A multi-channel-based sewage pump monitoring system

Abstract

The application discloses a sewage pump monitoring system based on multiple channels, and relates to the technical field of sewage pump monitoring.The sewage pump monitoring system comprises a target acquisition module and a target determination module.The target acquisition module is used for monitoring each flow channel of the sewage pump in real time to acquire fluctuation data of each flow channel, wherein the fluctuation data at least comprises flow, pressure and liquid level.The target determination module is used for determining a target flow channel causing fluctuation according to the acquired fluctuation data, wherein the target flow channel comprises a main adjustment flow channel and an auxiliary adjustment flow channel.According to the characteristics of the main flow channel and the auxiliary flow channel and the influence degree on fluctuation, different adjustment strategies are adopted, so that the adjustment range is gradually increased or decreased, thereby being favorable for avoiding new unstable factors or damage to equipment caused by excessively large or excessively aggressive adjustment range.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of sewage pump monitoring, and specifically relates to a sewage pump monitoring system based on multiple channels. BACKGROUND

[0002] A sewage pump is a device used for transporting sewage containing impurities, mainly used in the fields of urban drainage, sewage treatment plants and industrial wastewater treatment. It generates centrifugal force through impeller rotation to pump sewage from low to high or to transport it to treatment facilities. The sewage pump usually has the characteristics of non-clogging design, corrosion resistance and high reliability to adapt to the environment with many impurities and strong corrosion in sewage.

[0003] In the prior art, from the perspective of the influence of partial blockage on the working state of the sewage pump, partial blockage can significantly reduce the operating efficiency of the pump. The blocked channel hinders the flow of sewage, reduces the flow output, and causes the processing capacity of the entire pump system to decrease; at the same time, the blockage also causes the fluid flow in the flow passage to be turbulent, increasing the fluid resistance and forcing the pump to consume more energy to maintain the flow. Moreover, in order to cope with partial blockage, the sewage pump needs to frequently adjust the working parameters, such as increasing the speed or adjusting the blade angle. These adjustment measures not only increase the energy consumption, but also make the motor, impeller, bearing and other components of the pump bear additional mechanical stress and thermal stress, aggravate the wear of the components, shorten the service life of the equipment, and increase the maintenance and replacement costs. SUMMARY

[0004] The purpose of the present application is to provide a sewage pump monitoring system based on multiple channels, which solves the technical problem of preventing new unstable factors or damage to the equipment caused by excessive adjustment amplitude or excessive aggressiveness.

[0005] A sewage pump monitoring system based on multiple channels, comprising:

[0006] A target acquisition module for real-time monitoring of each flow passage of the sewage pump to obtain fluctuation data of each flow passage, the fluctuation data at least including flow, pressure and liquid level;

[0007] A target determination module for determining a target flow passage causing fluctuation according to the obtained fluctuation data, the target flow passage including a main adjustment flow passage and an auxiliary adjustment flow passage;

[0008] A parameter calculation module for calculating a theoretical adjustment parameter amplitude value of the main target flow passage, and if the parameter amplitude value of the main adjustment flow passage is adjusted to exceed a preset threshold value, a differential adjustment of the auxiliary adjustment flow passage is started to gradually increase or decrease the adjustment amplitude.

[0009] As a further scheme of the present application, the parameter calculation module further comprises the following steps:

[0010] The adjustment parameter of the auxiliary adjustment flow channel is analyzed to associate with the target flow channel, and a flow channel with high correlation with the target flow channel fluctuation and minimum adjustment parameter amplitude is selected as the auxiliary adjustment flow channel.

[0011] According to the fluctuation of the target flow channel and the parameter characteristics of the auxiliary adjustment flow channel, a step-by-step adjustment strategy is formulated, and by adjusting part of the parameters of the auxiliary adjustment flow channel first, the influence on the main adjustment flow channel fluctuation is monitored synchronously, and then other related parameters are gradually adjusted.

[0012] By gradually adjusting the parameters of the auxiliary adjustment flow channel, the adjustment amplitude is gradually increased or decreased, so as to achieve the same or similar effect as adjusting the main adjustment flow channel, and prevent energy waste caused by frequent parameter adjustment.

[0013] As a further scheme of the present application, the target determination module determines the target flow channel causing fluctuation, comprising:

[0014] The flow, pressure and liquid level fluctuation data of each flow channel are analyzed to obtain fluctuation frequency characteristics and amplitude variation law;

[0015] The design parameters and operation history data of the sewage pump are combined to establish a correlation model of flow channel fluctuation data and system head, operation efficiency and shaft power;

[0016] The influence weight value of each flow channel fluctuation on system performance is calculated, and the first type flow channel with an influence weight exceeding a set threshold is determined as the main adjustment flow channel;

[0017] The fluid connectivity of the second type flow channel with an influence weight not reaching the threshold is verified, including detecting the physical connection characteristics of the pipeline layout between the flow channels, verifying the suppression effect of adjusting the parameters of the flow channel on the fluctuation of the main adjustment flow channel, and monitoring the stability change of the system operation parameters, when the fluid connectivity condition is met and the adjustment behavior can improve the fluctuation state of the main adjustment flow channel, the second type flow channel is determined as the auxiliary adjustment flow channel.

[0018] As a further scheme of the present application, it further comprises a cross coordination module, specifically:

[0019] When the adjustment effects of at least two auxiliary adjustment flow channels on the target flow channel interfere with each other, and the target flow channel parameters deviate from the stable interval; or after multiple independent adjustments of a single auxiliary adjustment flow channel, the target flow channel parameters still do not achieve the expected adjustment effect and the fluctuation is abnormal, the cross adjustment process is started.

[0020] As a further scheme of the present application, the cross adjustment specifically comprises:

[0021] A parameter correlation model of each auxiliary adjustment flow channel and the target flow channel is constructed, and the adjustment sequence and combination mode of the parameters of each auxiliary adjustment flow channel are determined based on the model;

[0022] According to the determined order and combination, the parameters of the auxiliary adjustment flow channels are adjusted in sequence, and the target flow channel parameter change is monitored in real time after each adjustment, and it is determined whether to continue subsequent adjustment according to the change.

