An output terminal detection system and method based on intelligent temperature cabinet control

Abstract

This application relates to an output terminal detection system and method based on intelligent temperature cabinet control. The system includes an acquisition module, which is connected to the load connection point and is used to collect the circuit parameters and temperature parameters of the load connection point; a data processing module, which is signal-connected to the acquisition module and is used to receive the circuit parameters and temperature parameters, and analyze the safety risks of the load connection point based on the circuit parameters and temperature parameters; a driving module, which is connected to the load connection point and is used to control the on / off of the load connection point, and the driving module is signal-connected to the data processing module; the data processing module controls the on / off of the load connection point through the driving module according to the safety risks of the load connection point. The method is applied to the above system. By connecting the acquisition module and the driving module to the load connection point, this application can control the on / off according to the situation of the load connection point, and can play an effective monitoring and protection role, and is applicable to temperature cabinet equipment.

Description

Technical Field

[0001] This application relates to the technical field of temperature control equipment monitoring, and specifically relates to an output terminal detection system and method based on intelligent temperature cabinet control. Background Art

[0002] For refrigeration and heating equipment such as temperature cabinets, such as freezers, refrigerators, cold storage cabinets, heating cabinets, etc., which contain multiple loads, such as compressors, fans, heaters, lighting lamps, etc., the temperature cabinets are in a long-term automatic operation state. For example, components such as compressors, fans, and heaters start and stop periodically according to the refrigeration and heating plans. During this operation process, at the moment of starting and stopping of the load, the system will bear a large current impact. And due to no one monitoring, there may be faults such as the suction device (relay or circuit breaker) being unable to disconnect the load connection, the output contact point sticking and short-circuiting, until the output demand is uncontrollable, the load connection cannot be disconnected, resulting in the load outputting fixedly for a long time, or poor contact of the contact point due to aging of the suction device, contact point sparking, or even burning out or causing a fire, etc.

[0003] Currently, the circuit protection for temperature cabinet equipment is usually to perform tripping protection at the high-voltage input end of the load. When the load is overcurrent, it trips to disconnect the connection between the load and the power grid to protect the load. This tripping protection method has low accuracy and slow action response, and cannot be applied to equipment such as temperature cabinets that must work for a long time, and cannot achieve an effective monitoring and protection effect. Summary of the Invention

[0004] In order to solve the problems existing in the above-mentioned prior art, the purpose of this application is to provide an output terminal detection system and method based on intelligent temperature cabinet control. By connecting a collection module and a drive module to the load connection point, this application can control the on-off according to the situation of the load connection point, and can play an effective monitoring and protection role, and is applicable to temperature cabinet equipment.

[0005] An output terminal detection system based on intelligent temperature cabinet control described in this application includes:

[0006] A collection module, which is connected to the load access point and is used to collect the circuit parameters of the load connection point;

[0007] A data processing module, which is signal-connected to the collection module and is used to receive the circuit parameters and analyze the safety risks of the load connection point based on the circuit parameters;

[0008] A drive module, which is connected to the load connection point to control the on-off of the load connection point, and the drive module is signal-connected to the data processing module;

[0009] The data processing module controls the on / off of the load connection point through the drive module according to the security risk of the load connection point.

[0010] Preferably, the acquisition module also acquires the temperature parameter of the load connection point, and the data processing module analyzes the security risk of the load connection point based on the circuit parameter and the temperature parameter; the acquisition module includes a circuit parameter acquisition unit and a temperature parameter acquisition unit;

[0011] The circuit parameter acquisition unit includes a first resistor, a first zener diode, a second resistor, and a first rectifier diode connected in series in sequence; one end of the first resistor away from the first zener diode is respectively connected to the N terminal of the high-voltage input and the N terminal of the load;

[0012] One end of the first rectifier diode away from the second resistor is connected between the load connection point and the L terminal of the load;

[0013] The temperature acquisition unit includes a thermistor correspondingly arranged with the load connection point.

[0014] Preferably, the drive module includes a third resistor, a fourth resistor, a first triode, a first capacitor, a second rectifier diode, and a switch. One end of the third resistor is connected to the data processing module, and the other end is connected to the base of the first triode. The emitter of the first triode is grounded, and the collector is connected to the switch and then connected to an external voltage. The contact end of the switch is connected to the load connection point. The collector of the first triode is also connected to the first capacitor and then grounded; one end of the fourth resistor is connected to the emitter of the first triode, and the other end is connected between the base of the first triode and the third resistor; the positive pole of the second rectifier diode is connected between the base of the first triode and the switch, and the negative pole is connected between the switch and the external voltage.

[0015] Preferably, the output terminal detection system based on the intelligent temperature cabinet further includes an isolation module, an amplification module, and an optimization module connected in series in sequence. The input terminal of the isolation module is connected in parallel to both ends of the first zener diode, and the output terminal of the optimization module is connected to the data processing module.

[0016] Preferably, the circuit parameters include the no-load load of the load connection point, the signal at the moment of connection point connection, the working current, the aging state of the connection point, and the signal at the moment of connection point disconnection, and the temperature parameter includes the connection point temperature;

[0017] The data processing module controls the on / off of the load connection point through the drive module according to the security risk of the load connection point, including:

[0018] Before the start-up phase of the load, obtain the no-load load of the load connection point and numerically compare it with the first range value Rv1. If the no-load load belongs to the first range value, allow the load to start; otherwise, output an alarm message indicating that the no-load load is abnormal.

