Output end detection system and method based on intelligent temperature cabinet control

Abstract

The invention relates to an output end detection system and method based on intelligent temperature cabinet control, and the system comprises a collection module which is connected to a load access point and is used for collecting circuit parameters and temperature parameters of the load access point; the data processing module is in signal connection with the acquisition module and is used for receiving the circuit parameters and the temperature parameters and analyzing the safety risk of the load connection point based on the circuit parameters and the temperature parameters; the driving module is connected to the load connection point and is used for controlling the on-off of the load connection point, and the driving module is in signal connection with the data processing module; and the data processing module controls the on-off of the load connection point through the driving module according to the safety risk of the load connection point. The method is applied to the system. The acquisition module and the driving module are connected to the load connection point, on-off can be controlled according to the condition of the load connection point, an effective monitoring and protection effect can be achieved, and the temperature cabinet control circuit is suitable for temperature cabinet equipment.

Description

Technical Field

[0001] The present application relates to the technical field of temperature control equipment monitoring, and in particular to an output end 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., there are multiple loads, such as compressors, fans, heaters, lighting lamps, etc. The temperature cabinet is in automatic operation for a long time. For example, the compressor, fan, heater and other components are started and stopped periodically according to the refrigeration and heating plan. During this operation, the system will be subjected to a large current shock at the moment of starting and stopping the load, and due to unmanned monitoring, the suction device (relay or circuit breaker) may not be able to disconnect the load connection, the output contact point may be short-circuited due to adhesion, etc., until the output demand is uncontrollable and the load connection cannot be disconnected, resulting in a long-term fixed output of the load, or due to aging of the suction device, the contact point is poorly energized, the contact point sparks, and even burns or causes a fire.

[0003] At present, the circuit protection of temperature cabinet equipment is usually carried out by tripping protection at the high-voltage input end of the load. When the load is overcurrent, the circuit breaker trips and disconnects the load from the power grid to protect the load. This type of tripping protection has low accuracy and slow response. It is not applicable to equipment such as temperature cabinets that must work for a long time and cannot provide effective monitoring and protection. 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 detection system and method based on intelligent temperature cabinet control. This application can control the on and off according to the situation of the load connection point by connecting the acquisition module and the drive module at the load connection point, which can play an effective monitoring and protection role and is suitable for temperature cabinet equipment.

[0005] The output detection system based on intelligent temperature cabinet control described in the present application includes:

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

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

[0008] A driving module connected to a load connection point for controlling the on / off of the load connection point, wherein the driving 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 driving module according to the safety risk of the load connection point.

[0010] Preferably, the acquisition module also acquires the temperature parameters of the load connection point, and the data processing module analyzes the safety risk of the load connection point based on the circuit parameters and the temperature parameters; 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 voltage stabilizing diode, a second resistor, and a first rectifier diode connected in series in sequence; an end of the first resistor away from the first voltage stabilizing diode is respectively connected to the N end of the high voltage input and the N end 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 end of the load;

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

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

[0015] Preferably, the output detection system based on intelligent temperature cabinet control also includes an isolation module, an amplification module and an optimization module cascaded in sequence, the input end of the isolation module is connected in parallel to the two ends of the first voltage regulator diode, and the output end 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 connection instant signal of the connection point, the operating current, the connection point aging state and the connection point disconnection instant signal of the connection point, and the temperature parameters include the connection point temperature;

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

[0018] In the pre-startup stage of the load, the no-load load of the load connection point is obtained and compared with the first range value Rv1. If the no-load load belongs to the first range value, the load is allowed to start, otherwise, an alarm message of no-load load abnormality is output;

[0019] At the startup moment of the load, a connection point connection instant signal of the load connection point is obtained and a first reference signal is analyzed for similarity, if the similarity analysis result is not less than a first similarity threshold, it is judged that the load is started normally, otherwise, the load connection point is disconnected, and an alarm message of abnormal load startup is output;

[0020] During the load operation, the operating current I, the connection point aging state Ag and the connection point temperature T of the load connection point are obtained, and it is determined whether the normal working conditions are met. If so, it is determined that the load is working normally, otherwise the connection point is disconnected and an alarm message of abnormal load operation is output;

[0021] The normal working conditions are:

[0022]

[0023] Among them, Rv2, thr Ag , Rv3 represent 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 connection point aging state Ag, and the third weight corresponding to the connection point temperature T respectively, max|Rv2-I| represents the larger value of the difference between the two 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 two 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, the connection point disconnection instant signal of the load connection point is obtained and the similarity analysis is performed with the second reference signal. If the similarity analysis result is not less than the second similarity threshold, it is judged that the load has shut down normally, otherwise, an alarm message of abnormal load shutdown is output.

