Electrocoagulation water treatment plant detection method and system

Abstract

The present application relates to the technical field of measurement data processing, and particularly relates to a kind of electroflocculation water treatment equipment detection method and system, method includes: according to current processing task, each flocculation tube is detected globally, and the current impedance value of the electrode of each flocculation tube is obtained;Based on the electrode material of flocculation tube, set electrode passivation upper limit, when current impedance value exceeds upper limit, record duration of continuous overproof;According to the duration of continuous overproof, the loss of flocculation tube is divided;Based on the mapping rule of the grade result of division, loss grade and operating parameter are established, and the current density suggestion value data table and the water flow speed suggestion value data table corresponding to loss grade are generated;Output equipment state detection report containing current density suggestion value data table and water flow speed suggestion value data table.By the present application, how to realize the quantitative evaluation and visual expression of electrode loss state of electroflocculation equipment is effectively solved, and the process instability problem caused by electrode passivation in the process of imbalance of multiple flocculation tube cluster cooperation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of measurement data processing, and in particular to an electroflocculation water treatment equipment detection method and system. BACKGROUND

[0002] Electroflocculation technology is a highly efficient water treatment process. Metal cations are generated by anodic electrolysis of metal anodes, and then hydrolysis is formed to adsorb colloidal particles, heavy metals and organic matter in water. This technology has the advantages of no need to add chemical agents, less sludge, strong adaptability, etc., and is widely used in industrial wastewater, municipal sewage and reuse water treatment fields. Current impedance value is a key physical quantity representing electrode wear. When the impedance exceeds the upper limit of electrode passivation determined by the electrode material, a passivation film will be formed on the electrode surface, resulting in electrolytic efficiency decay.

[0003] The traditional method relies on empirical judgment method. The operator detects regularly and estimates the electrode wear degree only by subjective experience. No quantitative correlation between the duration of continuous over-standard current impedance and the wear state is established, resulting in that the wear evaluation is seriously dependent on individual experience and the data misjudgment rate is high. The threshold alarm linkage control method automatically triggers a preset formula to generate a control instruction when the current impedance value exceeds the preset threshold, and directly issues the control instruction to the actuator. The control instruction is directly transmitted to the execution end in the form of a signal, and there is a lack of standardized data carrier for recording parameter adjustment basis, which makes it impossible to trace the decision logic during fault diagnosis. The above defects together result in that the electrode wear degree cannot be quantitatively evaluated, the parameter adjustment suggestion has no standardized expression carrier, and the boundary between measurement function and control function is blurred.

[0004] The information disclosed in this BACKGROUND section is only intended to enhance the understanding of the general background of the present disclosure and is not intended to be a recognition or a suggestion that this information forms a prior art that is known to those of ordinary skill in the art. SUMMARY

[0005] The present application provides an electroflocculation water treatment equipment detection method and system, which can effectively solve the problems in the background art.

[0006] In order to achieve the above purpose, the technical scheme adopted by the present application is:

[0007] An electroflocculation water treatment equipment detection method, the method comprising:

[0008] Performing global wear detection on each flocculation tube according to the current treatment task, and detecting the current impedance value of the electrode of each flocculation tube in real time;

[0009] Setting an electrode passivation upper limit based on the electrode material of the flocculation tube, and recording the duration of continuous over-standard when the current impedance value exceeds the electrode passivation upper limit;

[0010] dividing the flocculation pipes according to the duration of the continuous over-standard;

[0011] establishing a mapping rule of loss level and operating parameter based on the level result of the loss division, generating a current density suggestion value data table and a water flow speed suggestion value data table corresponding to the loss level;

[0012] generating a device state detection report according to the current density suggestion value data table and the water flow speed suggestion value data table.

[0013] Further, based on the suggestion value data table in the device state detection report, the cluster flow balance of each flocculation pipe is used, including:

[0014] According to the current density suggestion value data table and the water flow speed suggestion value data table, the distribution flow of each flocculation pipe is calculated;

[0015] Integrate the distribution flow of each flocculation pipe to generate a cluster flow balance matrix, which contains the flow influence coefficient between the flocculation pipes;

[0016] According to the cluster flow balance matrix, the flow distribution suggestion value of each flocculation pipe is distributed;

[0017] Based on the flow distribution suggestion value, the flow distribution of each flocculation pipe is adjusted.

[0018] Further, the flow equation set is established based on the distribution flow of each flocculation pipe and substituted into time to obtain the flow influence coefficient between the flocculation pipes, and the cluster flow balance matrix is generated. The constraint condition of the flow equation set is that the sum of the product of the water flow speed change of all flocculation pipes and their distribution flow is zero.