[0019] At the moment of load start-up, obtain the connection instant signal of the load connection point and perform a similarity analysis with the first reference signal. If the similarity analysis result is not less than the first similarity threshold, determine that the load starts normally; otherwise, disconnect the load connection point and output an alarm message indicating that the load starts abnormally.

[0020] During the operation of the load, obtain the working current I, the aging state Ag of the connection point, and the connection point temperature T of the load connection point, and determine whether the normal working conditions are met. If so, determine that the load is working normally; otherwise, disconnect the connection point and output an alarm message indicating that the load is working abnormally.

[0021] The normal working conditions are:

[0022]

[0023] Among them, Rv2, thr Ag , Rv3 respectively represent the second range value, the aging threshold, and the third range value, ω1, ω2, ω3 respectively represent the first weight corresponding to the working current I, the second weight corresponding to the aging state Ag of the connection point, and the third weight corresponding to the connection point temperature T, max|Rv2 - I| represents the larger value of the difference between the boundary values of the second range value Rv2 and the working current I, thr1 represents the safety risk threshold, max|Rv3 - T| represents the larger value of the difference between the boundary values of the third range value Rv3 and the connection point temperature T, and c represents the comparison constant.

[0024] At the moment of load shutdown, obtain the connection point disconnection instant signal of the load connection point and perform a similarity analysis with the second reference signal. If the similarity analysis result is not less than the second similarity threshold, determine that the load shuts down normally; otherwise, output an alarm message indicating that the load shuts down abnormally.

[0025] Preferably, the data processing module obtains sample data of the load connection point regarding circuit parameters and temperature parameters, and based on the sample data, constructs an association model. The association model takes the no-load load and the connection instant signal of the load connection point as inputs, and takes the working current of the load connection point and the connection point disconnection instant signal as outputs. The association model is used to represent the association relationship between the input parameters and the output parameters.

[0026] When performing a security risk analysis of the load connection point each time, the data processing module inputs the no-load load of the load connection point and the signal at the moment of connection of the connection point obtained in real time into the correlation model, obtains the correlation value of the working current of the load connection point and the signal at the moment of disconnection of the connection point, and adjusts the second range value and the second reference signal based on the correlation value.

[0027] Preferably, the data processing module has a first prediction model, a second prediction model, and a third prediction model;

[0028] The first prediction model is used to predict the predicted value of the working current I in a certain future period, denoted as the predicted current I_pre;

[0029] The second prediction model is used to predict the predicted value of the aging state Ag of the connection point in a certain future period, denoted as the predicted aging state Ag_pre;

[0030] The third prediction model is used to predict the predicted value of the connection point temperature T in a certain future period, denoted as the predicted temperature T_pre;

[0031] During the operation of the load, the working current I, the aging state Ag of the connection point, and the connection point temperature T are respectively predicted through the first prediction model, the second prediction model, and the third prediction model to obtain the predicted current I_pre, the predicted aging state Ag_pre, and the predicted temperature T_pre. If the following conditions are met:

[0032]

[0033] Then a warning message of abnormal load operation is output. If not met, continuous monitoring is carried out.

[0034] Preferably, the data processing module adjusts the calculation weights in the normal working conditions according to the load working state and the load connection point state:

[0035] If the load performs power switching, the first weight is increased, and the second weight and the third weight are decreased;

[0036] If the usage duration of the load connection point is greater than the preset usage time threshold, the second weight is increased, and the first weight and the third weight are decreased;

[0037] If the single continuous working time of the load is greater than the preset working time threshold, the third weight is increased, and the first weight and the second weight are decreased.

[0038] Preferably, after each load shutdown, the data processing module compares the connection instant signal and disconnection instant signal of the connection point for consistency, and evaluates the electrical performance stability of the load based on the comparison result of the consistency comparison. The consistency comparison includes waveform symmetry comparison, signal change trend comparison, and signal duration comparison.

[0039] An output terminal detection method based on intelligent temperature cabinet control of the present application includes: connecting a collection module and a drive module to a load access point;

[0040] Collecting circuit parameters of the load connection point through the collection module;

[0041] Analyzing the safety risk of the load connection point based on the circuit parameters;

[0042] Controlling the on / off of the load connection point through the drive module according to the safety risk of the load connection point. The advantages of the output terminal detection system and method based on intelligent temperature cabinet control of the present application are as follows:

[0043] 1. In the present application, by connecting a collection module and a drive module to each load connection point of the high-voltage input, collecting the circuit parameters and temperature parameters (optional) of the load connection point through the collection module, analyzing the collected parameters through the data processing module, evaluating the safety risk of the load connection point, and controlling the on / off action of the load connection point through the drive module according to the safety risk level, this method can comprehensively monitor various parameters of the load connection point, and thus can comprehensively evaluate the safety risk of the load connection point, making the monitoring of the load comprehensive, timely, and effective, and enabling effective monitoring and protection of the temperature cabinet equipment.

