Industrial Internet of Things control method and system for inspection data processing

Abstract

The invention relates to the technical field of industrial equipment monitoring and prediction maintenance, and particularly discloses an industrial Internet of Things control method and system for inspection data processing, and the method comprises the steps: firstly, collecting a vibration signal of equipment, extracting key time domain features, evaluating the vibration state of the equipment, and carrying out the statistics of the operation time, starting frequency, used life and maintenance record of the equipment; the method comprises the following steps: firstly, quantifying the use intensity and maintenance effect of equipment, then constructing an equipment aging model and predicting the aging degree of the equipment based on the data, automatically triggering an early warning mechanism and sending an equipment service life early warning signal by a system when a predicted value exceeds a preset threshold value, and finally, deeply analyzing the specific aging reason of the equipment in an early warning state. The method can be used for timely notifying management personnel and taking targeted prevention measures, and can be used for effectively improving the equipment maintenance efficiency, reducing non-planned shutdown and ensuring the stability and safety of the production process.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial equipment monitoring and predictive maintenance, and in particular to an industrial Internet of Things control method and system for inspection data processing. Background Art

[0002] Currently, in the field of industrial equipment monitoring and predictive maintenance, industrial equipment monitoring and predictive maintenance began with post-event and regular maintenance. Monitoring technologies such as vibration analysis were introduced in the 1970s, and computer-aided systems improved management efficiency in the 1990s. In the 21st century, the Internet of Things, big data, and AI promoted real-time monitoring and predictive analysis, realizing the transformation from passive to active maintenance.

[0003] Traditional industrial equipment management relies on regular manual inspections and preventive maintenance strategies. This usually includes regular inspections of the physical condition of the equipment, recording the number of operating hours, and scheduling equipment maintenance based on empirical rules. However, manual inspections are time-consuming and costly, and may miss signs of early equipment failures due to long inspection intervals. Preventive maintenance is often based on a fixed schedule and cannot respond to the actual operating conditions of the equipment in real time, which may lead to unnecessary maintenance or missed opportunities for necessary repairs. Excessive maintenance not only increases costs, but may also interfere with production processes, while insufficient maintenance can lead to equipment failures and production interruptions.

[0004] In view of the above problems, the industry urgently needs a system that can monitor equipment status in real time, intelligently analyze data, predict equipment aging trends and automatically trigger early warning signals to achieve more accurate and efficient equipment maintenance, which can not only significantly reduce unplanned downtime, but also reduce maintenance costs and improve the overall reliability of equipment. Summary of the invention

[0005] The purpose of the present invention is to provide an industrial Internet of Things control method and system for inspection data processing to solve the problems raised in the above background.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] An industrial Internet of Things control method for inspection data processing includes the following steps:

[0008] Obtain the vibration signal value of the equipment and extract the time domain characteristics of the vibration signal, including the vibration peak value and root mean square value;

[0009] The vibration value of the equipment during the monitoring period is obtained through the vibration peak value and root mean square value of the equipment;

[0010] Obtain the total running time of the equipment and the running time during the monitoring period, and obtain the equipment usage intensity value, equipment startup frequency and equipment used life value;

[0011] The usage value of the equipment during the monitoring period is obtained through the usage intensity value, startup frequency and used life value of the equipment;

[0012] Obtain the number of maintenance times of the equipment in each monitoring cycle, and obtain the average maintenance time interval of the equipment in the monitoring cycle;

[0013] Obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period, and obtain the maintenance effect value of the equipment within the monitoring period;

[0014] The maintenance value of the equipment is obtained through the average maintenance time interval and maintenance effect value of the equipment within the monitoring period;

[0015] Based on the vibration value, usage value and maintenance value of the equipment during the monitoring period, the predicted aging value of the equipment is obtained, and the equipment service life warning signal and the equipment service life normal signal are generated;

[0016] Based on the equipment life warning signal, the vibration value, usage value and maintenance value are analyzed to obtain the specific cause of equipment aging, generate corresponding alarm signals, and send alarm notifications to management personnel.