[0019] Further, when the flow distribution suggestion value of any flocculation pipe exceeds the upper limit, the flow of the corresponding flocculation pipe is step-adjusted according to the gradient adjustment strategy until the actual water flow speed matches the distribution flow.

[0020] Further, the device state detection report contains association rules, including:

[0021] Obtain the turbidity change rate of the water in and out of each flocculation pipe;

[0022] When the current density suggestion value increases, the outflow turbidity reduction amplitude corresponding to the turbidity change rate and the increase of the current density suggestion value constitute a positive correlation;

[0023] When the water flow speed suggestion value increases, the outflow turbidity reduction amplitude corresponding to the turbidity change rate and the increase of the water flow speed suggestion value constitute a negative correlation.

[0024] Further, when the current impedance value exceeds the upper limit of electrode passivation, and the cumulative operating condition duration exceeds the upper limit, the flocculation pipe is divided into a high loss group, and the remaining flocculation pipes are divided into a low loss group, and a corresponding loss compensation coefficient is generated for cluster flow balance.

[0025] Further, different operating conditions are distinguished based on turbidity change rate, including:

[0026] The first load threshold is set based on historical normal operation data, and the second load threshold is set based on the maximum load tolerance of the flocculation pipe;

[0027] When the turbidity change rate is less than or equal to the first load threshold, it is determined to be a regular load operating condition;

[0028] When the turbidity change rate is greater than the first load threshold and less than the second load threshold, it is determined to be a transition load operating condition;

[0029] When the turbidity change rate continues to exceed the second load threshold for a preset duration, it is determined to be a shock load operating condition;

[0030] Wherein, the second load threshold is greater than the first load threshold.

[0031] Further, the equipment state detection report is updated, including:

[0032] Real-time monitoring of the change rate of the current impedance value of each flocculation pipe, when the change rate of any flocculation pipe shows a nonlinear rise, the current density recommendation value is updated;

[0033] Obtain the real-time turbidity change rate of the current water in and out, and obtain the deviation value from the target turbidity change rate interval;

[0034] With the minimum deviation value as the optimization goal, obtain each recommendation value data table under the safety range of current density and the process constraint condition of water flow speed;

[0035] The recommendation value data table is issued to the corresponding flocculation pipe for execution, and the outflow turbidity change rate is collected in real time;

[0036] Repeat the above steps until the outflow turbidity change rate collected continuously for multiple times falls within the preset stable range, and terminate the update process.

[0037] Electrocoagulation water treatment equipment detection system, the system comprises:

[0038] Impedance detection module, according to the current processing task, the global loss of each flocculation pipe is detected, and the current impedance value of each flocculation pipe electrode is detected in real time;

[0039] The exceeding comparison module sets an electrode passivation upper limit based on the electrode material of the flocculation pipe, and records the duration of continuous exceeding when the current impedance value exceeds the electrode passivation upper limit;

[0040] The loss division module divides the loss of the flocculation pipe according to the duration of continuous exceeding;

[0041] The parameter mapping module establishes a mapping rule of the loss level and the operating parameter based on the level result of the loss division, and generates a current density suggestion value data table and a water flow speed suggestion value data table corresponding to the loss level;

[0042] The report generation module generates a device state detection report according to the current density suggestion value data table and the water flow speed suggestion value data table.

[0043] Further, the report generation module comprises:

[0044] The distribution calculation unit calculates the distribution flow of each flocculation pipe according to the current density suggestion value data table and the water flow speed suggestion value data table;

[0045] The matrix generation unit integrates the distribution flow of each flocculation pipe to generate a cluster flow balance matrix, and the cluster flow balance matrix contains the flow influence coefficient between the flocculation pipes;

[0046] The cluster distribution unit distributes the flow distribution suggestion value of each flocculation pipe according to the cluster flow balance matrix;

[0047] The flow adjustment unit adjusts the flow distribution of each flocculation pipe based on the flow distribution suggestion value.

[0048] The technical scheme of the present application can achieve the following technical effects:

[0049] The technical scheme effectively solves the problems of how to realize quantitative evaluation and visual expression of the electrode loss state of the electrocoagulation device, and process instability caused by electrode passivation in the process of imbalance of the multi-flocculation pipe cluster.