[0044] 2. The circuit structures of the collection module and the drive module of the present application are simple, easy to implement, and have low implementation costs. They can be compatible with most conventional loads on the market, such as inductive loads, capacitive loads, resistive loads, etc., and can be connected without changing the original circuit structure of the temperature cabinet, with wide applicability.

[0045] 3. Combining the characteristics of a load operation cycle, the present application splits the operation cycle of the load connection point into different stages, sets the monitored parameters and corresponding actions to be executed in different stages, making the monitoring of the load connection point more accurate, being able to more accurately monitor abnormal conditions of the load connection point in different stages, and making action responses in a timely manner, improving the accuracy and reliability of load monitoring.

[0046] 4. The present application introduces an association model, which can obtain subsequent association parameters based on the no-load load and the signal at the moment of connection of the connection point obtained in real time, and use the obtained association parameters as a reference for adjusting benchmark values such as range values to adjust the benchmark values, so that the benchmark values can be close to the load actions actually occurring each time, that is, the benchmark values can be adjusted with the operation of the electrical system, making the monitoring process closer to the actual working conditions and effectively reducing the occurrence of false alarms.

[0047] 5. By introducing a prediction model, the present application predicts the working current, the temperature of the connection point and the aging state of the connection point during the operation of the load, can predict in advance the possible abnormalities of the load and give early warnings, and can further improve the timeliness and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a structural block diagram of an output terminal detection system based on intelligent temperature cabinet control described in the present application;

[0049] Figure 2 is a circuit schematic diagram of an output terminal detection system based on intelligent temperature cabinet control described in the present application.

[0050] Description of reference numerals: P - load connection point, 1 - acquisition module, 2 - data processing module, 3 - drive module, 4 - amplification module, 5 - communication module, 6 - data center, P - load connection point, R1 - first resistor, R2 - second resistor, R3 - third resistor, R4 - fourth resistor, R5 - fifth resistor, R6 - sixth resistor, R7 - seventh resistor, Rt - thermistor, Q1 - first triode, Q2 - second triode, D1 - first rectifier diode, D2 - second rectifier diode, DZ1 - first voltage regulator diode, U1 - isolation module, K - switch, C1 - first capacitor, C2 - second capacitor. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] As Figure 1 shown, an output terminal detection system based on intelligent temperature cabinet control described in the present application includes:

[0052] An acquisition module 1, which is connected to the load access point and is used to acquire the circuit parameters and temperature parameters of the load connection point P; specifically, the temperature parameter is a non-essential parameter. In other alternative embodiments, the circuit parameters can be acquired alone for monitoring, and acquiring the temperature parameter can improve the accuracy of the output terminal detection result.

[0053] Specifically, in detail as Figure 2As shown in the figure, the load connection point P refers to the connection point between loads such as compressors, fans, heaters, and lighting fixtures and the high-voltage input power grid. Usually in the form of an on-off control switch, the N terminal of the high-voltage input is connected to the N terminal of the load, and the L terminal of the high-voltage input is connected to the L terminal of the load. The load connection point P is set on the connection line between the L terminal of the high-voltage input and the L terminal of the load. When the load connection point P is turned on, the load is connected to the high-voltage power grid and powered on. When the load connection point P is turned off, the load is powered off and stops operating.

[0054] The acquisition module 1 includes a circuit parameter acquisition unit and a temperature parameter acquisition unit. The circuit parameter acquisition unit includes a first resistor R1, a first zener diode DZ1, a second resistor R2, and a first rectifier diode D1 connected in series in sequence. One end of the first resistor R1 far from the first zener diode DZ1 is respectively connected to the N terminal of the high-voltage input and the N terminal of the load.

[0055] One end of the first rectifier diode D1 far from the second resistor R2 is connected between the load connection point P and the L terminal of the load.

[0056] The above circuit composed of the first resistor R1, the first zener diode DZ1, the second resistor R2, and the first rectifier diode D1, when connected to the load connection point P, can obtain the original load voltage difference signal of the load connection point P, and can also calculate the no-load load, working current, connection point resistance, etc. of the load connection point P, and can collect the signals at the moment when the load connection point P is turned on and off and upload them.

[0057] Specifically, the original load voltage difference signal refers to the voltage difference signal across the loop formed by the N terminal of the load, the first resistor R1, the second resistor R2, the first rectifier diode D1, the L terminal of the load, and the load that forms the current path. The no-load load refers to the load of the small current path formed by the N terminal of the load, the first resistor R1, the second resistor R2, the first rectifier diode D1, the L terminal of the load, and the load after the drive module 3 is connected and the switching element K of the drive module 3 is in the off state. The connection point resistance can be calculated from the voltage and current at both ends of the connection point. The working current can be obtained by calculating the voltage drop across the switching element K formed by the equivalent resistance of the on-state of the switching element K, the L terminal of the load, and the L terminal of the high-voltage input, combined with the equivalent resistance of the switching element K. The aging state can be obtained by calculating the resistance growth rate of the connection point resistance.

[0058] The temperature acquisition unit includes a thermistor Rt corresponding to the load connection point P. Specifically, the thermistor Rt can be in thermal contact with the load connection point P, so that the thermistor Rt can sense the temperature of the load connection point P and convert it into an electrical signal for uploading.

