Method and system for detecting electric flocculation water treatment equipment

Abstract

The invention relates to the technical field of measurement data processing, in particular to an electric flocculation water treatment equipment detection method and system, and the method comprises the steps: carrying out the global loss detection of each flocculation tube according to a current treatment task, and obtaining the current impedance value of each flocculation tube electrode; setting an electrode passivation upper limit based on an electrode material of the flocculation tube, and when the current impedance value exceeds the upper limit, recording the duration of exceeding the standard; carrying out loss division on the flocculation tube according to the continuous standard exceeding duration; based on a grading result, establishing a mapping rule of loss grades and operation parameters, and generating a current density suggestion value data table and a water flow speed suggestion value data table corresponding to the loss grades; and outputting an equipment state detection report containing the current density suggestion value data table and the water flow speed suggestion value data table. By means of the method, the problems of how to achieve quantitative evaluation and visual expression of the electrode loss state of the electric flocculation equipment and process instability caused by electrode passivation in the cooperative unbalance process of multiple flocculation tube clusters are effectively solved.

Description

TECHNICAL FIELD

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

[0002] The electrocoagulation technology is a kind of efficient water treatment process, which generates metal cations by applying current to metal anode, and then hydrolyzes to form flocculants to adsorb colloidal particles, heavy metals and organic matters 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; the current impedance value is a key physical quantity representing electrode loss, and when the impedance exceeds the upper limit of electrode passivation determined by 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, and the operator detects regularly only by subjective experience to estimate the electrode loss degree, and no quantitative correlation between the duration of continuous over-standard current impedance and the loss state is established, resulting in that the loss evaluation is seriously dependent on individual experience, and the data misjudgment rate is high; and 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 no standardized data carrier to record the parameter adjustment basis, resulting in that the decision logic cannot be traced back during fault diagnosis. The above defects jointly result in that the electrode loss degree cannot be quantitatively evaluated, the parameter adjustment suggestion has no standardized expression carrier, and the measurement function and the control function are fuzzy.

[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 any form of suggestion that this information constitutes prior art. SUMMARY

[0005] The present application provides an electrocoagulation 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 solution adopted by the present application is: An electrocoagulation water treatment equipment detection method, the method comprising: conducting global loss detection on each flocculation pipe according to the current processing task, and detecting and obtaining the current impedance value of the electrode of each flocculation pipe in real time; setting an electrode passivation upper limit based on the electrode material of the flocculation pipe, and recording the duration of continuous over-standard when the current impedance value exceeds the electrode passivation upper limit; dividing the loss of the flocculation pipe according to the duration of continuous over-standard; Based on the loss classification results, a mapping rule between loss levels and operating parameters is established to generate a data table of recommended current density values ​​and a data table of recommended water flow velocity values ​​corresponding to the loss levels; An equipment status detection report is generated according to the current density recommended value data table and the water flow velocity recommended value data table.

[0007] Furthermore, each of the flocculation tubes is used for cluster flow balancing based on the recommended value data table in the equipment status detection report, including: Calculating the distribution flow of each flocculation tube according to the current density recommended value data table and the water flow velocity recommended value data table; Integrating the distributed flow rates of the flocculation tubes to generate a cluster flow balance matrix, wherein the cluster flow balance matrix includes flow influence coefficients between the flocculation tubes; allocating a recommended flow distribution value to each of the flocculation tubes according to the cluster flow balance matrix; The flow distribution of each of the flocculation tubes is adjusted based on the flow distribution recommended value.

[0008] Furthermore, a flow equation group is established based on the distributed flow of each flocculation tube and time is substituted into the flow influence coefficient between the flocculation tubes to generate the cluster flow balance matrix. The constraint condition of the flow equation group is that the sum of the product of the change in water flow velocity of all the flocculation tubes and their distributed flow is zero.

[0009] Furthermore, when the flow distribution recommended value of any of the flocculation tubes exceeds an upper limit, the flow of the corresponding flocculation tube is adjusted step by step according to a gradient adjustment strategy until the actual water flow rate matches the distributed flow rate.