[0050] The above description is only a summary of the technical scheme of the present application. In order to more clearly understand the technical means of the present application, the specific embodiments of the present application can be implemented according to the content of the description, and in order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical scheme of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments described in the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0052] Figure 1 A flowchart for detecting the electrocoagulation water treatment equipment;

[0053] Figure 2 A flowchart for obtaining flow distribution;

[0054] Figure 3 A flowchart for loss division;

[0055] Figure 4 A flowchart for updating the recommended value data table. DETAILED DESCRIPTION

[0056] 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 some of the embodiments of the present application, but not all the embodiments of the present application.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0058] Embodiment one;

[0059] As Figure 1 shown, the present application provides an electrocoagulation water treatment equipment detection method, the method comprising:

[0060] According to the current processing task, the global loss of each flocculation tube is detected, and the current impedance value of the electrode of each flocculation tube is detected in real time;

[0061] Based on the electrode material of the flocculation tube, an upper limit of electrode passivation is set, and when the current impedance value exceeds the upper limit of electrode passivation, the duration of continuous over-standard is recorded;

[0062] According to the duration of continuous over-standard, the loss of the flocculation tube is divided;

[0063] Based on the grade result of the loss division, a mapping rule of loss grade and operating parameter is established, and a current density recommended value data table and a water flow speed recommended value data table corresponding to the loss grade are generated;

[0064] According to the current density recommended value data table and the water flow speed recommended value data table, an equipment state detection report is generated.

[0065] Specifically, the electrocoagulation device includes several flocculation pipes, each of which is internally provided with an electrode to remove impurities from water. To ensure efficient operation and wear monitoring of the device during long-term use, the current impedance value needs to be detected in real time to evaluate the state of the electrodes of each flocculation pipe. An integrated detection unit is preferably provided for real-time acquisition of the current impedance value, and the value is compared with the preset upper limit of electrode passivation. If the impedance value exceeds the passivation upper limit, the duration of the excessive value will be recorded. In the specific implementation process, to improve the accuracy and automation level of detection, advanced sensor technology and data processing algorithms should be used to ensure the real-time and accuracy of the data. At the same time, electrodes made of corrosion-resistant materials are used to prolong the service life of the device. After receiving the continuous excessive duration, wear division is needed. In the preferred embodiment, the wear can be divided into several levels, such as slight wear, moderate wear, and severe wear, and the mapping rules of wear level and operating parameters are set accordingly, which can be optimized through a large amount of experimental data and machine learning algorithms. For the generated current density suggestion value data table and water flow speed suggestion value data table, it is preferably based on rich experimental data and automatically adjusted through a software system to help operators select the optimal operating conditions. Finally, the device generates a state detection report based on the data of each sensor. The report includes the current operating status of the device, as well as the predicted maintenance time and operating suggestions. Through the detailed report, the operator can have a comprehensive understanding of the state of the device and make maintenance preparations in advance to ensure the continuous operation of the device and the achievement of water treatment effect.

[0066] Through the technical solutions of the present application, the problem of how to quantitatively evaluate and visually express the electrode wear state of the electrocoagulation device, as well as the process instability caused by electrode passivation in the process of multi-flocculation pipe cluster imbalance, is effectively solved.

[0067] Further, as shown in Figure 2 Based on the suggestion value data table in the device state detection report, the flow of each flocculation pipe is balanced, including:

[0068] According to the current density suggestion value data table and the water flow speed suggestion value data table, the distribution flow of each flocculation pipe is calculated;

[0069] Integrate the distribution flow of each flocculation pipe to generate a cluster flow balance matrix, which includes the flow influence coefficient between the flocculation pipes;

[0070] According to the cluster flow balance matrix, the flow distribution suggestion value of each flocculation pipe is allocated;

[0071] Based on the flow distribution suggestion value, the flow distribution of each flocculation pipe is adjusted.