[0023] As a further scheme of the present application, it further comprises: when determining the adjustment order and combination mode of the parameters of the auxiliary adjustment flow channels, setting an upper limit of adjustment attempt times, if the target flow channel parameter does not achieve the expected effect after adjustment according to the initially determined mode, randomly changing the adjustment order of part of the flow channels and re-adjusting the attempt.

[0024] As a further scheme of the present application, it further comprises:

[0025] Before adjusting the parameters of the auxiliary adjustment flow channels, a small amplitude pre-adjustment is first performed on each parameter, the slight change of the target flow channel parameter is observed, and the actual adjustment parameter is selected according to the obvious degree of change, and the parameter causing moderate change of the target flow channel parameter is preferentially selected.

[0026] As a further scheme of the present application, the adjustment order and combination mode of the parameters of the auxiliary adjustment flow channels determined according to the parameter correlation relationship model comprises:

[0027] For each auxiliary adjustment flow channel , the sensitivity of the target flow channel parameter to the parameter of the auxiliary adjustment flow channel is calculated , wherein is the change amount of the target flow channel parameter, is the change amount of the auxiliary adjustment flow channel parameter;

[0028] According to the , a parameter subset with moderate sensitivity is screened out , and the screening condition is , wherein and are preset sensitivity threshold values.

[0029] As a further scheme of the present application, it further comprises:

[0030] When monitoring the target flow channel parameter change in real time after each adjustment, the current parameter change curve is compared with the parameter change curve shape in the historical successful adjustment, if the difference between the two is large, the subsequent adjustment is suspended, and the current adjustment is modified by referring to the adjustment mode corresponding to the historical successful curve.

[0031] As a further scheme of the present application, it further comprises:

[0032] When it is determined whether to continue subsequent adjustment according to the change of the target flow channel parameter, a plurality of different target parameter intervals are set, and when the target flow channel parameter enters different intervals, different adjustment speeds are correspondingly adopted, and the closer the parameter is to the final target, the slower the adjustment speed is.

[0033] Compared with the prior art, the present application has the following beneficial effects:

[0034] When the parameter amplitude value of the main adjustment flow channel exceeds the preset threshold (a critical value for measuring whether the adjustment amplitude is too large, used for judging whether the auxiliary flow channel needs to be involved), the present application starts differentiated adjustment of the auxiliary adjustment flow channel, and the differentiated adjustment refers to adopting different adjustment strategies according to the characteristics of the main and auxiliary flow channels and the influence degree on fluctuation, so that the adjustment amplitude gradually increases or decreases, thereby avoiding the situation that new unstable factors occur or damage to the equipment occurs due to too large or too aggressive adjustment amplitude. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 The figure is a schematic diagram of the system framework structure of the present application. DETAILED DESCRIPTION

[0036] The technical solutions of the present application will be described clearly and completely in combination with embodiments, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0037] Please refer to Figure 1 The present application provides a sewage pump monitoring system based on multiple channels, which comprises:

[0038] A target acquisition module is configured to monitor each flow channel of the sewage pump in real time to acquire fluctuation data of each flow channel, wherein the fluctuation data at least includes flow, pressure and liquid level.

[0039] A target determination module is configured to determine a target flow channel causing fluctuation according to the acquired fluctuation data, wherein the target flow channel comprises a main adjustment flow channel and an auxiliary adjustment flow channel.

[0040] A parameter calculation module is configured to calculate a theoretical adjustment parameter amplitude value of the main target flow channel, and when the parameter amplitude value of the main adjustment flow channel exceeds a preset threshold, differentiated adjustment of the auxiliary adjustment flow channel is started, so that the adjustment amplitude gradually increases or decreases.

[0041] The sensor network comprises flow sensors, pressure sensors, liquid level sensors and the like.

[0042] It should be understood that during the operation of the sewage pump, first, the flow channels of the sewage pump are monitored in real time to obtain fluctuation data of each flow channel. The fluctuation data refers to data that can reflect the change of the running state of the flow channel, at least including flow (the volume of sewage passing through the flow channel per unit time, used to measure the rate of sewage transportation), pressure (the pressure generated by the sewage in the flow channel on the pipe wall, reflecting the resistance condition of the system operation), and liquid level (the height of the sewage in the flow channel, which can reflect the sewage inventory and flow trend). By continuously collecting these data, real-time and accurate information basis is provided for subsequent analysis;

[0043] Then, the target flow channel causing the fluctuation is determined by the fluctuation data obtained by the target acquisition module. The target flow channel includes a main adjustment flow channel and an auxiliary adjustment flow channel. The main adjustment flow channel is the flow channel that has the most critical influence on the overall operation state of the sewage pump, and the change of its parameters plays a leading role in the generation and elimination of fluctuations. The auxiliary adjustment flow channel is a flow channel that cooperates with the main adjustment flow channel when the parameters of the main adjustment flow channel are adjusted, and the two work together to effectively control the fluctuation.

[0044] Subsequently, the theoretical adjustment parameter amplitude value of the main target flow channel (i.e. the main adjustment flow channel) is calculated, that is, according to the fluctuation data and the preset calculation model, the amplitude value of the parameter (such as the opening of the flow control valve, the parameter of the pressure regulating device, etc.) of the main adjustment flow channel that needs to be adjusted to eliminate the fluctuation is calculated. Specifically, assuming that the sewage pump of a sewage treatment plant is running, the main adjustment flow channel is the main conveying pipeline connected to the pump outlet. Through the target acquisition module, it is found that the current flow of the main conveying pipeline is 300 m³ / h, which is far lower than the set flow of 500 m³ / h under normal operating conditions, and the pressure value is 0.2 MPa, which is significantly lower than the normal pressure of 0.4 MPa, and the liquid level is within the normal range but fluctuates frequently.

[0045] At this time, the parameter calculation module starts to calculate the theoretical adjustment parameter amplitude value, based on the design parameters of the sewage pump (such as rated flow, head curve) and fluid mechanics formulas (Bernoulli equation, continuity equation), and combines historical operation data to construct a correlation model of flow-valve opening and pressure-pump speed, which will not be described in detail here.