[0059] The data processing module 2 is signal - connected to the acquisition module 1 and is used to receive the circuit parameters and temperature parameters, and analyze the safety risks of the load connection point P based on the circuit parameters and temperature parameters. In a specific embodiment, the data processing module 2 can select a controller with arithmetic processing functions such as an MCU.

[0060] The driving module 3 is connected to the load connection point P to control the on - off of the load connection point P, and the driving module 3 is signal - connected to the data processing module 2.

[0061] Specifically, the driving module 3 includes a third resistor R3, a fourth resistor R4, a first triode Q1, a first capacitor C1, a second rectifier diode D2, and a switch K. The switch K can be a relay. One end of the third resistor R3 is connected to the data processing module 2, and the other end is connected to the base of the first triode Q1. The emitter of the first triode Q1 is grounded, and the collector is connected to the switch K and then connected to an external voltage. The contact end of the switch K is connected to the load connection point P. The collector of the first triode Q1 is also connected to the first capacitor C1 and then grounded. One end of the fourth resistor R4 is connected to the emitter of the first triode Q1, and the other end is connected between the base of the first triode Q1 and the third resistor R3. The positive electrode of the second rectifier diode D2 is connected between the base of the first triode Q1 and the switch K, and the negative electrode is connected between the switch K and the external voltage.

[0062] By connecting the above - mentioned driving module 3 at the load connection point P, the on - off of the load connection point P can be controlled by the output signal of the data processing module 2. For example, when the data processing module 2 outputs a connection point conduction signal, the signal is input to the base of the first triode Q1, making the collector and emitter of the first triode Q1 conduct, and then making the relay contact end connected to the load connection point P conduct, forming a path, and enabling the load to be connected to the high - voltage input power grid. Through the above - mentioned driving module 3, the on - off of the load connection point P can be controlled by the output signal of the data processing module 2.

[0063] In a preferred embodiment, the output - end detection system further includes an isolation module U1, an amplification module 4, and an optimization module connected in series in sequence. The isolation module U1 is specifically an optocoupler. The input end of the optocoupler is connected in parallel at both ends of the first zener diode DZ1, and the output end is connected to the input end of the amplification module 4.

[0064] Exemplarily, the amplification module 4 includes a fifth resistor R5, a sixth resistor R6, and a second triode Q2. The optimization module includes a second capacitor C2, a seventh resistor R7, and an NC resistor. The second capacitor C2 is connected in parallel across both ends of the optocoupler output. The emitter of the second triode Q2 is grounded, the collector is connected to the data processing module 2, and the base is sequentially connected in series with the fifth resistor R5 and the seventh resistor R7 and then connected to the 3.3V VDD voltage. The fifth resistor R5 is connected to the NC resistor and then grounded. The collector of the second triode Q2 is also connected to the sixth resistor R6 and then connected between the 3.3V VDD voltage and the seventh resistor R7.

[0065] Through the above structure, the collected original load voltage difference signal can be isolated, signal amplified, and signal quality optimized, so that the signal received by the data processing module 2 is accurate.

[0066] In other alternative embodiments, the amplification module 4 and the optimization module can select existing integrated signal amplifiers and signal optimizers, and this embodiment does not limit this.

[0067] In other alternative embodiments, the data processing module 2 is also connected to the data center 6 in the background through the communication module 5, and the collected and processed data is uploaded to the data center 6 for storage.

[0068] The data processing module 2 controls the on / off of the load connection point P through the drive module 3 according to the safety risk of the load connection point P.

[0069] Specifically, taking the load from startup to shutdown as an action cycle, the action cycle is split into four stages: the stage before load startup, the moment of load startup, the process of load operation, and the moment of load shutdown. Monitoring the key parameters of the load connection point P in different stages will help comprehensively monitor the safety risk of the load connection point P. Compared with the general overcurrent monitoring in the prior art, the staged monitoring method in this embodiment has stronger pertinence.

[0070] The specific approach is as follows:

[0071] In the stage before load startup, that is, when the load is in the shutdown state, mainly detect whether the no-load load of the load connection point P is normal. The no-load load can reflect the stability and efficiency of the electrical system. Generally speaking, when the electrical system is normal, the no-load load of the load connection point P is within a normal range value, and this range value can be the average value of the no-load load historical data of the load connection point P. For example, analyze the no-load load historical data of the load connection point P in the previous seven days, calculate that its no-load load is 50w, then the reasonable range value of the no-load load can be set to 45w - 55w.

[0072] Before the start-up phase of the load, the no-load load of the load connection point P is obtained and numerically compared with the first range value Rv1. If the no-load load belongs to the first range value, the load is allowed to start. For example, if the real-time no-load load is within 45w to 55w as described above, it indicates that the no-load load of the load connection point P is at a normal level and the load is allowed to start normally. If it does not belong to this range value, it indicates that there may be an abnormal no-load load in the electrical system, and an alarm message for abnormal no-load load is output to prompt the maintenance personnel to perform inspection and confirmation.