[0072] As a preferred embodiment of the above-mentioned embodiment, firstly, the current density recommendation data table and the water flow velocity recommendation data table are fully considered when allocating the flow rate of each flocculation pipe, the current density recommendation data table is constructed according to the turbidity change and the current density, the flocculation pipe with a high current density needs to be allocated a high flow rate, and the water flow velocity recommendation data table is constructed according to the turbidity change and the water flow velocity, and reducing the water flow velocity can reduce the load of the flocculation pipe, so the flow rate of each pipe needs to be dynamically adjusted to optimize the treatment effect, and the preferred embodiment can include monitoring each flocculation pipe and calculating based on the corresponding technical indicators, which requires real-time analysis of the correlation of turbidity, flow rate, and current density to ensure that it meets the optimization standard; next, to generate the cluster flow balance matrix, integrate the allocated flow rate of each flocculation pipe, and aggregate this information to the central control panel and process the resulting data to establish a cluster flow balance matrix containing the flow influence coefficient between the flocculation pipes, the flow influence coefficient can be obtained by analyzing the influence of each flocculation pipe on each other's operation, which includes the flow direction, the flow size, and the degree of influence between devices, the cluster flow balance matrix not only reflects the current state, but also needs to estimate some trends to facilitate future adjustments; to allocate the flow rate recommendation value, the implementation scheme needs to distinguish all flocculation pipes through the central control panel, identify which pipes have significant wear or uneven flow, and then calculate the compensation value, because it can provide accurate influence coefficients to guide the allocation of compensation values to ensure that the width and flow requirements are matched to achieve uniform flow distribution; finally, the electric actuator of each flocculation pipe is synchronously driven to adjust the opening degree of the combined valve for flow allocation, the electric actuator adjusts the valve opening degree to adapt to the required flow allocation by receiving the compensation value instruction to achieve dynamic balance of the flow, at this step, the preferred implementation method monitors the adjustment effect through a real-time feedback mechanism to ensure that the valve adjustment truly realizes the flow balance of the cluster, and if necessary, some actuators can be directly fine-tuned under certain circumstances to further optimize the process.

[0073] Further, the flow equation set is established based on the allocated flow rate of each flocculation pipe and substituted into time to obtain the flow influence coefficient between the flocculation pipes to generate the cluster flow balance matrix, and the constraint condition of the flow equation set is that the sum of the product of the water flow velocity change of all flocculation pipes and their allocated flow rate is zero.

[0074] As a preferred embodiment of the above-mentioned embodiment, first, a flow equation set is established on the basis of the distribution flow of each flocculation pipe, which reflects the flow distribution of each flocculation pipe and the correlation between them, and the uniqueness of each equation is that it integrates many parameters in the electrocoagulation process, such as current density change, water flow velocity change, and reaction excess or deficiency under different working conditions. A central data integration module is set to collect and process these flow information in real time to ensure that the equation set can be accurately formed; then, time variables are substituted to dynamically reveal the real-time state of the flow equation set. The introduction of time variables aims to record and analyze the trend and influence of flow change over time, so that the equation set is not only a static mathematical expression, but also a dynamic system reflecting the relationship between flocculation pipes. Through this dynamic analysis, any unstable or abnormal changes in the flocculation process can be captured, thereby providing the basis for adjustment strategy; in order to generate the cluster flow balance matrix, accurate flow influence coefficients must be obtained, which reflect the mutual influence of flow between different flocculation pipes. The calculation of flow influence coefficients needs to be based on the solution of flow equation set, as well as the flow rate and flow change data of each flocculation pipe at different time points. This step can be calculated by a specially designed algorithm to ensure that it is consistent with the experimental results and has a guiding effect on the generation of flow balance matrix; the sum of the product of the flow rate change of all flocculation pipes in the flow equation set constraint condition and the distribution flow is zero, which is the standard constraint to ensure flow balance. The flow rate change of each flocculation pipe is automatically monitored by the central control panel to ensure that any individual pipe speed and flow change will not disrupt the flow balance of the entire system. In addition, through real-time monitoring software, the status of each flocculation pipe can be displayed on the central control panel, so that adjustments can be made at any time to meet the constraint conditions.

[0075] Further, when the flow distribution recommended value of any flocculation pipe exceeds the upper limit, the flow of the corresponding flocculation pipe is adjusted step by step according to the gradient adjustment strategy until the actual water flow velocity matches the distribution flow.

[0076] As a preferred embodiment of the above-mentioned embodiment, firstly, a specific flocculation pipe is comprehensively analyzed, not only to monitor its current flow and water flow speed, but also to further investigate the passivation state of the electrode and the flocculation effect, which can be realized by the central control panel by comprehensively analyzing the previous real-time data and comparing historical data, so as to determine the corresponding adjustment scheme; in order to realize step-by-step adjustment, the gradient adjustment strategy is preferably a step-by-step open adjustment mechanism, and in the specific implementation process, small amplitude adjustment is first carried out to fine-tune the combined valve opening degree and slowly change the water flow speed. The advantage of this method is to avoid the violent flow fluctuation and processing efficiency loss caused by one-time adjustment, and the flow and water flow speed are continuously monitored after each adjustment, and the effect brought by the adjustment is analyzed through the feedback mechanism to ensure that the water flow speed gradually tends to the distribution flow standard; in this process, the adjustment is preferably carried out in a way of automatic control combined with human intervention, automatic control can respond to flow changes in time, while in complex working conditions, more refined adjustment can be realized through personnel intervention in the control center, to achieve the effect of double insurance, at the same time, the adjustment process needs to be recorded for subsequent optimization and further improvement of the gradient adjustment strategy to provide data support.

