Non-inductive data acquisition system and method thereof

Abstract

The invention relates to the field of industrial equipment data acquisition, and particularly discloses a non-inductive data acquisition system and method, and the method comprises the steps: collecting the operation data of each block at each monitoring time point in each working mode; according to the operation data of each block at each monitoring time point in each working mode, acquiring a change trend curve of the operation data, and analyzing a coincidence coefficient of the operation data of each block at each working mode; according to the operation data coincidence coefficient of each block in each working mode, analyzing and feeding back the operation performance evaluation coefficient of each block; and acquiring a voltage sag coefficient, a current overload coefficient and a temperature rise abnormal coefficient of each block in an operation process, analyzing a fault tendency coefficient of each block according to the voltage sag coefficient, the current overload coefficient and the temperature rise abnormal coefficient, judging whether a fault hidden danger exists or not, and performing early warning.

Description

Technical Field

[0001] The present invention relates to the field of industrial equipment data acquisition, and in particular to a non-sensing data acquisition system. Background Art

[0002] Contactless data collection is the process of autonomously completing the entire process of data collection, transmission, preliminary processing and analysis through various sensors, smart devices or systems without human participation and intervention.

[0003] In the industrial field, contactless data collection is widely used, whether it is intelligent production lines or Internet of Things devices. For intelligent equipment and Internet of Things devices, their intelligence and networking are mainly supported by the operation of their chips or circuits. Therefore, by contactlessly collecting and analyzing the operating data of industrial equipment circuits, the working status of industrial equipment circuits can be monitored in real time, potential fault hazards can be accurately discovered, and maintenance measures can be taken in advance to ensure the stable and reliable operation of related electronic equipment. At the same time, it helps to understand the performance of each component of the industrial equipment circuit, providing a basis for subsequent optimization and upgrading, which is of practical significance.

[0004] However, existing methods for collecting and analyzing operational data from industrial equipment circuits still have several limitations and shortcomings in practical applications. For one thing, the entire industrial equipment circuit is monitored, without being divided into specific components for independent analysis. This hinders subsequent targeted performance evaluation and troubleshooting. Furthermore, discrete analysis is used to analyze the operational parameters of industrial equipment circuits. This involves comparing the values ​​collected at a specific moment with the expected or set values ​​to draw conclusions. This approach fails to fully utilize and deeply analyze the collected operational parameters, nor does it analyze their dynamic trends or patterns. Consequently, the reliability of the conclusions drawn from these operational parameters is low. Summary of the Invention

[0005] In response to the above problems, the present invention proposes a non-sensing data acquisition system to realize the functions of collecting, monitoring, processing and analyzing the circuit operation data of industrial equipment.

[0006] The technical solution adopted by the present invention to solve the technical problem is as follows: the present invention provides a non-sensing data acquisition system, comprising: an operation data acquisition module: collecting the operation data of each block at each monitoring time point in each working mode; Operation data analysis module: obtains the change trend curve of the operation data of each block at each monitoring time point under each working mode, and analyzes the compliance coefficient of the operation data of each block under each working mode; Operation performance evaluation module: Analyzes the operation performance evaluation coefficient of each block and provides feedback based on the operation data compliance coefficient of each block in each working mode; Fault monitoring and early warning module: obtains the voltage sag coefficient, current overload coefficient and temperature rise abnormality coefficient of each block during operation, analyzes the fault tendency coefficient of each block based on this, determines whether there are potential fault hazards and issues early warnings.

[0007] Database: used to store the frequency of block operation data collection, and store the expected values ​​of voltage, current, power consumption, operating frequency and surface temperature thresholds of each block in various operating modes, and store the rated current of each block.

[0008] The present invention also provides a non-sensing data collection method, which specifically includes: S1. Collect the operating data of each module at each monitoring time point in each working mode.

[0009] S2. Based on the operating data collected in S1, a change trend curve of the operating data of each block at each monitoring time point under each working mode is obtained, and a compliance coefficient of the operating data of each block under each working mode is analyzed.

