Online ion concentration monitoring equipment and method for waste acid regeneration based on Internet of Things

Abstract

The invention provides online ion concentration monitoring equipment and method for waste acid regeneration based on the Internet of Things, and relates to the technical field of ion monitoring, the equipment comprises a monitoring box, a cover plate is arranged at the upper end opening of the monitoring box, a feeding pipe for liquid supply is arranged at the center position of the cover plate in a penetrating mode, and a water drainage pipe for liquid drainage is arranged at the bottom of the monitoring box; a detection table is arranged in the center of the bottom of the monitoring box, a mounting hole penetrates through the center of the detection table, and a detection mounting column is arranged in the mounting hole in a matched mode. According to the invention, hardware and software are combined, so that the detection accuracy of the ion concentration is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ion monitoring, and in particular to an online monitoring device and method for ion concentration for waste acid regeneration based on the Internet of Things. Background Art

[0002] The production processes of industries like chemical, metallurgy, and electroplating generate large amounts of waste acid containing various metal ions and radical ions. Directly discharging this waste acid not only causes severe environmental pollution but also wastes the resources it contains. Therefore, waste acid regeneration and treatment technologies are becoming a key focus of the industry.

[0003] Currently, during the waste acid regeneration process, ion concentrations in the waste acid are mostly monitored using offline testing. This involves periodically sampling the waste acid treatment equipment and sending the samples to a laboratory for ion concentration testing using specialized analytical instruments. This approach has numerous drawbacks: First, offline testing cannot obtain real-time ion concentration data, failing to promptly reflect changes during the waste acid treatment process, hindering real-time adjustments and optimization of the waste acid regeneration process; second, offline testing requires significant manpower and time, resulting in low detection efficiency; and finally, the sampling process may lack representativeness, leading to inaccurate test results and impacting the effectiveness and quality of the waste acid regeneration process.

[0004] Although there are some online monitoring equipment, these devices often have problems such as untimely data transmission, inability to achieve remote monitoring and management, and information islands between devices, which makes it difficult to meet the needs of modern industrial production for intelligent and automated waste acid regeneration treatment processes. More importantly, when the existing online monitoring equipment detects the ion concentration of waste acid, the detection end is easily affected by the accumulation of impurities (such as metal particles, sediments, etc.) in the waste acid, and the detection accuracy is affected. As the use time increases, impurities adhere to the detection electrode or detection channel, resulting in distortion of the detection signal, making it impossible to achieve continuous and accurate ion concentration monitoring, thereby interfering with the precise control of the waste acid regeneration treatment process. Therefore, there is an urgent need for an online monitoring device and method that can monitor the ion concentration in the waste acid in real time and accurately, effectively solve the problem of impurity accumulation at the detection end, and realize remote data transmission and intelligent management. Summary of the Invention

[0005] The object of the present invention is to provide an online monitoring device and method for ion concentration of waste acid regeneration based on the Internet of Things to solve the problems in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The online ion concentration monitoring equipment for waste acid regeneration based on the Internet of Things includes a monitoring box, a cover plate is provided at the upper port of the monitoring box, a feed pipe for liquid supply is passed through the center of the cover plate, a drain pipe for liquid discharge is provided at the bottom of the monitoring box, a detection platform is provided at the center of the bottom of the monitoring box, a mounting hole is passed through the center of the detection platform, a detection mounting column is provided in the mounting hole, at least two ion concentration detection terminals are provided at the upper end of the detection mounting column, a data connector is provided at the interface position of the bottom of the detection mounting column, the data connector is electrically connected to the input end of the Internet of Things terminal through a data line, and a filter component is provided at the upper end of the detection platform to protect the ion concentration detection terminals.

[0008] On the basis of the above technical solutions, the present invention also provides the following optional technical solutions:

[0009] In an optional solution: the filter assembly includes a conical filter cover arranged at the upper end of the detection platform, and filter holes are distributed on the surface of the conical filter cover. The conical filter cover is a conical structure, and the conical filter cover is threadedly connected to the detection platform to facilitate the later disassembly of the conical filter cover. A cleaning mechanism for removing impurities on the surface of the conical filter cover is provided on the outside of the detection platform.