[0077] Further, the device state detection report contains association rules, including:

[0078] Obtain the turbidity change rate of the water in and out of each flocculation pipe;

[0079] When the current density recommended value increases, the outflow turbidity reduction amplitude corresponding to the turbidity change rate and the increase of the current density recommended value constitute a positive correlation relationship;

[0080] When the water flow speed recommended value increases, the outflow turbidity reduction amplitude corresponding to the turbidity change rate and the increase of the water flow speed recommended value constitute a negative correlation relationship.

[0081] As a preferred embodiment of the above-mentioned embodiment, first, a positive correlation relationship is defined, which indicates that when the current density increases, the corresponding decrease in effluent turbidity caused by the change rate of turbidity increases significantly, which is positively correlated with the increase in current density. During implementation, the decrease in effluent turbidity can be actively regulated by increasing the current density. This regulation shows the necessity of current strengthening in the process of electrocoagulation. In application, a hierarchical regulation strategy is preferably used, and the current density is increased in stages according to the change rate of real-time turbidity monitoring, to ensure that each increment brings significant turbidity reduction effect, thereby maintaining efficient flocculation treatment; Next, define the negative correlation relationship, which is that with the increase of water flow velocity, the corresponding decrease in effluent turbidity caused by the change rate of turbidity gradually decreases, and is negatively correlated with the increase of water flow velocity, which shows that high water flow velocity may slow down the flocculation effect, so the water flow velocity needs to be carefully managed. In specific implementation, the flow rate can be controlled by gradually adjusting the pump rate to keep it within an easy-to-manage gradient range. For high-turbidity water bodies, it is preferred to use the method of reducing flow rate in stages, which can help to stabilize the treatment conditions and improve the flocculation effect; In further optimization, the current density is increased in stages according to the increase of turbidity change rate. This implementation method is to gradually increase the current density through an adaptive adjustment system to enhance the effect of electrocoagulation. According to the turbidity monitoring data, multiple trigger points are set. When the turbidity increases to the trigger point in a certain interval, the current is automatically increased to improve the treatment efficiency. This implementation can optimize the flocculation process and ensure effective adaptation to complex water treatment situations; At the same time, the water flow velocity is attenuated in gradient with the increase of turbidity change rate. This attenuation strategy helps to slow down the adverse effects of high flow rate on flocculation effect. Specifically, when the turbidity change rate reaches the pre-set critical point, the flow rate is automatically reduced to maintain stable water treatment effect.

[0082] Further, as shown in Figure 3 When the current impedance value exceeds the upper limit of electrode passivation, and the cumulative working condition duration exceeds the upper limit, the flocculation pipe is divided into a high-loss group, and the remaining flocculation pipes are divided into a low-loss group, and the corresponding loss compensation coefficient is generated for cluster flow balance.

[0083] As a preferred embodiment of the above-mentioned embodiment, firstly, the current impedance value is monitored in real time by equipping precise sensors, and when the detection data indicates that the passivation state of certain flocculation tubes has exceeded the set upper limit of electrode passivation, a preliminary warning of the equipment wear condition is given, and at the same time, the central control system continuously records and tracks the working time of each flocculation tube, and when the wear condition is evaluated, the accumulated working time is another key indicator, especially when the length of time exceeds the preset upper limit, which indicates that these flocculation tubes are in a high wear risk state; at a certain time node, based on real-time monitoring data, all flocculation tubes are systematically classified, those flocculation tubes that both reach the upper limit of passivation state and exceed the upper limit of accumulated working time are classified into a high wear group, and the rest are classified into a low wear group, this classification not only helps equipment maintenance and management, but also significantly improves the accuracy of flow distribution; in order to further optimize the process, the compensation coefficient of the high wear group will be increased to make up for the loss of treatment efficiency due to electrode passivation, the process of generating the compensation coefficient is based on the results of flow influence analysis and electrode wear prediction, the compensation coefficient can be obtained through corresponding analysis of data algorithm and experimental results, and the adjustment of the compensation coefficient will be used to optimize the cluster flow balance matrix, so that the system can maintain stable operation under different wear conditions; in actual operation, the compensation coefficient is automatically calculated on the central control panel, and is applied through the flow balance system to adjust the distribution flow and current density of each flocculation tube, and when the compensation is carried out, the real-time monitoring system should continuously track the adjustment effect to correct in time and ensure the effectiveness and adaptability of the compensation measures.

