equipment stability and more severe long-term performance degradation. The magnitude of anomalies reflects the severity of a single anomaly; a larger magnitude indicates a more severe anomaly in the combustion heat exchange system and a more significant single-event performance loss. Combining these two factors to calculate the flue gas anomaly index transforms qualitative anomalies into quantitative indices, providing a quantifiable basis for subsequent preliminary performance index adjustments and avoiding the lack of standardized procedures for anomaly correction.

[0078] Specifically, please refer to Figure 3 As shown, the process of identifying abnormal smoke exhaust points includes: calculating the smoke exhaust temperature difference between adjacent collection time points based on real-time collected smoke exhaust parameters, and obtaining the smoke exhaust temperature change rate at the corresponding collection time point based on the smoke exhaust temperature difference and the time interval.

[0079] Similarly, the change rate of flue gas pressure and the change rate of oxygen volume fraction in the flue gas at each time point are calculated using the same method as the calculation of flue gas temperature change rate.

[0080] The changes in flue gas temperature, flue gas pressure, and the volume fraction of oxygen in the flue gas were standardized to obtain standardized flue gas temperature, flue gas pressure, and the volume fraction of oxygen in the flue gas. These were then aligned according to the data collection timestamps to construct a parameter change matrix.

[0081] It should be added that the above standardization process is achieved using the Z-score standardization method. The purpose is to remove dimensions from the flue gas temperature change rate, flue gas pressure change rate, and flue gas oxygen volume fraction change rate. The Z-score standardization method is existing technology and will not be described in detail in this invention.

[0082] The parameter change matrix is ​​clustered using the K-means clustering algorithm to obtain clusters of abnormal change rates.

[0083] Furthermore, the specific process for obtaining the abnormal change rate cluster is as follows: Considering the clustering efficiency and the identification efficiency of abnormal smoke emission points, this invention preferably sets the number of clusters to three. Then, one data point is randomly selected from the parameter change matrix as the first cluster center. The Euclidean distance from all remaining data points to the first cluster center is calculated.

[0084] When selecting the next cluster center, the ratio of the square of the Euclidean distance of each remaining data point not selected as a cluster center to the determined previous cluster center to the sum of the squares of the Euclidean distances of all remaining data points to the selected cluster center is used as the distance square ratio. The data point corresponding to the largest distance square ratio is selected as the next cluster center. The selection process is repeated until three cluster centers are obtained.

[0085] The distance between each data point and the three cluster centers is calculated using Euclidean distance. Each data point is assigned to the nearest cluster center, forming three temporary clusters. The mean vector of all data points within each temporary cluster is calculated and used as the new cluster center. This process of updating the new cluster centers is repeated until either of the following conditions is met: the iterative change of the cluster center is less than or equal to the cluster center convergence threshold, or the number of iterations reaches the preset maximum number of iterations. Considering the clustering efficiency and the identification efficiency of smoke emission anomalies, the cluster center convergence threshold is preferably set to 0.01, and the preset maximum number of iterations is set to 10.

[0086] It should be noted that the above-mentioned cluster center convergence threshold and preset maximum number of iterations are merely exemplary values ​​of the present invention and are not intended to limit the technical solution.

[0087] Calculate the absolute value of the mean of the rate of change of each parameter within the three clusters. If the absolute value of the mean of a parameter within a certain cluster is greater than the corresponding preset normal threshold, and the variance of the data points within the cluster is greater than the variance of other clusters, then the cluster is determined to be a cluster with a severely abnormal rate of change, and the remaining clusters are clusters with normal rates of change.

[0088] It should be added that the above-mentioned preset normal thresholds were obtained through full-condition measurement and statistical calibration. The specific process is as follows: select several qualified condensing wall-hung boiler samples, collect the corresponding flue gas temperature, flue gas pressure and volume fraction of oxygen in the flue gas in real time, calculate the flue gas temperature change rate, flue gas pressure change rate and volume fraction of oxygen in the flue gas change rate, and remove extreme outliers in each change rate parameter by using the 3σ criterion to obtain the effective data of each change rate parameter. After statistically analyzing the 95th percentile of the effective data of each change rate parameter, the preset normal threshold of each parameter is obtained.

