Intelligent self-diagnosis system and method of multi-medium transmission integrated connector

Abstract

The invention provides an intelligent self-diagnosis method and system for a multi-medium transmission integrated connector, and the system comprises a main control system which is connected with an acquisition and conditioning module and a temperature sensor signal acquisition and conditioning module through an AD chip. The main control system is respectively connected with the CAN bus transmission module, the power supply module and the temperature compensation circuit module, and the CAN bus transmission module is connected with the data storage module; the CAN bus transmission module is connected with the remote control terminal; the method comprises the following steps: initializing a system; judging whether a far-end control command is received or not by using a far-end control command processing module and processing the far-end control command; key characteristic quantity monitoring signals of the connector are monitored in real time, plugging detection and connector multi-module fault detection are carried out according to the key characteristic quantity monitoring signals, and fault information is fed back; and performing degradation fault time prediction by using a degradation fault time prediction module. According to the method, the maintenance cost is reduced, the service life of the connector is prolonged, and the operation efficiency and reliability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automation and control technology, and in particular to an intelligent self-diagnosis system and method for a connector. Background Art

[0002] At present, connectors are widely used in electronic systems in the fields of automobiles, industry, medical treatment, aerospace, and weapons and equipment, mainly to achieve electrical connection and signal energy transmission. Traditional integrated connectors are passive devices, and their internal state is unknown. Once a failure occurs, they can only be repaired or replaced passively. This passive maintenance method not only increases the maintenance cost of the system, but may also cause the system to fail suddenly due to connector failure, bringing unpredictable impact to the entire system.

[0003] With the development of technology, the application environment of connectors is becoming more and more complex, and the types of transmission signals are increasing. For example, in a multi-media transmission integrated connector, there may be contacts of different standards, forms, frequencies, sizes, and uses connected in the same connector. This diversified signal transmission method leads to reduced reliability inside the connector, mutual interference between different signals, and different failure modes and fault characteristics for different transmission methods.

[0004] To overcome the above problems, some existing solutions include:

[0005] External monitoring equipment: The status of the connector can be monitored through external sensors and monitoring equipment, but this will increase the complexity and cost of the system.

[0006] Scheduled maintenance: Failures are prevented through regular manual inspection and maintenance, but this method cannot achieve real-time monitoring and has high maintenance costs.

[0007] The invention with publication number CN115656889A discloses a new type of connector system and its intelligent diagnosis method, including: a connector male end, a connector female end, an intelligent diagnosis module and an information module. The intelligent diagnosis module includes: an isolation acquisition module, which isolates the main circuit from the monitoring circuit to prevent interference caused by electrical connections; a fault sensing module, which performs power-on self-test and timeout-triggered self-test during operation according to the current or signal level in the line for the poor contact fault of the current connector, detects whether the connector is connected correctly, and captures the transient multi-pulse characteristics generated by the high and low level changes of the signal in the female end of the connector. During use, it monitors whether the connector system has a fault in real time, and locates the fault position through numbering information. Information module, when the intelligent diagnosis module detects an abnormal situation, it transmits relevant signals to the information module to prompt engineering and technical personnel with information related to the connector fault. However, this method is suitable for fault detection of the entire connector, and cannot realize the visualization of the real-time status inside the connector and the detection and alarm of faults. Summary of the invention

[0008] In response to the technical problem of difficulty in detecting the real-time status inside the connector, the present invention proposes an intelligent self-diagnosis system and method for a multi-media transmission integrated connector, which uses hardware to monitor characteristic signals, software to process fault information, and communicates with a host computer through a bus interface to achieve intelligent monitoring of the internal working status of different connectors.

[0009] In order to achieve the above object, the technical solution of the present invention is achieved as follows:

[0010] An intelligent self-diagnosis system of a multi-media transmission integrated connector comprises a main control system, wherein the main control system is respectively connected to an acquisition and conditioning module and a temperature sensor signal acquisition and conditioning module through an AD chip; the main control system is respectively connected to a CAN bus transmission module, a power supply module and a temperature compensation circuit module, the CAN bus transmission module is connected to a data storage module; and the CAN bus transmission module is connected to a remote control terminal.

[0011] The main control system includes a remote control command processing module, a state monitoring and fault diagnosis module and a degradation fault time prediction module; the remote control command processing module, the state monitoring and fault diagnosis module and the degradation fault time prediction module are all connected to the CAN bus transmission module, and the state monitoring and fault diagnosis module and the degradation fault time prediction module are connected; the state monitoring and fault diagnosis module is respectively connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through the AD chip.

[0012] The state monitoring and fault diagnosis module includes a state monitoring module, which is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through an AD chip, and is connected to the plug-in detection module and the connector multi-module fault detection module, respectively; the state monitoring module, the plug-in detection module and the multi-module fault detection module are all connected to the CAN bus transmission module.