[0010] In an optional scheme: the cleaning mechanism includes a positioning outer ring fixed to the outside of the detection platform, a floating ring seat is provided for sliding on the outside of the detection platform below the positioning outer ring, a plurality of vertical slide rods are slidably passed through the floating ring seat, the upper end of the vertical slide rod is connected and fixed to the bottom of the positioning outer ring, the floating ring seat and the positioning outer ring are connected by a floating spring, the floating spring is sleeved on the outside of the vertical slide rod, and a water tank for storing water is provided on the outside of the floating ring seat for rotation, at least one scraper rack is fixed on the outside of the water tank, and a scraper brush is provided at one end of the scraper rack facing the conical filter cover, the scraper brush matches the scraper brush inclined surface, and a scraper brush matching the surface of the conical filter cover is provided on the lower side of the scraper brush.

[0011] In an optional solution: a limit block is fixedly provided at the lower end of the vertical slide bar, and a support wheel is rotatably provided at the outer end of the limit block, and the support wheel is used to limit the bottom of the water tank.

[0012] A method for online monitoring of ion concentration for waste acid regeneration, characterized by comprising the following steps:

[0013] S1: Data acquisition and preprocessing: The ion concentration in the waste acid is detected in real time through the ion concentration detection module, and the data acquisition and processing module performs preprocessing such as amplification, filtering, and analog-to-digital conversion on the detection signal;

[0014] S2: IoT communication transmission: Utilize at least one IoT communication technology among 5G, NB-IoT, and LoRa to transmit pre-processed ion concentration data, alarm information, and impurity accumulation detection information to the remote monitoring center in real time;

[0015] S3: Multi-technology collaborative detection and impurity prevention and control: Two detection ends are set up to use ion selective electrodes and ion chromatographs to detect ion concentrations respectively. The data acquisition and processing module compares and analyzes the two sets of detection data. When the data difference exceeds the threshold, the re-inspection procedure is started; at the same time, the impurity accumulation detection algorithm is used to analyze the detection signal fluctuation characteristics and the detection electrode impedance changes, and the impurity accumulation at the detection end is monitored in real time. If impurity accumulation is detected, the corresponding impurity cleaning program is triggered; the difference between the two sets of detection data is calculated by the formula ΔC = |C1-C2|, C1 is the ion concentration detected by the first detection end, and C2 is the ion concentration detected by the second detection end; in the impurity accumulation detection algorithm, the formula Calculate the detection electrode impedance change rate, Z current is the electrode impedance currently detected, Z normal is the impedance of the electrode when it is working normally. When ΔC>ΔC threshold (ΔC threshold is to set the difference threshold) or Z>Z threshold (Z threshold When the impedance change rate threshold is set, the corresponding operation is triggered;

[0016] S4: Intelligent data analysis and processing: The data acquisition and processing module determines whether the ion concentration is within the set normal range. If it exceeds the normal range, an alarm message is generated and stored. The historical trend analysis of the ion concentration data is performed to predict the trend of ion concentration changes. The impurity accumulation detection information is analyzed to calculate the frequency and degree of impurity accumulation. The impurity cleaning strategy and waste acid pretreatment process are optimized based on the ion concentration change trend. The historical trend analysis uses a time series prediction algorithm, such as the ARIMA model, and its prediction formula is: y t is the predicted value of ion concentration at time t, φ i and θ j is the model parameter, ∈ t is a white noise sequence; the impurity accumulation frequency f is calculated by the formula Calculate, n is the number of times impurity accumulation is detected per unit time T.

[0017] In an optional solution: the impurity cleaning procedure includes: when it is determined that the filter component at the entrance of the detection channel is clogged (at this time the liquid cannot enter the detection area, resulting in a serious drop in detection data, and it is determined that the filter component is clogged), a replacement prompt message is sent to the remote monitoring center, and the operator remotely controls the replacement; when it is detected that the ion selective electrode is greatly affected by impurities, the electrode is cleaned in combination with a purge device.

