Methods for controlling temperature in ultrasonic device
A generator, ultrasonic device, and method for controlling a temperature of an ultrasonic blade are disclosed. A control circuit coupled to a memory determines an actual resonant frequency of an ultrasonic electromechanical system comprising an ultrasonic transducer coupled to an ultrasonic blade by an ultrasonic waveguide. The actual resonant frequency is correlated to an actual temperature of the ultrasonic blade. The control circuit retrieves from the memory a reference resonant frequency of the ultrasonic electromechanical system. The reference resonant frequency is correlated to a reference temperature of the ultrasonic blade. The control circuit then infers the temperature of the ultrasonic blade based on the difference between the actual resonant frequency and the reference resonant frequency. The control circuit controls the temperature of the ultrasonic blade based on the inferred temperature.
1. A computer-implemented interactive surgical system for controlling an estimated temperature of an ultrasonic blade, the system comprising:
a generator configured to communicate with a modular control tower, the modular control tower in data communication with a modular communication hub, the modular communication hub in data communication with one or more modular devices located in one or more operating theaters of a healthcare facility, the generator comprising a control circuit coupled to a memory, the control circuit configured to:
determine an actual resonant frequency of an ultrasonic electromechanical system comprising an ultrasonic transducer coupled to an ultrasonic blade by an ultrasonic waveguide, wherein the actual resonant frequency is correlated to an actual temperature of the ultrasonic blade;
retrieve from the memory a reference resonant frequency of the ultrasonic electromechanical system, wherein the reference resonant frequency is correlated to a reference temperature of the ultrasonic blade;
infer an inferred temperature of the ultrasonic blade based on a difference between the actual resonant frequency and the reference resonant frequency;
control the estimated temperature of the ultrasonic blade based on the inferred temperature;
generate a temperature estimator and a state space model of the inferred temperature of the ultrasonic blade as a function of the actual resonant frequency of the ultrasonic electromechanical system based on a set of non-linear state space equations;
apply a Kalman filter to improve the temperature estimator and the state space model;
apply a state estimator in a feedback loop of the Kalman filter;
control power applied to the ultrasonic transducer; and
regulate the estimated temperature of the ultrasonic blade,
wherein to determine the actual resonant frequency of the ultrasonic electromechanical system, the control circuit is further configured to determine a phase angle φ between a voltage V g (t) and a current I g (t) signal applied to the ultrasonic transducer,
wherein the state space model is defined by:
[
F
˙
n
T
˙
]
=
f
(
t
,
T
(
t
)
,
F
n
(
t
)
,
E
(
t
)
)
y
.
=
h
(
t
,
T
(
t
)
,
F
n
(
t
)
,
E
(
t
)
)
.
wherein:
{dot over (F)} n represents a rate of change of a time (t) dependent natural frequency F n (t) of the ultrasonic electromechanical system;
{dot over (T)} represents a rate of change of the actual temperature of the ultrasonic blade with respect to the time (t) dependent natural frequency F n (t);
T(t) represents a time (t) dependent actual temperature of the ultrasonic blade;
E(t) represents a time (t) dependent energy;
t represents the time; and
y represents an observability of variables that are measurable and observable including the time dependent natural frequency F n (t) of the ultrasonic electromechanical system, the time dependent actual temperature T(t) of the ultrasonic blade, observable as the temperature estimator, the time dependent energy E(t) applied to the ultrasonic blade, and time t, and
wherein a state variance of the state estimator of the Kalman filter is defined by:
(σ k − ) 2 =σ k-1 − +σ P k 2 and
a gain K of the Kalman filter is defined by:
K
=
(
σ
k
-
)
2
(
σ
k
-
)
2
+
σ
m
2
.
wherein:
(σ k − ) is a variance of state k;
(σ k-1 − ) is a variance of the previous state k−1;
(σ Pk − ) is a predicted variance of state k; and
(σ m − ) is an observed system variance.
2. The computer-implemented interactive surgical system of claim 1 , further comprising an imaging module in data communication with the modular control tower.
3. The computer-implemented interactive surgical system of claim 2 , wherein the imaging module is in data communication with a surgical device.