[0013] An intelligent self-diagnosis method for a multi-media transmission integrated connector comprises the following steps:

[0014] S1: Initialize the main control system and set the initial parameters of the degradation failure time prediction model;

[0015] S2: using the remote control command processing module to determine whether a remote control command is received; if the determination is yes, decoding the information to obtain a function code, and executing the command in the function code according to the function code; if the determination is no, executing step S3;

[0016] S3: Use the status monitoring and fault diagnosis module to monitor the key characteristic quantity monitoring signal of the connector in real time, and perform plug-in detection and connector multi-module fault detection according to the key characteristic quantity monitoring signal;

[0017] S4: If the fault detection result is a fault, an alarm message is sent to the remote control terminal through the CAN bus transmission module after information encoding;

[0018] S5: If the fault detection result is that no fault has occurred, a degradation fault time prediction module is used to predict the degradation fault time, and a data storage module is used to store data.

[0019] Executing the command in the function code according to the function code described in step S2 includes reading the historical measurement value of the connector, reading the current working status and fault information, and setting the connector instantaneous fault judgment threshold and the plug-in detection threshold, the plug-in detection threshold includes the plug-in threshold and the loose threshold; parameter setting of the degradation fault time prediction model in the degradation fault time prediction module.

[0020] The method for performing plug-in detection and connector multi-module fault detection based on key characteristic quantity monitoring signals is as follows:

[0021] The key characteristic quantity monitoring signal is AD converted by using the AD chip in a continuous and sequential conversion mode; the adaptive range switching control is performed according to the key characteristic quantity monitoring signal; the key characteristic quantity monitoring signal of the connector is periodically obtained through the AD chip by using the state monitoring module, the key characteristic value is obtained according to the key characteristic quantity monitoring signal, and is stored in the data storage module in real time; when the plugging pressure value change in the key characteristic value is detected, the plugging and unplugging detection is performed; when the plugging pressure value change is not detected or the plugging and unplugging detection is completed, multi-module fault detection is performed.

[0022] The plug-in detection method comprises: obtaining the plug-in pressure value from the state monitoring module through the plug-in detection module, and then preprocessing the sampled data to obtain the preprocessed plug-in pressure value, and comparing the preprocessed plug-in pressure value with the plug-in threshold and the loose threshold to determine the plug-in state; selecting false touch, loose alarm or plug-in count according to the plug-in state; and exiting the plug-in detection after completing the selected operation;

[0023] The method for multi-module fault detection is: using a multi-module fault detection module to obtain a key characteristic quantity monitoring signal; preprocessing the key characteristic quantity monitoring signal, including eliminating abnormal data and data smoothing; calculating characteristic values ​​based on the preprocessed key characteristic quantity monitoring signal and making a fault judgment based on an instantaneous fault threshold.

[0024] The method for calculating characteristic values ​​and performing fault judgment based on the instantaneous fault threshold is as follows: reading the preprocessed key characteristic quantity monitoring signal, converting the preprocessed key characteristic quantity monitoring signal into characteristic values, wherein the characteristic values ​​include contact resistance value and connector temperature value, and comparing the contact resistance value and connector temperature value of the monitored module with the instantaneous threshold; when the contact resistance value and connector temperature value of the monitored module exceed the threshold, it is judged that a fault has occurred, and the fault information is stored in the data storage module, and a long-term failure database is constructed; when the contact resistance value and connector temperature value of the monitored module do not exceed the threshold, it is judged that no fault has occurred, and the binary contact resistance value and connector temperature value of the monitored module are first converted into corresponding decimal values, and then the corresponding contact resistance value and connector temperature value of the monitored module are calculated through a proportional amplification relationship, and then the obtained contact resistance value and connector temperature value of the monitored module are converted into corresponding BCD codes and stored;

[0025] The method for predicting the degradation fault time using the degradation fault time prediction module described in step S5 is: using the contact resistance value of the monitored module as experimental data, correcting the model parameters based on the grayscale model theory and predicting the degradation fault time.

[0026] The method for correcting the model parameters and predicting the degradation failure time based on the gray model theory is:

[0027] St1: Obtain the original sequence of contact resistance variation over time based on the long-term failure database;

[0028] St2: accumulate the original data sequence once to generate the accumulated sequence;

[0029] St3: Construct the GM(1,1) model based on the cumulative sequence and use the least squares method to perform regression analysis and correction on the degradation model parameters;

[0030] St4: Solve the whitening equation of the GM (1,1) model to obtain the prediction sequence expression, and obtain the final prediction sequence based on the prediction sequence expression;

[0031] St5: Calculate the residual sequence based on the final prediction sequence, calculate the posterior error ratio C based on the variance of the original data sequence and the variance of the residual sequence; and calculate the small error probability P based on the residual sequence;

[0032] St6: Accuracy is judged based on the posterior difference ratio C and the small error probability P;

[0033] St7: Reselect the original data sequence and repeat steps St2 to St5 until the GM(1,1) model accuracy reaches the expected value, and retain the best parameters;

[0034] St8: Input the experimental data into the GM(1,1) model with the optimal parameters retained to obtain a prediction sequence; based on the prediction sequence, calculate the degradation failure time.