[0018] In one optional solution: when comparing and analyzing two sets of test data in S1, if the data difference is within a reasonable range, the average value is taken as the test result. The average value calculation formula is:

[0019] In an optional solution: the remote monitoring center is any one of a cloud server and an enterprise monitoring platform, and the operator remotely obtains the equipment operating status and ion concentration information through monitoring software or a mobile terminal, and remotely configures and manages the online monitoring equipment.

[0020] In an optional solution: the historical trend analysis is implemented by data statistics and prediction algorithms, and the impurity cleaning strategy includes adjusting the frequency and duration of automatic purge; wherein the automatic purge frequency adjustment formula is f new =f old ×(1+k×Z), f new is the adjusted purge frequency, f old is the purge frequency before adjustment, k is the adjustment coefficient, and Z is the rate of change of the detection electrode impedance.

[0021] In an optional solution, the ions detected by the ion concentration detection terminal include metal ions and acid ions, the metal ions include at least one of iron ions, copper ions, and zinc ions, and the acid ions include at least one of sulfate ions and nitrate ions.

[0022] By adopting the above technical solution, the present invention has the following beneficial effects:

[0023] The present invention is designed to meet existing needs and can detect the ion concentration of recycled wastewater. During the detection, large particles of impurities can be blocked to prevent the large particles from affecting the detection end, thereby improving the accuracy of ion concentration detection from the hardware perspective.

[0024] The present invention has also been optimized in terms of data processing methods. Through the Internet of Things communication technology, it can realize real-time remote transmission of ion concentration data, alarm information and impurity accumulation detection information, breaking the limitations of data transmission and facilitating operators to remotely monitor and manage equipment; the dual-detection end collaborative detection and data comparison and analysis mechanism, combined with the re-inspection procedure, greatly improves data accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0026] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0027] Figure 2 It is a schematic diagram of the lower structure of the present invention.

[0028] Figure 3 It is a schematic diagram of the internal water tank structure of the present invention.

[0029] Figure 4 It is a schematic structural diagram of the lower side of the water carrying tank of the present invention.

[0030] Figure 5 For the present invention Figure 3 Schematic diagram of the structure of A.

[0031] Figure 6 This is a processing block diagram of the detection method of the present invention.

[0032] Reference numerals: monitoring box 100 , cover plate 101 , feeding tube 102 , Internet of Things terminal 103 , data cable 104 , data connector 105 , detection mounting column 106 , drain pipe 107 , detection platform 108 , ion concentration detection terminal 109 ;

[0033] Water carrying tank 200 , conical filter cover 201 , scraper brush 202 , floating spring 203 , positioning outer ring 204 , floating ring seat 205 , vertical slide bar 206 , limit block 207 , support wheel 208 , scraper frame 209 , and rotating drainage side pipe 210 . DETAILED DESCRIPTION

[0034] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0035] The left, right, up, and down positions of the components shown in the accompanying drawings are merely one arrangement, and the specific positions are set according to specific needs.

[0036] In one embodiment, Figures 1-6As shown, an online monitoring device for ion concentration of waste acid regeneration based on the Internet of Things includes a monitoring box 100, a cover plate 101 is provided at the upper port of the monitoring box 100, a feed pipe 102 for liquid supply is passed through the center of the cover plate 101, a drain pipe 107 for draining liquid is provided at the bottom of the monitoring box 100, a detection platform 108 is provided at the center of the bottom of the monitoring box 100, a mounting hole is passed through the center of the detection platform 108, a detection mounting column 106 is provided in the mounting hole, at least two ion concentration detection terminals 109 are provided at the upper end of the detection mounting column 106, a data connector 105 is provided at the interface position at the bottom of the detection mounting column 106, the data connector 105 is electrically connected to the input end of the Internet of Things terminal 103 through a data line 104, a filter component is provided at the upper end of the detection platform 108 to protect the ion concentration detection terminal 109, and the filter component isolates impurities with larger particles to prevent impurities from covering the surface of the ion concentration detection terminal 109, thereby ensuring the accuracy of real-time detection data;

[0037] A purge device is provided on the upper end of the detection platform 108 where the concentration detection probe 109 is located, which is used to clean impurities accumulated on the surface of the concentration detection probe 109;