[0046] When the amplitude value of the parameter of the main adjustment flow channel exceeds the preset threshold value (a critical value preset to measure whether the adjustment amplitude is too large, used to determine whether the auxiliary flow channel needs to be involved), the differential adjustment of the auxiliary adjustment flow channel is started. The differential adjustment refers to the use of different adjustment strategies according to the characteristics and influence of the main and auxiliary flow channels on the fluctuation, so that the adjustment amplitude gradually increases or decreases, thereby avoiding the occurrence of new unstable factors or damage to equipment and increasing energy consumption due to excessive adjustment amplitude or excessive aggressiveness.

[0047] As an optional embodiment, the parameter calculation module further comprises the following steps:

[0048] The correlation between the adjustment parameters of the auxiliary adjustment flow channel and the target flow channel is analyzed, and a flow channel with high correlation with the fluctuation of the target flow channel and the smallest adjustment parameter amplitude is selected as the auxiliary adjustment flow channel.

[0049] According to the fluctuation of the target flow channel and the parameter characteristics of the auxiliary adjustment flow channel, a step-by-step adjustment strategy is formulated, and part of the parameters of the auxiliary adjustment flow channel are adjusted first, and the influence on the fluctuation of the main adjustment flow channel is monitored synchronously, and then other related parameters are adjusted gradually.

[0050] By gradually adjusting the parameters of the auxiliary adjustment flow channel, the adjustment amplitude is gradually increased or decreased to achieve the same or similar effect as adjusting the main adjustment flow channel, thereby preventing energy waste caused by frequent parameter adjustment.

[0051] In the sewage pump flow channel fluctuation regulation process, if the auxiliary adjustment flow channel is selected at will or a rough adjustment strategy is adopted, problems such as poor regulation effect, energy waste, and increased equipment wear and tear may occur. For example, if a flow channel with low correlation with the target flow channel is selected, the fluctuation may not be effectively alleviated, and the parameters may be adjusted greatly and frequently, which not only increases the system energy consumption, but also may cause impact on the equipment due to pressure surge.

[0052] Therefore, after determining the main adjustment flow channel, a suitable auxiliary adjustment flow channel is first selected from a plurality of flow channels. At this time, by analyzing the correlation between the adjustment parameters (such as valve opening, pump speed, and other adjustable quantities affecting the running state of the flow channel) of each flow channel and the target flow channel (i.e., the main adjustment flow channel, which is the key flow channel causing fluctuation), a correlation analysis algorithm (such as Pearson correlation coefficient calculation) is used to quantify the relationship between the two.

[0053] Then, a flow channel with high correlation with the fluctuation of the target flow channel and the smallest adjustment parameter amplitude is selected as the auxiliary adjustment flow channel, which can ensure that the adjustment of the auxiliary flow channel can effectively act on the target flow channel to alleviate the fluctuation, and can also help to avoid the negative effects caused by excessive adjustment, thereby achieving the best regulation effect with the smallest adjustment cost.

[0054] Subsequently, according to the real-time fluctuation of the target flow channel (such as the fluctuation amplitude of the flow, the degree of abnormal pressure, etc.) and the parameter characteristics of the auxiliary adjustment flow channel (such as the parameter adjustment range, the response sensitivity, etc.), a step-by-step adjustment strategy is formulated, part of the parameters of the auxiliary adjustment flow channel are fine-tuned first, and in the adjustment process, the fluctuation of the main adjustment flow channel is monitored synchronously by using the target acquisition module to evaluate the actual effect of the current adjustment on alleviating the fluctuation, and based on the monitoring feedback, other related parameters are adjusted gradually, which helps to avoid uncontrollable shock or new abnormalities caused by one-time comprehensive adjustment of the system.

[0055] Finally, throughout the auxiliary adjustment flow channel parameter adjustment process, the principle of gradually increasing or decreasing the adjustment amplitude is followed, that is, gradient adjustment. In this way, the adjustment effect of the auxiliary adjustment flow channel is gradually accumulated, and finally the same or similar effect as adjusting the main adjustment flow channel is achieved, effectively controlling the fluctuation of the sewage pump flow channel. At the same time, gradient adjustment can avoid frequent and large-scale parameter adjustment, reduce energy loss caused by equipment start-stop and parameter mutation, and improve the economy and stability of system operation; thereby solving the problems of blind selection of auxiliary flow channel and extensive adjustment strategy in traditional sewage pump flow channel adjustment, ensuring the adjustment measures to be accurate and efficient, and achieving stable and efficient control of fluctuations, which helps to avoid energy waste and equipment damage caused by excessive adjustment.

[0056] To further facilitate understanding of the working process of the parameter calculation module, we assume that a large sewage pump in a sewage treatment plant has abnormal flow fluctuations during operation, and the main adjustment flow channel is the main conveying pipeline connected to the outlet of the sewage pump. At this time, the parameter calculation module works according to the following process:

[0057] In the auxiliary adjustment flow channel selection stage, it is found through analysis that the three branch pipes (labeled as branch pipes A, B, and C) connected to the main conveying pipeline can be used as potential auxiliary adjustment flow channels. By calculating the Pearson correlation coefficient of the adjustment of the valve opening of each branch pipe and the flow fluctuation of the main conveying pipeline, the correlation coefficient of branch pipe A is 0.85, and the adjustment valve opening needs to change by 20%; the correlation coefficient of branch pipe B is 0.6, and the adjustment valve opening needs to change by 35%; the correlation coefficient of branch pipe C is 0.7, and the adjustment valve opening needs to change by 25%. As can be seen, branch pipe A has the highest correlation with the main adjustment flow channel fluctuation and the smallest adjustment amplitude, so branch pipe A is selected as the auxiliary adjustment flow channel.