[0084] Further, different working conditions are distinguished based on the turbidity change rate, including:

[0085] The first load threshold is set based on historical normal operation data, and the second load threshold is set based on the maximum tolerance load of the flocculation tube;

[0086] When the turbidity change rate is less than or equal to the first load threshold, it is determined to be a regular load working condition;

[0087] When the turbidity change rate is greater than the first load threshold and less than the second load threshold, it is determined to be a transitional load working condition;

[0088] When the turbidity change rate continuously exceeds the second load threshold for a preset length of time, it is determined to be a shock load working condition;

[0089] Wherein, the second load threshold is greater than the first load threshold.

[0090] As a preferred embodiment of the above-mentioned embodiment, first, based on historical normal operation data, a first load threshold is set, which reflects the standard of turbidity change rate under normal working conditions, and is used to identify the normal load working condition, and by analyzing past processing data and working load conditions, these values can be automatically set, data analysis tools such as data mining techniques and machine learning models can be applied to accurately identify the turbidity rate in normal operation to ensure the applicability of the threshold setting; second, the maximum load tolerance of the flocculation pipe determines the setting of the second load threshold, which is used to identify the maximum turbidity change rate that the flocculation pipe can withstand within the critical limit, which is obtained through experimental verification and technical parameter evaluation to ensure its accuracy and reliability in processing transition load and impact load working conditions, the second load threshold must be greater than the first load threshold to distinguish between normal and overload states; when the turbidity change rate is less than or equal to the first load threshold, it is determined that the state is a normal load working condition, at this time the flocculation process can be carried out according to the standard operation requirements without additional adjustment, but when the turbidity change rate exceeds the first load threshold but is still less than the second load threshold, it is determined that it is a transition load working condition, in this case, the flocculation process may need to be adjusted partially, for example, the current density is appropriately increased to improve the processing efficiency; if the turbidity change rate continues to exceed the second load threshold and reaches the preset time length, it is automatically determined as an impact load working condition, in this case, the flocculation pipe may be under a large load, and emergency measures need to be taken to avoid a decrease in processing efficiency or damage to the equipment, the preferred method is to enable an emergency response mechanism, such as reducing the water flow speed or increasing the maintenance frequency, to ensure the safety of the equipment and the continuous effectiveness of the processing.

[0091] Further, as shown in Figure 4 the device status detection report is updated, including:

[0092] The rate of change of the current impedance value of each flocculation pipe is monitored in real time, and when the rate of change of any flocculation pipe shows a nonlinear rise, the current density suggestion value is updated;

[0093] The current turbidity change rate of the incoming and outgoing water is obtained, and the deviation value from the target turbidity change rate interval is obtained;

[0094] With the minimum deviation value as the optimization goal, the suggestion value data table is obtained under the safety range of current density and the process constraint condition of water flow speed;

[0095] The suggestion value data table is issued to the corresponding flocculation pipe for execution, and the outgoing water turbidity change rate is collected in real time;

[0096] The above steps are repeated until the outgoing water turbidity change rate collected continuously falls within the preset stable range, and the updating process is terminated.

[0097] As a preferred embodiment of the above embodiment, first, the rate of change of the current impedance value of each flocculation tube is monitored in real time, and when the passivation rate of any flocculation tube is detected to be nonlinearly rising, it means that the electrode efficiency may be reduced or excessive wear may occur, at which time the recommended value data table should be updated in a timely manner to maintain the effectiveness of the treatment process. This monitoring can be achieved by installing high-precision sensors, and the data of the sensors are processed and analyzed in real time by the central control panel to identify the trend of change and trigger parameter updating in a timely manner. Next, the real-time turbidity change rate of the current water in and out is obtained, and the deviation value between the rate and the target turbidity change rate interval is calculated. This deviation value is constantly updated by the system data acquisition and processing module, as it directly determines the adjustment range and direction that needs to be made. The deviation value provides a clear target, making the optimization strategy clear and easy to implement. On this basis, the ideal recommended value data table is developed with the optimization goal of minimizing the deviation value, within the safe range of current density and the process constraints of water flow speed. This parameter ensures that the current density does not exceed the safe operating limit of the equipment, and the water flow speed ensures the stability and sustainability of the treatment process. This can be achieved by a complex data algorithm that selects the best combination of multiple adjustable parameters to gradually reduce the deviation value. Once the recommended value data table is generated, the central control panel will issue it to the corresponding flocculation tube for execution. This process must be fast and accurate to ensure the shortest response time. After that, the outflow turbidity change rate is collected and analyzed in real time to confirm the adjustment effect. The adjustment process needs to be closely monitored, and records are kept regularly for future optimization and abnormal handling. This process is a continuous cycle until the outflow turbidity change rate collected continuously falls within the pre-defined stable range, which is defined in advance through a series of experiments and historical data analysis. Until it is confirmed that the adjustment has not produced new deviations, the update process can be terminated to ensure the stability and efficiency of the treatment.