[0035] The GM(1,1) model is:

[0036]

[0037] Among them, x (1) (k) is the k-th moment element of the cumulative sequence, x (0) (i) is the contact resistance value at the i-th moment in the original sequence; a and b are variable parameters;

[0038] The prediction sequence expression is:

[0039]

[0040] in, is the predicted contact resistance value at the k+1th moment in the prediction sequence, and n is the sequence length;

[0041] The residual sequence calculation formula is:

[0042]

[0043] Among them, q(k) is the residual of each element in the original data sequence and the final prediction sequence;

[0044] The posterior difference ratio C is:

[0045]

[0046] Among them, s1 is the variance of the original sequence, and s2 is the variance of the residual sequence;

[0047] The probability of small error P is:

[0048]

[0049] in, is the mean of the contact resistance values ​​in the original data series.

[0050] The beneficial effects of the present invention are:

[0051] The hardware circuit and software algorithm are integrated to realize online monitoring of multiple key characteristics such as electrical signal contact resistance, optical signal end face pressure, fluid working pressure, and plug and socket insertion and extraction status in the connector;

[0052] The design of the intelligent monitoring module takes into account high electromagnetic compatibility, ensuring long-term stable operation even in harsh environments and enhancing reliability;

[0053] Predictive maintenance reduces unnecessary repairs or replacements, reduces maintenance costs, and extends the service life of connectors;

[0054] The fault location can be quickly located based on real-time monitoring results, which speeds up the troubleshooting process and improves the operating efficiency of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying creative work.

[0056] Figure 1 This is a flow chart of the intelligent self-diagnosis method of the present invention.

[0057] Figure 2 It is a schematic diagram of the system structure of the present invention.

[0058] Figure 3 It is a structural schematic diagram of the main control system of the present invention.

[0059] Figure 4 A schematic diagram of the structure of a connector integrated with multi-media transmission for fault diagnosis according to the present invention.

[0060] Figure 5 It is a schematic diagram of the connection between the intelligent monitoring module and the monitored module in the connector integrated with multimedia transmission.

[0061] Figure 1 In the figure, 1 is a fluid transmission module; 2 is a displacement sensor; 3 is a radio frequency transmission module; 4 is a high-speed differential module; 5 is an intelligent detection module; 6 is a high-density optical fiber module; 7 is a plug; and 8 is a socket. DETAILED DESCRIPTION

[0062] 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 this patent.

[0063] For example Figure 4 Taking the fault diagnosis of the connector with integrated multi-media transmission as an example, the functional modules of the connector include a fluid transmission module 1, a displacement sensor 2, a radio frequency transmission module 3, a high-speed differential module 4, an intelligent detection module 5, and a high-density optical fiber module 6; the contact parts of the functional modules of the connector are respectively located on the plug 7 and the socket 8; among them, the fluid transmission module 1, the displacement sensor 2, the radio frequency transmission module 3, and the high-speed differential module 4 are monitored modules.

[0064] The contact resistance monitoring signal of the high-speed differential module 4 is transmitted to the daughter board printed circuit board through the button connector, and then transmitted to the intelligent monitoring module 5 through the daughter board printed circuit board; the contact resistance monitoring signal of the radio frequency transmission module 3 is transmitted to the daughter board printed circuit board through the coaxial cable, and then transmitted to the intelligent monitoring module 5 through the daughter board printed circuit board; the working pressure monitoring signal of the fluid transmission module 1 is first led out to the backplane printed circuit board, and then transmitted to the daughter board printed circuit board using the contact piece (button connector) of the high-speed differential module 4, and finally collected by the intelligent monitoring module 5; the plug-in pressure monitoring signal of the displacement sensor 2 The signal is transmitted to the intelligent monitoring module 5 through the daughter board printed circuit board. The pressure acting on the contact surface of the displacement sensor 2 during the plug-in operation is converted into resistance change through the flexible piezoresistive film sensor. The connector intelligent monitoring module 5 continuously monitors the resistance value to obtain the plug-in pressure monitoring signal of the displacement sensor 2; the end face pressure monitoring signal of the high-density optical fiber module 6 is transmitted to the remote control terminal through the optical fiber. The remote control terminal demodulates the wavelength and calibrates the measured wavelength-pressure measurement data during the demodulation process and returns it to the intelligent monitoring module 5; the interconnection relationship between the monitored module and the intelligent monitoring module 5 is as follows: Figure 5 shown.

[0065] Example 1

[0066] An intelligent self-diagnosis system for a multi-media transmission integrated connector, such as Figure 2As shown, it includes a main control system, which is used for data processing, fault diagnosis, communication with other system modules and timing control of sampled data. The sampled data includes key characteristic quantity monitoring signals of multiple modules assembled by the multi-media transmission integrated connector; the key characteristic quantity monitoring signals (in the form of voltage signal and current signal) include the contact resistance monitoring signal of the high-speed differential module 4, the contact resistance monitoring signal of the radio frequency transmission module 3, the working pressure monitoring signal of the fluid transmission module 1, the insertion pressure monitoring signal of the displacement sensor 2, the end face pressure monitoring signal of the high-density optical fiber module 6 and the connector temperature monitoring signal.

[0067] The main control system is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module respectively through the AD chip; the main control system is connected to the CAN bus transmission module, the power module and the temperature compensation circuit module respectively, and the CAN bus transmission module is connected to the data storage module.

