Intelligent monitoring system based on Internet of Things

Abstract

The invention relates to the technical field of intelligent monitoring of industrial equipment, and discloses an intelligent monitoring system based on Internet of Things, which comprises a rotating speed sensing unit, a noise sensing unit, a temperature data acquisition unit and a rotating shaft state output unit. According to the intelligent monitoring system based on the Internet of Things, the rotating speed fluctuation rate deviation value, the sound pressure value deviation value, the temperature change rate deviation value and the cooling oil pollution degree deviation value are calculated, the rotating shaft comprehensive score is calculated according to the values, the state of the rotating shaft is judged according to the rotating shaft comprehensive score, and when the rotating shaft comprehensive score is close to or exceeds 1, the state of the rotating shaft is judged. When the comprehensive score of the rotating shaft is close to 0, the state of the rotating shaft is better, so that the overall state of the rotating shaft can be quickly evaluated through the comprehensive score of the rotating shaft, and operation and maintenance personnel can timely maintain the rotating shaft according to the score; and the service life of the rotating shaft is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring of industrial equipment, and in particular to an intelligent monitoring system based on the Internet of Things. Background Art

[0002] An intelligent monitoring system based on the Internet of Things is an important achievement of modern technological development. It combines sensor technology, wireless communication technology, cloud computing and artificial intelligence to achieve efficient and intelligent monitoring of specific environments or objects. The application scenarios of such systems are very wide, including smart homes, industrial production, environmental protection, public safety and other fields; The shaft is a key component in many industrial machinery and equipment, and they play a vital role in various production processes, such as transmission, conveying, mixing, etc. Therefore, ensuring the normal operation of the shaft is crucial to maintaining the efficient operation of the equipment and extending its service life. The current defect of shaft detection is that the signal of the shaft in the early stage of failure is very weak, which is difficult to effectively identify and the shaft failure cannot be discovered in time, which leads to the deepening of shaft wear. Summary of the invention

[0003] 1. Technical issues to be resolved In view of the shortcomings of the prior art, the present invention provides an intelligent monitoring system based on the Internet of Things, which has the function of calculating the speed fluctuation rate deviation, sound pressure value deviation, temperature change rate deviation and cooling oil contamination deviation, and calculating the shaft comprehensive score according to these values. , and based on the comprehensive score of the axis Determine the state of the shaft, when the shaft comprehensive score When it is close to or exceeds 1, it indicates that the shaft has a fault or other problem and needs to be shut down for further inspection and maintenance. The closer it is to 0, the better the state of the axis is, and the comprehensive score of the axis can be obtained. The overall condition of the shaft can be quickly evaluated so that the operation and maintenance personnel can perform timely maintenance on the shaft according to the score, thereby extending the service life of the shaft and solving the above-mentioned problems.

[0004] (II) Technical solution To achieve the above-mentioned object, the present invention provides the following technical solutions: an intelligent monitoring system based on the Internet of Things, comprising a rotation speed sensing unit, a noise sensing unit, a temperature data acquisition unit, an oil contamination sensing unit, a shaft state analysis unit and a shaft state output unit; The speed sensing unit is used to collect real-time speed data of the rotating shaft when it is working, and send the real-time speed data to the rotating shaft state analysis unit connected to the speed sensing unit; The noise sensing unit is used to collect real-time sound data of the rotating shaft when it is working, and send the real-time sound data to the rotating shaft state analysis unit connected to the noise sensing unit; The temperature data acquisition unit is used to collect real-time temperature data of the rotating shaft when it is working, and send the real-time temperature data to the rotating shaft state analysis unit connected to the temperature data acquisition unit; The oil contamination sensing unit is used to collect the cooling oil contamination degree of the shaft when it is working, and send the cooling oil contamination degree to the shaft state analysis unit; The shaft state analysis unit combines a plurality of real-time speed data, a plurality of real-time noise data, and a plurality of real-time temperature data into corresponding real-time speed data sets, real-time noise data sets, and real-time temperature data sets according to the same time interval; the shaft state analysis unit obtains the maximum real-time speed data and the minimum real-time speed data in the real-time speed data sets; the shaft turntable analysis unit calculates the speed mean according to the real-time speed data sets, and calculates the speed fluctuation rate according to the speed mean, the maximum real-time speed data, and the minimum real-time speed data; the shaft state analysis unit calculates the noise mean according to the real-time noise data sets, and calculates the sound pressure value of the shaft when working according to the noise mean; the shaft state analysis unit calculates the temperature change rate according to the last real-time temperature data in the real-time temperature data sets and the duration of the time interval; the shaft state analysis unit calculates the cooling oil contamination degree according to the cooling oil contamination degree, the maximum cooling oil contamination degree, and the cooling oil initial contamination degree, and the cooling oil maximum contamination degree and the cooling oil initial contamination degree are oil product parameters of the cooling oil; The shaft state analysis unit is respectively preset with a speed fluctuation threshold, a maximum sound pressure value threshold and a maximum temperature change rate threshold. The shaft state analysis unit calculates the speed fluctuation rate deviation according to the speed fluctuation rate and the speed fluctuation threshold. The shaft state analysis unit calculates the sound pressure value deviation according to the sound pressure value and the maximum sound pressure value threshold. The shaft state analysis unit calculates the temperature change rate deviation according to the temperature change rate and the maximum temperature change rate threshold. The shaft state analysis unit calculates the cooling oil contamination degree deviation according to the cooling oil contamination degree and the maximum cooling oil contamination degree. The shaft state analysis unit generates a comprehensive shaft score according to the speed fluctuation rate deviation, the sound pressure value deviation, the temperature change rate deviation and the cooling oil contamination degree deviation, and determines the shaft state according to the comprehensive shaft score, and sends the shaft state to the shaft state output unit, and the shaft state output unit outputs the current state of the shaft to the operation and maintenance personnel.

