Method, system and device for automatically measuring hardness of water

Abstract

The invention relates to the technical field of water hardness measurement, in particular to an automatic measurement method, system and device for water hardness, and the method comprises the steps that color data of each water sample at each moment are obtained through an intelligent sensor, and the color data correspond to color components of all color channels in an RGB space; obtaining a titration end point moment of each water sample; determining the titration end point difference degree of each water sample; determining the trueness of a titration end point of each water sample; determining the hardness measurement accuracy of each water sample based on the titration end point difference degree and the titration end point trueness; and based on the hardness measurement accuracy of all the water samples, obtaining the water samples reaching the standard, and measuring the water hardness. The reliability and the accuracy of water hardness measurement are improved.

Description

Technical Field

[0001] This application relates to the technical field of water quality hardness measurement, and particularly to an automatic measurement method, system and device for water quality hardness. Background Art

[0002] Water quality hardness testing is extremely crucial in both daily life and the field of medical dialysis. In daily life, it ensures the safety of drinking water, prevents health problems such as gastrointestinal diseases caused by high-hardness water, guarantees the water quality for industries such as food processing, and avoids scale from affecting the lifespan of household appliances, thereby improving the quality of life and reducing usage costs. In the field of medical dialysis, it is related to the life safety of patients, can avoid acute complications such as hard water syndrome, reduce the risk of chronic complications, protect dialysis equipment from scale damage, ensure the quality of dialysis fluid, and improve the dialysis effect.

[0003] In the process of automatically measuring water quality hardness by the EDTA complexometric titration method, through the color change of the water sample and in combination with the total volume of the EDTA reagent titration, the total hardness of the water sample can be measured. However, during the measurement process, insufficient oscillation after titration will cause the end point to appear prematurely. Secondly, since the target water quality to be measured is unknown, it is very likely that due to the presence of tiny particulate calcium and magnesium salts in the water during the measurement process, the titration end point will be inaccurate, which will in turn cause deviations in the measurement results, and ultimately lead to low accuracy of the measurement data of the automatic measurement device. Summary of the Invention

[0004] In order to solve the above technical problems, an automatic measurement method, system and device for water quality hardness are provided to solve the existing problems.

[0005] The solution of this application to solve the technical problems is to provide an automatic measurement method, system and device for water quality hardness, including the following steps: In the first aspect, an embodiment of this application provides an automatic measurement method for water quality hardness, and the method includes the following steps: Through an intelligent sensor, obtain the color data of each water sample at each moment during the EDTA complexometric titration process, where the color data corresponds to the color components of all color channels in the RGB space; Obtain the titration end point moment of each water sample through the abnormal change situation of the color components of each water sample at all moments under each color channel; Analyze the difference situation of the titration end point moments between each water sample and all the other water samples, as well as the difference situation of the color data corresponding to the titration end point moments, and determine the titration end point difference degree of each water sample; Analyze the change trend of the color components of the color data of each water sample at all times after the titration end point in each color channel, as well as the difference in color components between the color data corresponding to the titration end point and the color data corresponding to the last time, to determine the true degree of the titration end point of each water sample; Based on the titration end point difference degree and the true degree of the titration end point, determine the hardness measurement accuracy of each water sample; Based on the hardness measurement accuracy of all water samples, obtain qualified water samples and measure the water quality hardness.

[0006] Preferably, the obtaining of the titration end point time of each water sample includes: Extract the color components corresponding to each color channel in the color data at each time; Perform mutation point detection on the color components of each water sample at all times in each color channel, and select the maximum mutation point; Take the average value of the times corresponding to the maximum mutation points of each water sample in all color channels as the titration end point time.

[0007] Preferably, the determination of the titration end point difference degree of each water sample includes: Take the average value of the differences between the titration end point time of each water sample and the titration end point times of all other water samples as the time difference; Take the average value of the differences between the color data corresponding to the titration end point of each water sample and the color data corresponding to the titration end point of all other water samples as the color difference; Take the sum of the time difference and the color difference as the titration end point difference degree of each water sample.

[0008] Preferably, the determination of the true degree of the titration end point of each water sample includes: Calculate the trend change amount according to the change trends of the R value and G value in the color data of each water sample at all times after the titration end point; Calculate the relative color difference according to the difference between the R value and G value between the color data corresponding to the titration end point and the color data corresponding to the last time of each water sample; The true degree of the titration end point is the reciprocal of the sum of the trend change amount and the relative color difference.