[0010] S3. Analyze the operating performance evaluation coefficient of each block based on the compliance coefficient obtained in S2 and provide feedback.

[0011] S4. Obtain the voltage sag coefficient, current overload coefficient, and temperature rise anomaly coefficient of each block during operation, and analyze the fault tendency coefficient of each block based on the obtained coefficient. If the fault tendency coefficient exceeds a preset threshold, it is determined that there is a potential fault and an early warning is triggered.

[0012] Compared with the prior art, the non-contact data acquisition system described in the present invention has the following beneficial effects: 1. The present invention divides the industrial equipment circuits and collects and analyzes the operating data of each block, which is conducive to subsequent targeted performance evaluation and troubleshooting of the industrial equipment circuits.

[0013] 2. The present invention obtains the changing trend curve of the operating data of each block under various working modes, evaluates the operating performance evaluation coefficient of each block, fully utilizes and deeply analyzes the operating parameters of the industrial equipment circuit, analyzes the dynamic change trend of the operating parameters, and thus improves the reliability of the performance evaluation based on the operating parameters.

[0014] 3. The present invention monitors voltage drops, current overloads, and abnormal temperature increases during the operation of industrial equipment circuits, and immediately triggers alarm signals, thereby facilitating timely implementation of corresponding measures to avoid damage to the circuit blocks of the industrial equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 This is a system module connection diagram of the present invention.

[0017] Figure 2 The figure is a flow chart of a non-sensing data collection method of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0019] See also Figure 1 As shown, the present invention provides a non-sensing data acquisition system, including an operation data acquisition module, an operation data analysis module, an operation performance evaluation module, a fault monitoring and early warning module, and a database.

[0020] The operation data analysis module is connected to the operation data acquisition module and the operation performance evaluation module respectively, the fault monitoring and early warning module is connected to the operation performance evaluation module, and the database is connected to the operation data acquisition module, the operation data analysis module, and the fault monitoring and early warning module respectively.

[0021] The operation data acquisition module is used to collect the operation data of each block at each monitoring time point under various operating modes, wherein the operation data includes voltage, current, surface temperature, power consumption, and operating frequency.

[0022] Furthermore, the specific working process of the operation data acquisition module is: obtaining the modules where each sub-circuit in the industrial equipment circuit is located, recording them as each block of the industrial equipment circuit, extracting the frequency of industrial equipment circuit operation data acquisition stored in the database, and obtaining the sample size of industrial equipment circuit operation data acquisition.

[0023] According to the frequency and sample size of industrial equipment circuit operation data collection, the monitoring time points corresponding to the operation data of the industrial equipment circuit are set, and the voltage, current, power consumption and operating frequency of each block at each monitoring time point under various operating modes are collected.

[0024] Obtain the surface temperature distribution diagram of each block at each monitoring time point under various working modes, record the highest temperature in the surface temperature distribution diagram of the industrial equipment circuit block as the surface temperature of the industrial equipment circuit block, and obtain the surface temperature of each block at each monitoring time point under various working modes.

[0025] As a preferred solution, the sub-circuits of the industrial equipment circuit include but are not limited to: an amplifier circuit, an oscillator circuit, a filter circuit, a logic circuit, a storage circuit, a power supply circuit, a comparison circuit, and a modulation and demodulation circuit.

[0026] As a preferred solution, the frequency of collecting industrial equipment circuit operational data stored in the database is set based on the operating characteristics of the industrial equipment circuits. In one specific embodiment, for slowly changing temperature parameters, the collection frequency can be set to 1-5 times per second. For parameters with large real-time fluctuations, such as current and voltage, the collection frequency is increased to 100-1000 times per second to ensure that every subtle change is captured.

[0027] As a preferred solution, the sample size of the industrial equipment circuit operation data collection is set according to actual application requirements.

[0028] As a preferred solution, the frequency and sample size of the operating data collection of each block are the same.

[0029] As a preferred solution, the various operating modes of industrial equipment circuits can be divided into multiple ways. In one specific embodiment, based on the application scenario, the operating modes of industrial equipment power circuits include buck mode, boost mode, and voltage regulation mode, while the operating modes of industrial equipment communication circuits include encoding and decoding mode, channel transmission mode, and signal processing mode.