[0073] At the moment of load start-up, the similarity analysis is performed on the connection instant signal of the load connection point P and the first reference signal. Specifically, the first reference signal can be the connection instant signal detected at the load connection point P when the load starts up normally. The first reference signal is obtained by sampling multiple times and taking the average value, and the first reference signal is used as the reference for evaluating whether the load starts up normally. At the actual start-up moment of the load, the connection instant signal at the load connection point P is obtained and similarity analysis is performed with the aforementioned first reference signal. The specific method is to draw the waveform diagram of the first reference signal. After obtaining the connection instant signal, the digital processing module converts it into the corresponding waveform diagram, and the similarity analysis of the two waveform diagrams is performed, that is, the degree of coincidence of the two waveform diagrams is judged as the similarity analysis result. If the similarity analysis result is not less than the first similarity threshold, it is judged that the load starts up normally, otherwise it is judged that the load starts up abnormally, the load connection point P is disconnected, and an alarm message for abnormal load start-up is output. Specifically, the first similarity threshold can be set according to the requirements for detection sensitivity. For example, when the similarity between the connection instant signal of the real-time start-up and the first reference signal reaches more than 80%, it is judged that the load starts up normally.

[0074] During the operation of the load, that is, in the live working state of the load, the working current I of the connection point, the aging state Ag of the connection point, and the connection point temperature T are obtained, and it is judged whether the normal working conditions are met. If so, it is judged that the load is working normally, otherwise the connection point is disconnected and an alarm message for abnormal load operation is output;

[0075] The normal working conditions are:

[0076]

[0077] Among them, Rv2, thr Ag, Rv3 represents the second range value, the aging threshold, and the third range value respectively, ω1, ω2, ω3 represent the first weight corresponding to the working current I, the second weight corresponding to the aging state Ag of the connection point, and the third weight corresponding to the connection point temperature T respectively, max|Rv2 - I| represents the larger value of the difference between the boundary values of the second range value Rv2 and the working current I, thr1 represents the safety risk threshold, max|Rv3 - T| represents the larger value of the difference between the boundary values of the third range value Rv3 and the connection point temperature T, and c represents the comparison constant;

[0078] Specifically, the second range value Rv2 and the third range value Rv3 can be set according to the working current and temperature when the load connection point P is working normally, and are used to judge whether the load connection point P is in a normal working state. The aging state of the connection point is quantitatively represented by the growth rate of the resistance of the load connection point P. As the load connection point P is affected by environmental oxidation and corrosion with the increase of the use time, the resistance gradually increases. Therefore, in this embodiment, the resistance growth rate is selected as the quantitative index of the aging state of the load connection point P. The specific calculation method is to record the resistance when the load connection point P is put into use as the initial resistance, obtain the real-time resistance of the load connection point P, and (real-time resistance - initial resistance) / initial resistance * 100% can be used to calculate the aging state of the connection point of the load connection point P.

[0079] Based on the above, during the operation of the load, the working current I, the aging state Ag of the connection point, and the connection point temperature T of the load connection point P can be obtained in real time, and whether the load is working normally can be judged by the above normal working conditions.

[0080] The setting idea of the normal working conditions is as follows:

[0081] For the load connection point P, its aging state is a critical index. When the aging state of the load connection point P reaches this critical index, that is, the aging threshold, there are great potential safety hazards for the load connection point P, and it should be repaired or replaced.

[0082] Both the working current and the connection point temperature are range indexes. For a normally working load, its working current should be within a normal range. Therefore, the second range value Rv2 is set for judgment. Similarly, for a normally working load, if the temperature of its load connection point P is too high or too low, it indicates that there may be abnormalities in the electrical system. Therefore, a range value is used for judgment.

[0083] In addition, through actual tests in this embodiment, it is found that even when the aging state of the connection point at the load connection point P is less than the aging threshold, and both the working current and the connection point temperature are within the normal range, the system may still exhibit abnormalities. Analyzing the reasons, it is found that when the aging state of the connection point is close to the aging threshold, the closer the working current and the connection point temperature of the connection point are to the critical values on one side of the second range value and the third range value, the superposition of these three factors will cause the system to enter an abnormal state and the load cannot operate normally. Therefore, it is necessary to monitor this situation. The specific approach is to perform a comprehensive weighted calculation on the three parameters to comprehensively evaluate the impact of the superposition of the three factors on the system operation. In addition, the differences between the three parameters and the reference values (the second range value, the third range value, and the aging threshold) for comparison need to be considered. For the aging state of the connection point, simply subtract it from the aging threshold directly, and this difference can represent the gap between the aging state of the connection point and the aging threshold. For the second range value and the third range value, taking the working current as an example, it is necessary to consider the differences between the real-time current value and the two boundary values of the second range value. Ideally, the real-time working current value should be in the middle of the second range value, and the differences from the two side boundary values are equal or close. When the real-time working current is close to any critical value, it indicates that the system may be in or about to enter an unstable state. Therefore, it is necessary to calculate the larger value of the differences between the two boundary values and the working current. The specific method is to subtract the working current from each of the two boundary values respectively and take the larger of the two differences. Similarly, calculate the larger value of the differences between the two boundary values and the connection point temperature, and then perform a weighted accumulation of the three parameters. In addition, when the system is operating normally, for example, when the load connection point P is just put into use and the load is in a normal working state, and the working current and the connection point temperature are respectively near the midpoints of the second range value and the third range value, use the above weighted formula for calculation, and take this calculation result as the above comparison constant. During actual monitoring, substitute the real-time working current, connection point temperature, and connection point aging state, use the weighted formula for calculation, and subtract the calculation result from the comparison constant. This difference can reflect the comprehensive degree to which the three parameters deviate from the normal operating conditions. By setting a judgment threshold for this difference, it is possible to comprehensively judge the superposition effect of the three parameters.