[0009] Preferably, the calculation of the trend change amount includes: Calculate the trend intensity of the color components of each water sample at all times after the titration end point in each color channel; Calculate the sum of the trend intensity of the color channel corresponding to the R value and the trend intensity of the color channel corresponding to the G value of each water sample, and record it as the trend change amount.

[0010] Preferably, the calculation of the relative color difference includes: Calculating the difference in the R value between the color data at the titration end point and the color data at the last moment of each water sample, denoted as the first difference; Calculating the difference in the G value between the color data at the titration end point and the color data at the last moment of each water sample, denoted as the second difference; Taking the sum of the first difference and the second difference as the relative color difference.

[0011] Preferably, the hardness measurement accuracy of each water sample is the ratio of the true degree of the titration end point to the difference degree of the titration end point.

[0012] Preferably, the obtaining of the qualified water sample and the measurement of the water quality hardness include: Adopting a threshold segmentation method to obtain the segmentation threshold of the hardness measurement accuracy of all water samples; selecting the water samples with the hardness measurement accuracy greater than or equal to the segmentation threshold, denoted as qualified water samples; Calculating the hardness of the water sample according to the volume of the EDTA standard titrant consumed at the titration end point of the qualified water sample through the water quality hardness calculation formula.

[0013] In a second aspect, an embodiment of the present application further provides an automatic measurement system for water quality hardness. The system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of the automatic measurement method for water quality hardness described in any one of the above are implemented.

[0014] In a third aspect, an embodiment of the present application further provides an automatic measurement device for water quality hardness. The device is connected to the user's mobile terminal, and the measurement device can be started through remote control or offline control, and the dynamic titration process of the water sample and the measurement result of the water sample hardness are displayed on the user's mobile terminal.

[0015] The present application has at least the following beneficial effects: This application obtains the titration end point moment of each water sample and determines the difference degree of the titration end point of each water sample. Its beneficial effect lies in considering the color jump moment of each water sample, thereby evaluating the titration end point moment in the EDTA complexometric titration process, further analyzing the differences in the titration end point moments of different water samples, as well as the color differences of different water samples at the titration end point moment, evaluating the difference situation of each water sample at the titration end point, reflecting the possibility of non-compliance in the titration process of the corresponding water sample, so as to ensure that the results of subsequent automatic measurement of water quality hardness will not be affected by insufficient titration oscillation, and solving the problem that insufficient oscillation after titration will cause the end point to appear prematurely, resulting in a low automatic measurement result; Secondly, determine the authenticity of the titration end point of each water sample. Its beneficial effect lies in considering the change trends of the R value and G value in the color data at all moments after the titration end point moment of each water sample, as well as the differences in the R value and G value between the color data corresponding to the titration end point moment and the color data corresponding to the last moment, reflecting the possibility of the end point turning back after the titration end point of the corresponding water sample, so as to evaluate the authenticity of the titration end point moment of the corresponding water sample, ensuring that the results of subsequent automatic measurement of water quality hardness will not be affected by the presence of small particles of calcium salts and magnesium salts in the water sample, and solving the problem that the presence of small particles of calcium salts and magnesium salts in the water sample itself affects the automatic measurement result when the end point turns back; Determine the hardness measurement accuracy of each water sample; Based on the hardness measurement accuracy of all water samples, obtain qualified water samples and measure the water quality hardness. Its beneficial effect lies in considering the differences in the titration end point moments of different water samples and the water quality differences of the water samples themselves, so as to evaluate the accuracy of the water quality hardness measurement of each water sample, and then measure the water quality hardness through the titration end point moment corresponding to the qualified water sample after titration, ensuring the accuracy of the automatically measured water quality hardness data output. Solving the problem that the automatic measurement of water quality hardness is easily affected by various factors, resulting in deviations in the measurement results, thereby improving the reliability and accuracy of water quality hardness measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The following further elaborates in detail on an automatic water quality hardness measurement method of this application with reference to the drawings.

[0017] Figure 1 It is the step flow chart of an automatic water quality hardness measurement method provided by an embodiment of this application; Figure 2 It is the step flow chart of the method for obtaining the authenticity of the titration end point of each water sample provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of this application more clearly understood, the following, in conjunction with the accompanying drawings and implementation examples, further describes in detail the method, system, and device for automatically measuring water hardness proposed in this application. It should be understood that the specific embodiments described herein are intended only to explain this application and are not intended to limit this application.