[0017] As a further solution of the present invention: all vibration signal values ​​are processed to extract the time domain features of the vibration signals. Specifically: all vibration signal values ​​are integrated into a vibration sequence, and the vibration signal value P with the largest absolute value in the vibration sequence is extracted. max , extract the vibration signal value P with the smallest absolute value in the vibration sequence min ;

[0018] By formula Get the vibration peak value Pk and assign a weight w1 to it;

[0019] By formula Get the root mean square data Jfg of the vibration signal, where X i is the vibration signal value, N is the number of time subunits in the monitoring period, i is the sequence number of time subunits in the monitoring period, i = 1, 2, ..., N;

[0020] Based on the root mean square data Jfg of the vibration signal in each monitoring cycle, extract the maximum root mean square data Jfg in all monitoring cycles max and the minimum root mean square data Jfg min , through the formula Get the root mean square value RMS and assign it a weight w2;

[0021] By formula Vz j =w1*Pk+w2*RMS to calculate the vibration value Vz of the equipment during the monitoring period j, where j is the number of monitoring cycle sequences within the total monitoring time, j = 1, 2, ..., n.

[0022] As a further solution of the present invention: the use intensity value of the device, the startup frequency of the device and the used life of the device are obtained, and the specific process is as follows:

[0023] Get the running time and startup times of the equipment during the monitoring period;

[0024] Compare the running time of the equipment during the monitoring cycle with the total duration of the monitoring cycle to obtain the equipment usage intensity value SYQ j ;

[0025] Compare the number of times the device is started within the detection period with the total duration of the detection period to obtain the device's startup frequency data PJ;

[0026] By formula Get the starting frequency PJQ j , where PJ max PJ is the maximum startup frequency data of the device in all monitoring cycles. min The preset minimum startup frequency data of the equipment in all monitoring cycles;

[0027] Obtain the total operating time of the equipment, compare the total operating time of the equipment with the rated life of the equipment, and obtain the used life value SMZ of the equipment j .

[0028] As a further solution of the present invention: the process of obtaining the usage value of the device during the monitoring period is:

[0029] The intensity of use of the equipment is SYQ j , starting frequency PJQ j and the used life value SMZ j to process;

[0030] By formula SYP j =SYQ j *PJQ j *SMZ j Calculate the usage value SYP of the equipment during the monitoring period j .

[0031] As a further solution of the present invention: the process of obtaining the average maintenance time interval value of the equipment within the monitoring period is:

[0032] Obtain the maintenance records of the equipment in each monitoring cycle and extract the number of maintenance times of the equipment in the monitoring cycle;

[0033] Compare the running time of the equipment in the monitoring period with the number of maintenance times of the equipment in the monitoring period to obtain the average maintenance time interval data BY of the equipment in the monitoring period;

[0034] By formula Get the maintenance average time interval value BYS j , where BY max The maximum maintenance interval data of the equipment in all monitoring cycles, BY min It is the minimum maintenance time interval data of the equipment in all monitoring cycles.

[0035] As a further solution of the present invention: the process of obtaining the maintenance value of the equipment within the monitoring period is:

[0036] Based on the average maintenance time interval, obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period;

[0037] The vibration value after maintenance is calculated by ratio with the vibration value before maintenance to obtain the single maintenance effect value;

[0038] Integrate the single maintenance values ​​calculated after each maintenance of the equipment, and use the mean calculation formula to obtain the maintenance effect value of the equipment within the monitoring period;

[0039] The average maintenance time interval of the equipment is multiplied by the maintenance effect value of the equipment to obtain the maintenance value of the equipment BYZ j .

[0040] As a further solution of the present invention: the process of obtaining the equipment service life warning signal and the equipment service life normal signal is as follows:

[0041] Based on the vibration value Vz of the equipment during the monitoring period j , use value SYP j and maintenance value BYZ j , through the prediction formula YSM = b 1 V j +b 2 SYP j +b 3 BYZ j Calculate the predicted aging value YSM of the equipment;

[0042] Compare the predicted aging value YSM with the threshold of the aging value;

[0043] If the predicted aging value is greater than or equal to the aging value threshold, it means that the remaining service life of the equipment is insufficient, and an equipment service life warning signal is generated;

[0044] If the predicted aging value is less than the aging value threshold, it means that the remaining service life of the equipment is sufficient, and a normal equipment service life signal is generated.