[0005] Preferably, the real-time speed data set is expressed as , the real-time noise data set is expressed as: , the real-time temperature data set is represented as The maximum real-time speed data in the real-time speed data set is expressed as , the minimum real-time speed data in the real-time speed data set is expressed as .

[0006] Preferably, the rotation speed mean value calculation expression is:

[0007] In the formula, Expressed as the mean speed, Indicates that all real-time speed data in the real-time speed data set are summed, and the summed result is divided by the number of real-time speed data in the real-time speed data set The result is the average speed .

[0008] Preferably, the rotation speed fluctuation rate calculation expression is as follows:

[0009] In the formula, Expressed as the speed fluctuation rate, It represents the difference between the maximum real-time speed data in the real-time speed data set and the minimum real-time speed data in the real-time speed data set. The difference between the two divided by the speed mean is the speed fluctuation rate. .

[0010] Preferably, the noise mean expression is:

[0011] In the formula, represents the noise mean, Indicates that all the real-time noise data in the real-time noise data set are summed, and the result of the sum is divided by the number of real-time noise data in the real-time noise data set , the result is the noise mean .

[0012] Preferably, the sound pressure value calculation expression is as follows:

[0013] In the formula, Indicates the sound pressure value, 20 means The result is converted to dB, Represents a logarithmic function that compresses the dynamic range of sound pressure values. Represents the noise mean, its unit is pa, represents the reference sound pressure data, It means converting the mean value of the noise during the operation of the shaft into the sound pressure value on a logarithmic scale.

[0014] Preferably, the temperature change rate calculation expression is as follows:

[0015] In the formula, Expressed as the rate of temperature change, It is expressed as the duration of the time interval, Indicates the real-time temperature data set The difference between the first real-time temperature data and the first real-time temperature data, divided by the length of the time interval The result is the temperature change rate .

[0016] Preferably, the cooling oil contamination degree calculation expression is:

[0017] In the formula, Expressed as the degree of cooling oil contamination, Indicates the degree of cooling oil contamination, Indicates the initial contamination degree of cooling oil, Indicates the maximum contamination degree of the cooling oil.

[0018] Preferably, the speed fluctuation threshold is expressed as , the maximum threshold of the sound pressure value is expressed as , the maximum temperature change rate threshold ; The speed fluctuation rate deviation calculation expression is as follows:

[0019] In the formula, Indicates the speed fluctuation rate deviation; The sound pressure deviation value calculation expression is as follows:

[0020] In the formula, Indicates the deviation of sound pressure value; The temperature change rate deviation value calculation expression is as follows:

[0021] In the formula, Indicates the deviation value of temperature change rate; The cooling oil contamination deviation value calculation expression is as follows:

[0022] In the formula, Expressed as cooling oil contamination deviation value.

[0023] Preferably, the calculation expression of the rotation axis comprehensive score is as follows:

[0024] In the formula, Expressed as a composite score of the rotation axis.