[0019] Unless defined otherwise, 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.

[0020] See also Figure 1 , which shows a flowchart of a method for automatically measuring water hardness provided by one embodiment of the present application, the method comprising the following steps: Step 1: Obtain the color data of each water sample at each moment during the EDTA complexometric titration process.

[0021] The main purpose of testing the total hardness of water is to determine whether the water quality meets the water use standards by measuring the total amount of calcium ions and magnesium ions contained in the water. Water hardness includes temporary hardness and permanent hardness. 2+ Mg 2+ The part that exists in the form of acid carbonate forms carbonate precipitates when heated and is removed, so it is temporary hardness; while the part that exists in the form of sulfate, nitrate and chloride is relatively stable and cannot be removed by heating, so it is permanent hardness.

[0022] EDTA complexometric titration, also known as "ethylenediaminetetraacetic acid titration," is a strong chelating agent that forms stable complexes with many metal ions. In water hardness titration experiments, EDTA, used as a standard titrant, can react with metal ions in the water.

[0023] When the EDTA standard titrant is added, the free Ca in the water 2+ Mg 2+ It will first react with the titrant to produce a stable complex, and then the free Ca in the water 2+ Mg 2+ After the reaction is complete, continue to add EDTA, and the titrant will capture the part of Ca that reacts with the indicator. 2+ Mg 2+ , causing the water color to suddenly change from purple-red to blue, and the titration endpoint is when the blue color just appears.

[0024] The hardness of water quality has no relation with the color change of water quality, but is related to the volume of the EDTA titrant consumed at the titration end point. Take a water quality water sample for EDTA titration. Determine the dosage of the EDTA standard titrant through the titration end point, and then calculate the hardness of the water quality to be measured. The specific calculation formula is as follows: In the formula, is the concentration of the EDTA reagent, is the volume of the EDTA reagent consumed during titration, is the molar mass of calcium carbonate, is the volume of the water sample.

[0025] It should be noted that the calculation formula for the hardness of water quality is a well-known technology and will not be elaborated here.

[0026] Therefore, the titration end point will affect the accuracy of the calculation of the hardness of water quality. Collect the color change during the EDTA titration of water quality through a color sensor to determine the titration end point. Among them, the color sensor identifies colors by detecting the light reflected or transmitted by the surface of an object. The core principle is to utilize the optical characteristics of the three primary colors of red, green, and blue (RGB), because any color can be mixed by different proportions of these three primary colors.

[0027] In the automatic water quality hardness measurement device, first start the electronic control valve on the sample injection section pipeline of the device to convey the water sample and clean the pipeline with the water sample. After cleaning, close the electronic control valve; start the electronic control valve on the reagent pipeline to convey the EDTA standard titrant to the reagent pipeline; start the electronic control valve on the sample injection pipeline to convey the water sample to be detected. The volume of the water sample is Z. After conveying, close the electronic control valve. Start the titration control valve on the reagent pipeline to titrate the EDTA reagent into the colorimetric chamber. Start the color sensor, collect the color data of the water sample through the color sensor, and transmit the collected color data to the control unit.

[0028] It should be noted that the startup methods of the automatic water quality hardness measurement device are mainly divided into two methods: remote control and offline control. If the user cannot start offline, they can use a mobile terminal, such as a mobile phone, tablet, laptop, etc., as a remote operation device, connect to the automatic water quality hardness measurement device through a wireless network, and send a startup control signal. The automatic water quality hardness measurement device collects the color data during the water sample titration in real time; and transmits the color data collected in real time to the user's mobile terminal. The interface of the user's mobile terminal can dynamically display the titration process of the water sample.

[0029] Take X samples of the same volume from the water quality. Measure 1 sample each time, and the volume of each sample is Z milliliters. After each sample completely enters the colorimetric chamber, start collecting the color data of the water sample through the intelligent sensor every T seconds until Y moments after the color data of the water sample jumps to blue, and then stop titration. Thus, obtain the color data of each water sample at each moment.

[0030] It should be noted that when measuring 50 water samples, the volume of each water sample is 200 milliliters, the intelligent sensor is a color sensor, and the color data of the water sample is collected every 0.01 seconds. The 50 moments after the color of the water sample changes from the initial purplish red to blue during titration are collected. As other implementation manners, the implementer can set it according to the actual situation.

[0031] It should be noted that the color data collected by the intelligent sensor at a certain moment is , where R, G, and B respectively represent the intensities of red, green, and blue light, corresponding to three color channels.