[0058] When developing a step-by-step adjustment strategy, the current flow of the main adjustment flow channel is 30% lower than the normal operating condition, and the maximum opening of the valve of branch pipe A is 100%. In the first step, the valve opening of branch pipe A is adjusted from 50% to 55%, and the flow of the main adjustment flow channel is monitored for 10 minutes, and it is observed that the flow of the main adjustment flow channel increases by 5%; based on this feedback, the valve opening of branch pipe A is adjusted from 55% to 60% in the second step, and the flow of the main adjustment flow channel is again observed to increase by 4%.

[0059] In the gradient parameter adjustment process, the valve opening of branch pipe A is controlled to increase by 5% each time, and after 5 times of step-by-step adjustment, the valve opening of branch pipe A reaches 70%, and the flow of the main adjustment flow channel recovers to 95% of the normal operating condition, successfully solving the flow abnormality problem. The entire adjustment process avoids the pressure shock that may be caused by direct large-scale adjustment of the main adjustment flow channel, and prevents energy waste caused by frequent adjustment, effectively solving the fluctuation problem while ensuring the stable and energy-saving operation of the sewage pump system.

[0060] As an optional embodiment, the target determination module determines that the target flow channel causing the fluctuation includes:

[0061] The flow, pressure and liquid level fluctuation data of each flow channel are analyzed to obtain fluctuation frequency characteristics and amplitude variation rules;

[0062] The fluctuation data of the flow channel are combined with the design parameters and operation history data of the sewage pump to establish a correlation model of the system head, operation efficiency and shaft power;

[0063] The influence weight value of each flow channel fluctuation on the system performance is calculated, and the first type of flow channel with an influence weight exceeding a set threshold is determined as a main adjustment flow channel;

[0064] The second type of flow channel with an influence weight not reaching the threshold is verified for fluid connectivity, including detecting the physical connection characteristics of the pipeline layout between flow channels, verifying the suppression effect of adjusting the parameters of the flow channel on the fluctuation of the main adjustment flow channel, and monitoring the stability changes of the system operation parameters. When the fluid connection condition is met and the adjustment behavior can improve the fluctuation state of the main adjustment flow channel, the second type of flow channel is determined as an auxiliary adjustment flow channel.

[0065] It should be understood that during the operation of the sewage pump, the causes of flow channel fluctuation are complex and interrelated between flow channels. Traditional methods rely only on single data or experience judgment, which is difficult to accurately locate the key flow channel, often resulting in invalid adjustment. Not only can it not effectively eliminate the fluctuation, but it can also cause new system problems, leading to increased energy consumption and shortened equipment life;

[0066] Therefore, first, the target determination module deeply analyzes the fluctuation data of the flow (the volume of sewage passing through the flow channel per unit time, which measures the transportation efficiency), pressure (the pressure of the sewage on the pipe wall in the flow channel, which reflects the system resistance) and liquid level (the height of the sewage in the flow channel, which is related to the operation safety) of each flow channel, for example, through Fourier transform algorithm, to obtain the fluctuation frequency characteristics and judge whether the fluctuation is a high-frequency periodic oscillation or a low-frequency sudden abnormality. Using sliding window statistics and other methods, the amplitude variation rule is analyzed, such as whether the fluctuation amplitude is continuously increasing, whether there is a peak abnormality, etc. These feature analysis provides basic data support for subsequent positioning of the fluctuation source;

[0067] Then, combined with the design parameters of the sewage pump (such as rated flow, head curve, power parameters, etc., reflecting the inherent performance of the equipment) and the operation history data (long-term accumulation of operation condition records, reflecting the actual operation law), the regression analysis or neural network algorithm in machine learning is used to establish the correlation model of the flow passage fluctuation data and the system head (the energy of the unit weight liquid lifted by the pump, measuring the pumping capacity), the operation efficiency (the ratio of actual output power to input power, reflecting the energy utilization efficiency), and the shaft power (the power required by the pump shaft, reflecting the energy consumption), which can quantify the influence of each flow passage fluctuation on the system performance indicators, such as how a certain flow passage pressure fluctuation affects the system head and shaft power.

[0068] Based on the above correlation model, the influence weight value of each flow passage fluctuation on the system performance is calculated, that is, the numerical value that measures the comprehensive influence of each flow passage fluctuation on the system head, operation efficiency, shaft power, etc. By setting a reasonable threshold value (determined according to the critical value of the safe operation requirements and historical experience of the equipment), the flow passage with an influence weight exceeding the threshold value is determined as the first type of flow passage, i.e., the main adjustment flow passage. The fluctuation of this type of flow passage is the main reason for the decline of the system performance and has the most critical impact on the system stability, and needs to be adjusted first.

[0069] For the second type of flow passage with an influence weight not reaching the threshold value, further verification of fluid connectivity is carried out. First, the physical connection characteristics of the pipeline layout between flow passages are detected to determine the connectivity relationship of each flow passage in the pipe network, such as whether there is parallel, series or branch connection. Second, the suppression effect of adjusting the parameters of the second type of flow passage on the fluctuation of the main adjustment flow passage is verified through simulation or actual operation, such as observing the changes of the flow and pressure of the main adjustment flow passage after changing the opening of a branch valve. Third, the stability changes of the system operation parameters are monitored, such as whether the system head and shaft power tend to be stable after adjustment. When the second type of flow passage meets the fluid connectivity condition and its parameter adjustment can effectively improve the fluctuation state of the main adjustment flow passage, it is determined as the auxiliary adjustment flow passage, which cooperates with the main adjustment flow passage for subsequent adjustment.

[0070] This target flow passage determination method effectively solves the problems of inaccurate positioning and low adjustment efficiency of traditional sewage pump flow passage fluctuation, and realizes accurate identification of the fluctuation source through multi-dimensional data feature analysis and scientific correlation model construction. The strict weight calculation and threshold judgment mechanism ensures the accuracy of the positioning of the main adjustment flow passage, and the comprehensive fluid connectivity verification process selects the auxiliary flow passage that can truly cooperate with the adjustment. This series of operations helps to avoid blind adjustment, greatly improves the pertinence and effectiveness of the adjustment, reduces energy consumption and equipment loss, and ensures the stable and efficient operation of the sewage pump system, providing reliable protection for the smooth development of sewage treatment work.