[0030] As a preferred solution, the operating data of each block at each monitoring time point in various operating modes can be obtained through sensors or acquisition circuits.

[0031] As a preferred solution, power consumption refers to the electrical power consumed by each block during operation.

[0032] As a preferred solution, the operating frequency refers to the clock frequency at which each block can operate normally.

[0033] It should be noted that the present invention divides the industrial equipment circuits and further collects and analyzes the operating data of each block, which is conducive to subsequent targeted performance evaluation and troubleshooting of the industrial equipment circuits.

[0034] The operation data analysis module is used to obtain the change trend curve of the operation data of each block under various working modes based on the operation data of each block at each monitoring time point under various working modes, and analyze the compliance coefficient of the operation data of each block under various working modes.

[0035] Furthermore, the specific working process of the operation data analysis module includes: D1: according to the voltage of each block at each monitoring time point under various working modes, a coordinate system is established with the monitoring time point as the horizontal axis and the voltage as the vertical axis, and the corresponding data points are further marked in the coordinate system. The trend curve of the voltage change of each block over time under various working modes is drawn by using the mathematical model establishment method, and it is recorded as the voltage change trend curve of each block under various working modes.

[0036] D2: Similarly, according to the analysis method of D1, obtain the change trend curve of current, surface temperature, power consumption and operating frequency of each block under various working modes.

[0037] Furthermore, the specific working process of the operation data analysis module also includes: E1: according to the voltage change trend curve of each block under various working modes, obtain the function corresponding to the voltage change trend curve of each block under various working modes, and record it as , Indicates the circuit of industrial equipment The number of the block, , Indicates the circuit of industrial equipment The number of the working mode, .

[0038] Extract the expected value of the voltage of each block in various working modes stored in the database and record it as , set the function corresponding to the reference curve of the voltage change trend curve of each block in various working modes , .

[0039] According to the frequency and sample size of industrial equipment circuit voltage collection, the monitoring time points corresponding to the voltage of the industrial equipment circuit are obtained, and the first monitoring time point and the last monitoring time point corresponding to the voltage of the industrial equipment circuit are further obtained, which are recorded as .

[0040] calculate The integral value within the time period of the starting monitoring time point is calculated at the same time and The integral absolute value of the difference within the time period of the starting monitoring time point is calculated, and the ratio of the integral value to the integral absolute value plus 1 is calibrated by the correction factor of the preset voltage compliance coefficient, and finally the compliance coefficient of the voltage of each block in each working mode is output.

[0041] As a preferred solution, the correction factor of the voltage compliance coefficient can obtain an initial empirical value range from the technical specifications provided by the equipment manufacturer. During actual application, the operator can set a specific value within the initial empirical value range according to the specific actual situation. The correction factor of the voltage compliance coefficient plays the role of amplifying, reducing, and rounding the voltage compliance coefficient, and is used to map the original calculated proportional value to a numerical range that meets engineering intuition and early warning requirements, so as to facilitate calculation analysis and actual use.

[0042] E2: According to the analysis method of the compliance coefficient of the voltage of each block in various working modes, the compliance coefficient of the current, power consumption and working frequency of each block in various working modes is obtained.

[0043] Furthermore, the specific working process of the operation data analysis module also includes: according to the surface temperature change trend curve of each block under various working modes, obtaining the function corresponding to the surface change trend curve of each block under various working modes, and recording it as .

[0044] Extract the threshold value of the surface temperature of each block in various working modes stored in the database and record it as , set the function corresponding to the reference curve of the surface temperature change trend curve of each block in various working modes , .

[0045] According to the frequency and sample size of the surface temperature collection of the industrial equipment circuit, the monitoring time points corresponding to the surface temperature of the industrial equipment circuit are obtained, and the first monitoring time point and the last monitoring time point corresponding to the surface temperature of the industrial equipment circuit are further obtained, which are recorded as .

