In this paper, a fuzzy controller for constant pressure water supply of fire pump is designed. Combining with the approximate mathematical model, the model of constant pressure water supply system of fire pump is established and simulated on the platform of Matlab. From the operation of the system and the simulation results, it can be seen that the response curve of the constant pressure fuzzy control of the model is in good agreement with the actual situation. It has the advantages of fast response and small overshoot, and can effectively make the constant pressure water supply of fire pump.
Because of the problem of uneven water supply in the city water supply system in different time periods, if the fire pump is set according to the maximum water supply, the motor speed is fixed, which will not only waste energy, but also cause a great pressure on the pipeline network when the water supply is very small, which will easily lead to accidents such as pipeline network explosion, thermostatic element and eventually delay fire fighting. The best time. The common method of constant pressure water supply is frequency conversion technology, that is, according to the change of pipe network pressure, change the frequency, change the speed of motor, achieve the effect of constant pressure. However, the water supply system has a great lag and time-varying, so there are still many shortcomings in frequency conversion and constant pressure. Aiming at the above background, this paper designs a constant pressure water supply system with ARM as the control center and frequency conversion speed regulation of water-proof pump based on fuzzy control. Among them, f is the frequency of the power supply, P is the number of poles of the motor, s is the slip rate of the asynchronous motor. From formula 1, it can be seen that if the power supply frequency f changes, the speed n of the motor will also change. This system is composed of fire pump unit, frequency converter, sensor and so on. When the fire pump is running, the motor drives the water supply. The pressure sensor is responsible for measuring the real-time pressure of the water supply network.
If the real-time pressure is detected to be less than the preset pressure stored, the controller obtains the positive pressure difference by calculating and converting it into digital quantity. By accumulating this increment with the current frequency value of the frequency converter, a new output frequency is obtained. The speed of the motor of the fire pump unit increases, and the pressure of the water supply network increases. The above process is the whole process of constant pressure control. Repeat this process continuously, so that the pressure reaches the rated pressure. Fig.
1 is a fuzzy control block diagram of variable frequency constant pressure control of fire pump. The fuzzy controller is in ARM. Among them, T represents lag time, K represents gain, and T represents inertial time constant. According to practical experience, K = 2, T = 300 and_ = 3 are obtained. The design steps of the fuzzy controller are: input of the fuzzy controller; fuzzy quantization; establishment of fuzzy rules; de-fuzzification; output. The specific schematic diagram is shown in Fig.
2. Bp93420 type pressure sensor is selected in this system, which has the characteristics of high reliability, good stability, high precision and long life. The principle of this system is to use piezoresistive isolation film filling core to detect pressure signal. In this paper, there are two inputs of the fuzzy controller: pressure difference e, pressure difference change EC and output: voltage change U. Therefore, it can be seen that the fuzzy controller has two inputs and one output. The pressure of the water supply network of the fire pump in this system is about 1.5 MPa. The range of pressure deviation e is (-25,25) (kPa).
The domain of selecting e is {-6,-5,-4,-3,-2,-1,0,… 4, 5, 6}, the quantification factor is Ke=6/25=0.24. Fuzzy linguistic variables: negative large, negative medium, negative small, zero, positive small, positive medium, positive large. The allowable range of pressure difference variation in this system is (-12,12). The field of EC is {-6,-5,-4,-3,-2,-l, 0, l, 2, 3, 4, 5, 6} and the quantification factor is Kec=6/12=0.5. Fuzzy linguistic variables: negative large, negative medium, negative small, zero, positive small, positive medium, positive large. The system allows voltage variation in the range of (-30,30)(V), u in the field of {-6,-5,-4,-3,-2,-l,0, l, 2, 3, 4, 5, 6}, the scale factor Ku=30/6=5. Fuzzy linguistic variables: negative large, negative medium, negative small, zero, positive small, positive medium, positive large. Fig. 3 is the membership function of pressure difference e, pressure difference variation EC and control variable U. Taking rule as an example, the meaning is: if the grade of E is negative large (NB), EC is negative large (NB), indicating that E has a tendency to increase, in order to quickly eliminate the existing negative large water pressure deviation, the change of control quantity u needs to be positively large (PB), and Table L is the table of fuzzy control rules. Fuzzy reasoning is the core of all the steps of the fuzzy controller.
According to some fuzzy reasoning algorithms and fuzzy rules, the quantity of Jq input is obtained by reasoning. But the fuzzy reasoning can only get a fuzzy set, and only the determinate value can drive the controller to work. So the last step of de-fuzzification is the process of converting the fuzzy value into the determinate value. The commonly used methods of de-fuzzification are weighted average method, maximum membership method and center of gravity method. C = 0.4/-1 0.7/-2 1.0/-3 0.2/-4. According to the maximum membership method, 13 has the largest membership among all elements, so 13 is the output of C. According to matrix R, when the pressure difference is E1 and the change rate of pressure difference is EC1, the corresponding output can be obtained. Formula 7 can be used to obtain the fuzzy set of output changes, and a series of output values can be obtained through the process of de-fuzzification. Finally, a fuzzy control query table is established, as shown in Table 2. The Table 2 is stored in the ARM processor and the query table is invoked through the program. When the system starts to run, it is initialized first. The pressure sensor measures the water pressure of the water supply network, converts the water pressure signal into a 0-5V voltage signal or a 4-20mA current signal, reads the data by ARM, calculates the difference e between the current water pressure and the preset water pressure and the change rate EC of the pressure difference, and then finds the fuzzy rule table to get the output. The output signal is transmitted to the converter through D/A conversion. The converter converts the power frequency AC input of 380V/50Hz into AC output of 0-380V/0-50-60Hz, which changes the speed of the motor of the fire pump. Figure 4 shows the flow chart of the above process. Fuzzy Logic toolbox provided in MATLAB is used to simulate the fuzzy control rules in this paper. Fig. 5 is the simulation diagram of the constant-pressure fuzzy control rules of the system. The simulation time of the system is lOOs. Fig. 6 is the simulation result diagram of the constant-pressure fuzzy control of the system. According to the simulation results of constant pressure fuzzy control in Fig. 6, the system tends to be stable in 32 seconds and the control curve is ideal through the control of the fuzzy controller. According to the law of curve change, the response time and overshoot control are very good. In this paper, the constant pressure water supply module of fire pump is designed based on the principle of fuzzy control. Combining with the approximate mathematical model, the constant pressure control of fire pump is simulated and verified on the platform of Matlab. From the operation of the system and the simulation results, it can be seen that the response curve of the constant pressure fuzzy control of the model is in good agreement with the actual situation.
It has the advantages of fast response and small overshoot, and can effectively make the constant pressure water supply of fire pump.