An automatic optimization system for sludge conditioner based on arduino development board control

Abstract

The application discloses a sludge conditioner automatic optimization system based on an Arduino development board control and belongs to the technical field of environmental protection. The application combines an Arduino Uno development board, Python programming and serial communication technology, realizes real-time processing of data by a PC end, and converts results into standard current signals by an Arduino controller to feed back to a dosing metering pump. Meanwhile, frequency scanning test is carried out by using an electrochemical impedance instrument, and Savitzky-Golay filters are used to smooth the obtained electrochemical parameters d s / f c , and the change rate thereof is calculated. Whether the dosing amount is in an optimal range is judged according to the change rate, if not, the dosing instruction is continuously executed until the change rate value is in the interval range of-0.001-0.001, and finally, a system prototype of sludge dewatering performance change-electrical signal transmission-brain-like decision-making-conditioning dosing intelligent control is established. The application is expected to solve the problems of existing overdosing and unstable conditioning effect.

Description

TECHNICAL FIELD

[0001] The present application relates to a sludge conditioner automatic optimization system based on an Arduino development board control, belonging to the technical field of environmental protection. BACKGROUND

[0002] With the acceleration of urbanization process in China, the urban sewage treatment rate is increasing year by year, and the sludge production of urban sewage treatment plants also increases sharply. The sludge of urban sewage treatment plant not only has high water content, is easy to rot, has strong odor, but also contains a large amount of pathogenic bacteria, parasitic eggs and chromium, mercury and other heavy metals and dioxin and other difficult-to-degrade toxic and harmful and carcinogenic substances. The sludge is randomly stacked without treatment, and through the erosion and leakage of rainwater, it is easy to cause secondary pollution to groundwater, soil and other substances, which directly endangers human health.

[0003] The recycling and safe disposal of excess activated sludge is an important part of the sewage treatment system. An effective sludge management process not only can reduce secondary pollution, but also can offset the energy consumption of the sewage treatment system and reduce carbon dioxide emissions. In this process, a conditioner is usually used to release bound water and improve the dewatering property of the sludge, which can minimize the volume of the sludge and is beneficial to subsequent transportation. However, due to the unstable nature of the sludge, the dosage parameters cannot be determined to ensure the best dewatering effect. During the sludge conditioning process, the phenomenon of exceeding the standard often occurs, which not only reduces the dewatering performance of the sludge, but also causes higher operating costs. At the same time, decentralized sewage sludge treatment is generally used in rural areas, towns, remote areas, scenic spots with high water treatment requirements, nature reserves or ecological red line areas. In sparsely populated rural areas, the use of centralized sewage treatment systems can easily cause economic burden.

[0004] Based on the above situation, the decentralized sewage treatment system will become a more suitable choice. At present, in the field of decentralized sludge treatment, an unattended decentralized treatment device has appeared. Through the intelligent remote management platform of the unattended sewage station, automatic detection of the water level and other parameters of the sewage tank can be realized, the water pump can be controlled to work in turn and the standby pump can be started in time, the operation of the water pump can be reasonably scheduled, the utilization rate of the pump can be effectively improved, the service life of the motor can be prolonged, the accident downtime can be reduced, the drainage capacity can be improved, and complete automation control of drainage and remote monitoring of the pump house can be realized. However, due to the fact that the traditional decentralized sewage treatment facilities cannot meet the requirements of fine treatment in terms of sludge conditioning agent addition, this hinders the development of unattended sewage treatment systems. SUMMARY

[0005] To solve the above problems, the present application is realized by the following technical scheme:

[0006] With eigenvalue as an indicator, real-time data processing is realized by calling Python script program. On the basis of existing electrochemical database, the results are converted into standard current signals by Arduino controller and fed back to the dosing pump. Finally, the system prototype of sludge dewatering performance change-electrical signal transmission-brain-like decision-making-conditioning dosing intelligent control is established.

[0007] To realize real-time data processing on the PC side and convert the results into standard current signals by the Arduino controller to feed back to the dosing pump, the technical route is designed to build the control unit.

[0008] In the hardware control part, to realize the automatic control of the peristaltic pump on the PC side, the Arduino Uno development board receives data messages from the PC side and transmits these data to the peristaltic pump through serial communication. The schematic diagram is shown in FIG. 8. Figure 3 Considering that the peristaltic pump is controlled externally by RS485 communication protocol, a TTL to RS485 module is added between the Arduino Uno development board and the peristaltic pump external control module to facilitate connection and communication. In addition, by connecting the TX pin of the development board and the TTL to RS485 module, as well as connecting the power supply and ground lines of the module and the development board, the module is in working condition. Under this wiring method, the development board can receive data from the PC side and transmit data to the peristaltic pump through the TX pin, thereby triggering the corresponding working process. In the Python programming environment, the serial library is used, the corresponding serial information is configured, and appropriate time intervals are set. After reading the data each time, the data message conforming to the communication protocol of the peristaltic pump is constructed and sent to the Arduino Uno development board through the USB line. At the same time, the running time is set to 10 s, and then the running is stopped.