[0068] The acquisition and conditioning module is used to sample and filter and amplify the key characteristic quantity monitoring signal corresponding to the monitored module of the multi-media transmission integrated connector. The acquisition and conditioning module includes a sampling circuit, the input of the sampling circuit is a sampling resistor, and the sampling resistor is connected to each functional module of the connector respectively; the output of the sampling circuit is connected to the operational amplifier circuit, and the operational amplifier circuit is connected to the protection circuit; the output of the protection circuit is connected to the main control system. The acquisition and conditioning module uses the sampling circuit to sample the key characteristic quantity monitoring signal of the monitored module assembled in the multi-media transmission integrated connector; uses the operational amplifier circuit to filter and amplify the sampled signal; and finally uses the protection circuit to ensure the safe and stable operation of the entire system.

[0069] The real-time and accuracy of the key characteristic monitoring signals collected by the signal sampling and conditioning circuit are directly related to the effectiveness of the fault state identification algorithm. In order to ensure the accuracy of signal processing, the sampling resistor in the sampling circuit selects the low-resistance alloy chip resistor Y14870R02000B0W, which has a resistance of 20mΩ and a temperature coefficient as low as 50ppm / ℃. It has excellent heat dissipation performance, good power coefficient, and extremely low self-inductance, which can fully guarantee the sampling accuracy. The operational amplifier corresponding to the operational amplifier circuit selects OPA4350, whose maximum input offset voltage is only 100uV and the temperature drift is less than 0.05uV / ℃. It is almost unaffected by the environment and is very suitable for amplifying small voltage signals.

[0070] The temperature sensor signal acquisition and conditioning module is used to realize the sampling of connector temperature signals corresponding to different temperatures and the operational amplification of the signals, monitor the temperature to prevent the connector from overheating and burning, and monitor abnormal heating. The temperature sensor signal acquisition and conditioning module includes a platinum resistance temperature sensor, the input of which is connected to the connector; the output of the platinum resistance temperature sensor is connected to a Wheatstone bridge, which is connected to an operational amplifier circuit, and the output of the operational amplifier circuit is connected to the main control system; the Wheatstone bridge is used to convert the small resistance change of the platinum resistance caused by the temperature change into a small voltage signal and a small current signal output; the operational amplifier circuit is used to amplify the corresponding voltage signal and current signal obtained from the Wheatstone bridge.

[0071] The CAN bus transmission module is used to realize the control command and data interaction between the main control system and the remote terminal, as well as the data interaction between the main control system and the data storage module. The CAN bus transmission module includes a CAN transceiver circuit and a filter circuit connected in sequence. It is connected to the remote control terminal and the main control system respectively through the CAN transceiver circuit. The transceiver signal is filtered and denoised through the filter circuit to realize the control command and data interaction between the main control system and the remote terminal; it also includes a data transmission line, which is connected to the filter circuit and is used for data transmission between the main control system and the data storage module and the remote terminal.

[0072] The power module supplies power to the AD chip, the acquisition and conditioning module, the temperature sensor signal acquisition and conditioning module, the temperature compensation circuit module, the CAN bus transmission module and the data storage module respectively through the main control system.

[0073] The power supply module is mainly composed of a constant current source circuit, a power supply filter protection circuit and a constant voltage source circuit connected in sequence; the constant voltage source circuit and the power supply filter protection circuit are provided by the inside of the intelligent monitoring module 5; the constant current source circuit is provided by the outside of the intelligent monitoring module 5, and the constant current source circuit requires external input as a monitoring function; each functional module is powered by the constant voltage source circuit through the main control system.

[0074] The temperature compensation circuit module is used to ensure that the chips and circuits of the monitored module can be used normally under extreme temperatures; the intelligent self-diagnosis multi-media transmission integrated connector requires an operating temperature of -55℃~125℃, while the operating temperature of some chips can only meet the requirements of -40℃~125℃. There is a large gap in low temperature. The chip needs to be heated at low temperatures to ensure the normal operation of the final product. The low-temperature heating circuit uses an NTC thermistor to monitor the temperature, and a resistor is connected in series to form a voltage divider circuit. The temperature change will cause the voltage divider to change. The MOS tube of the heating circuit is controlled by this voltage to achieve the purpose of automatic heating at low temperature.

[0075] The data storage module is used to store historical measurement values, including historical key characteristic values ​​calculated by the main control system based on the key characteristic quantity monitoring signal, and contact resistance values ​​calculated based on the key characteristic quantity monitoring signal; store the current working status, including plug-in status, normal, fault, current key characteristic value and current contact resistance value; store fault information, including fault location, fault detection value and fault time.

[0076] Example 2

[0077] An intelligent self-diagnosis system for a multi-media transmission integrated connector includes a main control system, such as Figure 3 As shown, the main control system is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through the AD chip to obtain the key characteristic quantity monitoring signal that needs to be processed.

[0078] The main control system includes a remote control command processing module, a state monitoring and fault diagnosis module, and a degradation fault time prediction module; the remote control command processing module is connected to the CAN bus transmission module, and obtains the remote control command and the storage information in the data storage module through the CAN bus transmission module; the state monitoring and fault diagnosis module is connected to the degradation fault time prediction module for performing fault diagnosis and degradation fault time prediction; the state monitoring and fault diagnosis module is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module respectively through the AD chip to monitor the key characteristic quantity monitoring signal in real time and perform fault diagnosis; the state monitoring and fault diagnosis module and the degradation fault time prediction module are both connected to the CAN bus transmission module, and the processing data of the state monitoring and fault diagnosis module and the processing data of the time prediction module are easy to store; the degradation fault time prediction module is provided with a degradation fault time prediction model.