[0025] Compared with the prior art, the present invention provides an intelligent monitoring system based on the Internet of Things, which has the following beneficial effects: The invention calculates the rotation speed fluctuation rate deviation, the sound pressure value deviation, the temperature change rate deviation and the cooling oil contamination deviation, and calculates the shaft comprehensive score based on these values. , and based on the comprehensive score of the axis Determine the state of the shaft, when the shaft comprehensive score When it is close to or exceeds 1, it indicates that the shaft has a fault or other problem and needs to be shut down for further inspection and maintenance. The closer it is to 0, the better the state of the axis is, and the comprehensive score of the axis can be obtained. Quickly evaluate the overall status of the shaft so that operation and maintenance personnel can perform timely maintenance on the shaft based on the score to extend the service life of the shaft. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] In order to effectively identify the early failure of the shaft and issue early warnings in time to avoid further shaft loss, an intelligent monitoring system based on the Internet of Things is proposed. Figure 1 ,The system is composed of a speed sensing unit, a noise sensing unit, a temperature data ,acquisition unit, an oil contamination sensing unit, a shaft state analysis unit and a shaft state output unit.

[0029] Among them, the rotation speed sensing unit, the noise sensing unit, the temperature data acquisition unit and the oil contamination sensing unit are respectively connected to the shaft state analysis unit.

[0030] The speed sensing unit is used to collect the real-time speed data of the rotating shaft when it is working, the noise sensing unit is used to collect the real-time sound data of the rotating shaft when it is working, the temperature data collection unit is used to collect the real-time temperature data of the rotating shaft when it is working, and the oil contamination sensing unit is used to collect the cooling oil contamination degree of the rotating shaft when it is working. After these units collect the corresponding data, they send these data to the rotating shaft state analysis unit; After receiving these data, the shaft state analysis unit combines the multiple real-time speed data, multiple real-time noise data, and multiple real-time temperature data into corresponding real-time speed data sets, real-time noise data sets, and real-time temperature data sets according to the same time interval.

[0031] Its: The real-time speed data set is expressed as , the real-time noise dataset is represented as: , the real-time temperature dataset is represented as .

[0032] The shaft state analysis unit obtains the maximum real-time speed data and the minimum real-time speed data in the real-time speed data set. The maximum real-time speed data in the real-time speed data set is expressed as , the minimum real-time speed data in the real-time speed data set is expressed as , the shaft turntable analysis unit calculates the mean speed according to the real-time speed data set, and its specific calculation expression is as follows:

[0033] In the formula, Expressed as the mean speed, Indicates that all real-time speed data in the real-time speed data set are summed, and the summed result is divided by the number of real-time speed data in the real-time speed data set The result is the average speed .

[0034] The shaft state analysis unit calculates the speed fluctuation rate according to the speed mean, the maximum real-time speed data and the minimum real-time speed data. The calculation expression is as follows:

[0035] In the formula, Expressed as the speed fluctuation rate, It represents the difference between the maximum real-time speed data in the real-time speed data set and the minimum real-time speed data in the real-time speed data set. The difference between the two divided by the speed mean is the speed fluctuation rate. .

[0036] The shaft state analysis unit calculates the noise mean value based on the real-time noise data set, that is, the calculation expression is as follows:

[0037] In the formula, represents the noise mean, Indicates that all the real-time noise data in the real-time noise data set are summed, and the result of the sum is divided by the number of real-time noise data in the real-time noise data set , the result is the noise mean .

[0038] The shaft state analysis unit calculates the sound pressure value of the shaft when it is working according to the noise mean value. The calculation expression is as follows:

[0039] In the formula, Indicates the sound pressure value, 20 means The result is converted to dB, Represents a logarithmic function that compresses the dynamic range of sound pressure values. Represents the noise mean, its unit is pa, represents the reference sound pressure data, It means converting the mean value of the noise during the operation of the shaft into the sound pressure value on a logarithmic scale.

[0040] The shaft state analysis unit calculates the temperature change rate according to the last real-time temperature data in the real-time temperature data set and the duration of the time interval, as shown below:

[0041] In the formula, Expressed as the rate of temperature change, It is expressed as the duration of the time interval, Indicates the real-time temperature data set The difference between the first real-time temperature data and the first real-time temperature data, divided by the length of the time interval The result is the temperature change rate .

[0042]

[0043] In the formula, Expressed as the rate of temperature change, It is expressed as the duration of the time interval, Indicates the real-time temperature data set The difference between the first real-time temperature data and the first real-time temperature data, divided by the length of the time interval The result is the temperature change rate .

[0044] The shaft state analysis unit calculates the cooling oil contamination degree according to the cooling oil contamination degree, the maximum cooling oil contamination degree and the initial cooling oil contamination degree, as shown below:

[0045] In the formula, Expressed as the degree of cooling oil contamination, Indicates the degree of cooling oil contamination, Indicates the initial contamination degree of cooling oil, Indicates the maximum contamination degree of the cooling oil.