[0010] Furthermore, the device status detection report includes association rules, including: Obtaining the turbidity change rate of the water inlet and outlet of each flocculation tube; When the recommended current density value increases, the reduction in outlet turbidity corresponding to the turbidity change rate forms a positive correlation with the increase in the recommended current density value; When the recommended water flow velocity value increases, the magnitude of the reduction in the outlet turbidity corresponding to the turbidity change rate forms a negative correlation with the increase in the recommended water flow velocity value.

[0011] Furthermore, when the current impedance value exceeds the electrode passivation upper limit and the cumulative operating time exceeds the upper limit, the flocculation tubes are divided into a high-loss group, and the remaining flocculation tubes are divided into a low-loss group, and corresponding loss compensation coefficients are generated for cluster flow balance.

[0012] Furthermore, different operating conditions are distinguished based on the turbidity change rate, including: a first load threshold is set based on historical normal operation data, and a second load threshold is set based on the maximum tolerable load of the flocculation pipe; When the turbidity change rate 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 turbidity change rate continues to exceed the second load threshold for a preset length of time, it is determined to be a shock load condition; Wherein, the second load threshold is greater than the first load threshold.

[0013] Further, the device state detection report is updated, including: 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; 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; With the optimization goal of minimizing the deviation value, obtain each recommendation value data table under the safety range of current density and the process constraint condition of water flow speed; 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; 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.

[0014] An electrocoagulation water treatment device detection system, the system comprising: An impedance detection module, which detects the global loss of each flocculation pipe according to the current processing task, and detects the current impedance value of each flocculation pipe electrode in real time; An over-standard comparison module, which sets an electrode passivation upper limit based on the electrode material of the flocculation pipe, and records the duration of continuous over-standard when the current impedance value exceeds the electrode passivation upper limit; A loss division module, which divides the loss of the flocculation pipe according to the duration of continuous over-standard; A parameter mapping module, which establishes a mapping rule between loss level and operating parameters based on the loss division level result, and generates a current density recommendation value data table and a water flow speed recommendation value data table corresponding to the loss level; A report generation module, which generates a device state detection report according to the current density recommendation value data table and the water flow speed recommendation value data table.

[0015] Further, the report generation module comprises: The distribution calculation unit calculates the distribution flow of each flocculation tube according to the current density recommended value data table and the water flow velocity recommended value data table; A matrix generation unit integrates the distribution flow of each flocculation tube to generate a cluster flow balance matrix, which includes the flow influence coefficients between the flocculation tubes; The cluster allocation unit allocates the recommended flow distribution value to 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 flow distribution recommended value.

[0016] The technical solution of the present invention can achieve the following technical effects: It effectively solves the problem of how to achieve quantitative evaluation and visual expression of the electrode loss status of electric flocculation equipment, as well as the problem of process instability caused by electrode passivation during the coordinated imbalance of multiple flocculation tube clusters.

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a flow chart of the detection method of the electro-flocculation water treatment equipment; Figure 2 A flow chart for obtaining flow distribution; Figure 3 Schematic diagram of the process for loss division; Figure 4 Flowchart for updating the recommended value data table. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0021] 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 herein is for 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.

[0022] Embodiment one; As Figure 1 The application provides an electroflocculation water treatment equipment detection method, which comprises the following steps: 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; Based on the electrode material of the flocculation tube, the upper limit of electrode passivation is set, and when the current impedance value exceeds the upper limit of electrode passivation, the duration of continuous overstandard is recorded; According to the duration of continuous overstandard, the loss of the flocculation tube is divided; Based on the grade result of the loss division, a mapping rule of the loss grade and the operation parameter is established, and a current density suggestion value data table and a water flow speed suggestion value data table corresponding to the loss grade are generated; According to the current density suggestion value data table and the water flow speed suggestion value data table, an equipment state detection report is generated.

[0023] 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, which 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.

[0024] 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 coordination imbalance, is effectively solved.