[0071] As an optional embodiment, it further includes a cross-coordination module, specifically:

[0072] When the adjustment effects of at least two auxiliary adjustment flow channels on the target flow channel interfere with each other, and the target flow channel parameter deviates from the stable interval; or after multiple independent adjustments of a single auxiliary adjustment flow channel, the target flow channel parameter still does not achieve the expected adjustment effect and abnormally fluctuates, a cross adjustment process is started.

[0073] As an optional embodiment, the cross adjustment specifically comprises:

[0074] A parameter correlation model of each auxiliary adjustment flow channel and the target flow channel is constructed, and the adjustment order and combination mode of the parameters of each auxiliary adjustment flow channel are determined based on the model;

[0075] According to the determined order and combination, the parameters of each auxiliary adjustment flow channel are adjusted in sequence, the target flow channel parameter is monitored in real time after each adjustment, and it is determined whether to continue subsequent adjustment according to the change.

[0076] As an optional embodiment, the adjustment order and combination mode of the parameters of each auxiliary adjustment flow channel are determined according to the parameter correlation model, which comprises:

[0077] For each auxiliary adjustment flow channel , the sensitivity of its parameters to the target flow channel parameter is calculated , wherein is the change amount of the target flow channel parameter, is the change amount of the auxiliary adjustment flow channel parameter;

[0078] According to , a parameter subset with moderate sensitivity is screened out , and the screening condition is , wherein, and are preset sensitivity threshold values.

[0079] Specifically, in the process of adjusting the flow channel of the sewage pump, when the independent adjustment effect of multiple auxiliary adjustment flow channels is poor or interference occurs, the traditional method often falls into the dilemma of repeated adjustment, resulting in intensified system oscillation and increased energy consumption. For example, when adjusting two parallel auxiliary flow channels of a sewage pump station, because the hydraulic coupling effect between the flow channels is not considered, the increase of the flow of A flow channel leads to a sharp drop in the pressure of B flow channel, forming a "tug-of-war" adjustment. In the adjustment of the flow channel of the sewage pump, the traditional independent adjustment method often ignores the complex correlation between the flow channels, resulting in low adjustment efficiency and even intensified system fluctuation. For example, when adjusting two parallel auxiliary flow channels of a sewage treatment plant, because the coupling effect of the two flow channels on the main adjustment flow channel is not considered, the valve opening of the two flow channels is adjusted separately, resulting in a large fluctuation of the pressure of the main pipeline between 0.3-0.5MPa, far exceeding the stable interval of 0.4±0.05MPa, increasing the time consumption of adjustment, etc.

[0080] Therefore, when there is negative coupling between the adjustment of at least two auxiliary adjustment flow channels to the target flow channel, that is, the adjustment of one flow channel causes the adjustment effect of another flow channel to be weakened, and the target flow channel parameter (such as flow, pressure) deviates from the stable interval (such as ±5% of the rated value); then, if the synchronous or single auxiliary flow channel appears for 3 times (configurable threshold) in succession, the target flow channel parameter still does not reach the expected adjustment effect (such as fluctuation decay rate <30%), and the fluctuation frequency abnormally increases (such as more than 150% of the historical average);

[0081] Finally, by establishing a transfer function matrix between flow channels, the influence coefficient of each auxiliary flow channel on the target flow channel is quantified. For example, when the A flow channel valve opening degree changes by 1%, the B flow channel pressure changes by more than 0.02 MPa, and the signs are opposite, it is determined that there is interference.

[0082] Among them, the target flow channel parameter refers to the core index that directly affects the system performance and operating state in the flow channel system, such as the flow of the main pipeline, the pressure in the reaction vessel, etc., which is the goal expected to be achieved in the whole parameter adjustment process.

[0083] Among them, the auxiliary adjustment flow channel is an auxiliary flow channel set to adjust the target flow channel parameter, which contains auxiliary adjustment flow channel parameters such as bypass valve opening degree, pump power, etc., which can indirectly affect the target flow channel parameter by changing its own value.

[0084] Among them, the parameter correlation relationship model is realized by means of mathematical models such as fluid mechanics principles, historical data of system operation, or machine learning algorithms, which can be:

[0085] First, the partial derivative of each auxiliary flow channel parameter (such as valve opening degree , pump speed ) to the target flow channel parameter (flow , pressure ) is calculated to form a correlation matrix M: , wherein is the partial derivative symbol, which is used to represent the change rate of a variable to another variable in a multivariate function, and the elements reflect the influence intensity of unit parameter change on the target parameter, which is obtained by historical data regression or CFD simulation;

[0086] Further, by introducing a time constant , the response delay of auxiliary flow i adjustment to target flow j is described, and a transfer function is used: Modeling ensures accurate adjustment timing, wherein G(s) represents the input-output relationship of the system in the complex frequency domain (s domain), wherein represents the response delay time of auxiliary flow channel i adjustment to target flow channel j, in s or min, is the time constant of the system (unit: s or min), reflecting the response speed of the target flow channel to the adjustment of the auxiliary flow channel, and e usually represents the natural constant;

[0087] On this basis, the calculation of the parameter sensitivity is introduced. For each auxiliary adjustment flow channel parameter, the sensitivity to the target flow channel parameter is calculated by the formula The sensitivity index can quantify the degree of influence of the change of a single auxiliary adjustment flow channel parameter on the change of the target flow channel parameter, like a "ruler", which can clearly show the degree of correlation between parameters;

[0088] Then, according to the preset sensitivity threshold and , a parameter subset with moderate sensitivity is screened out. The sensitivity threshold is a judgment standard set in combination with the characteristics of the flow channel system, operation requirements, and historical experience. The screening condition is Only the parameters that meet this condition have a reasonable sensitivity. If the parameter sensitivity is higher than , the adjustment may cause the target flow channel parameter to change too drastically, making it difficult to control accurately; if the parameter sensitivity is lower than , the influence on the target flow channel parameter after adjustment is negligible, and the expected effect cannot be achieved;

[0089] It should be understood that because there are many parameters in multiple auxiliary adjustment flow channels, different parameters have different influences on the target flow channel, and there are interactions between parameters. Therefore, the sensitivity analysis can quantify the influence of each parameter on the target flow channel and the interaction between parameters, which helps to screen out key parameter combinations, avoid blind adjustment, and screen out parameter combinations with moderate sensitivity and mutual promotion, making the adjustment more targeted, which is conducive to reducing invalid adjustment, improving adjustment accuracy, avoiding excessive adjustment range or poor adjustment effect due to improper parameter selection, and ensuring stable operation of the system.