[0079] The state monitoring and fault diagnosis module includes a state monitoring module, which is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through an AD chip; the state monitoring module is connected to the plug-in detection module and the connector multi-module fault detection module respectively, the state monitoring module obtains real-time key characteristic quantity monitoring signals, and transmits them to the plug-in detection module and the connector multi-module fault detection module for processing; the connector multi-module fault detection module is connected to the degradation fault time prediction module; the state monitoring module, the multi-module fault detection module and the plug-in detection module are all connected to the CAN bus transmission module, and the data storage and transmission are realized through the CAN bus transmission module, and it is convenient to timely feedback the fault information to the remote control terminal.

[0080] The other structures and principles are the same as those in Example 1.

[0081] Example 3

[0082] like Figure 1 As shown, an intelligent self-diagnosis method for a multi-media transmission integrated connector includes the following steps:

[0083] S1: Initialize the main control system and set the initial parameters of the degradation failure time prediction model.

[0084] When the system is powered on, the initialization process includes the initialization settings of each sub-functional module of the main control system, as well as the connector instantaneous fault judgment threshold, plug-in detection threshold, etc. The initial parameters of the time prediction model include the accuracy level threshold in the accuracy level table.

[0085] S2: Use the remote control command processing module to determine whether a remote control command is received; if it is determined to be yes, decode the information to obtain a function code, and execute the command in the function code according to the function code; if it is determined to be no, execute step S3.

[0086] Execute the commands in the function code according to the function code: including reading the historical measurement values ​​of the connector, reading the current working status and fault information; setting the instantaneous fault judgment threshold of the connector; and setting the parameters of the degradation fault time prediction model in the degradation fault time prediction module.

[0087] S3: Use the status monitoring and fault diagnosis module to monitor the key characteristic quantity monitoring signal of the connector in real time, and perform plug-in detection and connector multi-module fault detection based on the key characteristic quantity monitoring signal.

[0088] The AD chip adopts a continuous conversion mode to perform AD conversion on key characteristic quantity monitoring signals such as the contact power monitoring signal of the high-speed differential module 4, the contact resistance monitoring signal of the radio frequency transmission module 3, the working pressure monitoring signal of the fluid transmission module 1, the connector temperature monitoring signal and the insertion pressure monitoring signal of the displacement sensor 2.

[0089] Adaptive range switching control is performed based on the key characteristic quantity monitoring signal; specifically: check whether the value of the key characteristic quantity monitoring signal is close to the upper or lower limit of the current range. If the measured value is too high or too low, immediately switch to the appropriate range and continue AD conversion.

[0090] After obtaining the key characteristic quantity monitoring signal after AD conversion, in the state monitoring module, the key characteristic quantity monitoring signal (voltage and current signal) after AD conversion measured and collected by the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module is calculated by volt-ampere method to obtain the current contact resistance value of the high-speed differential module 4, the current contact resistance value of the radio frequency transmission module 3, the current contact resistance value of the fluid transmission module 1, the current resistance value of the platinum resistance temperature sensor, and the current contact resistance value of the displacement sensor 2; and the current working pressure value of the fluid transmission module 1 is calculated according to the current contact resistance value of the fluid transmission module 1 and the working pressure mapping formula; the plugging pressure value of the displacement sensor 2 is calculated according to the current contact resistance value of the displacement sensor 2 and the working pressure mapping formula; the current connector temperature value is obtained according to the temperature-resistance correspondence table of the platinum resistance sensor. In this way, the key characteristic quantity monitoring signal is converted into a key characteristic value, and stored in the data storage module in real time, so that it is convenient for the remote control terminal to view when executing the function code.

[0091] The state monitoring module is used to periodically obtain key characteristic quantity monitoring signals through the AD chip, including the contact resistance value monitoring signal of the high-speed differential module 4, the contact resistance monitoring signal of the radio frequency transmission module 3, the working pressure monitoring signal of the fluid transmission module 1, the connector temperature monitoring signal and the plug-in pressure monitoring signal of the displacement sensor 2, and store them in real time in the data storage module; when the plug-in pressure value change of the displacement sensor 2 is detected, the interrupt service subroutine is entered to perform plug-in detection; when the plug-in pressure value change of the displacement sensor 2 is not detected or the plug-in detection is completed, multi-module fault detection is performed; for the sake of clarity, an example is given here, the above-mentioned plug-in pressure value represents the pressure value, and the plug-in pressure signal refers to the voltage value and current value corresponding to the measured plug-in pressure value.

[0092] In this embodiment, a displacement sensor 2 is used. The pressure acting on the contact surface during the plugging and unplugging operation is converted into resistance change through the flexible piezoresistive film sensor. The intelligent monitoring module 5 continuously monitors the resistance value and then reads the signal peak value. In order to prevent false alarms, the plugging and unplugging threshold and the loosening threshold are set according to the pressure value of normal operation. When the monitored pressure value is greater than the plugging and unplugging threshold or the loosening threshold, it is considered that a plugging and unplugging operation has occurred or the connector is loose.