[0046] calculate The integral value within the time period of the starting monitoring time point is calculated at the same time The integral value within the time period of the starting monitoring time point is calculated, and the ratio of the two is calibrated by the preset correction factor of the surface temperature compliance coefficient, and finally the compliance coefficient of the surface temperature of each block in each working mode is output. The preset correction factor of the surface temperature compliance coefficient is the same as the correction factor of the voltage compliance coefficient in terms of acquisition method and effect.

[0047] The operation performance evaluation module is used to analyze the operation performance evaluation coefficient of each block according to the compliance coefficient of the operation data of each block under various working modes, and provide feedback.

[0048] Furthermore, the specific working process of the operation performance evaluation module is: setting the threshold values ​​of the voltage, current, surface temperature, power consumption and operating frequency compliance coefficients of each block in each working mode, and calculating the ratio between the actual values ​​of voltage, current, surface temperature, power consumption and operating frequency and each corresponding threshold value.

[0049] As a preferred solution, the threshold value of the operating data compliance coefficient of each block in various working modes is set according to actual application requirements.

[0050] Setting the industrial equipment circuit The influence factors of the working modes are used to correct the sum of the ratios and then accumulate them, and finally the operating performance evaluation coefficient of each block is calibrated and output through the correction factor of the preset operating performance evaluation coefficient; the correction of the influence factor of the working mode and the correction factor of the preset operating performance evaluation coefficient are the same as the correction factor of the voltage compliance coefficient in terms of acquisition method and effect.

[0051] It should be noted that the present invention obtains the changing trend curve of the operating data of each block under various working modes, evaluates the operating performance evaluation coefficient of each block, fully utilizes and deeply analyzes the operating parameters of the industrial equipment circuit, analyzes the dynamic change trend of the operating parameters, and thus improves the reliability of the performance evaluation based on the operating parameters.

[0052] The fault monitoring and early warning module is used to obtain the voltage sag coefficient, current overload coefficient, and temperature rise abnormality coefficient of each block during the operation of the industrial equipment circuit, analyze the fault tendency coefficient of each block during the operation of the industrial equipment circuit, determine whether there are hidden fault hazards in each block during the operation of the industrial equipment circuit, and issue an early warning.

[0053] Furthermore, the specific working process of the fault monitoring and early warning module includes: setting a monitoring period during the operation of the industrial equipment circuit according to a preset principle, and setting each sampling time point within the monitoring period according to a preset equal time interval principle.

[0054] The voltage of each block at each sampling time point in a monitoring period during the operation of the industrial equipment circuit is collected, and the voltage reduction amount of each block at each sampling time point in the monitoring period during the operation of the industrial equipment circuit relative to the voltage of each block at the previous sampling time point is obtained. The reduction amount is recorded as the voltage reduction amount of each block at each sampling time point in the monitoring period during the operation of the industrial equipment circuit. The reduction amounts are compared with each other to obtain the maximum voltage reduction amount of each block in the monitoring period during the operation of the industrial equipment circuit. The maximum voltage reduction amount is substituted into a preset relationship function between the maximum voltage reduction amount and the voltage sag coefficient to obtain the voltage sag coefficient of each block in the operation of the industrial equipment circuit.

[0055] As a preferred solution, during the operation of the industrial equipment circuit, the voltage reduction amount of each block at the first sampling time point in the monitoring cycle is a set value.

[0056] As a preferred solution, the relationship function between the maximum voltage reduction amount and the voltage sag coefficient is a positive correlation function. Specifically, the relationship function between the maximum voltage reduction amount and the voltage sag coefficient is an exponential decay function, which is expressed as follows: , among which is the voltage sag coefficient, is the maximum voltage reduction, that is, the larger the maximum voltage reduction, the larger the voltage sag coefficient. The exponential decay function can adaptively represent the non-complete linear relationship between the maximum voltage reduction and the severity of the voltage sag.