[0032] Thus, obtain the color data of each water sample at each moment.

[0033] Step 2: Obtain the titration end point moment of each water sample through the abnormal change of the color components of each water sample at all moments under each color channel; analyze the difference in the titration end point moments between each water sample and all the other water samples, as well as the difference in the color data corresponding to the titration end point moments, and determine the titration end point difference degree of each water sample.

[0034] As the EDTA titrant is dropped in, the color of the water sample will gradually change from purplish red to blue. At this time, the R value and G value in the color data collected by the color sensor will decrease significantly, while the B value will increase significantly. Due to the different oscillation conditions when dropping EDTA, there may be a certain difference in the color jump moments measured for different water samples during measurement, and the colors after the jump are quite different.

[0035] Therefore, by analyzing the jump moments of the R value, G value, and B value in the color data of all moments of each water sample respectively, determine the titration end point moment of each water sample, specifically: Extract the color components corresponding to each color channel in the color data of each moment; Perform mutation point detection on the color components of all moments of each water sample on each color channel, and select the maximum mutation point; In this embodiment, the Bayesian mutation point detection algorithm is used to obtain the maximum mutation point. Among them, the Bayesian mutation point detection algorithm is a well-known technology and will not be elaborated here.

[0036] It should be noted that in the color data of each water sample at all times, the R value, G value, and B value at all times are respectively extracted, and mutation point detection is performed on the R value, G value, and B value at all times.

[0037] The mean value of the corresponding time of the maximum mutation point of each water sample in all color channels is recorded as the titration end point time; Furthermore, the titration end point difference degree is calculated through the difference situation of the titration end point times of multiple water samples and the difference situation of the corresponding color data, specifically as follows: The mean value of the differences between the titration end point time of each water sample and the titration end point times of all other water samples is recorded as the time difference; In this embodiment, the mean value of the absolute values of the differences between the titration end point time of each water sample and the titration end point times of all other water samples is recorded as the time difference.

[0038] The mean value of the differences between the color data corresponding to the titration end point time of each water sample and the color data of all other water samples is recorded as the color difference; In this embodiment, the mean value of the absolute values of the differences between the color data corresponding to the titration end point time of each water sample and the color data of all other water samples is recorded as the time difference.

[0039] The sum of the time difference and the color difference is used as the titration end point difference degree of each water sample; It should be noted that for the convenience of understanding, assume that the th water sample at the titration end point time has color data , and the th water sample at the titration end point time has color data , then the calculation process of the differences between the color data is as follows: .

[0040] It should be noted that the greater the time difference, the greater the difference in the titration end point times of different water samples. The greater the color difference, the greater the difference in the colors corresponding to the titration end point times of different water samples. The greater the obtained titration end point difference degree, the greater the difference between the corresponding water sample and the other water samples at the titration end point, indicating that the titration process of the corresponding water sample is more likely to have a lower accuracy in calculating the water quality hardness based on the titration end point time, and the greater the possibility that the titration process of this water sample does not meet the standard.

[0041] Thus, the titration end point difference degree of each water sample is obtained.

[0042] Step 3: Analyze the change trend of the color components of the color data of each water sample at all times after the titration end point in each color channel, as well as the difference in color components between the color data corresponding to the titration end point and the color data corresponding to the last time, and determine the true degree of the titration end point of each water sample.

[0043] Furthermore, each water sample may contain fine particles of calcium salts and magnesium salts. Therefore, after the color of the water sample jumps during the measurement process, magenta will reappear after a period of time. This phenomenon is called end point turning back or end point returning red. This is because after EDTA reacts with calcium and magnesium ions in the water sample, due to the presence of fine particles of calcium salts and magnesium salts, the overall water sample becomes alkaline, and magnesium ions turn back into magnesium hydroxide precipitate, and then react with chromo black T in the water to form a magenta complex, resulting in the end point turning back phenomenon. Then, in the collected color data, the R value and G value in the color data of the water sample will decrease rapidly, and the B value will increase rapidly. After reaching the titration end point, the R value and G value show an upward trend, and the B value shows a downward trend. Therefore, the titration end point difference degree cannot guarantee the accuracy of water quality hardness measurement. It is necessary to evaluate the authenticity of the titration end point moment and calculate the true degree of the titration end point. The step flow chart of the method for obtaining the true degree of the titration end point of each water sample provided in the embodiments of the present application is as Figure 2 shown, specifically: Calculate the trend intensity of the color components of each water sample at all times after the titration end point in each color channel; In this embodiment, the STL decomposition algorithm is used to calculate the trend intensity. Among them, the STL decomposition algorithm and the calculation of the trend intensity are well-known technologies and will not be elaborated here.