[0093] Plug and unplug detection: When a change in the mating pressure value is detected, the interrupt service subroutine is entered. The mating pressure value is obtained through the plug and unplug detection module, and then preprocessing of the sampled data is performed to obtain the preprocessed mating pressure value F. First, the mating pressure value F is compared with the plug and unplug threshold F0 and the loosening threshold F1 respectively. In this embodiment, the plug and unplug threshold is set to F0. If F > F0, it is determined that a plug and unplug operation has occurred, and plug and unplug counting is performed, and the counting data is stored in the data storage module. In this embodiment, the loosening threshold is set to F1. If F < F1 and the duration t > 200 ms, it is considered that the connector is loose, and the fault information at this time, including the fault location, the fault detection value, and the fault time, is recorded, and a loosening alarm is given: information encoding is performed, and the fault information is sent to the remote control terminal through the CAN bus transmission module. If the voltage value is restored after F < F0 and the duration t < 200 ms, it is considered a false touch. After the above operations are completed, the interrupt service subroutine is exited, and multi-module fault detection is performed.

[0094] Multi-module fault detection: When the mating pressure value of the displacement sensor 2 is not detected or the plug and unplug detection is completed, the multi-module fault detection module is used to obtain the key characteristic quantity monitoring signals such as the contact resistance monitoring signal of the high-speed differential module 4, the contact resistance monitoring signal of the radio frequency transmission module 3, the working pressure monitoring signal of the fluid transmission module 1, the connector temperature monitoring signal, and the mating pressure monitoring signal of the displacement sensor 2.

[0095] Preprocessing is performed on the key characteristic quantity monitoring signals, including the elimination of abnormal data and data smoothing processing; eigenvalue calculation is performed based on the preprocessed key characteristic quantity monitoring signals, and fault judgment is performed according to the eigenvalues using the instantaneous fault threshold. The eigenvalues are the contact resistance value of the monitored module and the connector temperature value.

[0096] Perform fault judgment and calculate characteristic values: read the key characteristic quantity monitoring signal after preprocessing, and convert the key characteristic quantity monitoring signal collected by the signal sampling and conditioning circuit into the contact resistance value of the monitored module obtained by the voltage signal and the resistance signal corresponding to the monitoring signal of the monitored module; convert the voltage and current signals corresponding to the key characteristic quantity monitoring signal collected by the temperature sensor signal acquisition and conditioning module into corresponding resistance values, and obtain the connector temperature value according to the temperature-resistance correspondence table of the platinum resistance sensor; compare the contact resistance value and connector temperature value of the monitored module with the instantaneous threshold value. When the contact resistance value and connector temperature value of the monitored module exceed the threshold value, it is judged that a fault has occurred and the fault information is stored in the data storage module. The fault information includes the fault location, fault value (resistance value, temperature value), and fault time, are used to build a long-term failure database; when the contact resistance value and connector temperature value of the monitored module do not exceed the threshold value, it is judged that no fault has occurred; the binary contact resistance value and connector temperature value of the monitored module are first converted into corresponding decimal values, namely, the contact resistance value of the high-speed differential module 4, the contact resistance value of the radio frequency transmission module 3, the contact resistance value of the fluid transmission module 1, the connector temperature value and the contact resistance value of the displacement sensor 2; in order to ensure that the measurement results can accurately reflect the actual physical conditions, the contact resistance value and connector temperature value of the corresponding monitored module are calculated through the proportional amplification relationship; in order to facilitate transmission and display, the contact resistance value and connector temperature value of the monitored module are converted into corresponding BCD codes according to hundreds, tens, units and decimal places, and stored.

[0097] S4: If the fault detection result is that a fault has occurred, an alarm message is sent to the remote control terminal through the CAN bus remote communication module after information encoding.

[0098] S5: If the fault detection result is that no fault has occurred, a degradation fault time prediction module is used to predict the degradation fault time, and a data storage module is used to store data.

[0099] The contact resistance value of the monitored module is used as experimental data, and the model parameters are corrected based on the gray model theory, and the degradation failure time is predicted and stored.

[0100] The method is:

[0101] St1: Based on the long-term failure database, the original sequence of contact resistance (such as the contact resistance of the high-speed differential module 4) changing with time is obtained to ensure that these data are non-negative discrete sequences.

[0102] The original sequence is:

[0103] X (0) ={x (0) (1),x (0)(2),…,x (0) (k),…,x (0) (n)}

[0104] Among them, x (0) (k) represents the contact resistance value at the kth moment.

[0105] St2: original data sequence X (0) Perform an accumulation to generate an accumulation sequence:

[0106] X (1) ={x (1) (1),x (1) (2),…,x (1) (k),…,x (1) (n)}

[0107] in,

[0108] St3: According to the cumulative sequence X (1) Construct the GM(1,1) model.

[0109]

[0110] Among them, a and b are variable parameters. The least square method is used to perform regression analysis on the degradation model parameters a and b to correct the model parameters. This process is actually to find the a and b values ​​that minimize the sum of squares of the errors between the model prediction value and the actual value.