[0057] Furthermore, the specific working process of the fault monitoring and early warning module also includes: collecting the current of each block at each sampling time point in the monitoring period during the operation of the industrial equipment circuit, and comparing it with the rated current of each block stored in the database, obtaining the difference in the current of each block at each sampling time point in the monitoring period during the operation of the industrial equipment circuit that exceeds the rated current of its block, recording it as the current increase amount of each block at each sampling time point in the monitoring period during the operation of the industrial equipment circuit, and comparing them with each other to obtain the maximum current increase amount of each block in the monitoring period during the operation of the industrial equipment circuit, and taking the relative deviation value between the maximum current increase amount and the rated current as the current overload coefficient of each block in the operation of the industrial equipment circuit, which reflects the sensitivity of each block to instantaneous overload during the operation of the industrial equipment circuit, that is, the larger the maximum current increase amount, the larger the current overload coefficient.

[0058] Furthermore, the specific operation process of the fault monitoring and early warning module also includes: obtaining a surface temperature distribution map of each block at each sampling time point during the monitoring period of the industrial equipment circuit operation; obtaining the highest temperature and the area of ​​the temperature region above the set surface temperature early warning value in the surface temperature distribution map of each block at each sampling time point during the monitoring period of the industrial equipment circuit operation; recording these as the surface temperature and high-temperature region area of ​​each block at each sampling time point during the monitoring period of the industrial equipment circuit operation; further analyzing the maximum surface temperature rise rate and the maximum diffusion rate of the high-temperature region area of ​​each block during the monitoring period of the industrial equipment circuit operation; converting the maximum surface temperature rise rate and the maximum diffusion rate of the high-temperature region area of ​​each block into dimensionless relative values ​​through normalization; and calculating the product of the maximum surface temperature rise rate and the maximum diffusion rate of the high-temperature region area as the temperature rise anomaly coefficient of each block during the industrial equipment circuit operation. This reflects the synergistic effect of temperature rise and regional diffusion. When both are simultaneously high, the anomaly coefficient increases significantly. For example, when local overheating and heat spread rapidly, the failure risk is much higher than when a single factor is abnormal.

[0059] Furthermore, the specific working process of the fault monitoring and early warning module also includes: calculating the weighted average value of the voltage sag coefficient, current overload coefficient, and temperature rise abnormality coefficient of each block during the operation of the industrial equipment circuit to obtain the fault tendency coefficient of each block during the operation of the industrial equipment circuit.

[0060] The failure tendency trends of each block in the operation of industrial equipment circuits are quantitatively calculated by calculating the weighted average value. On the one hand, the weight distribution can more comprehensively reflect the influence of different parameters and avoid the limitations of a single indicator. For example, in the case of voltage sag, current overload and abnormal temperature rise, each parameter contributes differently to the failure, and the weighted average can highlight the role of important parameters. On the other hand, by assigning high weights to key parameters, the system can more sensitively capture abnormal changes that contribute most to the failure, issue early warnings in a timely manner, and avoid missed reports.

[0061] At the same time, if a secondary parameter exceeds the standard individually but the overall risk is not high, giving a lower weight to the abnormality of the secondary parameter can reduce false alarms.

[0062] As a preferred solution, the weights of the voltage sag coefficient, current overload coefficient, and temperature rise anomaly coefficient are set values, wherein the set values ​​of the weights can be set based on industry experience, or can be obtained through a limited number of test data, such as first collecting historical operating data of the equipment or similar equipment and corresponding fault records; analyzing which parameter anomalies are most frequent, have the largest amplitude, and last the longest before the fault occurs, and calculating the correlation coefficient between the anomaly of each parameter and the occurrence of the fault; using regression analysis or logistic regression analysis to determine the contribution of each parameter, and finally, after normalization, converting the contribution into the set value of the weight and the sum of them is 1.

[0063] The fault tendency coefficient of each block in the industrial equipment circuit operation process is compared with a preset fault tendency coefficient threshold. If the fault tendency coefficient of a block in the industrial equipment circuit is greater than the preset fault tendency coefficient threshold during the industrial equipment circuit operation process, then there is a potential fault in the block in the industrial equipment circuit during the industrial equipment circuit operation process. Statistics are collected on the blocks in the industrial equipment circuit that have potential faults, and early warnings are issued.