[0045] As a further solution of the present invention: based on the equipment service life warning signal, the vibration value is analyzed, specifically:

[0046] Based on the equipment life warning signal, the vibration value is compared with the vibration threshold, the use threshold and the maintenance threshold to obtain one or more of the vibration value, the use value and the maintenance value that is greater than or equal to the threshold;

[0047] Based on the situation that the vibration value of the equipment is greater than or equal to the vibration threshold, the vibration signal of the equipment when the time subunit is in the middle of the monitoring period is obtained, and the fast Fourier transform algorithm is used to convert the vibration signal into the frequency domain to obtain the spectrum;

[0048] The converted spectrum data is displayed as a graph, with the horizontal axis representing frequency and the vertical axis representing amplitude;

[0049] Based on the spectrum graph, the motor speed of the device is obtained, and the fundamental harmonic frequency of the device is calculated by the motor speed of the device. By traversing the spectrum graph, the frequency peak closest to the fundamental harmonic frequency in the spectrum graph is obtained and recorded as the fundamental frequency of the device;

[0050] Obtain peaks in the spectrum that are inconsistent with the fundamental frequency and the fundamental frequency harmonic frequency, calculate the difference between these peaks and the fundamental frequency, and if the difference is greater than the difference threshold, mark the peak as an abnormal peak;

[0051] If the harmonic frequency of the abnormal peak is twice or more than the fundamental harmonic frequency, an equipment imbalance alarm signal is generated;

[0052] If there are random frequencies that are irregular and unrelated to the fundamental frequency and harmonic frequency that appear in the spectrum for a period of time, a loose equipment component alarm signal is generated;

[0053] If the abnormal peaks appear regularly at a specific frequency, a component damage alarm signal is generated.

[0054] As a further solution of the present invention: based on the equipment life warning signal, the usage value and maintenance value are analyzed, and the specific process is as follows:

[0055] Based on the situation that the usage value of the device is greater than or equal to the usage threshold, the usage intensity value, the standard value of the startup frequency and the used life value of the device are compared with the corresponding thresholds respectively;

[0056] If the usage intensity value of the device is greater than or equal to the usage intensity threshold, an excessive usage intensity alarm signal is generated;

[0057] If the standard value of the device startup frequency is greater than or equal to the standard value threshold of the startup frequency, a high startup frequency alarm signal is generated;

[0058] If the used life value of the equipment is greater than or equal to the used life value threshold, an equipment replacement alarm signal is generated;

[0059] Based on the situation that the maintenance value of the equipment is greater than or equal to the maintenance value threshold, the average maintenance time interval and the maintenance effect value of the equipment are compared with the corresponding thresholds respectively;

[0060] If the average maintenance time interval is greater than or equal to the average maintenance time interval threshold, an equipment maintenance alarm signal is generated;

[0061] If the maintenance effect value is greater than or equal to the maintenance effect value threshold, a maintenance mode change alarm signal is generated.

[0062] As a further solution of the present invention: an industrial Internet of Things control system for inspection data processing, characterized in that:

[0063] The vibration signal acquisition and analysis module obtains the vibration signal value of the equipment and extracts the time domain characteristics of the vibration signal, including the vibration peak value and the root mean square value;

[0064] The vibration value of the equipment during the monitoring period is obtained through the vibration peak value and root mean square value of the equipment;

[0065] The effect collection and analysis module obtains the total running time of the equipment and the running time in the monitoring period to obtain the equipment's usage intensity value, equipment startup frequency and equipment's used life value;

[0066] The usage value of the equipment during the monitoring period is obtained through the usage intensity value, startup frequency and used life value of the equipment;

[0067] Obtain the number of maintenance times of the equipment in each monitoring cycle, and obtain the average maintenance time interval of the equipment in the monitoring cycle;

[0068] Obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period, and obtain the maintenance effect value of the equipment within the monitoring period;

[0069] The maintenance value of the equipment is obtained through the average maintenance time interval and maintenance effect value of the equipment within the monitoring period;

[0070] The aging prediction module obtains the predicted aging value of the equipment through the vibration value, usage value and maintenance value of the equipment during the monitoring period, and generates equipment service life warning signal and equipment service life normal signal;

[0071] The aging analysis and warning module analyzes the vibration value, usage value and maintenance value through the equipment service life warning signal, obtains the specific cause of equipment aging, and sends an alarm notification.

[0072] Beneficial effects of the present invention:

[0073] (1) The system comprehensively collects the vibration signals, behavior status and maintenance information of the equipment and uses advanced data analysis algorithms to accurately predict the aging degree and remaining service life of the equipment. Long-term equipment health monitoring helps to extend the service life and reduce capital expenditures. By identifying potential equipment failures in advance, enterprises can implement preventive maintenance and optimize maintenance strategies.