[0098] Embodiment two;

[0099] Based on the same inventive concept as the detection method of the electrocoagulation water treatment device in the foregoing embodiment, the present application also provides an electrocoagulation water treatment device detection system, which comprises:

[0100] An impedance detection module detects the global loss of each flocculation tube according to the current treatment task, and detects the current impedance value of the electrode of each flocculation tube in real time;

[0101] An over-limit comparison module sets an upper limit of electrode passivation based on the electrode material of the flocculation tube, and records the duration of continuous over-limit when the current impedance value exceeds the upper limit of electrode passivation;

[0102] A loss division module divides the loss of the flocculation tube according to the duration of continuous over-limit;

[0103] A parameter mapping module establishes a mapping rule between the loss level and the operating parameter based on the grading result of the loss division, and generates a current density suggestion value data table and a water flow speed suggestion value data table corresponding to the loss level;

[0104] A report generation module generates a device state detection report according to the current density suggestion value data table and the water flow speed suggestion value data table.

[0105] The above adjustment system in the application can effectively realize the detection method of the electric flocculation water treatment device, and the technical effects thereof are as described in the above embodiments, which will not be repeated here.

[0106] Further, the report generation module comprises:

[0107] A distribution calculation unit calculates the distribution flow of each flocculation pipe according to the current density suggestion value data table and the water flow speed suggestion value data table;

[0108] A matrix generation unit integrates the distribution flow of each flocculation pipe to generate a cluster flow balance matrix, and the cluster flow balance matrix contains the flow influence coefficient between the flocculation pipes;

[0109] A cluster distribution unit distributes the flow distribution suggestion value of each flocculation pipe according to the cluster flow balance matrix;

[0110] A flow adjustment unit adjusts the flow distribution of each flocculation pipe based on the flow distribution suggestion value.

[0111] Similarly, the above optimization scheme of the system can also correspondingly realize the optimization effects of the method in Embodiment One, which will not be repeated here.

[0112] Although the present application has been described in connection with specific features and embodiments thereof, it will be evident to those skilled in the art that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the description and drawings are to be regarded as illustrative in nature and are not to be regarded as limiting the scope of the application. Obviously, various modifications and changes can be made to the present application by those skilled in the art without departing from the scope of the present application. Thus, it is intended that the present application cover modifications and variations of this application provided they come within the scope of the appended claims and their equivalents.

Claims

1. An electric flocculation water treatment device detection method characterized by, The method includes: Global loss detection is performed on each flocculation tube according to the current processing task, and the current impedance value of each flocculation tube electrode is obtained in real time. Based on the electrode material of the flocculation tube, an upper limit for electrode passivation is set. When the current impedance value exceeds the upper limit for electrode passivation, the duration of the continuous exceedance is recorded. The flocculation pipe is classified into loss categories based on the duration of continuous exceedance. Based on the loss classification results, a mapping rule between loss levels and operating parameters is established, and a data table of recommended current density values ​​and water flow velocity values ​​corresponding to the loss levels is generated. A device status monitoring report is generated based on the current density recommended value data table and the water flow velocity recommended value data table. Update the device status detection report, including: The rate of change of the current impedance value of each of the flocculation tubes is monitored in real time. When the rate of change of any of the flocculation tubes increases non-linearly, the current density recommendation value is updated. Obtain the real-time turbidity change rate of the current influent and effluent, and obtain the deviation value from the target turbidity change rate range; With minimizing the deviation as the optimization objective, and under the process constraints of the safe range of current density and water flow velocity, a data table of recommended current density values ​​and a data table of recommended water flow velocity values ​​are obtained. The recommended current density data table and the recommended water flow velocity data table are sent to the corresponding flocculation pipe for execution, and the rate of change of effluent turbidity is collected in real time. Repeat the above steps until the rate of change of turbidity in the effluent collected in multiple consecutive samples falls within the preset stable range, at which point the update process will terminate.