[0038] The filter assembly includes a conical filter cover 201 disposed at the upper end of the test platform 108. Filter holes are distributed on the surface of the conical filter cover 201. The conical filter cover 201 is a conical structure. The conical filter cover 201 is threadedly connected to the test platform 108 to facilitate the later disassembly of the conical filter cover 201. A cleaning mechanism for removing impurities from the surface of the conical filter cover 201 is provided on the outside of the test platform 108. The cleaning mechanism promptly removes attachments on the surface of the conical filter cover 201, thereby ensuring that the test liquid can smoothly enter the ion concentration detection terminal 109 to complete the test of the test liquid.

[0039] The cleaning mechanism includes a positioning outer ring 204 fixed to the outside of the detection platform 108, and a floating ring seat 205 is slidingly provided on the outside of the detection platform 108 below the positioning outer ring 204, and a plurality of vertical slide bars 206 are slidingly passed through the floating ring seat 205, and the upper ends of the vertical slide bars 206 are connected and fixed to the bottom of the positioning outer ring 204, and the floating ring seat 205 is connected to the positioning outer ring 204 by a floating spring 203, and the floating spring 203 is sleeved on the outside of the vertical slide bar 206, and a water tank 200 for storing water is rotated on the outside of the floating ring seat 205, and at least one scraper frame 209 is fixedly provided on the outside of the water tank 200, and a scraper brush 202 is provided on one end of the scraper frame 209 facing the conical filter cover 201, and the scraper brush 202 matches the inclined surface of the scraper brush 202, The scraper brush 202 is provided on the lower side thereof with a scraper brush that matches the surface of the conical filter cover 201. In the initial state, the scraper brush 202 here does not contact the conical filter cover 201. Only when the liquid stored in the water tank 200 reaches a set value, the scraper brush 202 and the conical filter cover 201 will contact. A plurality of rotating drainage side pipes 210 are distributed in an array on the outer side of the water tank 200. The plurality of rotating drainage side pipes 210 are arranged at an acute angle to the cross section of the water tank 200. In this way, when the liquid in the water tank 200 flows out along the rotating drainage side pipes 210, the outflowing liquid generates a reaction force, thereby forming a rotational torque that drives the water tank 200 to rotate. When the water tank 200 rotates, the scraper frame 209 drives the scraper brush 202 to rotate, thereby cleaning the surface of the conical filter cover 201.

[0040] A limit block 207 is fixedly provided at the lower end of the vertical slide bar 206, and a support wheel 208 is rotatably provided at the outer end of the limit block 207. The support wheel 208 is used to limit the bottom of the water tank 200. When the water tank 200 descends to the end, the support wheel 208 contacts the bottom of the water tank 200. At this time, the water tank 200 will not move further downward, otherwise the scraping brush 202 will interfere with the conical filter cover 201. The support wheel 208 here supports the water tank 200 and assists the rotation of the water tank 200.

[0041] Combined with specific industrial scenarios, the practical application and operation process of the online monitoring method of ion concentration for waste acid regeneration are explained in detail.

[0042] 1. Application Scenarios and Device Configuration

[0043] For example, in the waste acid regeneration system of a large electroplating plant, online monitoring equipment was installed at the outlet pipe of the waste acid storage tank. This equipment features two detection terminals. The first terminal uses an ion-selective electrode to detect copper and zinc ion concentrations, with a detection range of 0-1000 mg / L and an accuracy of ±1%. The second terminal uses an ion chromatograph to simultaneously measure copper, zinc, nickel, and nitrate ion concentrations. The detection range varies depending on the ion type, with an accuracy of ±0.5%.

[0044] The data acquisition and processing module utilizes an ARM-based embedded processor with a 2GHz clock speed, 16 analog signal acquisition channels, and a sampling rate of 10 times per second. This enables rapid and accurate amplification, filtering, and analog-to-digital conversion of detection signals. The IoT communication module utilizes an NB-IoT communication module with a communication range of up to 3 kilometers, meeting the data transmission needs within the electroplating plant. Its low power consumption makes it suitable for long-term online operation. The remote monitoring center, housed within the plant's monitoring room, utilizes an enterprise monitoring platform equipped with high-performance servers and monitoring terminals, enabling operators to easily view data and manage equipment in real time.

