Using a variable frequency drive (VFD) in order to drive the vacuum pump of a milking machine allows a dramatic reduction in energy use, while still producing equivalent vacuum stability. The VFD technology is able to adjust the rate of air removal from the milking system by changing the speed of the vacuum pump motor. A PID controller was developed in order to command the electric motor driving the vacuum pump. The PID controller used by the vacuum regulating system was tuned using the Ziegler-Nichols tuning rules for the frequency response method. In order to proceed to a more systematic approach a mathematical model of the vacuum system was developed, assuming that the system consists of a single air tank, provided with a vacuum pump port and an air-using port. In order to validate the model and study the system's response to vacuum variation due to a pulse air leak the detachment (fall-off) of one teatcup was simulated; the teatcup was detached for 10, 20 and 30 seconds respectively. During the fall-off tests the rate of air flow into the system was measured by the means of a rotameter and the vacuum level was recorded. The experimental results were compared with the ones predicted by the model and it was concluded that the model accurately describes the response of the system.
The mechanical milking is achieved due to the vacuum applied to the teat, by the
means of a teatcup. In order to limit the development of congestion and edema and
provide relief to the teat from the milking vacuum, the pulsation principle is used
Figure 2 presents the layout of a typical mechanical milking system
The importance of vacuum level and stability is due to the fact that cows have a biological limit for a positive reaction to vacuum and exceeding it may lead to damage of the teat tissue or slipping of milking clusters off the teat, resulting in an extended milking time and in improper milking; vacuum fluctuations generated within the milking cluster may lead to direct bacterial penetration, thus causing mastitis (Pařilová et al., 2011).
In order to make the vacuum pump draw only the amount of air needed to
maintain the desired vacuum level, the speed of the pump should be variable (as air
flow depends on the pump speed); in this case no conventional regulator is needed to
maintain the imposed vacuum during milking. The electric motor of vacuum pump is
controlled by the means of a variable frequency driver (VFD). This solution has the
potential to significantly reduce the energy consumption of the milking system; in a
study conducted by Pazzona et al. (2003) energy savings between 24 and 87% were
reported. It was concluded that, if the VFD controller is adjusted properly, it can
meet or even exceed the vacuum stability recorded by the systems equipped with
conventional regulators
The first stage of the study was aimed to validate the principle of the vacuum regulation by the means of the VFD controlled vacuum pump. In order to proceed to a more systematic approach of the problem in the second part of the paper a mathematical model of the vacuum system was developed and tested, based on the system’s response to vacuum variation due to a pulse air leak - detachment (fall-off) of one teatcup.
A bucket type milking machine was tested and modeled; Fig. 3 presents the diagram of the milking system. The original system was equipped with a valve and spring type of vacuum regulator, placed on the pipeline connecting the interceptor (I) to the bucket (B); the electric motor (M) driving the vacuum pump (VP) was connected to the three phase power grid. A BRK pneumatic pulsator (P) was used to achieve the liner pulsation; the machine was equipped with four Boumatic R-1CX type teatcups. Artificial teats, manufactured according to the ISO 6690:2007 standard, were inserted into the teatcups. The vacuum pump provided an airflow q=4.69·10-3 m3 s-1 at a speed of 1350 min-1.
In order to use the VFD controller for driving the vacuum pump a Smartec SPD015AAsil absolute pressure sensor (T, fig. 3) was used to monitor the vacuum in the permanent vacuum line, providing the pressure signal for the VFD controller. The electric signal from the pressure sensor was fed to the data acquisition (DAQ) board by the means of a signal conditioning unit (SC).
The data aquision board was USB 6009 (National Instruments), with a sample rate of 48 ksamples/s, four differential analog input channels and two analog output channels.
Based on the software running on the computer the entire system (DAQ board,
VFD controller and computer) acts as a PID regulator for the vacuum level, for
which the set point (SP) is the desired vacuum level and the process variable (PV) is
the actual vacuum level in the vacuum pipeline. The controller calculates the output
signal u(t), which is then used to command the VFD and adjust the running speed of
the electric motor and vacuum pump. The PID controller output is given by the
relation
⎡ u(t) = K p ⋅ ⎢e(t) + ⎣ where the error signal is e(t) = SP-PV; KP is the proportional gain, TI is the integral time and Td is the derivative time.