[0084] Through this step, by separately performing range value / threshold judgment on the three parameters during the load operation process and comprehensively judging the superposition effect of the three parameters, the abnormal judgment of the load operation process can be made more comprehensive and accurate.

[0085] At the moment when the load shuts down, obtain the signal at the moment when the connection point P of the load disconnects and perform similarity analysis with the second reference signal. If the similarity analysis result is not less than the second similarity threshold, it is determined that the load shuts down normally; otherwise, an alarm message indicating abnormal shutdown of the load is output. The determination process of the signal at the moment when the connection point disconnects is the same as that of the signal at the moment when the foregoing connection point connects, and can be understood with reference to the description above, which will not be elaborated here. This step is used to determine whether the load shuts down normally.

[0086] During the actual testing process, it is found that as the system is used, various parameters will change. If abnormal judgments are always made according to the range values set in the initial state, it cannot well fit the actual operation of the system, and false alarms and missed alarms often easily occur. Therefore, combined with the actual operation of the system, dynamically adjusting the range values can make the abnormal judgment more in line with the actual working conditions. The specific method is as follows:

[0087] The data processing module 2 obtains the sample data of the load connection point P regarding circuit parameters and temperature parameters. Based on the sample data, an association model is constructed. The association model takes the no-load load of the load connection point P and the signal at the moment when the connection point connects as inputs, and takes the working current of the load connection point P and the signal at the moment when the connection point disconnects as outputs. The association model is used to characterize the association relationship between the input parameters and the output parameters.

[0088] Each time the data processing module 2 performs a safety risk analysis on the load connection point P, it inputs the real-time obtained no-load load of the load connection point P and the signal at the moment when the connection point connects into the association model to obtain the association values regarding the working current of the load connection point P and the signal at the moment when the connection point disconnects. Based on the association values, the second range value and the second reference signal are adjusted.

[0089] The specific idea is that the no-load load, as a key parameter before the load starts, has a great influence on subsequent parameters, especially the working current. If the no-load load changes, it will affect the monitored values of subsequent parameters. The signal at the moment when the connection point connects will affect the working current and also the signal at the moment when the connection point disconnects. Therefore, when both the no-load load and the signal at the moment when the connection point connects change significantly, it may have a great impact on the working current and the signal at the moment when the connection point disconnects. Therefore, it is necessary to dynamically adjust the second range value and the signal at the moment when the connection point disconnects in combination with the no-load load and the signal at the moment when the connection point connects. The specific method is to construct an association model that takes the no-load load of the load connection point P and the signal at the moment when the connection point connects as inputs, and takes the working current of the load connection point P and the signal at the moment when the connection point disconnects as outputs. For example, a linear regression model, a support vector machine model, etc. Through the training of a large amount of sample data, this model can characterize the association relationship between the input and the output.

[0090] During actual monitoring, the no-load load of the load connection point P and the signal at the instant of connection of the connection point obtained by real-time detection are input into the correlation model, and the correlation value of the no-load load and the signal at the instant of connection of the connection point can be obtained. That is, under normal conditions, the working current and the signal at the instant of disconnection of the connection point corresponding to the no-load load and the signal at the instant of connection of the connection point. Based on this correlation value, the second range value and the second reference signal are adjusted. For example, the correlation value of the working current is used as the midpoint value of the second range value, and the boundary values of the second range value are readjusted. The correlation value of the signal at the instant of disconnection of the connection point (expressed as time-series data, such as data of voltage changing with time series) is used as the new second reference signal.

[0091] Through the above steps, when performing load monitoring each time, the comparison reference for the subsequent parameters can be adjusted in combination with the prior parameters, so that the comparison process is more in line with the actual working conditions and the phenomena of false alarms and missed alarms are reduced.

[0092] The data processing module 2 has a first prediction model, a second prediction model and a third prediction model. For example, a linear regression model, a support vector machine model, etc. can be used to predict the changes in the future time period based on historical data;

[0093] The first prediction model is used to predict the predicted value of the working current I in a future certain time period, such as the predicted value in the next 30 minutes, denoted as the predicted current I_pre;

[0094] The second prediction model is used to predict the predicted value of the aging state Ag of the connection point in a future certain time period, denoted as the predicted aging state Ag_pre;

[0095] The third prediction model is used to predict the predicted value of the connection point temperature T in a future certain time period, denoted as the predicted temperature T_pre;

[0096] During the load working process, the working current I, the aging state Ag of the connection point and the connection point temperature T are respectively predicted through the first prediction model, the second prediction model and the third prediction model to obtain the predicted current I_pre, the predicted aging state Ag_pre and the predicted temperature T_pre. If the following conditions are met:

[0097]

[0098] Then a warning message of abnormal load operation is output. If not, continuous monitoring is carried out.