[0090] It should be specially noted that the adjustment sequence and combination optimization can also be achieved by the following methods. According to the column norm of the correlation matrix , the adjustment priority is determined, and the auxiliary flow channel with the largest influence coefficient on the target flow channel is adjusted first. For example, if , the A flow channel is adjusted before the B flow channel;

[0091] L9( ) orthogonal table is used to design parameter combinations, for example, adjusting the valve opening degree (low, medium, and high) and the pump speed (decrease, rated, and increase) at the same time, and the optimal combination is quickly determined through 9 tests;

[0092] Further, only adjust part of parameters of single auxiliary flow channel (such as 5%-10% of valve opening) each time, and set an observation period (such as 15 seconds) to ensure that the system response is fully manifested, and according to the target flow channel parameter change rate Adjust the subsequent step size dynamically, if r>0.8 (sensitive response) then reduce the step size, if r<0.2 (delayed response) then increase the step size, through the ratio of the target flow channel flow rate change rate and the auxiliary flow channel valve opening adjustment rate, to judge the sensitivity of the system response, when the target flow channel parameter fluctuation decay rate , and the parameter deviation , wherein The standard deviation of the target flow channel parameter before and after adjustment reflects the parameter fluctuation amplitude, when It is explained that the fluctuation amplitude has been attenuated by more than 70%, and the system tends to be stable.

[0093] By quantifying the correlation between flow channels, multi-parameter collaborative optimization is achieved, breaking the limitations of traditional single flow channel independent adjustment, achieving precise regulation and control of complex flow channel systems, especially suitable for multi-pump parallel, pipe network staggered sewage treatment systems, which is conducive to significantly improving the stability and operation efficiency of the system.

[0094] As an optional embodiment, it also includes:

[0095] When determining the adjustment order and combination method of each auxiliary adjustment flow channel parameter, set an upper limit for the number of adjustment attempts, if the target flow channel parameter does not achieve the expected effect after adjustment according to the initially determined method, then randomly change the adjustment order of part of the flow channels and reattempt adjustment.

[0096] Specifically, in the sewage pump flow channel adjustment process, the traditional fixed sequence adjustment strategy often fails to consider the complex nonlinear coupling effect between flow channels, resulting in adjustment into local optimum or infinite loop. For example, when adjusting the valve opening of three parallel auxiliary flow channels in a certain sewage treatment plant, the fixed sequence (A→B→C) adjustment, because of the negative coupling between B flow channel and A flow channel, each adjustment of B will offset the adjustment effect of A, resulting in poor adjustment effect;

[0097] Therefore, setting an upper limit for the number of adjustment attempts is a setting mechanism to prevent ineffective adjustment, by setting a maximum number of attempts (such as 5 times), when the termination condition is still not met after reaching the number of attempts, the order optimization process is triggered.

[0098] Further, by randomly changing the adjustment order means that on the basis of keeping all flow channels participating in adjustment, the adjustment order is rearranged by a random algorithm (such as Fisher-Yates shuffle algorithm), for example, the original order [A→B→C] is randomly adjusted to [C→A→B];

[0099] Further, the absolute number threshold and the relative effect threshold are set as follows: when the number of continuous adjustments exceeds a preset value (e.g., 5 times), and the target flow channel parameter fluctuation decay rate is lower than 30%, the cumulative effect (e.g., energy consumption increase and fluctuation improvement ratio) of the current adjustment sequence exceeds 150% of the historical optimal sequence.

[0100] Further, on the basis of maintaining priority ranking, the last 50% of the flow channels are randomly exchanged, for example, the original order is [A→B→C→D], and after disturbance, it becomes [A→B→D→C], and the last 3 failed adjustment sequences are recorded, which is beneficial to avoid repeated attempts leading to a cycle.

[0101] If a flow channel does not produce a positive effect in multiple attempts, its priority weight in subsequent ranking is reduced (e.g., from 0.8 to 0.5), and the parameter adjustment step size is scaled by 5% (e.g., from 10% to 9.5%) after each sequence adjustment, thereby preventing missing the optimal due to excessive step size.

[0102] As an optional embodiment, it further comprises:

[0103] Before adjusting the parameters of each auxiliary adjustment flow channel, a small amount of pre-adjustment is performed on each parameter, the target flow channel parameter is observed, and the actual adjustment parameter is selected according to the obviousness of the change, and the parameter that causes moderate change of the target flow channel parameter is preferentially selected.

[0104] It should be understood that in the sewage pump flow channel adjustment process, if the parameters of the auxiliary adjustment flow channel are blindly selected for adjustment, it is easy to cause over-adjustment or ineffective adjustment. For example, directly adjusting the pump speed by a large margin may cause the system pressure to suddenly increase, causing pipe vibration and even equipment damage; and selecting to adjust parameters with low correlation will waste adjustment time and cannot effectively improve the target flow channel fluctuation problem.

[0105] The small amount of pre-adjustment refers to applying a small change to each adjustable parameter (e.g., valve opening, pump speed, pipe throttling coefficient, etc.) before formally adjusting the parameters of the auxiliary adjustment flow channel. The adjustment range of the valve opening is usually set to ±2%-±5% of the current opening, and the pump speed adjustment range is ±1%-±3% of the current speed. The pre-adjustment duration is determined according to the system response time, and is generally 1 / 3-1 / 2 of the time required to reach preliminary stability, ensuring that the immediate effect of parameter adjustment can be observed, and excessive interference with the stable state can be avoided.