[0074] (2) Once abnormal signs are detected, the system immediately generates an early warning, conducts in-depth analysis of the cause of aging, and promptly notifies relevant personnel to ensure that the problem is resolved in a timely manner. The early warning mechanism enhances workplace safety, reduces the possibility of accidents, avoids excessive maintenance, reduces costs, and improves equipment availability and overall efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] The present invention will be further described below in conjunction with the accompanying drawings.

[0076] Figure 1 It is a structural schematic diagram of an industrial Internet of Things control system for inspection data processing of the present invention;

[0077] Figure 2 It is a structural schematic diagram of an industrial Internet of Things control method for inspection data processing in the present invention;

[0078] Figure 3 It is a structural schematic diagram of performing abnormal analysis on the vibration signal of the device based on the case where the vibration value of the device is greater than a threshold value in the present invention. DETAILED DESCRIPTION

[0079] 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.

[0080] See also Figure 1-2 As shown, the present invention is an industrial Internet of Things control method for inspection data processing, comprising:

[0081] Example 1

[0082] Step 1

[0083] Obtain the vibration signal value of the equipment and extract the time domain characteristics of the vibration signal, including the vibration peak value and root mean square value;

[0084] The vibration value of the equipment during the monitoring period is obtained through the vibration peak value and root mean square value of the equipment; Step 2

[0085] Obtain the total running time of the equipment and the running time during the monitoring period, and obtain the equipment usage intensity value, equipment startup frequency and equipment used life value;

[0086] The usage value of the equipment during the monitoring period is obtained through the usage intensity value, startup frequency and used life value of the equipment;

[0087] Obtain the number of maintenance times of the equipment in each monitoring cycle, and obtain the average maintenance time interval of the equipment in the monitoring cycle;

[0088] Obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period, and obtain the maintenance effect value of the equipment within the monitoring period;

[0089] The maintenance value of the equipment is obtained through the average maintenance time interval and maintenance effect value of the equipment within the monitoring period;

[0090] Step 3

[0091] Based on the vibration value, usage value and maintenance value of the equipment during the monitoring period, the predicted aging value of the equipment is obtained, and the equipment service life warning signal and the equipment service life normal signal are generated;

[0092] Step 4

[0093] Based on the equipment life warning signal, the vibration value, usage value and maintenance value are analyzed to obtain the specific cause of equipment aging and send an alarm notification.

[0094] Example 2

[0095] The total monitoring time of the equipment is divided into a number of monitoring cycles of equal length, and the monitoring cycle is divided into a number of time sub-units of equal length, and the vibration signal value of the equipment is obtained when each time sub-unit is in the middle moment;

[0096] All vibration signal values ​​are processed to extract the time domain characteristics of the vibration signal. Specifically:

[0097] All vibration signal values ​​are integrated into a vibration sequence, and the vibration signal value with the largest absolute value in the vibration sequence is extracted, which is recorded as P max , extract the vibration signal value P with the smallest absolute value in the vibration sequence min ;

[0098] By formula Get the vibration peak value Pk and assign a weight w1 to it;

[0099] By formula Get the root mean square data Jfg of the vibration signal, where X i is the vibration signal value, N is the number of time subunits in the monitoring period, i is the sequence number of time subunits in the monitoring period, i = 1, 2, ..., N;

[0100] Based on the root mean square data Jfg of the vibration signal in each monitoring cycle, extract the maximum root mean square data Jfg in all monitoring cycles max and the minimum root mean square data Jfg min , through the formula Get the root mean square value RMS of the equipment vibration signal during the monitoring period and assign a weight w2 to it;

[0101] By formula Vz j =w1*Pk+w2*RMS to calculate the vibration value Vz of the equipment during the monitoring period j , where j is the number of monitoring cycle sequences within the total monitoring time, j = 1, 2, ..., n;

[0102] It should be noted that in the analysis of equipment degradation, the vibration peak value P is the maximum fluctuation intensity in the equipment vibration signal, which can be used to analyze whether the equipment is subjected to instantaneous impact. The root mean square value Jfg is the average fluctuation intensity in the equipment vibration signal, which is the continuous vibration level of the equipment and can be used to analyze whether the equipment has impact loads or local failures.