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

[0026] Each time the data processing module performs a safety risk analysis on the load connection point, the data processing module inputs the no-load load of the load connection point and the instantaneous signal 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 instantaneous signal of the connection point disconnection, 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 period of time in the future, which is recorded as the predicted current I_pre;

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

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

[0032]

[0033] The system will output warning information of abnormal load operation, and continue monitoring if the conditions are not met.

[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 use time of the load connection point is longer than the preset use 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 performs a consistency comparison on the instantaneous signal of connection of the connection point and the instantaneous signal of disconnection of the connection point, and evaluates the electrical performance stability of the load based on the comparison result of the consistency comparison, wherein the consistency comparison includes waveform symmetry comparison, signal change trend comparison and signal duration comparison.

[0039] The present application discloses an output terminal detection method based on intelligent temperature cabinet control, comprising: connecting a collection module and a drive module at a load access point;

[0040] Collecting the circuit parameters of the load connection point by the acquisition module;

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

[0042] According to the safety risk of the load connection point, the on and off of the load connection point is controlled by the driving module. The output terminal detection system and method based on intelligent temperature cabinet control described in the present application have the following advantages:

[0043] 1. The present application connects an acquisition module and a drive module at each load connection point between the load and the high-voltage input, collects the circuit parameters and temperature parameters (optional) of the load connection point through the acquisition module, analyzes the collected parameters through the data processing module, evaluates the safety risk of the load connection point, and controls 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 then comprehensively evaluate the safety risk of the load connection point, so that the monitoring of the load is comprehensive, timely and effective, and can effectively monitor and protect the temperature cabinet equipment.

[0044] 2. The circuit structure of the acquisition module and the driving module of the present application is simple, easy to implement, and has low implementation cost. It is compatible with most conventional loads on the market, such as inductive loads, capacitive loads, resistive loads, etc. It can be connected without changing the original circuit structure of the temperature cabinet and has a wide range of applicability.

[0045] 3. This application combines the characteristics of a load action cycle, divides the action cycle of the load connection point into different stages, sets the monitoring parameters and corresponding actions to be performed in different stages, makes the monitoring of the load connection point more precise, and can more accurately monitor the abnormal conditions of the load connection point at different stages, and make timely action responses, thereby improving the accuracy and reliability of load monitoring.

[0046] 4. This application introduces an association model, which can obtain subsequent association parameters based on the real-time acquired no-load load and connection point connection instantaneous signal, and use the acquired association parameters as a reference for adjusting benchmark values ​​such as range values. The benchmark value is adjusted so that the benchmark value can be close to each actual load action, that is, the benchmark value can be adjusted with the operation of the electrical system, which can make the monitoring process closer to the actual working conditions and effectively reduce the occurrence of false alarms.

[0047] 5. This application introduces a prediction model to predict the working current, connection point temperature and connection point aging status during load operation, which can predict possible load abnormalities in advance and issue early warnings, further improving the timeliness and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0050] Explanation of the accompanying drawings: P-load connection point, 1-acquisition module, 2-data processing module, 3-driving 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 transistor Q2-second transistor, D1-first rectifier diode, D2-second rectifier diode, DZ1-first voltage regulator diode, U1-isolation module, K-switch element, C1-first capacitor, C2-second capacitor. DETAILED DESCRIPTION

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

[0052] The acquisition module 1 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 optional embodiments, the circuit parameters can be acquired separately for monitoring, and the acquisition of the temperature parameter can improve the accuracy of the output end detection result.

[0053] Specifically, the details are as follows Figure 2As shown, the load connection point P refers to the connection point between loads such as compressors, fans, heaters, and lighting lamps and the high-voltage input power grid. It is usually in the form of an on-off control switch. The N end of the high-voltage input is connected to the N end of the load, and the L end of the high-voltage input is connected to the L end of the load. The load connection point P is set on the connection line between the L end of the high-voltage input and the L end 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 disconnected, the load is powered off and shut down.

[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 voltage 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 away from the first voltage zener diode DZ1 is respectively connected to the N end of the high voltage input and the N end of the load;

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

[0056] The above circuit consisting of the first resistor R1, the first voltage-stabilizing diode DZ1, the second resistor R2, and the first rectifier diode D1 is connected to the load connection point P, and can obtain the original load voltage difference signal of the load connection point P. The no-load load, working current, connection point resistance, etc. of the load connection point P can also be calculated, and the signal of the load connection point P at the moment of on and off can be collected and uploaded.