[0089] Extract the collection locations corresponding to each parameter in the abnormal rate of change cluster, and mark the collection locations as smoke exhaust anomaly points.

[0090] Specifically, the statistical process of the smoke exhaust anomaly index includes: when the smoke exhaust temperature is greater than the upper limit of the reference smoke exhaust temperature range, the difference between the real-time smoke exhaust temperature and the upper limit is taken as the temperature anomaly amplitude.

[0091] It should be added that the reference flue gas temperature range is taken from the flue gas temperature range specified in the manufacturer's technical manual for condensing wall-hung boilers.

[0092] When the flue gas temperature is lower than the lower limit of the reference flue gas temperature range, the difference between the lower limit and the real-time flue gas temperature is taken as the temperature anomaly range.

[0093] Similarly, the abnormal amplitudes of flue gas pressure and oxygen volume fraction in the flue gas can be calculated using the same method as for calculating abnormal amplitudes of flue gas temperature.

[0094] The abnormal amplitudes of temperature, flue gas pressure, and oxygen volume fraction in the flue gas were used as the various abnormal indicators.

[0095] For each abnormal smoke emission point, when a certain abnormal indicator corresponding to a certain time point is not 0, an abnormality mark is made for that time point. The total number of abnormality marks is counted and compared with the total number of time points to obtain the frequency of occurrence of the abnormal smoke emission point.

[0096] Each abnormal indicator is normalized, and the normalized abnormal indicators are weighted and summed to calculate the comprehensive abnormality magnitude.

[0097] The weights of abnormal temperature amplitude, abnormal flue gas pressure amplitude, and abnormal volume fraction of oxygen in flue gas are determined based on the quantitative determination of the impact of each flue gas parameter on the efficiency of the condensing wall-hung boiler.

[0098] Specifically, temperature anomalies directly affect condensation heat recovery efficiency. Excessively high or low flue gas temperatures can lead to insufficient latent heat recovery and may also cause problems such as condensation and corrosion, having the greatest impact on efficiency. Therefore, the weight of temperature anomaly amplitude should be set to the highest. Abnormal oxygen content in flue gas reflects abnormal combustion sufficiency. When the oxygen content is too high, it means that oxygen is discharged without participating in effective heat exchange during combustion, while when the oxygen content is too low, it indicates that the fuel gas is discharged with the flue gas without complete oxidation. Combustion anomalies directly affect thermal efficiency and safety. Therefore, the weight of abnormal oxygen volume fraction amplitude in flue gas is the second highest. Abnormal flue gas pressure mainly affects the smoothness of flue gas emission and is an indirect effect, meaning that the impact on efficiency is relatively small. Therefore, the weight of abnormal flue gas pressure amplitude should be set to the lowest.

[0099] For example, the weight of the abnormal temperature amplitude is 0.45, the weight of the abnormal oxygen volume fraction amplitude in the flue gas is 0.35, and the weight of the abnormal flue gas pressure amplitude is 0.2.

[0100] It should be added that the above normalization adopts a linear normalization method. The present invention preferably adopts a minimum-maximum normalization method, and the normalization method is the prior art, so it will not be described in detail.

[0101] The final smoke emission anomaly index is calculated by weighted summation based on the frequency of occurrence of the aforementioned smoke emission anomalies and the overall anomaly magnitude.

[0102] It should be added that the frequency of occurrence of the above-mentioned smoke exhaust anomalies reflects the prevalence of the anomalies and is directly related to the risk of long-term performance degradation, while the overall anomaly magnitude reflects the severity of a single anomaly and determines the magnitude of instantaneous performance loss. The two contribute equally to the final impact of the anomaly. Therefore, the weight of the frequency of occurrence of smoke exhaust anomalies is 0.5, and the weight of the overall anomaly magnitude is 0.5.

[0103] S5. Correct the preliminary performance index using the smoke exhaust anomaly index, and output the final performance index. .

[0104] It should be noted that the above final efficiency index The corrected calculation formula is as follows: In the formula, To conduct a preliminary assessment of the performance index, This is the smoke emission abnormality index.