[0099] In this step, the working current I, the aging state Ag of the connection point, and the connection point temperature T are mainly predicted through a prediction model. When the predicted value exceeds the range value / threshold, it indicates that the system may malfunction in a certain period in the future. By sending out early warning information to alert the operator and intervening in advance, the number of system malfunctions can be reduced.

[0100] Under different working conditions, during the operation of the load, the probability of abnormality occurring at the load connection point P is different. Therefore, the monitoring focuses are different. The data processing module 2 adjusts the calculation weights in the normal working conditions according to the working state of the load and the state of the load connection point P:

[0101] If the load performs a power switch, when the load performs a power switch, the circuit current changes significantly. At this time, the load connection point P is prone to abnormality due to the current impact. Therefore, the first weight is increased, and the second and third weights are decreased;

[0102] If the usage duration of the load connection point P is greater than the preset usage time threshold, the longer the usage duration of the load connection point P, the greater the probability of aging abnormality. Therefore, when the usage duration is greater than the preset threshold, the second weight is increased, and the first and third weights are decreased;

[0103] If the single continuous working time of the load is greater than the preset working time threshold, the single continuous working time of the load will have a significant impact on the heat generation of the load connection point P. Specifically, the longer the single continuous working time of the load, the more serious the heat generation situation of the load connection point P may be, and the higher the temperature of the load connection point P. Therefore, when the single continuous working time of the load is greater than the preset threshold, the third weight is increased, and the first and second weights are decreased.

[0104] In this step, according to the influence of different working conditions on each parameter, the weights of each parameter are dynamically adjusted, making the monitoring of the load working process more reasonable and accurate.

[0105] After each load shutdown, the data processing module 2 compares the connection instant signal of the connection point with the disconnection instant signal of the connection point for consistency. Based on the comparison result of the consistency comparison, the electrical performance stability of the load is evaluated. The consistency comparison includes waveform symmetry comparison, signal change trend comparison, and signal duration comparison. Under normal working conditions of the system, the connection instant signal of the connection point and the disconnection instant signal of the connection point should have high consistency. The electrical performance stability of the load can be evaluated according to the consistency comparison result. If the consistency comparison result is high, it indicates that the electrical performance stability of the load is high; otherwise, it is low. Through this comparison, the electrical performance stability of the load can be evaluated and targeted maintenance can be carried out.

[0106] This embodiment also provides an output terminal detection method based on intelligent temperature cabinet control, including: connecting a collection module 1 and a driving module 3 at the load access point;

[0107] Collecting the circuit parameters and temperature parameters of the load connection point P through the collection module 1;

[0108] Analyzing the safety risk of the load connection point P based on the circuit parameters and temperature parameters;

[0109] Controlling the on / off of the load connection point P through the driving module 3 according to the safety risk of the load connection point P.

[0110] The method of this embodiment and the above system belong to the same inventive concept and can be understood with reference to the above description, and will not be elaborated here.

[0111] By connecting the collection module 1 and the driving module 3 at the load connection point P in this application, the on / off can be controlled according to the situation of the load connection point P, which can play an effective monitoring and protection role and is applicable to temperature cabinet equipment.

[0112] In the description of this application, it should be understood that the orientation or positional relationship indicated by orientation words such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is usually based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing this application and simplifying the description. Without contrary description, these orientation words do not indicate and imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, so it cannot be understood as a limitation on the protection scope of this application.

[0113] For those skilled in the art, various corresponding changes and deformations can be made according to the technical solutions and concepts described above, and all these changes and deformations should fall within the protection scope of the claims of this application.

Claims

1. An output end detection system based on intelligent temperature cabinet control, characterized in that, Comprising: A collection module, which is connected to the load connection point and is used to collect the circuit parameters and temperature parameters of the load connection point; A data processing module, which is signal-connected to the collection module and is used to receive the circuit parameters and temperature parameters, and analyze the safety risks of the load connection point based on the circuit parameters and temperature parameters; A driving module, which is connected to the load connection point and is used to control the on / off of the load connection point. The driving module is signal-connected to the data processing module; The data processing module controls the on / off of the load connection point through the driving module according to the safety risks of the load connection point; The circuit parameters include the no-load load of the load connection point, the signal at the moment of connection of the connection point, the working current, the aging state of the connection point, and the signal at the moment of disconnection of the connection point. The temperature parameters include the temperature of the connection point; The data processing module controls the on / off of the load connection point through the driving module according to the safety risks of the load connection point, including: Before the start-up phase of the load, obtain the no-load load of the load connection point and the first range value Perform a numerical comparison. If the no-load load belongs to the first range value, the load is allowed to start; otherwise, an alarm message indicating abnormal no-load load is output. At the moment of starting the load, obtain the signal at the moment of connection of the load connection point and perform similarity analysis with the first reference signal. If the similarity analysis result is not less than the first similarity threshold, it is determined that the load starts normally; otherwise, disconnect the load connection point and output an alarm message for abnormal start of the load; During the operation of the load, obtain the working current of the load connection point , the aging state of the connection point and the temperature of the connection point , and determine whether the normal working conditions are met. If so, determine that the load is working normally; otherwise, disconnect the connection point and output an alarm message indicating that the load is working abnormally; The normal working conditions are: ， Among them, , , respectively represent the second range value, the aging threshold, and the third range value, , , respectively represent the first weight corresponding to the working current , the second weight corresponding to the aging state of the connection point , and the third weight corresponding to the temperature of the connection point , represents the larger value of the difference between the two boundary values of the second range value and the working current , represents the safety risk threshold, represents the third range value and the larger value of the difference between the two boundary values and the temperature of the connection point , represents a comparison constant; At the moment of stopping the load, obtain the signal at the moment of disconnection of the load connection point and perform similarity analysis with the second reference signal. If the similarity analysis result is not less than the second similarity threshold, it is determined that the load stops normally; otherwise, output an alarm message for abnormal stop of the load.

