Method and system for detecting an applicance based on users' feedback information
A method and system for detecting an appliance based on users' feedback information, particularly a nonintrusive load monitoring method and system based on a user's feedback information and a joint strategic decision search algorithm are disclosed. By means of obtaining the users' feedback information on an appliance inputted by users or a search result of the appliances being confirmed by the users to generate a mapping between the model of the appliances and at least one load signature of each model of appliances; the users' feedback information is recorded into a smart meter or a cloud computing system, and a mathematical analysis is further used to compute an occurrence of any one signature of the appliance and the identification rate of each signature; then the joint strategic decision search algorithm automatically identifies various models of appliances and analyzes the operating states of the electric appliances in homes or offices.
1. A method for detecting an appliance based on users' feedback information, comprising the steps of:
1. obtaining the users' feedback information on an appliance, the feedback information being inputted by users or a search result of the appliances being confirmed by the users to generate a mapping between the model of the appliances and at least one load signature of each model of appliances, wherein the load signature is produced by a voltage and/or current change when the appliance is turned on/off and/or the operating states of the appliance is being changed;
2. computing occurrence of any one of signature of the appliance and an identification rate of each signature with the users' feedback information and the occurrence of any one of the signature of the appliance is further defined as a confidence factor, and the identification rate of each signature is further defined as a signature weighted value; and
3. using a joint strategic decision search algorithm to automatically determine models of appliances, and analyze operating conditions of the appliances.
2. The method for detecting an appliance based on users' feedback information as recited in claim 1 , wherein the users' feedback information v k has three conditions v c , v n and v w shown as below:
v
k
=
{
v
c
,
if
the
feedback
of
the
electric
appliance
search
result
is
correct
;
v
n
,
if
the
feedback
of
the
electric
appliance
search
result
is
in
correct
;
and
v
w
,
whether
the
search
result
is
correct
or
incorrect
is
not
feedback
.
3. The method for detecting an appliance based on users' feedback information as recited in claim 1 , further comprising the step of recording the user's feedback information into a smart meter, a datacenter or a cloud computing system.
4. The method for detecting an appliance based on a user's feedback information as recited in claim 1 , wherein the user's feedback information converts each signature of the appliance into a discrete value by a discrete function, and the discrete function is represented by the equation of
x
_
i
,
j
,
k
=
[
x
i
,
j
,
k
U
j
]
×
U
j
,
wherein i is the number of different models of appliances, j is the number of signatures of each appliance i, k is the number of data of the appliance i coming from different user's feedback information, x i,j,k is the value of the signature j of the k th feedback information of the appliance i, and x i,j,k is the result of a numeric value processed by a discrete function and Uj is the unit of the discrete form of signature j.
5. The method for detecting an appliance based on users' feedback information as recited in claim 1 , wherein the users' feedback information falling within the same discrete interval is summed to obtain distribution of each signature contributed by the users' feedback information, and the summation is given below:
g i,j ( x )= g i,j ( x )+ v k , if x i,j,k =x
wherein g i,j (x) shows the occurrence times of a signature when the signature is recorded as x, if the k th feedback information ( x i,j,k ) of the signature j of the appliance i falls within an interval x in the discrete interval, then g i,j (x) increases v k .
6. The method for detecting an appliance based on a user's feedback information as recited in claim 1 , wherein the confidence factor can be defined base on the occurrence, the confidence factor is a ratio relative to all users' feedback information of the appliances when a signature is calculated and determined to fall within a discrete interval according to the users' feedback information of the appliance, and the confidence factor is a ratio derived from the function g i,j (x), the confidence factor can be shown below:
f
i
,
j
(
x
)
=
g
i
,
j
(
x
)
MAX
(
g
i
,
j
(
x
)
,
∀
x
)
,
Wherein, i is the number of different models of appliances, and j is the number of signatures of each appliance i.
7. The method for detecting an appliance based on users' feedback information as recited in claim 1 , wherein the load signature (also known as signature) has a weighted value dynamically varied with the user's feedback information, and the appliance of a different model has a different weighted value.
8. The method for detecting an appliance based on users' feedback information as recited in claim 7 , wherein the weighted value is expressed by the equation of
w
j
=
∑
i
∈
ℤ
h
i
,
j
(
x
)
×
δ
,
wherein, w j is the significant level of a signature j to an appliance i; the higher the w j value, the higher the identification rate of the signature j to the appliance i, and vice versa; and δ represents a weighted function for distributing the calculation results to a real number interval to obtain an appropriate comparison space; Z is a set representing all appliances or some appliances of the same model; the function of the weighted value can be dynamically adjusted by the overlapping rate of the signature j of each appliance, and the summation of the overlapping rate through the function is used for calculating an average overlapping rate and the function can be shown as below:
h
i
,
j
(
x
)
=
{
0
(
f
i
,
j
(
x
)
∑
m
≠
i
f
m
,
j
(
x
)
)
,
if
∑
m
≠
i
f
m
,
j
(
x
)
≠
0
1
,
otherwise
,
wherein, i is the number of different models of appliances, j is the number of signatures of each appliance i, and θ(α) is a weighted function.
9. The method for detecting an appliance based on users' feedback information as recited in claim 1 , further comprising the step of calculating a similarity between an unknown appliance and a known appliance by the signature of each model of appliances and the identification rate (or weighted value) of each signature of each appliance, the similarity between the unknown appliance and the known appliance is given by the equation of
\
∑
j
=
1
J
w
j
×
f
i
,
j
(
x
)
,
wherein i is the number of different models of appliances, j is the number of signatures of each appliance i; after the plurality of signatures confidence factors of the appliance and weighted value of signatures are calculated, the joint strategic decision search algorithm is further used to determine the most similar appliance who having the maximum value, the weighted value gives different model of appliance with different signature and gives weighted value to different signature, according to analysis and statistical result, and the weighted value compares the similarity of the appliances and searches the appliance by means of different confident factors.
10. A system for detecting an appliance based on users' feedback information, comprising:
a smart meter, for retrieving and computing a load signature, wherein the load signature is produced by a voltage and/or current change when the appliance is turned on/off and/or the operating states of the appliance is being changed;
a home gateway, for saving each load signature of the electric home appliances to facilitate the search of the appliances, and recording the operating states of the electric home appliance for a user to inquire the power consumption situation through the connection of a mobile phone or computer, while providing the functions of power saving recommendations and appliance diagnosis through the mobile phone or computer; and
a datacenter, for saving the users' electric home appliance information, and if the home gateway cannot find the signature of the appliance, the signature will be transmitted to the datacenter for further searching.