[0046] It should be noted that the maximum contamination degree of the cooling oil and the initial contamination degree of the cooling oil mentioned above are oil quality parameters of the cooling oil.

[0047] The storage medium in the shaft state analysis unit also presets a speed fluctuation threshold, a maximum sound pressure value threshold, and a maximum temperature change rate threshold. The speed fluctuation threshold is expressed as , the maximum threshold of sound pressure value is expressed as , maximum temperature change rate threshold .

[0048] The shaft state analysis unit calculates the speed fluctuation rate deviation according to the speed fluctuation rate and the speed fluctuation threshold. The calculation expression is as follows:

[0049] In the formula, Indicates the speed fluctuation rate deviation.

[0050] The shaft state analysis unit calculates the sound pressure deviation value according to the sound pressure value and the maximum threshold value of the sound pressure value. The calculation expression is as follows:

[0051] In the formula, Indicates the sound pressure deviation value.

[0052] The shaft state analysis unit calculates the temperature change rate deviation value according to the temperature change rate and the maximum temperature change rate threshold value. The calculation expression is as follows:

[0053] In the formula, Indicates the temperature change rate deviation value.

[0054] The shaft state analysis unit calculates the cooling oil contamination deviation value according to the cooling oil contamination degree and the cooling oil maximum contamination degree. The calculation expression is as follows:

[0055] In the formula, Expressed as cooling oil contamination deviation value.

[0056] After the speed fluctuation rate deviation, sound pressure value deviation, temperature change rate deviation and cooling oil contamination deviation are calculated, the shaft state analysis unit calculates the shaft comprehensive score according to these deviation values, as shown below:

[0057] In the formula, Expressed as a composite score of the rotation axis.

[0058] After the shaft comprehensive score is calculated, the shaft state analysis unit determines the shaft state according to the shaft comprehensive score. The specific judgment criteria are as follows: When the axis comprehensive rating When it is close to or exceeds 1, it indicates that the shaft has a fault or other problem and needs to be shut down for further inspection and maintenance. The closer it is to 0, the better the state of the axis is, and the comprehensive score of the axis can be obtained. Quickly evaluate the overall status of the shaft so that operation and maintenance personnel can perform timely maintenance on the shaft based on the score to extend the service life of the shaft.

[0059] After the comprehensive score of the shaft is calculated, the shaft status analysis unit sends the comprehensive score of the shaft to the shaft status output unit, and the shaft status output unit outputs the current state of the shaft to the operation and maintenance personnel, so that the operation and maintenance personnel can grasp the real-time state of the shaft in time.

[0060] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent monitoring system based on the Internet of Things, characterized by: It includes a speed sensing unit, a noise sensing unit, a temperature data acquisition unit, an oil contamination sensing unit, a shaft state analysis unit and a shaft state output unit; The speed sensing unit is used to collect real-time speed data of the rotating shaft when it is working, and send the real-time speed data to the rotating shaft state analysis unit connected to the speed sensing unit; The noise sensing unit is used to collect real-time sound data of the rotating shaft when it is working, and send the real-time sound data to the rotating shaft state analysis unit connected to the noise sensing unit; The temperature data acquisition unit is used to collect real-time temperature data of the rotating shaft when it is working, and send the real-time temperature data to the rotating shaft state analysis unit connected to the temperature data acquisition unit; The oil contamination sensing unit is used to collect the cooling oil contamination degree of the shaft when it is working, and send the cooling oil contamination degree to the shaft state analysis unit; The shaft state analysis unit combines a plurality of real-time speed data, a plurality of real-time noise data, and a plurality of real-time temperature data into corresponding real-time speed data sets, real-time noise data sets, and real-time temperature data sets according to the same time interval; the shaft state analysis unit obtains the maximum real-time speed data and the minimum real-time speed data in the real-time speed data sets; the shaft turntable analysis unit calculates the speed mean according to the real-time speed data sets, and calculates the speed fluctuation rate according to the speed mean, the maximum real-time speed data, and the minimum real-time speed data; the shaft state analysis unit calculates the noise mean according to the real-time noise data sets, and calculates the sound pressure value of the shaft when working according to the noise mean; the shaft state analysis unit calculates the temperature change rate according to the last real-time temperature data in the real-time temperature data sets and the duration of the time interval; the shaft state analysis unit calculates the cooling oil contamination degree according to the cooling oil contamination degree, the maximum cooling oil contamination degree, and the cooling oil initial contamination degree, and the cooling oil maximum contamination degree and the cooling oil initial contamination degree are oil product parameters of the cooling oil; The shaft state analysis unit is respectively preset with a speed fluctuation threshold, a maximum sound pressure value threshold and a maximum temperature change rate threshold. The shaft state analysis unit calculates the speed fluctuation rate deviation according to the speed fluctuation rate and the speed fluctuation threshold. The shaft state analysis unit calculates the sound pressure value deviation according to the sound pressure value and the maximum sound pressure value threshold. The shaft state analysis unit calculates the temperature change rate deviation according to the temperature change rate and the maximum temperature change rate threshold. The shaft state analysis unit calculates the cooling oil contamination degree deviation according to the cooling oil contamination degree and the maximum cooling oil contamination degree. The shaft state analysis unit generates a comprehensive shaft score according to the speed fluctuation rate deviation, the sound pressure value deviation, the temperature change rate deviation and the cooling oil contamination degree deviation, and determines the shaft state according to the comprehensive shaft score, and sends the shaft state to the shaft state output unit, and the shaft state output unit outputs the current state of the shaft to the operation and maintenance personnel.