[0106] Wherein, the small changes of the observation target flow channel parameters are recorded by the high-precision sensors (the flow sensor accuracy is ±0.5%, and the pressure sensor response time is less than 100 ms) of the target acquisition module with high frequency sampling (1-2 times per second) to record the changes of the flow, pressure, liquid level and other parameters of the target flow channel during the pre-adjustment. The data filtering algorithm (such as Kalman filtering) is used to remove noise interference and accurately capture the parameter change trend;

[0107] Wherein, the obvious degree of change is evaluated by a quantitative index, and the change rate of the target flow channel parameter after pre-adjustment is calculated (Taking flow regulation as an example, is the flow change amount, is the initial flow, is the parameter adjustment amount). The evaluation criteria are set as follows: when R>1.5, the parameter is an over-sensitive parameter, and a large adjustment is easy to cause system oscillation; when 0.5≤R≤1.5, it is identified as a moderate parameter, and the regulation controllability is strong; when R<0.5, it belongs to a sluggish parameter, and the regulation efficiency is low;

[0108] The parameters causing moderate changes of the target flow channel parameters are preferentially selected as the actual adjustment parameters, and if there is no moderate parameter, the parameters close to the moderate standard (R close to 1) are preferentially selected. If all the parameters are over-sensitive parameters, a segmented fine-tuning strategy is adopted, and the adjustment amplitude is further reduced (such as 1% adjustment of the valve opening each time), and the monitoring frequency is encrypted;

[0109] The parameters selected by the pre-adjustment provide a data basis for determining the adjustment order and combination mode of the auxiliary adjustment flow channel, so that the cross-adjustment process is more targeted; the parameter sensitivity data obtained in the selection process can be used to optimize the flow channel parameter correlation model, which is beneficial to improve the prediction accuracy of the model.

[0110] As an optional embodiment, it further includes:

[0111] When monitoring the target flow channel parameter changes in real time after each adjustment, the current parameter change curve is compared with the parameter change curve shape in the historical successful adjustment, if the difference is large, the subsequent adjustment is suspended, and the current adjustment is modified by referring to the adjustment mode corresponding to the historical successful curve.

[0112] Wherein, the target flow channel parameter change refers to the numerical variation of the target flow channel parameter (such as the core indicators of the main pipeline flow and the reaction kettle pressure) with time after the auxiliary adjustment flow channel parameter is changed.

[0113] Wherein, the current parameter change curve is the curve formed by the target flow channel parameter changing with time during this parameter adjustment process, which is recorded by real-time monitoring equipment (such as sensors and data acquisition systems), and it directly reflects the actual influence of the current adjustment operation on the target parameter.

[0114] The parameter change curve in the historical successful adjustment is a target flow channel parameter change curve corresponding to the adjustment operation that achieves the expected target and realizes stable and efficient operation of the system in the past flow channel parameter adjustment process. The curves contain experience information of the past successful adjustment.

[0115] It should be understood that, in the flow channel system parameter adjustment process, even if a suitable parameter combination is screened out and the adjustment order is determined based on the sensitivity analysis, there is still a dynamic risk in the adjustment process. Due to the complex and changeable operation environment of the flow channel system, the coupling relationship between parameters may change with the working condition, and the adjustment scheme simply relying on theoretical calculation may deviate in actual execution. For example, sudden external interference and performance degradation caused by equipment aging may cause the current parameter adjustment effect to deviate from the expectation, and if the original plan is continued, it is likely to cause system instability or even failure;

[0116] The specific workflow is: after each adjustment of the auxiliary adjustment flow channel parameter of the flow channel system, the target flow channel parameter change is monitored in real time, and the current parameter change curve is drawn. The curve is compared with the parameter change curve in the historical successful adjustment in the time-parameter change amount coordinate system. The curve shape comparison mainly analyzes the slope change, fluctuation amplitude, rising or falling trend and other characteristics of the curve. If the difference between the two is large, it means that the current adjustment operation does not produce similar effects to the historical successful cases, and at this time the system has the risk of deviating from the expected target, so the subsequent adjustment operation is suspended, which is beneficial to avoid further expansion of the wrong adjustment. Subsequently, referring to the adjustment mode corresponding to the historical successful curve, including the adjustment parameter combination, the adjustment order, the adjustment amplitude, the adjustment time interval and other information, the current adjustment is corrected, so that the change trend of the target flow channel parameter gradually approaches the historical successful curve;

[0117] By comparing the current and historical successful parameter change curves, the deviation in the adjustment process is identified in time, the adjustment is corrected using historical experience, which is beneficial to effectively solve the adjustment failure problem caused by system dynamic changes, helps to avoid system instability caused by blind operation when the adjustment deviates, enhances the reliability and adaptability of the parameter adjustment process, and is beneficial to ensure that the flow channel system can maintain stable and efficient operation through precise adjustment under various working conditions.

[0118] As an optional embodiment, it further comprises:

[0119] When it is determined whether to continue the subsequent adjustment according to the target flow channel parameter change, a plurality of different target parameter intervals are set, and different adjustment speeds are correspondingly adopted when the target flow channel parameter enters different intervals. The closer the parameter is to the final target, the slower the adjustment speed is.

[0120] Among them, the target flow channel parameter is still the core index that determines the system performance in the flow channel system, such as the fluid flow of the chemical pipeline and the temperature of the heat exchanger.

[0121] Among them, the final target refers to the ideal value or range that the expected target flow channel parameter reaches, which is the final direction of the entire parameter adjustment process.

[0122] Among them, the target parameter interval is the range from the current target flow channel parameter value to the final target value, which is divided into multiple sub-intervals according to different distance standards, and each interval corresponds to a different adjustment strategy.

[0123] Among them, the adjustment speed refers to the change amount of the auxiliary adjustment flow channel parameter per unit time, which directly affects the change rate of the target flow channel parameter.

[0124] It should be understood that, first of all, in the parameter adjustment process of the flow channel system, simply relying on sensitivity analysis to screen parameters and correcting adjustment strategies according to historical successful curves still has the problem of insufficient precision control. When the target flow channel parameter is close to the final target value, if the initial adjustment speed continues to operate, the "overshoot" phenomenon may occur, that is, the parameter adjustment amplitude exceeds the expected target, causing the system to deviate from the stable state; and when the parameter is far from the final target value, if the adjustment speed is too slow, it will greatly increase the adjustment time and reduce the system running efficiency.