[0045] 2. Data Collection and Preprocessing

[0046] The ion-selective electrodes and ion chromatograph in the ion concentration detection module continuously detect the ion concentration of the waste acid in the outlet pipe of the waste acid storage tank. The ion-selective electrodes convert the detected ion concentration signal into a voltage signal output, and the ion chromatograph outputs the test results in the form of a digital signal. The data acquisition and processing module collects the signals output by the two detection terminals at a sampling frequency of 10 times per second. The collected analog signal first passes through a low-pass filter to remove high-frequency noise, and then is converted into a digital signal by a 16-bit analog-to-digital converter. Subsequently, the digital signal is normalized and converted into a standard concentration value for subsequent analysis.

[0047] Third, IoT communication transmits pre-processed ion concentration data, alarm information generated during equipment operation (such as excessive ion concentration alarms and equipment failure alarms), and impurity accumulation detection information. The IoT communication module transmits this data in real time via the NB-IoT network to the enterprise monitoring platform at the remote monitoring center. During data transmission, TCP / IP is used for data encapsulation and transmission, and the AES-128 encryption algorithm is used to encrypt the data to ensure the security and integrity of the data transmission. After receiving the data, the enterprise monitoring platform stores it in a database and displays it in real time on the monitoring terminal interface for easy viewing by operators.

[0048] 4. Multi-Technology Collaborative Detection and Impurity Prevention

[0049] (1) Data comparison and re-inspection The data collection and processing module compares and analyzes the copper ion and zinc ion concentration data collected by the two detection terminals. For example, at a certain moment, the copper ion concentration C1 detected by the first detection terminal is 200 mg / L, and the copper ion concentration C2 detected by the second detection terminal is 210 mg / L. The difference between the two sets of data is calculated by the formula ΔC = |C1-C2| = |200-210| = 10 mg / L. The data difference threshold ΔC of the copper ion concentration is pre-set. threshold =15mg / L, since ΔC = 10mg / L < ΔC threshold , then take the average value As the test result of copper ion concentration at that moment. If in a certain test, the calculated ΔC>ΔC threshold , the re-test procedure is immediately initiated. The data acquisition and processing module controls the two detection terminals to re-test and compare and analyze the data again. If the data difference still exceeds the threshold after multiple tests, an abnormal prompt message is sent to the remote monitoring center to remind the operator to check whether there is any fault in the detection equipment.

[0050] (2) Detection and cleaning of impurity accumulation

[0051] The data acquisition and processing module uses the impurity accumulation detection algorithm to monitor the impurity accumulation at the detection end in real time. Taking the ion selective electrode as an example, the electrode impedance Z normal =1000Ω, the electrode impedance Z detected at a certain moment current =1200Ω, through the formula Calculate the electrode impedance change rate. Preset the electrode impedance change rate threshold Z threshold =0.15, since Z=0.2>Z threshold , judging that the ion-selective electrode is significantly affected by impurities, triggering the impurity cleaning alarm program. The data acquisition and processing module sends a replacement prompt message to the remote monitoring center. The operator remotely controls the filter replacement mechanism through the monitoring platform to automatically replace the filter with a new one.

[0052] 5. Intelligent Data Analysis and Processing

[0053] (1) Ion Concentration Judgment and Alarm The data acquisition and processing module compares the detected ion concentration with the pre-set normal range. For example, the normal range of copper ion concentration is set to 50-300 mg / L. When the detected copper ion concentration exceeds this range, an alarm message is generated and the alarm time, alarm ion type, alarm concentration value and other information are stored in the database. At the same time, an audible and visual alarm is issued on the monitoring terminal of the remote monitoring center to remind the operator to take timely action.

[0054] (II) Historical trend analysis The data collection and processing module uses the ARIMA model to perform historical trend analysis on ion concentration data. Based on the copper ion concentration data of the past week, the ARIMA model parameters p=1, q=1 are determined, and the formula Predict the copper ion concentration trend over the next 24 hours. Display the prediction results as a line graph on the monitoring terminal of the remote monitoring center, providing a reference for operators to adjust the spent acid regeneration process.