4. The computer-implemented interactive surgical system of claim 1 , further comprising one or more surgical instruments in data communication with the modular communication hub.
5. The computer-implemented interactive surgical system of claim 1 , wherein the modular communication hub is in data communication with an internet cloud resource.
6. The computer-implemented interactive surgical system of claim 1 , further comprising a surgical robot hub in data communication with the modular control tower.
7. A computer-implemented interactive surgical system for controlling an estimated temperature of an ultrasonic blade, the system comprising:
an ultrasonic device comprising a control circuit coupled to a memory and configured to communicate with a modular control tower, wherein the modular control tower is in data communication with a modular communication hub, wherein the modular communication hub is in data communication with one or more modular devices located in one or more operating theaters of a healthcare facility, wherein the control circuit configured to:
determine an actual resonant frequency of an ultrasonic electromechanical system comprising an ultrasonic transducer coupled to an ultrasonic blade by an ultrasonic waveguide, wherein the actual resonant frequency is correlated to an actual temperature of the ultrasonic blade;
retrieve from the memory a reference resonant frequency of the ultrasonic electromechanical system, wherein the reference resonant frequency is correlated to a reference temperature of the ultrasonic blade;
infer an inferred temperature of the ultrasonic blade based on a difference between the actual resonant frequency and the reference resonant frequency;
control the estimated temperature of the ultrasonic blade based on the inferred temperature;
generate a temperature estimator and a state space model of the inferred temperature of the ultrasonic blade as a function of the actual resonant frequency of the ultrasonic electromechanical system based on a set of non-linear state space equations;
apply a Kalman filter to improve the temperature estimator and the state space model;
apply a state estimator in a feedback loop of the Kalman filter;
control power applied to the ultrasonic transducer; and
regulate the estimated temperature of the ultrasonic blade,
wherein to determine the actual resonant frequency of the ultrasonic electromechanical system, the control circuit is further configured to determine a phase angle φ between a voltage V g (t) and a current I g (t) signal applied to the ultrasonic transducer,
wherein the state space model is defined by:
[
F
˙
n
T
˙
]
=
f
(
t
,
T
(
t
)
,
F
n
(
t
)
,
E
(
t
)
)
y
.
=
h
(
t
,
T
(
t
)
,
F
n
(
t
)
,
E
(
t
)
)
.
wherein:
{dot over (F)} n represents a rate of change of a time (t) dependent natural frequency F n (t) of the ultrasonic electromechanical system;
{dot over (T)} represents a rate of change of the actual temperature of the ultrasonic blade with respect to the time (t) dependent natural frequency F n (t);
T(t) represents a time (t) dependent actual temperature of the ultrasonic blade;
E(t) represents a time (t) dependent energy;
t represents the time; and
{dot over (y)} represents an observability of variables that are measurable and observable including the time dependent natural frequency F n (t) of the ultrasonic electromechanical system, the time dependent actual temperature T(t) of the ultrasonic blade, observable as the temperature estimator, the time dependent energy E(t) applied to the ultrasonic blade, and time t, and
wherein a state variance of the state estimator of the Kalman filter is defined by:
(σ k − ) 2 =σ k-1 2 +σ P k 2 and
a gain K of the Kalman filter is defined by:
K
=
(
σ
k
-
)
2
(
σ
k
-
)
2
+
σ
m
2
.
wherein:
(σ k − ) is a variance of state k;
(σ k-1 − ) is a variance of the previous state k−1;
(σ Pk − ) is a predicted variance of state k; and
(σ m − ) is an observed system variance.
8. The computer-implemented interactive surgical system of claim 7 , further comprising an imaging module in data communication with the modular control tower.
9. The computer-implemented interactive surgical system of claim 8 , wherein the imaging module is in data communication with a surgical device.
10. The computer-implemented interactive surgical system of claim 7 , further comprising one or more surgical instruments in data communication with the modular communication hub.
11. The computer-implemented interactive surgical system of claim 7 , wherein the modular communication hub is in data communication with an internet cloud resource.
12. The computer-implemented interactive surgical system of claim 7 , further comprising a surgical robot hub in data communication with the modular control tower.