[0064] It should be noted that the present invention monitors voltage drops, current overloads, and abnormal temperature increases during the operation of industrial equipment circuits, and immediately triggers alarm signals, thereby facilitating timely adoption of corresponding measures to avoid damage to circuit blocks of industrial equipment.

[0065] The database is used to store the frequency of industrial equipment circuit operation data collection, and store the expected values ​​of voltage, current, power consumption and operating frequency and surface temperature thresholds of each block in various operating modes, and store the rated current of each block.

[0066] See Figure 2 The present invention also provides a non-sensing data collection method, which specifically includes: S1. Collect the operating data of each module at each monitoring time point in each working mode.

[0067] S2. Based on the operating data collected in S1, a change trend curve of the operating data of each block at each monitoring time point under each working mode is obtained, and a compliance coefficient of the operating data of each block under each working mode is analyzed.

[0068] S3. Analyze the operating performance evaluation coefficient of each block based on the compliance coefficient obtained in S2 and provide feedback.

[0069] S4. Obtain the voltage sag coefficient, current overload coefficient, and temperature rise anomaly coefficient of each block during operation, and analyze the fault tendency coefficient of each block based on the obtained coefficient. If the fault tendency coefficient exceeds a preset threshold, it is determined that there is a potential fault and an early warning is triggered.

[0070] The above formulas are all dimensionless and numerically calculated, and the preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0071] The above embodiments may be implemented in whole or in part through software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0072] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0073] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0074] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0075] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A non-sensing data acquisition system, characterized in that: include: Operation data acquisition module: collects the operation data of each block of the industrial equipment circuit at each monitoring time point in each working mode; Operation data analysis module: Based on the operation data of each block at each monitoring time point under each working mode, obtain the change trend curve of its operation data, and analyze the compliance coefficient of the operation data of each block under each working mode; Operation performance evaluation module: Analyzes the operation performance evaluation coefficient of each block of the industrial equipment circuit and provides feedback based on the operation data compliance coefficient of each block in each working mode; Fault monitoring and early warning module: obtains the voltage sag coefficient, current overload coefficient and temperature rise abnormality coefficient of each block during operation, analyzes the fault tendency coefficient of each block based on this, determines whether there are potential fault hazards and issues early warnings.

2. The non-sensing data acquisition system according to claim 1, characterized in that: The specific working process of the operation data acquisition module is as follows: Define the sub-circuit modules of industrial equipment circuits as blocks; Extract the collection frequency and sample size of industrial equipment circuit operation data stored in the database; Set the monitoring time points corresponding to the operating data of the industrial equipment circuit according to the collection frequency and sample size, and collect the voltage, current, power consumption and operating frequency of each block at each monitoring time point in each operating mode; Obtain the surface temperature distribution diagram of each block at each monitoring time point, and record the highest temperature as the surface temperature of the block.

3. The non-contact data acquisition system according to claim 1, characterized in that: The specific working process of the operation data analysis module includes: D1: Based on the voltage of each block at each monitoring time point under each working mode, a coordinate system is established with the monitoring time point as the horizontal axis and the voltage as the vertical axis. The corresponding data points are marked in the coordinate system, and a trend curve of the voltage change over time of each block under each working mode is drawn; D2: Based on the same method as D1, obtain the changing trend curve of current, surface temperature, power consumption and operating frequency of each block in each working mode.

4. The non-contact data acquisition system according to claim 2, characterized in that: The specific working process of the operation data analysis module also includes: E1: The function corresponding to the voltage variation trend curve of each block in each working mode is recorded as , Indicates the block The number of the block, , Indicates the block The number of the working mode, ; Extract the expected value of voltage of each block in each working mode from the database , and use it as the function corresponding to the reference curve of the voltage change trend curve of each block in each working mode ; According to the voltage acquisition frequency and sample size, the corresponding monitoring time points of the voltage are obtained, and the starting monitoring time points are obtained and recorded as ; calculate The integral value within the time period of the starting monitoring time point is calculated at the same time and The integral absolute value of the difference within the time period of the starting monitoring time point is calculated, and the ratio of the integral value to the integral absolute value plus 1 is calibrated by the preset voltage compliance coefficient correction factor, and finally the voltage compliance coefficient of each block in each working mode is output; E2: Obtain the compliance coefficients of the current, power consumption and operating frequency of each block based on the same method used to analyze the compliance coefficient of the voltage in each operating mode.

