1. A method which may be used for automatically monitoring the performance of a refrigerated compressor while it is operating, said method comprising:
a) measuring the operating parameters of a refrigerated compressor with a measurement means, wherein said operating parameters comprise:
1) the flow rate of a gas through said compressor;
2) the pressure of said gas entering said compressor;
3) the pressure of said gas exiting said compressor; and
4) the temperature of a coolant for said compressor;
b) calculating, with a calculating means, a performance factor representative of the operation of said compressor, wherein said calculating means uses said measured operating parameters and a calculating rule stored in a storage means; and
c) indicating to a user, with an indicating means, performance monitoring information wherein said information comprises a function of said calculated performance factor.
2. The method of claim 1, further comprising a calibration step wherein said calibration step comprises:
a) automatically measuring said operating parameters with said measurement means at least once;
b) storing said measured operating parameters in a memory means; and
c) calibrating said calculation rule as a function of at least one said measured operating parameter located in said memory means.
3. The method of claim 2, wherein said calibration step is capable of being reinitiated by a user for a new calibration of said calculation rule.
4. The method of claim 1, wherein said rule for calculating said performance factor comprises a calculation of an estimated efficiency \u03b7est of said compressor according to the equation:
\u03b7
est
=
A
\u2062
\u2062
Q
+
B
\u2062
P
out
P
i
\u2062
\u2062
n
+
C
\u2062
\u2062
T
cool
+
D
2
\u2062
T
g
+
E
wherein:
a) Q represents said flow rate of said gas through said compressor;
b) Pin represents said pressure of said gas entering said compressor;
c) Pout represents said pressure of said gas leaving said compressor;
d) Tcool represents said temperature of said coolant for said compressor;
e) A, B, C, and E represent predetermined adjustment parameters;
f) D2 represents a non-zero, predetermined adjustment parameter; and
g) Tg represents the measured temperature of said gas entering said compressor, as measured by said measurement means.
5. The method of claim 4, wherein said performance factor corresponds to an estimated energy consumption Pest of said compressor, according to the following equation:
Pest=QRTcool\xd7ln(PoutPin)\u03b7est.
6. The method of claim 5, wherein said R represents the Universal Gas Constant.
7. The method of claim 5, further comprising calculating said adjustment parameters, by linear regression, from at least one of said measured operating parameters present in said memory means.
8. The method of claim 5, further comprising determining said calculation rule with a neural network means, wherein the self-learning of said neural network means is achieved on the basis of at least one of said measured operating parameters present in said memory.
9. The method of claim 4, wherein said calibration step is carried out on command by a user.
10. The method of claim 1, further comprising triggering an alarm when said calculated performance factor does meet prescribed conditions.
11. The method of claim 1, wherein said operating parameters further comprise the temperature of said gas entering said compressor.
12. An apparatus which maybe used for automatically monitoring the performance of a refrigerated compressor while it is operating, wherein:
a) said apparatus comprises:
1) a measuring means suitable to measure the operating parameters of a refrigerated compressor, wherein said operating parameters comprise:
i) the flow rate of a gas through said compressor;
ii) the pressure of said gas entering said compressor;
iii) the pressure of said gas exiting said compressor; and
iv) the temperature of a coolant for said compressor;
2) a storage means suitable to store a calculation rule;
3) a calculating means suitable to calculate a performance factor representative of the operation of said compressor from said calculation rule stored in said storage means and from said measured operating parameters; and
4) an indicating means suitable to indicate information for monitoring the performance of said compressor; and
b) said automatically monitoring the performance of said refrigerated compressor comprises:
1) measuring said operating parameters with said measurement means;
2) calculating, with said calculating means, said performance factor; and
3) indicating, with said indication means, performance monitoring information to a user wherein said information comprises a function of said calculated performance factor.
13. The apparatus of claim 12, further comprising a means to initiate a calculation rule calibration, wherein said calculation rule calibration comprises:
a) automatically measuring said operating parameters with said measuring means at least once;
b) storing said measured operating parameters in a memory means; and
c) calibrating said calculation rule as a function of at least one said measured operating parameter located in said memory means.
14. The apparatus of claim 12, wherein said operating parameters further comprise the temperature of said gas entering said compressor.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method, comprising:
obtaining, by a network device, a reference matrix based on estimates of perceived audio quality of at least portions of one or more first packetized audio messages, the reference matrix modeling values of a plurality of characteristics associated with a particular quality level;
receiving, by the network device, one or more second packetized audio messages;
evaluating, by the network device, at least portions of one or more of the one or more second packetized audio messages to obtain measurements associated with the plurality of characteristics;
creating, by the network device, a test matrix using the obtained measurements; and
comparing, by the network device, the test matrix and the reference matrix to predict a quality level associated with the one or more second packetized audio messages.