2. The method of claim 1, wherein the method further comprises: Based on the recommended value data table in the equipment status monitoring report, each of the flocculation pipes is used for cluster flow balancing, including: Based on the current density recommended value data table and the water flow velocity recommended value data table, calculate the distribution flow rate of each of the flocculation tubes; The distributed flow rates of each of the flocculation tubes are integrated to generate a cluster flow balance matrix, which includes the flow influence coefficients between the flocculation tubes. The flow influence coefficients are obtained by analyzing the operational influence of each of the flocculation tubes on each other, including flow direction, flow rate, and the degree of influence between the devices. Based on the cluster flow balance matrix, allocate recommended flow allocation values ​​for each of the flocculation tubes; The flow distribution of each of the flocculation tubes is adjusted based on the recommended flow distribution value.

3. The method of claim 2, wherein the method further comprises: A flow equation set is established based on the allocated flow rate of each of the flocculation pipes, and the flow influence coefficient between the flocculation pipes is obtained by substituting time into the equation. The cluster flow balance matrix is ​​then generated. The constraint condition of the flow equation set is that the sum of the products of the water flow velocity changes of all the flocculation pipes and their allocated flow rates is zero.

4. The method of claim 2, wherein the method further comprises: When the recommended flow rate allocation value of any of the flocculation tubes exceeds the upper limit, the flow rate of the corresponding flocculation tube is adjusted step by step according to the gradient adjustment strategy until the actual water flow velocity matches the allocated flow rate.

5. The method of claim 2, wherein the method further comprises: The device status detection report includes association rules, including: Obtain the turbidity change rate of the inlet and outlet water of each of the aforementioned flocculation pipes; When the recommended current density value increases, the decrease in effluent turbidity corresponding to the turbidity change rate is positively correlated with the increase in the recommended current density value. When the recommended water flow velocity increases, the decrease in effluent turbidity corresponding to the turbidity change rate is negatively correlated with the increase in the recommended water flow velocity.

6. The testing method for electrocoagulation water treatment equipment according to claim 1, characterized in that, When the current impedance value exceeds the upper limit of electrode passivation and the cumulative operating time exceeds the upper limit, the flocculation tube is divided into a high-loss group and the remaining flocculation tubes are divided into a low-loss group, and a corresponding loss compensation coefficient is generated for cluster flow balance.

7. The testing method for electrocoagulation water treatment equipment according to claim 5, characterized in that, Different operating conditions are distinguished based on the rate of turbidity change, including: A first load threshold is set based on historical normal operation data, and a second load threshold is set based on the maximum load that the flocculation pipe can withstand. When the rate of change of turbidity is less than or equal to the first load threshold, it is determined to be a normal load condition; When the turbidity change rate is greater than the first load threshold and less than the second load threshold, it is determined to be a transitional load condition; When the rate of change of turbidity continuously exceeds the second load threshold for a preset duration, it is determined to be an impact load condition; Wherein, the second load threshold is greater than the first load threshold.

8. A testing system for electrocoagulation water treatment equipment, characterized in that, The system employing the detection method for electrocoagulation water treatment equipment as described in claim 1 comprises: The impedance detection module performs global loss detection on each flocculation tube according to the current processing task and obtains the current impedance value of each flocculation tube electrode in real time. The out-of-limit comparison module sets an upper limit for electrode passivation based on the electrode material of the flocculation tube. When the current impedance value exceeds the upper limit of electrode passivation, the duration of continuous out-of-limit is recorded. The loss classification module classifies the loss of the flocculation pipe based on the duration of continuous exceedance. The parameter mapping module establishes mapping rules between loss levels and operating parameters based on the loss classification results, and generates a data table of recommended current density values ​​and water flow velocity values ​​corresponding to the loss levels. The report generation module generates an equipment status monitoring report based on the recommended current density data table and the recommended water flow velocity data table.

9. The detection system for electrocoagulation water treatment equipment according to claim 8, characterized in that, The report generation module includes: The distribution calculation unit calculates the distribution flow rate of each flocculation pipe based on the recommended current density value data table and the recommended water flow velocity value data table. The matrix generation unit integrates the distributed flow of each flocculation tube to generate a cluster flow balance matrix, which includes the flow influence coefficient between flocculation tubes. The cluster allocation unit allocates the recommended flow allocation values ​​for each flocculation tube according to the cluster flow balance matrix. The flow adjustment unit adjusts the flow distribution of each flocculation tube based on the recommended flow distribution value.

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