5. The non-contact data acquisition system according to claim 4, characterized in that: The specific working process of the operation data analysis module also includes: According to the function corresponding to the trend curve of the surface temperature of each block in each working mode ; The threshold value of the surface temperature of each block in the database under each working mode As the function corresponding to the reference curve of the surface temperature change trend curve of each block in each working mode ; According to the acquisition frequency and sample size, the monitoring time points corresponding to the surface temperature of the block are obtained, and the starting monitoring time points are obtained and recorded as ; calculate The integral value within the time period of the starting monitoring time point is calculated at the same time The integral value within the time period of the starting monitoring time point is calculated, and the ratio of the two is calibrated by the correction factor of the preset surface temperature compliance coefficient, and finally the compliance coefficient of the surface temperature of each block in each working mode is output.

6. The non-contact data acquisition system according to claim 5, characterized in that: The specific working process of the operation performance evaluation module is as follows: Setting thresholds for the voltage, current, surface temperature, power consumption, and operating frequency compliance coefficients of each block in each operating mode, and calculating the ratios between the actual values ​​of voltage, current, surface temperature, power consumption, and operating frequency and the corresponding thresholds; Setting the industrial equipment circuit The influencing factors of the working modes are used to correct the sum of the ratios and then perform cumulative processing. Finally, the operating performance evaluation coefficient of each block is calibrated and output through the correction factor of the preset operating performance evaluation coefficient.

7. The non-contact data acquisition system according to claim 4, characterized in that: The specific working process of the fault monitoring and early warning module includes: The monitoring period is set during the operation of the block according to the preset principle, and each sampling time point is set within the monitoring period according to the preset equal time interval principle; The voltage of each block at each sampling time point is collected, the voltage reduction amount of each block at adjacent sampling time points is calculated, the maximum voltage reduction amount of each block is screened out, and the maximum voltage reduction amount is substituted into the preset relationship function between the maximum voltage reduction amount and the voltage sag coefficient to obtain the voltage sag coefficient of each block.

8. The non-contact data acquisition system according to claim 7, characterized in that: The specific working process of the fault monitoring and early warning module also includes: The current of each block at each sampling time point is collected and compared with the rated current of each block stored in the database. The difference in the current of each block exceeding its rated current is obtained and used as the current increase amount of each block. The maximum current increase amount of each block is screened, and the relative deviation value between the maximum current increase amount and the rated current is used as the current overload coefficient of each block during the operation of the industrial equipment circuit.

9. The non-contact data acquisition system according to claim 7, characterized in that: The specific working process of the fault monitoring and early warning module also includes: The surface temperature distribution diagram of each block at each sampling time point is obtained, and the area of ​​the temperature area with the highest temperature and higher than the set surface temperature warning value in the surface temperature distribution diagram of each block is extracted and recorded as the surface temperature and high-temperature area of ​​each block. The maximum surface temperature rise rate and the maximum diffusion rate of the high-temperature area of ​​each block are analyzed, and the product of the maximum surface temperature rise rate and the maximum diffusion rate of the high-temperature area is used as the temperature rise anomaly coefficient of each block during the operation of the industrial equipment circuit.

10. The non-contact data acquisition system according to claim 1, characterized in that: The specific working process of the fault monitoring and early warning module also includes: The fault tendency coefficient of each block is obtained by calculating the weighted average value of the voltage sag coefficient, current overload coefficient and temperature rise anomaly coefficient of each block; If the fault tendency coefficient of a certain block exceeds the preset fault tendency coefficient threshold, it is determined that the block has a potential fault hazard and an early warning is issued.

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