[0125] Next, according to the target flow channel parameter change condition, it is determined whether to continue subsequent adjustment, and the range from the current value of the target flow channel parameter to the final target value is divided into multiple different target parameter intervals. For example, the range can be divided into "initial adjustment interval", "fine adjustment interval" and "fine tuning interval". When the target flow channel parameter is in the "initial adjustment interval" far from the final target, in order to improve the adjustment efficiency, a faster adjustment speed is adopted to quickly reduce the difference between the parameter and the final target; as the target flow channel parameter gradually enters the "fine adjustment interval" closer to the final target, the adjustment speed is appropriately reduced to ensure the adjustment effect while reducing the impact of adjustment on the system; when the parameter enters the "fine tuning interval" close to the final target, the adjustment speed is further slowed down to make the parameter accurately approach the final target with a small adjustment amplitude, which is beneficial to avoid the "overshoot" situation caused by too large adjustment amplitude.

[0126] By setting multiple target parameter intervals and matching different adjustment speeds, the problem of difficult to balance adjustment efficiency and accuracy in traditional adjustment methods is effectively solved. When the parameter is far from the final target, fast adjustment is adopted to save time; when the parameter is close to the final target, fine tuning is adopted to ensure accuracy and prevent "overshoot", so that the parameter adjustment process of the flow channel system is more scientific and reasonable, the stability and reliability of the system operation are enhanced, and the overall performance and work efficiency of the flow channel system are improved.

[0127] The above description is only specific embodiments of the present application, but the protection scope of the present application is not limited thereto, any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A multi-channel sewage pump monitoring system, characterized in that, include: The target acquisition module monitors each flow channel of the sewage pump in real time to obtain fluctuation data of each flow channel. The fluctuation data includes at least flow rate, pressure, and liquid level. The target determination module determines the target flow channel causing the fluctuation based on the acquired fluctuation data. The target flow channel includes a main adjustment flow channel and an auxiliary adjustment flow channel. The parameter calculation module calculates the theoretical adjustment parameter amplitude value of the main adjustment channel. If the adjustment of the parameter amplitude value of the main adjustment channel exceeds the preset threshold, the auxiliary adjustment channel is used to start differentiated adjustment, so that the adjustment amplitude gradually increases or decreases. The parameter calculation module also includes the following steps: Analyze the correlation between the adjustment parameters of the auxiliary adjustment channel and the main adjustment channel, and select the channel with a high correlation to the fluctuation of the main adjustment channel and the smallest adjustment parameter amplitude as the auxiliary adjustment channel; Based on the fluctuation of the main adjustment channel and the parameter characteristics of the auxiliary adjustment channel, a step-by-step adjustment strategy is formulated. This involves first adjusting some parameters of the auxiliary adjustment channel while simultaneously monitoring the impact on the fluctuation of the main adjustment channel, and then gradually adjusting other relevant parameters. By gradually adjusting the parameters of the auxiliary adjustment channel, the adjustment range can be gradually increased or decreased to achieve the same or similar effect as adjusting the main adjustment channel, thus preventing energy waste caused by frequent parameter adjustments. The target determination module determines the target flow channel that causes the fluctuation, including: Analyze the flow rate, pressure, and liquid level fluctuation data of each flow channel to obtain the fluctuation frequency characteristics and amplitude variation patterns; By combining the design parameters and historical operating data of the sewage pump, a correlation model was established between the flow channel fluctuation data and the system head, operating efficiency, and shaft power. Calculate the weight value of the impact of each flow channel fluctuation on the system performance, and determine the first type of flow channel whose impact weight exceeds the set threshold as the main adjustment flow channel; For the second type of flow channel whose influence weight does not reach the threshold, fluid connectivity verification is performed, including detecting the physical connection characteristics of the pipe layout between flow channels, verifying the effect of adjusting the flow channel parameters on the suppression of the main adjustment flow channel fluctuation, and monitoring the stability changes of the system operating parameters. When the fluid connectivity conditions are met and the adjustment behavior can improve the fluctuation state of the main adjustment flow channel, the second type of flow channel is identified as an auxiliary adjustment flow channel.

2. The sewage pump monitoring system based on a multi-channel according to claim 1, characterized in that, It also includes a cross-coordination module, specifically: When the adjustment effects of at least two auxiliary adjustment channels on the target channel interfere with each other, causing the target channel parameters to deviate from the stable range; or when the target channel parameters still fail to achieve the expected adjustment effect and fluctuate abnormally after multiple independent adjustments of a single auxiliary adjustment channel, the cross adjustment process is initiated.

3. The sewage pump monitoring system based on a multi-channel according to claim 2, characterized in that, The cross adjustment specifically refers to: Construct a parameter correlation model between each auxiliary adjustment channel and the target channel, and determine the adjustment order and combination method of each auxiliary adjustment channel parameter based on the model; Following a predetermined sequence and combination, the parameters of each auxiliary adjustment channel are adjusted sequentially. After each adjustment, the changes in the target channel parameters are monitored in real time, and a decision is made on whether to continue subsequent adjustments based on the changes.

4. The sewage pump monitoring system based on a multi-channel according to claim 3, characterized in that, Also includes: When determining the adjustment order and combination of each auxiliary flow channel parameter, an upper limit is set for the number of adjustment attempts. If the target flow channel parameter does not achieve the expected effect after adjustment according to the initially determined method, the adjustment order of some flow channels is randomly changed, and the adjustment attempt is repeated.

5. A sewage pump monitoring system based on a multi-channel according to claim 3, characterized in that, Also includes: Before adjusting some parameters of each auxiliary flow channel, make small pre-adjustments to each parameter, observe the slight changes in the target flow channel parameters, and select the parameters to be adjusted according to the degree of change, giving priority to parameters that cause moderate changes in the target flow channel parameters.

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