[0103] Example 3

[0104] Get the running time and startup times of the equipment during the monitoring period;

[0105] Compare the running time of the equipment during the monitoring cycle with the total duration of the monitoring cycle to obtain the equipment usage intensity value SYQ j ;

[0106] Compare the number of times the device is started within the detection period with the total duration of the detection period to obtain the device's startup frequency data PJ;

[0107] By formula Get the starting frequency PJQ j , where PJ max PJ is the maximum startup frequency data of the device in all monitoring cycles. min The preset minimum startup frequency data of the equipment in all monitoring cycles;

[0108] Obtain the total operating time of the equipment, compare the total operating time of the equipment with the rated life of the equipment, and obtain the used life value SMZ of the equipmentj ;

[0109] By formula SYP j =SYQ j *PJQ j *SMZ j Calculate the usage value SYP of the equipment during the monitoring period j ;

[0110] It should be noted that in addition to the intensity of equipment use and the duration of operation, frequent startup of equipment will cause additional burden on the electrical system of the equipment, resulting in accelerated aging of the equipment. Therefore, the greater the equipment use value, the shorter the remaining service life of the equipment.

[0111] Obtain the maintenance records of the equipment in each monitoring cycle and extract the number of maintenance times of the equipment in the monitoring cycle;

[0112] Compare the running time of the equipment in the monitoring period with the number of maintenance times of the equipment in the monitoring period to obtain the average maintenance time interval data BY of the equipment in the monitoring period;

[0113] By formula Get the maintenance average time interval value BYS j , where BY max The maximum maintenance interval of the equipment in all monitoring cycles, BY min The minimum maintenance interval for the equipment during all monitoring cycles;

[0114] Obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period;

[0115] The vibration value after maintenance is calculated by ratio with the vibration value before maintenance to obtain the single maintenance effect value;

[0116] Integrate the single maintenance values ​​calculated after each maintenance of the equipment, and use the mean calculation formula to obtain the maintenance effect value BYX of the equipment during the monitoring period;

[0117] The average maintenance interval value of the equipment BYS j BYX j Perform product calculation to obtain the equipment maintenance value BYZ j ;

[0118] It should be noted that the extension of the average maintenance time interval will reduce the service life of the equipment. If the vibration value of the equipment after maintenance is greater than or equal to the vibration value before maintenance, it means that the maintenance of the equipment has not extended the service life of the equipment. Therefore, the maintenance value of the equipment BYZ j The larger it is, the less remaining useful life the device has.

[0119] Example 4

[0120] Based on the vibration value Vz of the equipment during the monitoring period j , use value SYP j and maintenance value BYZ j , through the prediction formula YSM = b 1 *V j +b 2 *SYP j +b 3 *BYZ j Calculate the predicted aging value YSM of the equipment, where b 1 、b 2 and b 3 They are vibration values ​​Vz j , use value SYP j and maintenance value BYZ j The coefficient of

[0121] (b 1 、b 2 、b 3 ) is obtained by: using the least squares formula The residual sum of squares RSS for each monitoring period is calculated, where n is the number of monitoring periods within the total monitoring time of the device;

[0122] By formula Get coefficient b e The matrix form of the partial derivative equations is XP T XB e =XP T YSM, through the matrix inverse b e =(XP T XP) -1 XP T YSM calculates b e The least squares estimate of j SYP j BYZ j , e is the sequence number of coefficient b, e is (1,2,3);

[0123] The predicted aging value YSM is compared with the threshold of the aging value. If the predicted aging value is greater than or equal to the threshold of the aging value, it means that the remaining service life of the equipment is insufficient, and an equipment service life warning signal is generated;

[0124] If the predicted aging value is less than the aging value threshold, it means that the remaining service life of the equipment is sufficient, and a normal equipment service life signal is generated.

[0125] Example 5

[0126] See also Figure 3 As shown, based on the equipment life warning signal, the vibration value, usage value and maintenance value are compared with the vibration threshold, usage threshold and maintenance threshold respectively, and one or more of the vibration value, usage value and maintenance value that are greater than or equal to their own thresholds are obtained and analyzed;

[0127] Specific:

[0128] Based on the situation that the vibration value of the equipment is greater than or equal to the vibration threshold, the vibration signal of the equipment when the time subunit is in the middle of the monitoring period is obtained, and the fast Fourier transform algorithm is used to convert the vibration signal into the frequency domain to obtain the spectrum;

[0129] The converted spectrum data is displayed as a graph, with the horizontal axis representing frequency and the vertical axis representing amplitude;

[0130] It should be noted that FFT can convert vibration signals into frequency domain signals, thereby showing the amplitudes of different frequency components. The spectrum graph constructed through the spectrum can show the intensity of each frequency component in the device;

[0131] Based on the spectrum diagram, analyze and identify the fundamental frequency and harmonic frequencies of the device, specifically:

[0132] Get the motor speed DN of the device through the formula The fundamental harmonic frequency f of the device is obtained, and the frequency peak closest to the fundamental harmonic frequency f in the spectrum graph is obtained by traversing the spectrum graph, which is recorded as the fundamental frequency of the device;

[0133] Obtain peaks in the spectrum that are inconsistent with the fundamental frequency and the fundamental frequency harmonic frequency, calculate the difference between these peaks and the fundamental frequency, and if the difference is greater than the difference threshold, mark the peak as an abnormal peak;

[0134] If the harmonic frequency of the abnormal peak is twice or more than the fundamental harmonic frequency, it indicates that the equipment is at risk of imbalance and misalignment, and an equipment imbalance alarm signal is generated;

[0135] If there are random frequencies that are not related to the fundamental harmonic frequency and appear in the spectrum for a period of time, it means that there is a risk of loose parts in the equipment, and an alarm signal for loose parts is generated;

[0136] If the abnormal peaks appear at a regular specific frequency, it means that the equipment has caused bearing or gear wear, generating a component damage alarm signal;

[0137] Based on the situation that the usage value of the device is greater than or equal to the usage threshold, the usage intensity value, the standard value of the startup frequency and the used life value of the device are compared with the corresponding thresholds respectively;

[0138] If the usage intensity value of the device is greater than or equal to the usage intensity threshold, it means that the device has been running for too long within the monitoring period, and an excessive usage intensity alarm signal is generated;

[0139] If the standard value of the device startup frequency is greater than or equal to the standard value threshold of the startup frequency, it means that the startup frequency of the device during the monitoring period is too high, and a high startup frequency alarm signal is generated;

[0140] If the used life value of the device is greater than or equal to the used life value threshold, it means that the remaining life of the device is insufficient, and a device replacement alarm signal is generated;

[0141] Based on the situation that the maintenance value of the equipment is greater than or equal to the maintenance value threshold, the average maintenance time interval and the maintenance effect value of the equipment are compared with the corresponding thresholds respectively;

[0142] If the average maintenance time interval is greater than or equal to the average maintenance time interval threshold, it means that the equipment has been maintained too few times within the monitoring period, and an equipment maintenance alarm signal is generated;

[0143] If the maintenance effect value is greater than or equal to the maintenance effect value threshold, it means that the current maintenance method has no positive feedback on the equipment, and a maintenance method change alarm signal is generated;

[0144] Based on the above types of problems, corresponding alarm signals are generated according to the actual situation, and targeted alarm reminders are sent to management personnel.

[0145] Example 6

[0146] An industrial Internet of Things control system for inspection data processing, including a vibration signal acquisition and analysis module, an effect acquisition and analysis module, an aging prediction module and an aging analysis and early warning module;

[0147] The vibration signal acquisition and analysis module obtains the vibration signal value of the equipment and extracts the time domain characteristics of the vibration signal, including the vibration peak value and the root mean square value;

[0148] The vibration value of the equipment during the monitoring period is obtained through the vibration peak value and root mean square value of the equipment;

[0149] The effect collection and analysis module obtains the total running time of the equipment and the running time in the monitoring period to obtain the equipment's usage intensity value, equipment startup frequency and equipment's used life value;

[0150] The usage value of the equipment during the monitoring period is obtained through the usage intensity value, startup frequency and used life value of the equipment;

[0151] Obtain the number of maintenance times of the equipment in each monitoring cycle, and obtain the average maintenance time interval of the equipment in the monitoring cycle;

[0152] Obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period, and obtain the maintenance effect value of the equipment within the monitoring period;

[0153] The maintenance value of the equipment is obtained through the average maintenance time interval and maintenance effect value of the equipment within the monitoring period;

[0154] The aging prediction module obtains the predicted aging value of the equipment through the vibration value, usage value and maintenance value of the equipment during the monitoring period, and generates equipment service life warning signal and equipment service life normal signal;

[0155] The aging analysis and warning module analyzes the vibration value, usage value and maintenance value through the equipment service life warning signal, obtains the specific cause of equipment aging, and sends an alarm notification.