2. The method of claim 1, wherein the network device is in a first portion of a communications network, the first portion comprising a public switched telephone network (PSTN), and receiving the one or more second packetized audio messages comprises receiving the one or more second packetized audio messages from a second portion of the communications network, the second portion comprising a packet switched network.
3. The method of claim 1, wherein comparing the reference matrix and the test matrix comprises:
creating a reference pattern matrix, the reference pattern matrix corresponding to differences between the test matrix and the reference matrix, and
comparing the reference pattern matrix to a threshold quality level.
4. The method of claim 1, wherein comparing the reference matrix and the test matrix comprises:
creating a cumulative matrix, including summing each row of the test matrix, where each element in a row in the cumulative matrix is a sum of all preceding elements in a corresponding row of the test matrix;
deriving a cumulative distribution function (CDF) matrix based on the cumulative matrix, including assigning, to each of element of the CDF matrix, a value of a corresponding one of the elements in the cumulative matrix divided by a largest value in a corresponding one of the rows in the cumulative matrix; and
comparing each of the elements of the CDF matrix with a corresponding element of the reference matrix to create a reference pattern matrix,
wherein one of the elements of the reference pattern matrix is populated with a zero when either:
the corresponding element of the CDF matrix is populated with zero, or
the corresponding element of the CDF matrix is populated with a value greater than a prespecified value, and
wherein one of the elements of the reference pattern matrix is populated with a 1 when the corresponding element of the CDF matrix is populated with a value greater than zero and less than or equal to the prespecified value.
5. The method of claim 1, wherein evaluating the at least portions of one or more of the one or more second packetized audio messages further comprises evaluating a characteristic of a reconstituted digital representation of the at least portions of one or more of the one or more second packetized audio messages.
6. The method of claim 1, where the plurality of characteristics comprise at least one of:
a dropped packet rate (DPR), or
a round trip packet latency (RTL).
7. The method of claim 1 further comprising:
evaluating, by a network device, the at least portions of the one or more first packetized audio messages to obtain sample measurements of the plurality of characteristics;
processing, by the network device, the sample measurements to produce the estimates of perceived audio quality; and
creating, by the network device, the reference matrix based on the estimates of perceived audio quality of the at least portions of one or more first packetized audio messages.
8. The method of claim 1 further comprising:
comparing, by the network device, the quality level and a threshold quality level; and
generating, by the network device, an error message in response to the quality level being less than the threshold quality level.
9. The method of claim 8, wherein the one or more second packetized audio messages are routed on a first path over a communications network, and further comprising causing, based on generating the error message, one or more third packetized audio messages to be routed on a second path over the communications network, the second path being different from the first path.
10. The method of claim 8, wherein generating the error message occurs in near real time of receiving the one or more second packetized audio messages.
11. The method of claim 8, wherein generating the error message comprises:
generating a description associated with comparing the quality level to the threshold quality level; and
generating a cumulative distribution function (CDF) matrix, where the CDF matrix is derived from the test matrix and includes at least one non-zero entry indicating that the quality level is below the threshold quality level.
12. A method comprising:
receiving, by a network device, a packetized audio message;
evaluating, by the network device, at least portions of the packetized audio message to obtain measurements associated with a plurality of characteristics, each of the plurality of characteristics affecting user perception of audio quality, the evaluating of the at least portions of the packetized audio message comprising:
evaluating a characteristic of a reconstituted digital representation of the packetized audio communication, including:
identifying a difference between successive samples in the reconstituted digital representation, and
calculating at least one of:
a raw distortion measurement associated with the reconstituted digital representation,
a normalized score corresponding to the raw distortion measurement, or
a kurtosis value of a distribution of the difference;
predicting, by the network device and based on the measurements, a quality level associated with the packetized audio message.
13. The method of claim 12 further comprising:
comparing, by the network device, the quality level and a threshold quality level; and
generating, by the network device, an error message in response to the quality level being less than the threshold quality level.
14. An apparatus comprising:
a computing device configured to:
obtain, based on estimates of perceived audio quality of at least portions of one or more first packetized audio messages, a reference matrix that models values of the plurality of characteristics associated with a particular quality level;
create a test matrix using measurements of at least portions of one or more second packetized audio messages, the measurements being associated with the plurality of characteristics;
compare the test matrix and the reference matrix to produce a comparison result; and
predict, based on the comparison result, a quality level associated with the packetized audio message.
15. The apparatus of claim 14, where, the plurality of characteristics include at least one of a dropped packet rate (DPR) or a round trip packet latency (RTL).
16. The apparatus of claim 14, wherein the computing device is further configured to generate an error message when the quality level is below a threshold level.
17. The apparatus of claim 16, wherein the error message includes a cumulative distribution function (CDF) matrix, and the CDF matrix is derived from the test matrix and includes at least one non-zero entry that indicates that the quality level is predicted as below the threshold quality level.