2. According to claim 1, the intelligent monitoring system based on the Internet of Things is characterized by: The real-time speed data set is expressed as , the real-time noise data set is expressed as: , the real-time temperature data set is represented as The maximum real-time speed data in the real-time speed data set is expressed as , the minimum real-time speed data in the real-time speed data set is expressed as .

3. The intelligent monitoring system based on the Internet of Things according to claim 2 is characterized in that: The speed mean value calculation expression is: In the formula, Expressed as the mean speed, Indicates that all real-time speed data in the real-time speed data set are summed, and the summed result is divided by the number of real-time speed data in the real-time speed data set The result is the mean speed .

4. The intelligent monitoring system based on the Internet of Things according to claim 3 is characterized in that: The speed fluctuation rate calculation expression is as follows: In the formula, Expressed as the speed fluctuation rate, It represents the difference between the maximum real-time speed data in the real-time speed data set and the minimum real-time speed data in the real-time speed data set. The difference between the two divided by the speed mean is the speed fluctuation rate. .

5. The intelligent monitoring system based on the Internet of Things according to claim 4 is characterized in that: The noise mean expression is: In the formula, represents the noise mean, Indicates that all the real-time noise data in the real-time noise data set are summed, and the result of the sum is divided by the number of real-time noise data in the real-time noise data set , the result is the noise mean .

6. The intelligent monitoring system based on the Internet of Things according to claim 5 is characterized in that: The sound pressure value calculation expression is as follows: In the formula, Indicates the sound pressure value, 20 means The result is converted to dB, Represents a logarithmic function that compresses the dynamic range of sound pressure values. Represents the noise mean, its unit is pa, represents the reference sound pressure data, It means converting the mean value of the noise during the operation of the shaft into the sound pressure value on a logarithmic scale.

7. The intelligent monitoring system based on the Internet of Things according to claim 6 is characterized in that: The temperature change rate calculation expression is as follows: In the formula, Expressed as the rate of temperature change, It is expressed as the duration of the time interval, Indicates the real-time temperature data set The difference between the first real-time temperature data and the first real-time temperature data, divided by the length of the time interval The result is the temperature change rate .

8. The intelligent monitoring system based on the Internet of Things according to claim 7 is characterized in that: The cooling oil contamination degree calculation expression is: In the formula, Expressed as the degree of cooling oil contamination, Indicates the degree of cooling oil contamination, Indicates the initial contamination degree of cooling oil, Indicates the maximum contamination degree of the cooling oil.

9. The intelligent monitoring system based on the Internet of Things according to claim 8, characterized in that: The speed fluctuation threshold is expressed as , the maximum threshold of the sound pressure value is expressed as , the maximum temperature change rate threshold ; The speed fluctuation rate deviation calculation expression is as follows: In the formula, Indicates the speed fluctuation rate deviation; The sound pressure deviation value calculation expression is as follows: In the formula, Indicates the deviation of sound pressure value; The temperature change rate deviation value calculation expression is as follows: In the formula, Indicates the deviation value of temperature change rate; The cooling oil contamination deviation value calculation expression is as follows: In the formula, Expressed as cooling oil contamination deviation value.

10. The intelligent monitoring system based on the Internet of Things according to claim 9, characterized in that: The calculation expression of the rotation axis comprehensive score is as follows: In the formula, Expressed as a composite score of the rotation axis.

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