[0055] (III) Impurity accumulation analysis and strategy optimization The data acquisition and processing module analyzes the impurity accumulation detection information and counts the number of impurity accumulations n per unit time (such as one day). For example, if the ion selective electrode impurity accumulation is detected 3 times in one day, the time period T = 24h, and the formula Calculate the impurity accumulation frequency.

[0056] According to the impurity accumulation frequency and ion concentration change trend, the impurity cleaning strategy is optimized. If the impurity accumulation frequency is high and the ion concentration fluctuates greatly, the impurity cleaning strategy is optimized according to the formula f new =f old ×(1+k×Z)(assuming k=0.5) adjust the automatic purge frequency. Original purge frequency The current electrode impedance change rate Z = 0.2, then the adjusted purge frequency At the same time, it is recommended that operators optimize the waste acid pretreatment process, increase the dosage of flocculants, and reduce suspended impurities in the waste acid.

[0057] Through the above specific implementation methods, the online monitoring method of ion concentration for waste acid regeneration can be effectively operated in actual industrial scenarios, realizing accurate monitoring of waste acid ion concentration, impurity prevention and control, and intelligent management, thereby improving the efficiency and quality of waste acid regeneration treatment.

[0058] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An online ion concentration monitoring device for waste acid regeneration based on the Internet of Things, comprising a monitoring box (100), wherein an upper port of the monitoring box (100) is provided with a cover plate (101), and a feed pipe (102) for liquid supply is provided at the center of the cover plate (101), characterized in that: The bottom of the monitoring box (100) is provided with a drain pipe (107) for draining liquid, and a detection platform (108) is provided at the center position of the bottom of the monitoring box (100). The center position of the detection platform (108) is penetrated by a mounting hole, and a detection mounting column (106) is provided in the mounting hole. The upper end of the detection mounting column (106) is provided with at least two ion concentration detection terminals (109). The bottom interface position of the detection mounting column (106) is provided with a data connector (105), and the data connector (105) is electrically connected to the input end of the Internet of Things terminal (103) through a data line (104). The upper end of the detection platform (108) is provided with a filter component for protecting the ion concentration detection terminal (109), and the upper end of the detection platform (108) where the concentration detection probe (109) is located is provided with a purge device.

2. The online monitoring device for ion concentration of waste acid regeneration based on the Internet of Things according to claim 1, characterized in that: The filter assembly comprises a conical filter cover (201) arranged at the upper end of the detection platform (108), filter holes are distributed on the surface of the conical filter cover (201), the conical filter cover (201) is a conical structure, the conical filter cover (201) and the detection platform (108) are connected by a thread, which facilitates the later disassembly of the conical filter cover (201), and a cleaning mechanism for removing impurities on the surface of the conical filter cover (201) is provided on the outside of the detection platform (108).

3. The online monitoring device for ion concentration of waste acid regeneration based on the Internet of Things according to claim 2, characterized in that: The cleaning mechanism includes a positioning outer ring (204) fixed on the outside of the detection platform (108), a floating ring seat (205) is slidably provided on the outside of the detection platform (108) below the positioning outer ring (204), and a plurality of vertical slide bars (206) are slidably passed through the floating ring seat (205), the upper ends of the vertical slide bars (206) are connected and fixed to the bottom of the positioning outer ring (204), the floating ring seat (205) and the positioning outer ring (204) are connected by a floating spring (203), and the floating ring seat (205) and the positioning outer ring (204) are connected by a floating spring (203). A spring (203) is sleeved on the outside of a vertical slide rod (206); a water tank (200) for storing water is rotatably provided on the outside of a floating ring seat (205); at least one scraper frame (209) is fixedly provided on the outside of the water tank (200); a scraper brush (202) is provided at one end of the scraper frame (209) facing the conical filter cover (201); the scraper brush (202) matches the inclined surface of the scraper brush (202); and a scraper brush matching the surface of the conical filter cover (201) is provided on the lower side of the scraper brush (202).