[0025] 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: 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; 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; According to the cluster flow balance matrix, the flow distribution suggestion value of each flocculation pipe is distributed; Based on the flow distribution suggestion value, adjust the flow distribution of each flocculation pipe.

[0026] 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.

[0027] Further, the flow equation set is established according to 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.

[0028] As a preferred embodiment of the above, first, based on the distributed flow of each flocculation tube, a flow equation group is established. The flow equation group reflects the flow distribution of each flocculation tube and the relationship between them. The uniqueness of each equation is that it integrates many parameters in the electroflocculation process, such as current density changes, water flow velocity changes, and over- or under-reaction under different working conditions. By setting up a central data integration module to collect and process these flow information in real time, it is ensured that the equation group can be accurately formed; then, the time variable is substituted to dynamically reveal the real-time status of the flow equation group. The introduction of the time variable is intended to record and analyze the trend and impact of flow changes over time, so that the equation group is not just a static mathematical expression, but a dynamic system reflecting the relationship between flocculation tubes. Through this dynamic analysis, any unstable or abnormal changes in the flocculation process can be captured, thereby providing a basis for adjustment strategies; in order to generate To form a cluster flow balance matrix, an accurate flow influence coefficient must be obtained. The flow influence coefficient reflects the mutual influence of flows between different flocculation tubes. The calculation of the flow influence coefficient needs to be based on the solution of the flow equation group and the flow velocity and flow change data of each flocculation tube at different time points. This step can be calculated through a specially designed algorithm to ensure that it is consistent with the experimental results and has guidance for the generation of the flow balance matrix; the sum of the product of the change in water flow velocity and the distributed flow of all flocculation tubes in the flow equation group constraints is zero, which is a standard constraint to ensure flow balance. The flow velocity changes of each flocculation tube are automatically monitored through the central control panel to ensure that any individual tube velocity and flow changes will not destroy the flow balance of the entire system. In addition, through real-time monitoring software, the status of each flocculation tube can be displayed on the central control panel, so that adjustments can be made at any time to meet the constraints.

[0029] Furthermore, when the recommended flow distribution value of any flocculation tube exceeds the upper limit, the flow of the corresponding flocculation tube is adjusted step by step according to the gradient adjustment strategy until the actual water flow rate matches the distributed flow rate.

[0030] 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 the 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.

[0031] Further, the device state detection report contains association rules, including: Obtain the turbidity change rate of the water in and out of each flocculation pipe; 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; 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.

[0032] 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.

[0033] 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.

[0034] 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 evaluating the wear condition, the accumulated working time is another key indicator, especially when the 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 algorithms 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 continue to track the effect of the adjustment to correct in time and ensure the effectiveness and adaptability of the compensation measures.

[0035] Further, different working conditions are distinguished based on the turbidity change rate, including: 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; 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; 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; When the turbidity change rate continuously exceeds the second load threshold for a preset time, it is determined to be an impact load working condition; Wherein, the second load threshold is greater than the first load threshold.

[0036] 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 to be a transition load working condition, in which case, the flocculation process may need to be partially adjusted, such as appropriately increasing the current density to improve processing efficiency; if the turbidity change rate continues to exceed the second load threshold and reaches a preset time length, it is automatically determined to be an impact load working condition, in which 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.

[0037] Further, as shown in Figure 4 the update device state detection report includes: 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 suggestion value is updated; 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; With the optimization goal of minimizing the deviation value, obtain each suggestion value data table under the safety range of current density and the process constraint condition of water flow speed; The suggestion value data table is issued to the corresponding flocculation pipe for execution, and the outflow turbidity change rate is collected in real time; Repeat the above steps until the outflow turbidity change rate collected continuously falls within the preset stable range, and terminate the update process.