18. The apparatus of claim 14, where the computing device, when predicting the quality level, is further configured to:
create a cumulative matrix, including summing each row of the test matrix, where each element in a row in the cumulative matrix is a sum of all preceding elements in a corresponding one of the rows of the test matrix;
derive a cumulative distribution function (CDF) matrix based on the cumulative matrix, including assigning, to each of the elements of the CDF matrix, a value of a corresponding one of the elements in the cumulative matrix divided by a largest value in a corresponding one of the rows in the cumulative matrix; and
compare each of the elements of the CDF matrix with a corresponding element of the reference matrix to create a reference pattern matrix,
wherein one of the elements of the reference pattern matrix is populated with zero when either
the corresponding element of the CDF matrix is populated with zero, or
the corresponding element of the CDF matrix is populated with a value greater than a prespecified value, and
wherein one of the elements of the reference pattern matrix is populated with 1 when the corresponding element of the CDF matrix is populated with a value between zero and the prespecified value.
19. The apparatus of claim 14, where the computing device, when creating the test matrix, is further configured to evaluate a characteristic of a reconstituted digital representation of the at least portions of the one or more second packetized audio messages.
20. The apparatus of claim 14, where the processor is further configured to generate an error message in response to determining that the quality level is below a threshold level.
21. The apparatus of claim 14 wherein the processor is further configured to:
evaluate the at least portions of the one or more first packetized audio messages to obtain sample measurements of the plurality of characteristics;
process the sample measurements to produce the estimates of perceived audio quality; and
create, based on the estimates of perceived audio quality of the at least portions of one or more first packetized audio messages, the reference matrix.
22. An apparatus comprising:
a computing device configured to:
create a test matrix using measurements of a packetized audio message associated with a plurality of characteristics by:
evaluating a characteristic of a reconstituted digital representation of the packetized audio communication,
identifying a difference between successive samples in the reconstituted digital representation, and
calculating at least one of:
a raw distortion measurement associated with the reconstituted digital representation,
a normalized score corresponding to the raw distortion measurement, or
a kurtosis value of a distribution of the difference; and
predict a quality level associated with the packetized audio message, where predicting the quality level includes comparing the test matrix to a reference matrix that models values of the plurality of characteristics associated with a particular quality level.
23. A non-transitory computer-readable medium having instructions stored thereon configured to cause a computing device to perform operations, the operations comprising:
obtaining a reference matrix based on estimates of perceived audio quality of at least portions of one or more first packetized audio messages, the reference matrix modeling values of a plurality of characteristics associated with a particular quality level;
creating a test matrix using measurements of at least portions of one or more second packetized audio messages associated with the plurality of characteristics;
predicting a quality level associated with the at least portions of one or more second packetized audio messages by comparing the test matrix to the reference matrix.
24. The non-transitory computer-readable medium of claim 23, wherein the plurality of characteristics comprise at least one of:
a dropped packet rate (DPR); or
a round trip packet latency (RTL).
25. The non-transitory computer-readable medium of claim 23, wherein the plurality of characteristics comprise a characteristic of a reconstituted digital representation of the one or more second packetized audio messages.
26. The non-transitory computer-readable medium of claim 23, wherein the one or more second packetized audio messages are routed on a first path over a network, and the operations further comprise routing, in response to generating the error message, one or more third packetized audio messages on a second path over the network, the second path being different from the first path.
27. The non-transitory computer readable medium of claim 23, wherein the operations further comprise:
evaluating the at least portions of the one or more first packetized audio messages to obtain sample measurements of the plurality of characteristics;
processing the sample measurements to produce the estimates of perceived audio quality; and
creating the reference matrix based on the estimates of perceived audio quality of at least portions of the one or more first packetized audio messages.
28. The non-transitory computer-readable medium of claim 27, wherein the operations to generate the error message further comprise:
generating a description associated with comparing the quality level to the threshold quality level; and
generating a cumulative distribution function (CDF) matrix, wherein the CDF matrix is derived from the test matrix and includes at least one non-zero entry indicating that the quality level is below the threshold quality level.
29. A non-transitory computer-readable medium having instructions stored thereon configured to cause a computing device to perform operations, the operations comprising:
create a test matrix using measurements of at least portions of one or more packetized audio messages associated with a plurality of characteristics, the plurality of characteristics comprising a characteristic of a reconstituted digital representation of the packetized audio communication that comprises:
a difference between successive samples in the reconstituted digital representation, and
at least one of:
a raw distortion measurement associated with the reconstituted digital representation,
a normalized score corresponding to the raw distortion measurement, or
a kurtosis value of a distribution of the difference;
predict a quality level associated with the packetized audio message by comparing the test matrix to a reference matrix that models values of the plurality of characteristics associated with a particular quality level.
30. The non-transitory computer readable medium of claim 23, wherein the operations further comprise generating an error message in response to determining that the quality level is below a threshold quality level.