[0105] This invention corrects the preliminary performance index by using an abnormal exhaust gas index, thereby enabling the correction results to truly reflect the impact of abnormal operating conditions on performance. While improving the reliability of the final performance index, it also achieves a quantitative characterization of the degree of abnormality, and provides an objective basis for performance correction. Furthermore, it establishes a quantitative correlation between abnormality and performance loss, so that the final performance index can truly reflect the long-term operating performance of the wall-hung boiler under the superposition of normal and abnormal operating conditions.

[0106] Please see Figure 4 As shown, a gas-fired wall-hung boiler performance testing and evaluation system includes: an operating parameter acquisition module, an operating efficiency calculation module, an efficiency determination and judgment module, a flue gas anomaly analysis module, and an efficiency evaluation output module.

[0107] In the above, the operating efficiency calculation module is connected to the operating parameter acquisition module and the efficiency determination and judgment module, respectively; the smoke exhaust anomaly analysis module is connected to the efficiency determination and judgment module and the efficiency evaluation output module, respectively; and the smoke exhaust anomaly analysis module is also connected to the operating parameter acquisition module.

[0108] The operating parameter acquisition module starts the condensing wall-hung boiler, enabling it to operate under variable load conditions and synchronously acquire the first thermal parameter, the second thermal parameter, and the energy consumption operating parameter in real time.

[0109] The operating efficiency calculation module calculates the real-time actual thermal efficiency and real-time condensing heat recovery efficiency based on the first thermal parameter and the second thermal parameter, respectively, and calculates the real-time energy consumption operating efficiency based on the energy consumption operating parameters.

[0110] The efficiency determination module performs a linear weighted calculation of the real-time actual thermal efficiency, real-time condensing heat recovery efficiency, and real-time energy consumption operation efficiency, outputs a real-time preliminary efficiency index, judges the stability of the efficiency index, and determines a preliminary evaluation efficiency index based on the judgment result.

[0111] The flue gas anomaly analysis module calculates the dynamic change rate of flue gas parameters in real time based on the second thermal parameter, identifies flue gas anomaly points through cluster analysis, and statistically analyzes the flue gas anomaly index based on the frequency and amplitude of the flue gas anomaly points.

[0112] The performance evaluation output module corrects the preliminary performance evaluation index using the smoke exhaust anomaly index and outputs the final performance index.

[0113] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for detecting and evaluating the efficiency of a gas wall-hanging stove, characterized in that, The method comprises: starting the condensing wall-hanging stove to run under variable load conditions, and synchronously collecting first thermal parameters, second thermal parameters and energy consumption operation parameters in real time; calculating real-time actual thermal efficiency and real-time condensing heat recovery efficiency based on the first thermal parameters and the second thermal parameters respectively, and calculating real-time energy consumption operation efficiency based on the energy consumption operation parameters; linearly weighting the real-time actual thermal efficiency, the real-time condensing heat recovery efficiency and the real-time energy consumption operation efficiency to output a real-time preliminary performance index, judging the stability of the preliminary performance index, and determining a preliminary evaluation performance index based on the judgment result; calculating a dynamic change rate of flue gas emission parameters in real time according to the second thermal parameters, identifying flue gas emission abnormal points through cluster analysis, and calculating a flue gas emission abnormality index based on the frequency and amplitude of the flue gas emission abnormal points; correcting the preliminary evaluation performance index by the flue gas emission abnormality index to output a final performance index.

2. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 1, characterized in that: The collection process of the first thermal parameters, the second thermal parameters and the energy consumption operation parameters comprises: collecting the temperatures at the water inlet and the water outlet of the wall-hanging stove, and recording the temperatures as water inlet temperature and water outlet temperature respectively, and collecting the water flow at the water inlet and the gas flow at the gas inlet; combining the water inlet temperature, the water outlet temperature, the water flow and the gas flow, and the corresponding collection time points and collection positions to form the first thermal parameters; collecting the flue gas emission temperature, the flue gas emission pressure and the volume fraction of oxygen in the flue gas in the flue gas pipeline, and collecting the flue gas condensate flow at the water outlet of the collection disc; combining the flue gas emission temperature, the flue gas emission pressure, the volume fraction of oxygen in the flue gas and the flue gas condensate flow, and the corresponding collection time points and collection positions to form the second thermal parameters; collecting the power consumption through a single-phase electric energy metering module connected in series with the power inlet end of the wall-hanging stove, calculating the collected gas consumption according to the gas flow, and combining the gas consumption, the power consumption and the corresponding collection time points and collection positions to form the energy consumption operation parameters.

3. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 2, characterized in that: The calculation process of the real-time condensing heat recovery efficiency comprises: calculating the real-time flue gas dew point temperature based on the real-time gas flow, the volume fraction of oxygen in the flue gas and the flue gas emission pressure, and calling the latent heat of vaporization of water at the corresponding dew point temperature; extracting the low calorific value of gas corresponding to the gas flow based on the real-time gas flow; calculating the real-time condensing heat recovery efficiency based on the real-time flue gas condensate flow, the gas flow, the low calorific value of gas and the latent heat of vaporization of water through a condensing heat recovery efficiency calculation formula based on the low calorific value of gas.

4. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 3, characterized in that: The calculation process of the real-time actual thermal efficiency comprises: calculating the real-time total heat output of water based on the real-time collected water inlet temperature, water outlet temperature and water flow, combining the specific heat capacity of water, and calculating the real-time total heat output of water through a real-time cumulative total heat output calculation formula based on the water side of the condensing wall-hanging stove, and taking the ratio of the total heat output of water to the real-time total heat input of gas as the real-time reference thermal efficiency; when the flue gas dew point temperature is greater than the condensing critical flue gas emission temperature threshold, if the flue gas emission temperature is greater than the flue gas dew point temperature, the conversion coefficient is assigned as 0. If the flue gas temperature is less than or equal to the flue gas dew point temperature and greater than the condensation critical flue gas temperature threshold, the difference between the flue gas dew point temperature and the flue gas temperature and the difference between the flue gas dew point temperature and the condensation critical flue gas temperature threshold are calculated respectively, and the ratio of the two is taken as the conversion coefficient; If the flue gas temperature is less than or equal to the condensation critical flue gas temperature threshold, the conversion coefficient is assigned a value of 1; When the flue gas dew point temperature is less than or equal to the condensation critical flue gas temperature threshold, the conversion coefficient is assigned a value of 0; The conversion coefficient is multiplied by the real-time condensation heat recovery efficiency to obtain the real-time conversion efficiency, and the sum of the real-time conversion efficiency and the real-time baseline thermal efficiency is taken as the real-time actual thermal efficiency.

5. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 3, characterized in that: The calculation process of the real-time energy consumption operation efficiency includes: According to the real-time gas consumption and the low calorific value of the gas, the real-time gas energy consumption is calculated, and the real-time gas energy consumption and the real-time power consumption are added to obtain the real-time total input energy consumption; The ratio of the real-time total output heat of water to the real-time total input energy consumption is taken as the energy consumption operation efficiency.

6. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 1, characterized in that: The determination process of the stability of the efficiency index includes: A curve of the efficiency index changing over time is constructed with time as the horizontal coordinate and the efficiency index as the vertical coordinate; Each peak point and the adjacent valley point are recorded as an extreme value pair, the difference between each peak point and the adjacent valley point is taken as the fluctuation amplitude of the corresponding extreme value pair, the mean of the fluctuation amplitudes is calculated and recorded as the average fluctuation amplitude, and the number of extreme value pairs whose fluctuation amplitudes exceed the average fluctuation amplitude and the number of extreme value pairs whose fluctuation amplitudes do not exceed the average fluctuation amplitude are recorded as the exceeding number and the non-exceeding number respectively; The curve of the efficiency index changing over time is segmented according to a preset time window, the slope of each curve segment and the slope of the curve are extracted; The number of curve segments whose slopes are inconsistent with the slope of the curve is counted, and the ratio of the number to the total number of curve segments is taken as the deviation proportion; When the following conditions are all met, it is determined that the efficiency index is stable: The exceeding number is less than the non-exceeding number; The deviation proportion is less than a preset proportion threshold; Otherwise, it is determined that the efficiency index is unstable.

7. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 6, characterized in that: The determination process of the preliminary evaluation efficiency index includes: When the efficiency index judgment result is stable, the maximum preliminary efficiency index is extracted as the preliminary evaluation efficiency index; When the efficiency index judgment result is unstable, the real-time preliminary efficiency indexes are sorted according to time to construct an efficiency index time sequence; Based on a preset time window, the efficiency index time sequence is intercepted to obtain the efficiency index under each time window, and the mean of the efficiency index under each time window is calculated; The mean of the efficiency index under each time window is linearly weighted to obtain the preliminary evaluation efficiency index.

8. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 2, characterized in that: The identification process of the flue gas abnormal point includes: Based on the real-time collected flue gas parameters, the flue gas temperature difference between adjacent collection time points is calculated, and the flue gas temperature change rate of the corresponding collection time point is obtained according to the flue gas temperature difference and the time interval; The flue gas pressure change rate and the volume fraction change rate of oxygen in the flue gas of each time point are calculated in the same way as the calculation method of the flue gas temperature change rate; The change rates of the flue gas temperature, the flue gas pressure and the volume fraction of oxygen in the flue gas are standardized respectively, the processing results are aligned according to the collection time stamp, and a parameter change matrix is constructed; The parameter change matrix is clustered by a K-means clustering algorithm to obtain an abnormal change rate cluster; An acquisition position corresponding to each parameter in the abnormal change rate cluster is extracted, and the acquisition position is marked as a flue gas emission abnormal point.

9. The method for detecting and evaluating the efficiency of a gas wall-mounted boiler according to claim 2, characterized in that: The statistical process of the flue gas emission abnormality index includes: Comparing the flue gas emission temperature with the reference flue gas emission temperature range, calculating the difference between the flue gas emission temperature and the upper limit or lower limit of the reference flue gas emission temperature range, and taking the absolute value of the difference as the temperature abnormality amplitude; The calculation method of the flue gas emission temperature abnormality amplitude is the same as that of the flue gas emission pressure abnormality amplitude and the volume fraction of oxygen in the flue gas emission abnormality amplitude; The temperature abnormality amplitude, the flue gas emission pressure abnormality amplitude and the volume fraction of oxygen in the flue gas emission abnormality amplitude are used as each abnormality index; For each flue gas emission abnormal point, when a certain abnormality index corresponding to a certain time point is not 0, the time point is marked as abnormal once, the total number of abnormality marks is counted, and the total number of time points is compared to obtain the occurrence frequency of the flue gas emission abnormal point; Each abnormality index is normalized, and the weighted sum of the normalized each abnormality index is calculated to obtain the comprehensive abnormality amplitude; According to the occurrence frequency of the flue gas emission abnormal point and the comprehensive abnormality amplitude, the final flue gas emission abnormality index is calculated by weighted sum.

10. A gas-fired wall-hung boiler efficiency detection and evaluation system, characterized in that: The system includes: The operating parameter acquisition module starts the condensing wall-mounted stove and makes it run under variable load conditions, and synchronously collects the first thermal parameter, the second thermal parameter and the energy consumption operating parameter in real time; The operating efficiency calculation module calculates the real-time actual thermal efficiency and the real-time condensing heat recovery efficiency based on the first thermal parameter and the second thermal parameter, respectively, and calculates the real-time energy consumption operating efficiency based on the energy consumption operating parameter; The performance determination and judgment module linearly weights the real-time actual thermal efficiency, the real-time condensing heat recovery efficiency and the real-time energy consumption operating efficiency, outputs a real-time preliminary performance index, judges the stability of the performance index, and determines a preliminary evaluation performance index based on the judgment result; The flue gas emission abnormality analysis module calculates the dynamic change rate of the flue gas emission parameter in real time according to the second thermal parameter, identifies the flue gas emission abnormal point through clustering analysis, and calculates the flue gas emission abnormality index based on the frequency and amplitude of the flue gas emission abnormal point; The performance evaluation output module corrects the preliminary evaluation performance index by the flue gas emission abnormality index, and outputs the final performance index.

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