[0009] In the software part, the peristaltic pump is controlled to perform dosing operation by reading sensor data, i.e., the code realizes accurate control of the dosing machine, which can dynamically adjust the dosing action according to real-time data to ensure the accuracy and efficiency of dosing. At the same time, through reasonable waiting and circulation mechanism, the stability and sustainability of the dosing operation are ensured.

[0010] According to the dynamic change of the electrochemical parameter d s / f c of the sludge during the sludge conditioning and dosing process, the steps to determine whether the dosing amount at this time is the optimal dosing amount are as follows:

[0011] (1) The sludge is tested by frequency scanning with an electrochemical impedance instrument connected with a conductivity electrode probe to extract d s / f cAfter X1 is detected, the control system opens the dosing pump, adds a certain dosage a0, the value of a0 is 1 mg / g dry sludge-5 mg / g dry sludge, and is set to end dosing within 10 s, and then the dosing pump is closed;

[0012] (2) The above operation is repeated six times to obtain X1, X2, X3, X4, X5 and X6, the data is smoothed by using a Savitzky-Golay filter, and then the change rate value of the electrochemical parameter d s / f c is calculated.

[0013]

[0014] Among them, is a smoothing coefficient, which is obtained by fitting a polynomial by the least square method.

[0015] (3) The calculation formula of the slope is:

[0016]

[0017] Among them, h is the interval of adjacent points.

[0018] (4) The slope Y1' of X6 is calculated by using the above method, and it is judged whether the value of Y1' is within the range of-0.001-0.001.

[0019] ① If it is, stop dosing, record the number of dosing at this time as n1, and the total dosing amount as a0n1 mg / g dry sludge.

[0020] ② If it is not, continue to add a certain dosage a0, and end dosing within 10 s, and then close the dosing pump, and the electrochemical impedance instrument of the conductance electrode probe carries out the seventh frequency scanning test on the sludge, extracts the value of d s / f c , denoted as X7, and continues to smooth the data by using a Savitzky-Golay filter, and then calculates the change rate value of the electrochemical parameter d s / f c .

[0021] (5) If the slopes obtained in the previous n-1 times are not within the range of-0.001-0.001, the above operation is repeated until the absolute value of the change slope of the electrochemical parameter d n s / fc after the nth frequency scanning is less than 0.001, and finally the cumulative dosing amount a n is obtained, and the calculation formula is:

[0022] a n =na0mg / g dry sludge

[0023] The reagents include polyaluminum chloride, aluminum chloride and its hydrate, aluminum salts and their hydrates, ferric salts and their hydrates, ferrous salts and their hydrates, and polyferric sulfate. The time interval between two consecutive frequency scans performed by the electrochemical impedance spectroscopy is 2.5 minutes. The sinusoidal voltage applied during the frequency scan of the electrochemical impedance spectroscopy ranges from 1 to 1000 mV, and the scan frequency ranges from 0.1 Hz to 10 MHz. Attached Figure Description

[0024] Appendix Figure 1 This is an overall schematic diagram of the present invention. In the figure: 1-PC terminal, 2-electrochemical impedance meter, 3-conductivity electrode probe, 4-stirrer, 5-dosing pump, 6-reagent, 7-Arduino controller.

[0025] Appendix Figure 2 This represents the relationship between characteristic values ​​and dosage. The vertical axis represents the ratio between the characteristic value and the corresponding dosage, while the horizontal axis represents the dosage.

[0026] Appendix Figure 3 This is a pin diagram for Arduino Uno development.

[0027] Appendix Figure 4 This is the flowchart described in this invention. Detailed Implementation Plan

[0028] The present invention will now be described in detail with reference to embodiments. However, the accompanying drawings and embodiments are merely exemplary and do not constitute any limitation on the scope of the present invention. Those skilled in the art should understand that modifications or substitutions to the details and form of the technical solutions of the present invention can be made without departing from the spirit and scope of the invention, but all such modifications and substitutions fall within the protection scope of the present invention.

[0029] Example 1:

[0030] Excess activated sludge with a concentration of 12.4 g / L was collected from an anaerobic / aerobic biological reaction process at a Beijing reclaimed water plant with a daily treatment capacity of 1 million tons. Frequency scanning tests were performed on the sludge using an electrochemical impedance spectroscopy (EIS) meter connected to a conductivity electrode probe. Based on the dynamic changes in ds / fc, the optimal dosage was determined in real time to control the staged addition of a fixed amount of Fe2(SO4)3 coagulant liquid to the sludge. Parallel experiments showed that the average final dosage was 65 mg / g, while the optimal dosage indicated by traditional manual conditioning for sludge dewatering performance assessment was 80 mg / g, a difference of 18.75%. Simultaneously, the average value of the traditional offline index CST, which reflects sludge dewatering performance, was measured to be 30.2 mm. 2 / s, while the average CST measured by traditional manual administration at the optimal dosage was 37.4 mm. 2The difference is 19.25%. This shows that the intelligent conditioning system can effectively and quickly condition the sludge to the best state of dewatering.