The PID controller was built with the help of the PID control toolbox from LabVIEW 7.1 and a virtual instrument was created in order to provide the control signal to the VFD. The control panel of the virtual instrument (Fig. 4) allowed the adjustment of the desired vacuum level (vacuum set point) and of the PID gains: proportional gain, integral time [min] and derivative time [min].
The output range of the PID controller was 0…5V, due to the characteristics of the data aquision board; an additional signal conditioning unit (not shown in Fig. 3) was used to obtain the 0…10V range imposed by the variable frequency drive.
An oscilloscope display allowed the visualization of the vacuum set point, system vacuum and output signal of the PID controller.
The variable frequency drive unit was VFD 007M43B (0.7 kW maximum power of the electric motor); the output frequency range was set to 0...60 Hz for a range of the analog comand signal comprised between 0 and 10V.
In order to establish the working parameters of the milking process (pulsation rate and ratio, duration of the phases), two additional Smartec SPD015Aasil absolute pressure sensors (not shown on the diagram in Fig. 3) were attached to the short pulse tube (SPT, Fig. 3) and short milk tube (SMT). The pulsation ratio was defined according to the specifications of the ISO 5707:2007 standard.
The Ziegler-Nichols tuning rules for the frequency response method were used; the disturbance was induced by changing the set point. After that the permanent vacuum values were recorded in a series of dry tests, performed for three vacuum levels: 0.35 bar, 0.40 bar and 0.45 bar (35, 40 and 45 kPa). In order to asses vacuum stability the results were compared, using the average value of the vacuum, the standard deviation and the standard error of the mean. Three tests were performed for each vacuum level and vacuum regulation method and the mean, standard error and standard error of the mean were calculated.
In order to evaluate whether there was a significant difference between the two
pairs of data (the permanent vacuum levels recorded for two regulation methods) a
statistical analysis was performed. The Kolmogorov-Smirnov test proved that data
distribution was not normal; as a result, the Man Whitney rank sum test was
performed; this test is a substitute for the two-sample t test when the samples are not
normally-distributed populations
The mathematical model of the vacuum system was developed assuming that the
system is composed of a single air tank, provided with a vacuum pump port and an
air-using port
Using equations (2) and (3) the transfer function of the system is
The mass flow rate resulting from the pulse air leak m! p is
(5)
Introducing equation (5) into equation (4) and applying the inverse Fourier transform finally leads to: p(t) =
R ⋅ T q
⋅ m!p ⋅ [Φ(t) − Φ(t − t1) − e−q⋅t / V + Φ(t − t1) ⋅ e−q⋅(t−t1 ) / V ] , where Φ(t) is the step function, defined as follows: Φ(t) = { 0, if t < 0 .
1, if t ≥ 0
For the milking system taken into account the singe tank volume (which includes the interceptor volume and the bucket volume) was V=3.5⋅10-2 m3 and the air temperature was T=293 K.
In order to validate the model and study the system’s response to vacuum variation due to a pulse air leak the detachment (fall-off) of one teatcup was performed; the teatcup was detached for 10, 20 and 30 seconds respectively. During the fall-off tests the rate of air flow into the system was measured by the means of a rotameter and the evolution of the vacuum level was recorded using the pressure sensor (T, Fig. 3).
The air flow rate into the system during the fall-off test was m! p =7.6⋅10-5 kg⋅s-1 (average value).
The steady state gain K of the model and the time constant τ were calculated with
the relations
K =
R ⋅ T q , τ = V .
q K s = Δp , m!p (6) (7) (8) (9) For the milking system taken into account the following values were obtained: • K=1.79⋅105 kPa⋅s⋅kg-1; • τ=7.47 s.
Using the experimental data the system steady state gain Ks and the time constant τs were evaluated. The system steady-state gain was calculated with the formula: where Δp is the vacuum drop when the teatcup is detached.
The time constant τs was considered to be the time required for the output vacuum to reach 63.2% of the final value when the teatcup was detached.