[0044] It should be noted that in this embodiment, the STL sequence decomposition algorithm is used to decompose the color components of each water sample at all times after the titration end point in each color channel into a trend sequence and a residual sequence. The formula for the trend intensity is: , where is the trend intensity, is the variance of the residual sequence, is the variance of the trend sequence and the residual sequence, is the calculated maximum value.

[0045] Calculate the sum of the trend intensity of the color channel corresponding to the R value and the trend intensity of the color channel corresponding to the G value of each water sample, and record it as the trend change amount; Calculate the difference between the R value in the color data at the titration end point and the last time of each water sample, and record it as the first difference; Calculate the difference between the G value in the color data at the titration end point and the last time of each water sample, and record it as the second difference; In this embodiment, the absolute value of the difference between the R value in the color data at the titration end point and the last moment of each water sample is calculated and denoted as the first difference; the absolute value of the difference between the G value in the color data at the titration end point and the last moment of each water sample is calculated and denoted as the second difference.

[0046] The sum of the first difference and the second difference is denoted as the relative color difference. The reciprocal of the sum of the trend change amount and the relative color difference is taken as the true degree of the titration end point of each water sample. It should be noted that the larger the trend change amount, the greater the change trend of the R value and the G value of the water sample after the titration end point; the larger the relative color difference, the greater the gap between the R value and the G value of the water sample at the last moment and the R value and the G value at the titration end point, indicating that it is more likely to have a phenomenon of the end point turning back after the titration end point of this water sample. Then the authenticity of this titration end point moment is lower, the obtained true degree of the titration end point is smaller, the titration end point moment of the corresponding water sample is less real, and the measurement data is more likely to have deviations. Calculating the water quality hardness through this data is more likely to be inaccurate.

[0047] Thus, the true degree of the titration end point of each water sample is obtained.

[0048] Step 4: Based on the titration end point difference degree and the true degree of the titration end point, determine the hardness measurement accuracy of each water sample; based on the hardness measurement accuracy of all water samples, obtain the qualified water samples and measure the water quality hardness.

[0049] Furthermore, based on the titration end point difference degree and the true degree of the titration end point, calculate the hardness measurement accuracy, specifically: The ratio of the true degree of the titration end point to the titration end point difference degree is taken as the hardness measurement accuracy of each water sample. It should be noted that when measuring the hardness of each water sample, the smaller the change difference at the titration end point moment and the larger the true degree of the titration end point, the higher the hardness measurement accuracy of this water sample.

[0050] Furthermore, based on the hardness measurement accuracy, evaluate the titration conditions of all water samples and screen out the qualified water samples, specifically: Adopt the threshold segmentation method to obtain the segmentation threshold of the hardness measurement accuracy of all water samples. In this embodiment, the cross-validation method is used to obtain the segmentation threshold. Among them, cross-validation is a well-known technology and will not be elaborated here.

[0051] Select the water samples with the hardness measurement accuracy greater than or equal to the segmentation threshold and denote them as qualified water samples. According to the water quality hardness calculation formula, the hardness of the water sample is calculated based on the volume of the EDTA standard titrant consumed at the titration end point of the qualified water sample, so as to measure the water quality hardness.

[0052] It should be noted that the water sample with the hardness measurement accuracy less than the segmentation threshold is an unqualified water sample, and there are deviations in the measurement data of the water sample.

[0053] After the automatic water quality hardness measurement device completes the above steps, it can transmit the device parameter information of the current device and the measurement result of the water sample hardness to the user's mobile terminal.

[0054] The embodiment of the present application also provides an automatic water quality hardness measurement system, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above methods for automatically measuring water quality hardness.

[0055] Based on the same inventive concept as the above method, the embodiment of the present application also provides an automatic water quality hardness measurement device. The device is connected to the user's mobile terminal, and the measurement device can be started through remote control or offline control, and the dynamic water sample titration process and the measurement result of the water sample hardness are displayed on the user's mobile terminal.

[0056] It should be understood that although Figure 1 the steps in the flowchart are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, Figure 1 at least a part of the steps in

[0057] may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

[0058] The above-described embodiments merely represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limitations on the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made. Therefore, any simple modifications, equivalent changes, and decorations made to the above embodiments based on the technical essence of the present application without departing from the content of the technical solution of the present application all fall within the protection scope of the technical solution of the present application.