[0156] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An industrial Internet of Things control method for inspection data processing, characterized in that: The following steps are involved: Obtain the vibration signal data of the equipment and obtain the vibration value of the equipment within the monitoring period; The vibration signal data includes the vibration peak value and the root mean square value; Obtain the behavior status data of the device and obtain the usage value of the device during the monitoring period; The status behavior data includes the usage intensity value of the device, the startup frequency of the device, and the used life value of the device; Obtain equipment maintenance status data and obtain equipment maintenance values ​​within the monitoring period; Among them, the maintenance status data includes the average maintenance time interval value and maintenance effect value of the equipment; Based on the vibration value, usage value and maintenance value of the equipment during the monitoring period, the predicted aging value of the equipment is obtained, and the equipment service life warning signal and the equipment service life normal signal are generated; Based on the equipment life warning signal, the vibration value, usage value and maintenance value are analyzed to obtain the specific cause of equipment aging, generate corresponding alarm signals, and send alarm notifications to management personnel.

2. The industrial Internet of Things control method for inspection data processing according to claim 1 is characterized in that: All vibration signal values ​​are processed to extract the time domain characteristics of the vibration signal. Specifically: Integrate all vibration signal values ​​into a vibration sequence and extract the largest vibration signal value P in the vibration sequence max , extract the minimum vibration signal value P in the vibration sequence min ; By formula Get the vibration peak value Pk and assign it a weight w1; By formula Get the root mean square data Jfg of the vibration signal, where X i is the vibration signal value, N is the number of time subunits in the monitoring period, i is the sequence number of time subunits in the monitoring period, i = 1, 2, ..., N; Based on the root mean square data Jfg of the vibration signal in each monitoring cycle, extract the maximum root mean square data Jfg in all monitoring cycles max and the minimum root mean square data Jfg min , through the formula Get the root mean square value RMS and assign it a weight w2; By formula Vz j =w1*Pk+w2*RMS to calculate the vibration value Vz of the equipment during the monitoring period j , where j is the number of monitoring cycle sequences within the total monitoring time, j = 1, 2, ..., n.

3. The industrial Internet of Things control method for inspection data processing according to claim 1 is characterized in that: The specific process of obtaining the usage intensity value of the device, the startup frequency of the device, and the used life of the device is as follows: Get the running time and startup times of the equipment during the monitoring period; Compare the running time of the equipment during the monitoring cycle with the total duration of the monitoring cycle to obtain the equipment usage intensity value SYQ j ; Compare the number of times the device is started within the detection period with the total duration of the detection period to obtain the device's startup frequency data PJ; By formula Get the starting frequency PJQ j , where PJ max PJ is the maximum startup frequency data of the device in all monitoring cycles. min The preset minimum startup frequency data of the equipment in all monitoring cycles; Obtain the total operating time of the equipment, compare the total operating time of the equipment with the rated life of the equipment, and obtain the used life value SMZ of the equipment j .

4. The industrial Internet of Things control method for inspection data processing according to claim 2 is characterized in that: The process of obtaining the usage value of the device during the monitoring period is as follows: The intensity of use of the equipment is SYQ j , starting frequency PJQ j and the used life value SMZ j to process; That is, through the formula SYP j =SYQ j *PJQ j *SMZ j Calculate the usage value SYP of the equipment during the monitoring period j .

5. The industrial Internet of Things control method for inspection data processing according to claim 1 is characterized in that: The process of obtaining the average maintenance time interval value of the equipment within the monitoring period is as follows: Obtain the maintenance records of the equipment in each monitoring cycle and extract the number of maintenance times of the equipment in the monitoring cycle; Compare the running time of the equipment in the monitoring period with the number of maintenance times of the equipment in the monitoring period to obtain the average maintenance time interval data BY of the equipment in the monitoring period; By formula Get the maintenance average time interval value BYS j , where BY max The maximum maintenance interval data of the equipment in all monitoring cycles, BY min It is the minimum maintenance time interval data of the equipment in all monitoring cycles.

6. The industrial Internet of Things control method for inspection data processing according to claim 5 is characterized in that: The process of obtaining the maintenance value of the equipment during the monitoring period is as follows: Based on the average maintenance time interval value, obtain the vibration value of the equipment during the last operation before maintenance and the vibration value of the equipment during the first operation after maintenance within the monitoring period; The vibration value after maintenance is calculated by ratio with the vibration value before maintenance to obtain the single maintenance effect value; Integrate the single maintenance values ​​calculated after each maintenance of the equipment, and use the mean calculation formula to obtain the maintenance effect value of the equipment within the monitoring period; The average maintenance time interval of the equipment is multiplied by the maintenance effect value of the equipment to obtain the maintenance value of the equipment BYZ j .