2. The output terminal detection system based on intelligent temperature cabinet control according to claim 1, wherein The collection module includes a circuit parameter collection unit and a temperature parameter collection unit; The circuit parameter collection unit includes a first resistor, a first zener diode, a second resistor, and a first rectifier diode connected in series in sequence. One end of the first resistor far from the first zener diode is respectively connected to the N terminal of the high-voltage input and the N terminal of the load; One end of the first rectifier diode far from the second resistor is connected between the load connection point and the L terminal of the load; The temperature collection unit includes a thermistor corresponding to the load connection point.

3. The output terminal detection system based on the intelligent temperature cabinet control according to claim 2, wherein The driving module includes a third resistor, a fourth resistor, a first triode, a first capacitor, a second rectifier diode, and a switch. One end of the third resistor is connected to the data processing module, and the other end is connected to the base of the first triode. The emitter of the first triode is grounded, and the collector is connected to the switch and then connected to an external voltage. The contact end of the switch is connected to the load connection point. The collector of the first triode is also connected to the first capacitor and then grounded; One end of the fourth resistor is connected to the emitter of the first triode, and the other end is connected between the base of the first triode and the third resistor; The positive pole of the second rectifier diode is connected between the base of the first triode and the switch, and the negative pole is connected between the switch and the external voltage.

4. The output terminal detection system based on intelligent temperature cabinet control according to claim 2 or 3, characterized in that It further includes an isolation module, an amplification module, and an optimization module connected in series in sequence. The input end of the isolation module is connected in parallel to both ends of the first zener diode, and the output end of the optimization module is connected to the data processing module.

5. The output terminal detection system based on intelligent temperature cabinet control according to claim 2, wherein The data processing module obtains sample data of the load connection point regarding circuit parameters and temperature parameters. Based on the sample data, an association model is constructed. The association model takes the no-load load of the load connection point and the signal at the moment of connection point connection as inputs, and takes the working current of the load connection point and the signal at the moment of connection point disconnection as outputs. The association model is used to characterize the association relationship between input parameters and output parameters. Each time the data processing module conducts a safety risk analysis of the load connection point, it inputs the real-time obtained no-load load of the load connection point and the signal at the moment of connection point connection into the association model to obtain an association value regarding the working current of the load connection point and the signal at the moment of connection point disconnection. Based on the association value, the second range value and the second reference signal are adjusted.

6. The output terminal detection system based on intelligent temperature cabinet control according to claim 2 or 5, characterized in that, The data processing module has a first prediction model, a second prediction model, and a third prediction model. The first prediction model is used to predict the predicted value of the operating current in a certain future period, denoted as the predicted current ;​ The second prediction model is used to predict the aging state of the connection point The predicted value in a certain future time period is denoted as the predicted aging state ; The third prediction model is used to predict the temperature of the connection point at a predicted value within a certain period of time in the future, denoted as the predicted temperature ; During the operation of the load, the working current is predicted respectively by the first prediction model, the second prediction model and the third prediction model , the aging state of the connection point , and the temperature of the connection point to obtain the predicted current , the predicted aging state , and the predicted temperature . If the following conditions are met: ； If the conditions are not met, continuous monitoring is carried out. If the conditions are met, a warning message of abnormal load operation is output.

7. The output terminal detection system based on the intelligent temperature cabinet control according to claim 2, wherein The data processing module adjusts the calculation weights in the normal working conditions according to the load working state and the load connection point state: If the load performs power switching, the first weight is increased, and the second weight and the third weight are decreased. If the usage duration of the load connection point is greater than a preset usage time threshold, the second weight is increased, and the first weight and the third weight are decreased. If the single continuous working time of the load is greater than a preset working time threshold, the third weight is increased, and the first weight and the second weight are decreased.

8. The output terminal detection system based on intelligent temperature cabinet control according to claim 1, characterized in that, After each load shutdown, the data processing module compares the signal at the moment of connection point connection with the signal at the moment of connection point disconnection for consistency. Based on the comparison result of the consistency comparison, the electrical performance stability of the load is evaluated. The consistency comparison includes waveform symmetry comparison, signal change trend comparison, and signal duration comparison.

9. An output terminal detection method based on intelligent temperature cabinet control, which is detected by using the output terminal detection system based on intelligent temperature cabinet control described in claim 1, characterized in that, It includes: A collection module and a drive module are connected at the load access point. The circuit parameters of the load connection point are collected through the collection module. Based on the circuit parameters, the safety risk of the load connection point is analyzed. According to the safety risk of the load connection point, the on / off of the load connection point is controlled through the drive module.

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