[0038] As a preferred embodiment of the above, first, the current impedance value change rate of each flocculation tube is monitored in real time. When it is detected that the passivation change rate of any flocculation tube increases nonlinearly, it means that the electrode efficiency may decrease or excessive loss may occur. At this time, the recommended value data table should be updated in time to maintain the effectiveness of the treatment process. This monitoring can be achieved by installing high-precision sensors. The sensor data is processed and analyzed in real time by the central control panel, so as to timely identify the change trend and trigger the parameter update; then, the real-time turbidity change rate of the current inlet and outlet water is obtained, and the deviation value between the rate and the target turbidity change rate range is calculated. The deviation value is continuously updated by the data acquisition and processing module of the whole system, because it directly determines the adjustment range and direction to be made. The deviation value provides a clear target, making the optimization strategy clear and easy to implement; on this basis, the optimization goal is to minimize the deviation value, and within the safe range of current density and the process of water flow velocity, the deviation value is continuously updated. A table of ideal recommended values ​​is developed under specific constraints. These parameters must ensure that the current density does not exceed the equipment's safe operating limits, while the water flow rate must ensure the stability and sustainability of the treatment process. This can be achieved through a complex data algorithm that selects the optimal combination from multiple adjustable parameters to gradually reduce deviations. Once the recommended value table is generated, the central control panel will transmit it to the corresponding flocculation tubes for execution. This process must be fast and accurate to ensure the shortest response time. Subsequently, the effluent turbidity change rate is collected in real time and analyzed to confirm the effectiveness of the adjustments. The adjustment process requires close monitoring and regular recording to facilitate future optimization and exception handling. This process is a continuous cycle until the effluent turbidity change rate collected multiple times falls within the preset stability range. This preset range must be defined in advance and derived through a series of experiments and historical data analysis. The update process can only be terminated after it is confirmed that the adjustments have not introduced new deviations, ensuring treatment stability and efficiency.

[0039] Embodiment 2: Based on the same inventive concept as the electric flocculation water treatment equipment detection method in the aforementioned embodiment, the present invention also provides an electric flocculation water treatment equipment detection system, which includes: 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 over-standard comparison module sets the electrode passivation upper limit based on the electrode material of the flocculation tube. When the current impedance value exceeds the electrode passivation upper limit, the duration of the over-standard is recorded. The loss classification module divides the loss of flocculation tubes according to the duration of continuous exceeding the standard; The parameter mapping module establishes the 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 a device state detection report according to the current density suggestion data table and the water flow speed suggestion data table.

[0040] The adjustment system in the present application can effectively realize the electric flocculation water treatment device detection method, and the technical effects are as described in the above embodiments, which will not be repeated here.

[0041] Further, the report generation module comprises: The distribution calculation unit calculates the distribution flow of each flocculation pipe according to the current density suggestion data table and the water flow speed suggestion data table; 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; The cluster distribution unit distributes the flow distribution suggestion value of each flocculation pipe according to the cluster flow balance matrix; The flow adjustment unit adjusts the flow distribution of each flocculation pipe based on the flow distribution suggestion value.

[0042] Similarly, the above optimization scheme of the system can also correspondingly realize the optimization effect of the method in Embodiment 1, which will not be repeated here.

[0043] Although the present application is described in conjunction with specific features and embodiments thereof, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of the present application. Accordingly, the present specification and drawings are merely illustrative of the exemplary embodiments of the present application, and any and all modifications, variations, combinations or equivalents that fall within the scope of the present application are intended to be embraced by the appended claims. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. A method for detecting an electrocoagulation water treatment device, characterized in that: The method comprises: Performing global loss detection on each flocculation tube according to the current processing task, and obtaining the current impedance value of each flocculation tube electrode in real time; An upper limit of electrode passivation is set based on the electrode material of the flocculation tube, and when the current impedance value exceeds the upper limit of electrode passivation, the duration of the exceeding limit is recorded; Classifying the loss of the flocculation tube according to the duration of the continuous exceeding of the standard; Based on the loss classification results, a mapping rule between loss levels and operating parameters is established to generate a data table of recommended current density values ​​and a data table of recommended water flow velocity values ​​corresponding to the loss levels; An equipment status detection report is generated according to the current density recommended value data table and the water flow velocity recommended value data table.