Claims

1. An automated measurement method for water quality hardness, characterized in that, The method includes the following steps: Obtain the color data of each water sample at each moment during the EDTA complexometric titration through an intelligent sensor, where the color data corresponds to the color components of all color channels in the RGB space; Obtain the titration end point moment of each water sample through the abnormal change situation of the color components of each water sample at all moments under each color channel; Analyze the difference situation of the titration end point moments between each water sample and all other water samples, as well as the difference situation of the color data corresponding to the titration end point moments, to determine the titration end point difference degree of each water sample; Analyze the change trend situation of the color components of the color data of each water sample at all moments after the titration end point moment on each color channel, as well as the difference situation of the color components between the color data corresponding to the titration end point moment and the color data corresponding to the last moment, to determine the titration end point authenticity of each water sample; Based on the titration end point difference degree and the titration end point authenticity, determine the hardness measurement accuracy of each water sample; Based on the hardness measurement accuracy of all water samples, obtain the qualified water samples and measure the water quality hardness.

2. The automated measurement method for water quality hardness according to claim 1, wherein The obtaining of the titration end point moment of each water sample includes: Extract the color components corresponding to each color channel in the color data of each moment; Perform mutation point detection on the color components of each water sample at all moments on each color channel, and select the maximum mutation point; Take the mean value of the moments corresponding to the maximum mutation points of each water sample on all color channels as the titration end point moment.

3. An automated measurement method for water quality hardness as described in claim 1, characterized in that, The determination of the titration end point difference degree of each water sample includes: Take the mean value of the differences between the titration end point moment of each water sample and the titration end point moments of all other water samples as the time difference; Take the mean value of the differences between the color data corresponding to the titration end point moment of each water sample and the color data of all other water samples as the color difference; Take the sum of the time difference and the color difference as the titration end point difference degree of each water sample.

4. The automated measurement method for water quality hardness according to claim 1, characterized in that, The determination of the titration end point authenticity of each water sample includes: Calculate the trend change amount according to the change trends of the R value and G value in the color data of each water sample at all moments after the titration end point moment; Calculate the relative color difference according to the difference situation of the R value and G value between the color data corresponding to the titration end point moment of each water sample and the color data corresponding to the last moment; The titration end point authenticity is the reciprocal of the sum of the trend change amount and the relative color difference.

5. The automated measurement method of water quality hardness according to claim 4, characterized in that, The calculation of the trend change amount includes: Calculate the trend intensity of the color components of each water sample at all moments after the titration end point moment on each color channel; Calculate the sum of the trend intensity of the color channel corresponding to the R value and the trend intensity of the color channel corresponding to the G value of each water sample, and denote it as the trend change amount.

6. The automated measurement method of water quality hardness according to claim 4, characterized in that, The calculation of the relative color difference includes: Calculate the difference between the R value in the color data of the titration end point moment and the last moment of each water sample, and denote it as the first difference; Calculate the difference between the G value in the color data of the titration end point moment and the last moment of each water sample, and denote it as the second difference; Denote the sum of the first difference and the second difference as the relative color difference.

7. An automated measurement method for water quality hardness according to claim 1, characterized in that, The hardness measurement accuracy of each water sample is the ratio of the true value of the titration end point to the difference degree of the titration end point.

8. The automated measurement method for water quality hardness according to claim 1, characterized in that, The obtaining of qualified water samples and the measurement of water quality hardness include: Adopt the threshold segmentation method to obtain the segmentation threshold of the hardness measurement accuracy of all water samples; select the water samples with the hardness measurement accuracy greater than or equal to the segmentation threshold and denote them as qualified water samples; According to the water quality hardness calculation formula, calculate the hardness of the water sample based on the volume of the EDTA standard titrant consumed at the titration end point of the qualified water sample.

9. An automated measurement system for water quality hardness, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and running on the processor. It is characterized in that when the processor executes the computer program, it implements the steps of an automatic measurement method for water quality hardness as described in any one of claims 1-8.

10. An automated measuring device for water quality hardness, applying an automated measuring method for water quality hardness as described in claim 1, characterized in that, The device is connected to the user's mobile terminal, and the measurement device can be started through remote control or offline control, and the dynamic water sample titration process and the measurement result of the water sample hardness are displayed on the user's mobile terminal.

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