4. The online monitoring device for ion concentration of waste acid regeneration based on the Internet of Things according to claim 3, characterized in that: A limit block (207) is fixedly provided at the lower end of the vertical slide bar (206), and a support wheel (208) is rotatably provided at the outer end of the limit block (207), and the support wheel (208) is used to limit the bottom of the water tank (200).

5. A method for online monitoring of ion concentration for waste acid regeneration, characterized in that: The following steps are involved: S1: Data acquisition and preprocessing: The ion concentration in the waste acid is detected in real time through the ion concentration detection module, and the data acquisition and processing module amplifies, filters, and performs analog-to-digital conversion preprocessing on the detection signal; S2: IoT communication transmission: Utilize at least one IoT communication technology among 5G, NB-IoT, and LoRa to transmit pre-processed ion concentration data, alarm information, and impurity accumulation detection information to the remote monitoring center in real time; S3: Multi-technology collaborative detection and impurity prevention and control: Two detection terminals are set up to respectively use ion-selective electrodes and ion chromatographs to detect ion concentration. The data acquisition and processing module compares and analyzes the two sets of detection data. When the data difference exceeds the threshold, the re-inspection procedure is initiated. At the same time, the impurity accumulation detection algorithm is used to analyze the detection signal fluctuation characteristics and the change of the detection electrode impedance, and the impurity accumulation at the detection terminal is monitored in real time. If impurity accumulation is detected, the corresponding impurity cleaning procedure is triggered. The difference between the two sets of detection data is calculated by the formula ΔC = |C1-C2|, where C1 is the ion concentration detected by the first detection end and C2 is the ion concentration detected by the second detection end. In the impurity accumulation detection algorithm, the formula Calculate the detection electrode impedance change rate, Z current is the electrode impedance currently detected, Z normal is the impedance of the electrode when it is working normally. When ΔC>ΔC threshold , or Z>Z threshold , triggering the corresponding operation; ΔC threshold To set the difference threshold, Z threshold To set the impedance change rate threshold; S4: Intelligent data analysis and processing: The data acquisition and processing module determines whether the ion concentration is within the set normal range. If it exceeds the normal range, an alarm message is generated and stored. The module also performs historical trend analysis on the ion concentration data to predict the trend of ion concentration changes. The module also analyzes the impurity accumulation detection information, calculates the frequency and degree of impurity accumulation, and optimizes the impurity cleaning strategy and waste acid pretreatment process based on the ion concentration change trend. Among them, historical trend analysis uses time series prediction algorithms, such as the ARIMA model, and its prediction formula is y t is the predicted value of ion concentration at time t, φ i and θ j is the model parameter, ∈ t is a white noise sequence; the impurity accumulation frequency f is calculated by the formula Calculate, n is the number of times impurity accumulation is detected per unit time T.

6. The method for online monitoring of ion concentration according to claim 5, characterized in that: The impurity cleaning procedure includes: when it is determined that the filter component at the entrance of the detection channel is blocked, a replacement prompt message is sent to the remote monitoring center, and the operator remotely controls the replacement; when it is detected that the ion-selective electrode is greatly affected by impurities, the electrode is cleaned.

7. The method for online monitoring of ion concentration according to claim 6, characterized in that: When comparing and analyzing the two sets of test data in S1, if the data difference is within a reasonable range, the average value is taken as the test result. The average value calculation formula is:

8. The method for online monitoring of ion concentration according to claim 5, wherein: The remote monitoring center is any one of a cloud server and an enterprise monitoring platform. Operators remotely obtain equipment operating status and ion concentration information through monitoring software or mobile terminals, and remotely configure and manage online monitoring equipment.

9. The method for online monitoring of ion concentration according to claim 5, characterized in that: The historical trend analysis is achieved through data statistics and prediction algorithms. The impurity cleaning strategy includes adjusting the frequency and duration of automatic purge. The automatic purge frequency adjustment formula is f new =f old ×(1+k×Z), f new is the adjusted purge frequency, f old is the purge frequency before adjustment, k is the adjustment coefficient, and Z is the rate of change of the detection electrode impedance.

Images