2. The detection method for electric flocculation water treatment equipment according to claim 1, characterized in that: Based on the recommended value data table in the equipment status detection report, each flocculation tube is used for cluster flow balance, including: Calculating the distribution flow of each flocculation tube according to the current density recommended value data table and the water flow velocity recommended value data table; Integrating the distributed flow rates of the flocculation tubes to generate a cluster flow balance matrix, wherein the cluster flow balance matrix includes flow influence coefficients between the flocculation tubes; allocating a recommended flow distribution value to each of the flocculation tubes according to the cluster flow balance matrix; The flow distribution of each of the flocculation tubes is adjusted based on the flow distribution recommended value.

3. The detection method of electric flocculation water treatment equipment according to claim 2, characterized in that: A flow equation group is established based on the distributed flow of each flocculation tube and time is substituted into the flow influence coefficient between the flocculation tubes to generate the cluster flow balance matrix. The constraint condition of the flow equation group is that the sum of the product of the change in water flow velocity of all the flocculation tubes and their distributed flow is zero.

4. The method for detecting electric flocculation water treatment equipment according to claim 2, characterized in that: When the flow distribution recommended value of any of the flocculation tubes exceeds an upper limit, the flow of the corresponding flocculation tube is adjusted step by step according to a gradient adjustment strategy until the actual water flow rate matches the distributed flow rate.

5. The method for detecting electric flocculation water treatment equipment according to claim 2, characterized in that: The device status detection report contains association rules, including: Obtaining the turbidity change rate of the water inlet and outlet of each flocculation tube; When the recommended current density value increases, the reduction in outlet turbidity corresponding to the turbidity change rate forms a positive correlation with the increase in the recommended current density value; When the recommended water flow velocity value increases, the magnitude of the reduction in the outlet turbidity corresponding to the turbidity change rate forms a negative correlation with the increase in the recommended water flow velocity value.

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

7. The method for detecting electric flocculation water treatment equipment according to claim 5, characterized in that: Different operating conditions are distinguished based on the rate of turbidity change, including: Setting a first load threshold based on historical normal operating data, and setting a second load threshold based on the maximum tolerable load of the flocculation tube; When the turbidity change rate 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 transition load condition; When the turbidity change rate continues to exceed the second load threshold for a preset time, it is determined to be an impact load condition; The second load threshold is greater than the first load threshold.

8. The method for detecting electric flocculation water treatment equipment according to claim 1, characterized in that: Update the device status detection report, including: monitoring the change rate of the current impedance value of each flocculation tube in real time, and updating the recommended current density value when the change rate of any flocculation tube increases nonlinearly; Obtain the real-time turbidity change rate of the current inlet and outlet water, and obtain the deviation value from the target turbidity change rate range; Taking minimizing the deviation value as the optimization goal, a data table of recommended values ​​is obtained within the process constraints of the current density safety range and the water flow rate; Send the recommended value data table to the corresponding flocculation tube for execution, and collect the turbidity change rate of the effluent in real time; Repeat the above steps until the effluent turbidity change rate collected multiple times falls within the preset stable range, and terminate the update process.

9. The detection system of electric flocculation water treatment equipment is characterized by: The system 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 over-standard comparison module sets the electrode passivation upper limit based on the electrode material of the flocculation tube. When the current impedance value exceeds the electrode passivation upper limit, the duration of the over-standard is recorded. The loss classification module divides the loss of flocculation tubes according to the duration of continuous exceeding the standard; The parameter mapping module establishes the 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 detection report based on the current density recommended value data table and the water flow velocity recommended value data table.

10. The electro-flocculation water treatment equipment detection system according to claim 9, characterized in that: The report generation module includes: The distribution calculation unit calculates the distribution flow of each flocculation tube according to the current density recommended value data table and the water flow velocity recommended value data table; A matrix generation unit integrates the distribution flow of each flocculation tube to generate a cluster flow balance matrix, which includes the flow influence coefficients between the flocculation tubes; The cluster allocation unit allocates the recommended flow distribution value to 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 flow distribution recommended value.

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