[0111] The method of solving the parameters a and b using the least squares method is:

[0112] According to the cumulative sequence X (1) Construct background value sequence Z (1) :

[0113] Z (1) (k) = 0.5[X (1) (k)+X (1) (k-1)]

[0114] According to the background value sequence Z (1) Construct matrix B and vector Y n ;

[0115] Matrix B is a (n-1)*2 matrix with the first column being -Z (1) (1),-Z (1) (3),...,-Z (1) (n), the second column is all 1;

[0116] Vector Y n is a (n-1)*1 matrix consisting of the original sequence x (0)(2),x (0) (3),…,x (0) (n) constitute;

[0117] Solve linear equations:

[0118] [a,b] T =(B T B) -1 B T Y n .

[0119] St4: Solve the whitening equation of the GM(1,1) model to obtain the prediction sequence expression, and obtain the final prediction sequence based on the prediction sequence expression.

[0120] The whitening equation of the GM(1,1) model is:

[0121]

[0122] Predict sequence expression:

[0123]

[0124] The final prediction sequence is:

[0125]

[0126] St5: Calculate the residual sequence based on the final prediction sequence, calculate the posterior error ratio C based on the variance of the original data sequence and the variance of the residual sequence; and calculate the small error probability P based on the residual sequence.

[0127] Compute the residual sequence:

[0128]

[0129] Among them, q(k) is the residual of each element in the original data sequence and the final prediction sequence.

[0130] St6: Perform accuracy evaluation based on the posterior difference ratio C and the small error probability P; the benchmark value described in step S1 includes the accuracy evaluation thresholds of the posterior difference ratio C and the small error probability P.

[0131] The posterior difference ratio C is:

[0132]

[0133] Among them, s1 is the variance of the original sequence, and s2 is the variance of the residual sequence.

[0134] The probability of small error P is:

[0135]

[0136] in, is the mean of the contact resistance values ​​in the original data series.

[0137] Table 1 Precision level table of the posterior difference test method

[0138]

[0139] St7: Reselect the original data sequence and repeat steps St2 to St5 until the GM(1,1) model accuracy reaches the expected level and retain the optimal parameters.

[0140] St8: Input the experimental data into the GM(1,1) model with the optimal parameters retained to obtain a prediction sequence; based on the prediction sequence, calculate the degradation failure time.

[0141] The fault threshold of the contact resistance of the monitored module is set based on the long-term failure database, and the time required for the contact resistance value of the monitored module in the current experimental data to reach the fault threshold is calculated from the prediction sequence, which is the degradation fault time of the contact resistance of the monitored module. Finally, the degradation fault time experimental data is stored in the data storage.

[0142] The other structures and principles are the same as those in Example 1.

[0143] 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 principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent self-diagnosis system for a multi-media transmission integrated connector, characterized in that: It includes a main control system, which is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through an AD chip; the main control system is connected to a CAN bus transmission module, a power supply module and a temperature compensation circuit module, the CAN bus transmission module is connected to a data storage module; and the CAN bus transmission module is connected to a remote control terminal.

2. The intelligent self-diagnosis system of the multimedia transmission integrated connector according to claim 1, characterized in that: The main control system includes a remote control command processing module, a state monitoring and fault diagnosis module and a degradation fault time prediction module; the remote control command processing module, the state monitoring and fault diagnosis module and the degradation fault time prediction module are all connected to the CAN bus transmission module, and the state monitoring and fault diagnosis module and the degradation fault time prediction module are connected; the state monitoring and fault diagnosis module is respectively connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through the AD chip.

3. The intelligent self-diagnosis system of the multimedia transmission integrated connector according to claim 2, characterized in that: The state monitoring and fault diagnosis module includes a state monitoring module, which is connected to the acquisition and conditioning module and the temperature sensor signal acquisition and conditioning module through an AD chip, and is connected to the plug-in detection module and the connector multi-module fault detection module, respectively; the state monitoring module, the plug-in detection module and the multi-module fault detection module are all connected to the CAN bus transmission module.

4. An intelligent self-diagnosis method for a multimedia transmission integrated connector, using the intelligent self-diagnosis system for a multimedia transmission integrated connector according to any one of claims 1 to 3, characterized in that: Includes steps: S1: Initialize the main control system and set the initial parameters of the degradation failure time prediction model; S2: using the remote control command processing module to determine whether a remote control command is received; If the judgment is yes, the information is decoded to obtain the function code, and the command in the function code is executed according to the function code; if the judgment is no, step S3 is executed; S3: Use the status monitoring and fault diagnosis module to monitor the key characteristic quantity monitoring signal of the connector in real time, and perform plug-in detection and connector multi-module fault detection according to the key characteristic quantity monitoring signal; S4: If the fault detection result is a fault, an alarm message is sent to the remote control terminal through the CAN bus transmission module after information encoding; S5: If the fault detection result is that no fault has occurred, a degradation fault time prediction module is used to predict the degradation fault time, and a data storage module is used to store data.