7. The industrial Internet of Things control method for inspection data processing according to claim 1 is characterized in that: The process of obtaining the equipment life warning signal and the equipment life normal signal is as follows: Based on the vibration value Vz of the equipment during the monitoring period j , use value SYP j and maintenance value BYZ j , through the prediction formula YSM = b1 * Vz j +b2*SYP j +b3*BYZ j Calculate the predicted aging value YSM of the equipment; Compare the predicted aging value YSM with the threshold of the aging value; If the predicted aging value is greater than or equal to the aging value threshold, it means that the remaining service life of the equipment is insufficient, and an equipment service life warning signal is generated; If the predicted aging value is less than the aging value threshold, it means that the remaining service life of the equipment is sufficient, and a normal equipment service life signal is generated.

8. The industrial Internet of Things control method for inspection data processing according to claim 1 is characterized in that: Based on the equipment life warning signal, the vibration value is analyzed abnormally, specifically: Based on the equipment life warning signal, the vibration value is compared with the vibration threshold, the use threshold and the maintenance threshold to obtain one or more of the vibration value, the use value and the maintenance value that is greater than or equal to the threshold; Based on the situation that the vibration value of the equipment is greater than or equal to the vibration threshold, the vibration signal of the equipment when the time subunit is in the middle of the monitoring period is obtained, and the fast Fourier transform algorithm is used to convert the vibration signal into the frequency domain to obtain the spectrum; The converted spectrum data is displayed as a graph, with the horizontal axis representing frequency and the vertical axis representing amplitude; Based on the spectrum graph, the motor speed of the device is obtained, and the fundamental harmonic frequency of the device is calculated by the motor speed of the device. By traversing the spectrum graph, the frequency peak closest to the fundamental harmonic frequency in the spectrum graph is obtained and recorded as the fundamental frequency of the device; Obtain peaks in the spectrum that are inconsistent with the fundamental frequency and the fundamental frequency harmonic frequency, calculate the difference between these peaks and the fundamental frequency, and if the difference is greater than the difference threshold, mark the peak as an abnormal peak; If the harmonic frequency of the abnormal peak is twice or more than the fundamental harmonic frequency, an equipment imbalance alarm signal is generated; If there are random frequencies that are irregular and unrelated to the fundamental frequency and harmonic frequency that appear in the spectrum for a period of time, a loose equipment component alarm signal is generated; If the abnormal peaks appear regularly at a specific frequency, a component damage alarm signal is generated.

9. The industrial Internet of Things control method for inspection data processing according to claim 8 is characterized in that: Based on the equipment life warning signal, the usage value and maintenance value are analyzed. The specific process is as follows: Based on the situation that the usage value of the device is greater than or equal to the usage threshold, the usage intensity value, the standard value of the startup frequency and the used life value of the device are compared with the corresponding thresholds respectively; If the usage intensity value of the device is greater than or equal to the usage intensity threshold, an excessive usage intensity alarm signal is generated; If the standard value of the device startup frequency is greater than or equal to the standard value threshold of the startup frequency, a high startup frequency alarm signal is generated; If the used life value of the equipment is greater than or equal to the used life value threshold, an equipment replacement alarm signal is generated; Based on the situation that the maintenance value of the equipment is greater than or equal to the maintenance value threshold, the average maintenance time interval and the maintenance effect value of the equipment are compared with the corresponding thresholds respectively; If the average maintenance time interval is greater than or equal to the average maintenance time interval threshold, an equipment maintenance alarm signal is generated; If the maintenance effect value is greater than or equal to the maintenance effect value threshold, a maintenance mode change alarm signal is generated.

10. An industrial Internet of Things control system for inspection data processing, characterized in that: The vibration signal acquisition and analysis module obtains the vibration signal data of the equipment to obtain the vibration value of the equipment during the monitoring period; The vibration signal data includes the vibration peak value and the root mean square value; The effect collection and analysis module obtains the equipment's behavior status data and equipment's maintenance status data to obtain the equipment's usage value and maintenance value during the monitoring period. Among them, the status behavior data includes the usage intensity value of the equipment, the startup frequency of the equipment and the used life value of the equipment, and the maintenance status data includes the average maintenance time interval value and maintenance effect value of the equipment; The aging prediction module obtains the predicted aging value of the equipment through the vibration value, usage value and maintenance value of the equipment during the monitoring period, and generates equipment service life warning signal and equipment service life normal signal; The aging analysis and warning module uses the equipment life warning signal to analyze the vibration value, usage value and maintenance value, obtains the specific cause of equipment aging, generates corresponding alarm signals, and sends alarm notifications to management personnel.

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