3.1
In order to tune the PID controller using the Ziegler-Nichols tuning rules for the
frequency response method, the integral time was set at 10000 and the derivative
time was set to 0; the proportional gain was adjusted until the oscillations were
sustained and had a constant amplitude. Finally, the critical gain was Kc = 68. The
critical period Tc was measured using the recorded vacuum signal; it was established
that the critical period was Tc = 7.53±0.46 s. The PID gains were then calculated
using the formula presented in Table 1
For the case of the PID controller, the following gains were obtained: KP = 40, Ti = 4.76 s (0.062 min), Td = 0.941 s (0.015 min).
The results referring to the working parameters of the system and vacuum stability are shown in Tables 2 and 3.
The results presented in Table 2 show that the working parameters of the system (pulsation rate and ratio, duration of the cycle phases) did not change significantly when passing from the classical method for vacuum regulation (based on the use of a valve type regulator) to the new one, based on the adjustment of the vacuum pump speed. A slight increase of the pulsation rate was however noticed when the second method was used, but the differences did not exceed 1%; the slightly higher pulsation rate resulted in a shorter b phase when the PID controller was used for vacuum regulation, but the requirements of the ISO 5707 standard were fulfilled.
An analysis of the individual values of the permanent vacuum showed that, for the both methods, the working vacuum was maintained within ±2 of the nominal vacuum kPa, in accordance with the requirements of the ISO 5707 standard.
The results presented in Table 3 show that the use of the PID controller method for vacuum regulation led to lower standard deviations and standard errors of the mean than the ones recorded when the classical vacuum regulator was used, proving a better vacuum stability.
The statistical analysis of the results, performed by the means of the Man Whitney rank sum test (SigmaPlot ver. 12.5, demo), confirmed that, for each set value of the vacuum level (35, 40 and 45 kPa, respectively) there were significant differences between the two sets of data.
20% lower than the value predicted by the model.
30 time [s] a) model experiment1 experiment2 experiment3 b) model experiment1 experiment2 experiment3
The inaccuracy of the predicted time constant may be due to the assumptions that
air is a perfect gas and that the system is isothermal, with only small variations of the
air temperature
γ ⋅ q where γ=1.4 is the heat capacity ratio of air.
As a result the time constant of the model becomes τ=5.33 s, a value which is much closer to the average value of 6 s given by the experiments (12,5% lower).
The permanent vacuum level in a bucket milking machine was adjusted by the means of a PID regulator, using a variable frequency driver in order to power the electrical motor driving the vacuum pump. The PID regulator, implemented using the NI LabView capabilities, was aimed to maintain a constant vacuum level.
The PID regulator was tuned in order to establish the PID gains using the ZieglerNichols frequency response method.
A series of dry tests were performed, at different vacuum levels, in order to compare the two methods of vacuum regulation (using a mechanical vacuum regulator and a PID regulator, respectively); the tests proved that vacuum regulation by the means of the PID controller has the potential to replace the classical method of regulation as it did not adversely affect the working parameters of the system, while achieving better results regarding the stability of the permanent vacuum.
As the principle of the vacuum regulation by controlling the vacuum pump speed was confirmed the next step was to develop a mathematic model of the milking system in order to proceed to a more rigourous analysis of the system. As a first step a simplified physical model was adopted, considering the mechanical milking system as first order dynamic system with a single air tank, provided with a vacuum pump port and an air-using port.
In order to validate the model and study the system’s response to vacuum variation due to a pulse air leak the detachment (fall-off) of one teatcup was simulated; the teatcup was detached for 10, 20 and 30 seconds respectively. During the fall-off tests the rate of air flow into the system was measured by the means of a rotameter and the vacuum level was recorded.
As a result of the tests it was concluded that the developed model is accurate, the majority of the experimental values being comprised within the ±2.5% range of the model.
However, the assumption that the process is isothermal led to a relatively high difference between the predicted value of the time constant and the value obtained during the experiments. This difference diminished if the adiabatic hypothesis was considered.
Developing a more complex model of the milking system is taken into account for a future work, aiming to obtain more accurate predictions.