[0031] Example Two:

[0032] The residual activated sludge was taken from an anaerobic / aerobic biological reaction process of a Beijing reclaimed water plant with a daily water treatment capacity of 1 million tons, and the sludge concentration was 12.4 g / L. The sludge was tested by frequency scanning test using an electrochemical impedance instrument connected with a conductivity electrode probe. According to the dynamic change of ds / fc, it was judged in real time whether the dosage was in the best dosage range, so as to control the dosing pump to add FeCl3 coagulant liquid to the sludge in sections. Through parallel experiments, the average value of the final dosage of the system was 50 mg / g, the best dosage indicated by the traditional manual conditioning evaluation of sludge dewatering performance was 60 mg / g, and the difference was 16.67%. At the same time, the average value of the traditional offline indicator CST for feedback of sludge dewatering performance was 17.8 mm / s, while the average value of CST measured by traditional manual conditioning at the best dosage was 21.1 mm / s, with a difference of 15.64%. This shows that the intelligent conditioning system can effectively and quickly condition the sludge to the best state of dewatering. 2 2 / s, while the average value of CST measured by traditional manual conditioning at the best dosage was 21.1 mm / s, with a difference of 15.64%. This shows that the intelligent conditioning system can effectively and quickly condition the sludge to the best state of dewatering.​

Claims

1. An automatic optimization system for sludge conditioner based on Arduino development board control, comprising a PC end (1), an electrochemical impedance instrument (2), a conductivity electrode probe (3), a stirring instrument (4), a dosing metering pump (5), a medicament (6), an Arduino controller (7), and a dynamic change of an electrochemical parameter d of sludge in a sludge conditioning and dosing process, wherein the system determines whether the dosing amount is in an optimal dosing amount interval in real time, and if so, the system automatically stops; otherwise, the system continues to dose until the optimal dosing amount interval is reached. s c The step of determining whether the dosing amount is in the optimal dosing amount interval in real time is as follows: ​​ (1) use the electrochemical impedance instrument with the electric conductive electrode probe to test the sludge by frequency scanning, extract d s / f c value, record as X1, after detecting X1, the control system opens the dosing pump, adds a certain dosage a0, the value of a0 is 1 mg / g dry sludge-5 mg / g dry sludge, and sets to end dosing within 10 s, and then closes the dosing pump; (2) Repeat the above operation six times to obtain X1, X2, X3, X4, X5, and X6. Smooth the data using a Savitzky-Golay filter, and then calculate the electrochemical parameter d s / f c The rate of change of the value of the electrochemical parameter d is calculated as follows: wherein is the smoothing coefficient, obtained from a least square polynomial fit; (3) The calculation formula of the slope of the data points is: Wherein, h is the interval of adjacent points; (4) The slope Y1' of X6 is calculated by using the above method, and whether the value of Y1' is in the range of -0.001-0.001 is determined: ① If it is, stop dosing, record the number of times of dosing at this time as n1, and the total dosing amount as a0n1 mg / g dry mud; If not, continue to add a certain dose a0, also end the drug in 10 s, then close the drug pump, and the electrochemical impedance meter of the conductivity electrode probe conducts the seventh frequency scanning test on the sludge, extracts d s / f c value, denoted as X7, and continues to smooth the data with the Savitzky-Golay filter, and then calculates the change rate value of the electrochemical parameter d s / f c ; (5) If the slope of the previous n-1 times is not in the range of -0.001-0.001, repeat the above operation until the absolute value of the slope of the change of the electrochemical parameter d s / f c is less than 0.001 after the n times of frequency scanning, and finally the cumulative dosage is obtained, and the calculation formula is: a n = na 0 mg / g dry mud wherein a n is the cumulative dosage.

2. The sludge conditioner automatic optimization system based on Arduino development board control according to claim 1, characterized in that, The Arduino controller (7) comprises an Arduino Uno development board, a Python programming module and a serial communication module, the Arduino Uno development board adopts a design based on an ATmega328P microcontroller, has 14 digital input / output pins, of which 6 support PWM output, for accurately controlling digital devices, and simultaneously, the development board is internally provided with a real serial port, provides hardware support and can realize data exchange with a PC end.

3. The sludge conditioner automatic optimization system based on Arduino development board control according to claim 1, characterized in that, The types of the sludge include municipal residual sludge, digested sludge, industrial wastewater sludge, river and lake sludge, pipeline sediment, fecal sludge, organic biogas residue and drug residue, and the concentration of the sludge ranges from 3 to 100 g / L.

4. The sludge conditioner automatic optimization system based on Arduino development board control according to claim 1, characterized in that, The medicaments include polyaluminum chloride, aluminum chloride and its hydrate, aluminum salt and its hydrate, ferric salt and its hydrate, ferrous salt and its hydrate, and polymeric ferric sulfate.

5. The sludge conditioner automatic optimization system based on Arduino development board control according to claim 1, characterized in that, The time interval between two adjacent frequency scans performed by the electrochemical impedance instrument is 2.5 min.

6. The sludge conditioner automatic optimization system based on Arduino development board control according to claim 1, characterized in that, The range of the sinusoidal voltage applied in the frequency scanning process of the electrochemical impedance instrument is 1-1000 mV, and the scanning frequency range is 0.1 Hz-10 MHz.

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