5. The intelligent self-diagnosis method of the multimedia transmission integrated connector according to claim 4, characterized in that: Executing the command in the function code according to the function code in step S2 includes reading the historical measurement value of the connector, reading the current working status and fault information, and setting the instantaneous fault judgment threshold and the plug-in detection threshold of the connector, and the plug-in detection threshold includes the plug-in threshold and the loose threshold; Parameter setting of the degradation failure time prediction model in the degradation failure time prediction module.

6. The intelligent self-diagnosis method of the multimedia transmission integrated connector according to claim 5, characterized in that: The method for performing plug-in detection and connector multi-module fault detection based on key characteristic quantity monitoring signals is as follows: The key characteristic quantity monitoring signal is AD converted by using the AD chip in a continuous and sequential conversion mode; the adaptive range switching control is performed according to the key characteristic quantity monitoring signal; the key characteristic quantity monitoring signal of the connector is periodically obtained through the AD chip by using the state monitoring module, the key characteristic value is obtained according to the key characteristic quantity monitoring signal, and is stored in the data storage module in real time; when the plugging pressure value change in the key characteristic value is detected, the plugging and unplugging detection is performed; when the plugging pressure value change is not detected or the plugging and unplugging detection is completed, multi-module fault detection is performed.

7. The intelligent self-diagnosis method of the multimedia transmission integrated connector according to claim 6, characterized in that: The plug-in detection method comprises: obtaining the plug-in pressure value from the state monitoring module through the plug-in detection module, and then preprocessing the sampled data to obtain the preprocessed plug-in pressure value, and comparing the preprocessed plug-in pressure value with the plug-in threshold and the loose threshold to determine the plug-in state; selecting false touch, loose alarm or plug-in count according to the plug-in state; and exiting the plug-in detection after completing the selected operation; The method of multi-module fault detection is: using a multi-module fault detection module to obtain a key characteristic quantity monitoring signal; The key characteristic quantity monitoring signal is preprocessed, including the elimination of abnormal data and data smoothing; the characteristic value is calculated based on the preprocessed key characteristic quantity monitoring signal and the fault judgment is made based on the instantaneous fault threshold.

8. The intelligent self-diagnosis method of the multimedia transmission integrated connector according to claim 7, characterized in that: The method for calculating characteristic values ​​and performing fault judgment based on the instantaneous fault threshold is as follows: reading the preprocessed key characteristic quantity monitoring signal, converting the preprocessed key characteristic quantity monitoring signal into characteristic values, the characteristic values ​​including the contact resistance value and the connector temperature value, and comparing the contact resistance value and the connector temperature value of the monitored module with the instantaneous threshold; When the contact resistance value and connector temperature value of the monitored module exceed the threshold, it is judged as a fault, and the fault information is stored in the data storage module, and a long-term failure database is built; When the contact resistance value and connector temperature value of the monitored module do not exceed the threshold value, it is determined that no fault has occurred. The binary contact resistance value and connector temperature value of the monitored module are first converted into corresponding decimal values, and then the corresponding contact resistance value and connector temperature value of the monitored module are calculated through the proportional amplification relationship. The obtained contact resistance value and connector temperature value of the monitored module are then converted into corresponding BCD codes and stored; The method for predicting the degradation fault time using the degradation fault time prediction module described in step S5 is: using the contact resistance value of the monitored module as experimental data, correcting the model parameters based on the grayscale model theory and predicting the degradation fault time.

9. The intelligent self-diagnosis method of the multimedia transmission integrated connector according to claim 8, characterized in that: The method for correcting the model parameters and predicting the degradation failure time based on the gray model theory is: St1: Obtain the original sequence of contact resistance variation over time based on the long-term failure database; St2: accumulate the original data sequence once to generate the accumulated sequence; St3: Construct the GM(1,1) model based on the cumulative sequence and use the least squares method to perform regression analysis and correction on the degradation model parameters; St4: Solve the whitening equation of the GM (1,1) model to obtain the prediction sequence expression, and obtain the final prediction sequence based on the prediction sequence expression; St5: Calculate the residual sequence based on the final prediction sequence, calculate the posterior error ratio C based on the variance of the original data sequence and the variance of the residual sequence; and calculate the small error probability P based on the residual sequence; St6: Accuracy is judged based on the posterior difference ratio C and the small error probability P; St7: Reselect the original data sequence and repeat steps St2 to St5 until the GM(1,1) model accuracy reaches the expected value, and retain the best parameters; St8: Input the experimental data into the GM(1,1) model with the optimal parameters retained to obtain a prediction sequence; based on the prediction sequence, calculate the degradation failure time.

10. The intelligent self-diagnosis method of the multimedia transmission integrated connector according to claim 9, characterized in that: The GM(1,1) model is: Among them, x (1) (k) is the k-th moment element of the cumulative sequence, x (0) (i) is the contact resistance value at the i-th moment in the original sequence; a and b are variable parameters; The prediction sequence expression is: in, is the predicted contact resistance value at the k+1th moment in the prediction sequence, and n is the sequence length; The residual sequence calculation formula is: Among them, q(k) is the residual of each element in the original data sequence and the final prediction sequence; The posterior difference ratio C is: Among them, s1 is the variance of the original sequence, and s2 is the variance of the residual sequence; The probability of small error P is: in, is the mean of the contact resistance values ​​in the original data series.

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