[0057] Specifically, the original load voltage difference signal refers to the voltage difference signal at both ends of the loop formed by the N end of the load, the first resistor R1, the second resistor R2, the first rectifier diode D1, the L end of the load, and the load constituting the current channel. The no-load load refers to the load of the small current channel composed of the N end of the load, the first resistor R1, the second resistor R2, the first rectifier diode D1, the L end of the load, and the load after the driver module 3 is connected and the switch K of the driver module 3 is disconnected. The connection point resistance can be obtained by calculating the voltage and current at both ends of the connection point. The working current can be calculated by the voltage difference drop formed on the switch K by the loop composed of the conduction equivalent resistance of the switch K, the L end of the load, and the L end of the high-voltage input, combined with the equivalent resistance of the switch K to obtain the working current. 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 arranged 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 risk 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. 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 transistor Q1, a first capacitor C1, a second rectifier diode D2 and a switch element K. The switch element 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 transistor Q1. The emitter of the first transistor Q1 is grounded, and the collector is connected to the switch element K and then connected to an external voltage. The contact end of the switch element K is connected to the load connection point P, and the collector of the first transistor 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 transistor Q1, and the other end is connected between the base of the first transistor Q1 and the third resistor R3; the positive electrode of the second rectifier diode D2 is connected between the base of the first transistor Q1 and the switch element K, and the negative electrode is connected between the switch element 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 the connection point conduction signal, the signal is input to the base of the first transistor Q1, so that the collector and emitter of the first transistor Q1 are turned on, and then the relay contact end connected to the load connection point P is turned on, forming a path, so that the load is 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 also includes an isolation module U1, an amplification module 4 and an optimization module cascaded in sequence. The isolation module U1 specifically uses an optocoupler, the input end of the optocoupler is connected in parallel to the two ends of the first voltage regulator 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 transistor 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 to the two ends of the optocoupler output, the emitter of the second transistor Q2 is grounded, the collector is connected to the data processing module 2, the base is connected in series with the fifth resistor R5 and the seventh resistor R7 in sequence and then connected to the 3.3VVDD voltage, the fifth resistor R5 is connected to the NC resistor and then grounded, and the collector of the second transistor 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, amplified and the signal quality optimized, so that the signal received by the data processing module 2 is accurate.

[0066] In other optional embodiments, the amplification module 4 and the optimization module may select existing integrated signal amplifiers and signal optimizers, which is not limited in this embodiment.

[0067] In other optional embodiments, the data processing module 2 is also connected to a background data center 6 via the communication module 5, and uploads the collected and processed data to the data center 6 for storage.

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

[0069] Specifically, the load from startup to shutdown is regarded as an action cycle, and the action cycle is split into four stages: the load pre-startup stage, the load startup moment, the load working process, and the load shutdown moment. Monitoring the key parameters of the load connection point P in different stages will be beneficial to comprehensively monitor the safety risks of the load connection point P. Compared with the general over-current monitoring in the prior art, the staged monitoring method of this embodiment is more targeted.

[0070] The specific steps are as follows:

[0071] In the pre-startup stage of the load, that is, when the load is in the shutdown state, the main purpose is to detect whether the no-load load at 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 at the load connection point P is within a normal range of values, which can be the average value of the no-load load historical data of the load connection point P. For example, by analyzing the no-load load historical data of the load connection point P seven days before, it is calculated that the no-load load is 50w, and the reasonable range of the no-load load can be set to 45w~55w.

[0072] In the pre-startup stage of the load, the no-load load at the load connection point P is obtained and 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 belongs to the above-mentioned 45w~55w, it means that the no-load load at the load connection point P is at a normal level, and the load is allowed to start normally. If it does not belong to the range value, it means that the electrical system may have an abnormal no-load load, and an alarm message of abnormal no-load load is output to prompt the operation and maintenance personnel to conduct inspection and confirmation.

[0073] At the startup moment of the load, a connection point connection instant signal of the load connection point P is obtained and a similarity analysis is performed with the first reference signal. Specifically, the first reference signal may be a connection point connection instant signal detected from the load connection point P when the load is started normally. The first reference signal is obtained by taking the average of multiple samplings. The first reference signal serves as a reference for evaluating whether the load is started normally. At the moment when the load is actually started, the connection point connection instant signal at the load connection point P is obtained, and a similarity analysis is performed with the aforementioned first reference signal. Specifically, a waveform diagram of the first reference signal is drawn. After obtaining the connection point connection instant signal, the digital processing module converts it into a corresponding waveform diagram, and the two waveform diagrams are subjected to similarity analysis, that is, the overlap degree of the two waveform diagrams is determined as the similarity analysis result. If the similarity analysis result is not less than the first similarity threshold, the load is judged to be started normally, otherwise the load is judged to be abnormally started, the load connection point P is disconnected, and an alarm message of abnormal load startup is output. Specifically, the first similarity threshold can be set according to the requirements for detection sensitivity, for example 80%. When the similarity between the connection point connection instant signal of the real-time startup and the first reference signal reaches more than 80%, the load is judged to be started normally.

[0074] During the load operation, that is, when the load is energized, the operating current I, the aging state Ag and the temperature T of the connection point are obtained, and it is determined whether the normal working conditions are met. If so, the load is judged to be working normally. Otherwise, the connection point is disconnected and an alarm message of abnormal load operation is output;

[0075] The normal working conditions are:

[0076]

[0077] Among them, Rv2, thr Ag, Rv3 represent 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 connection point aging state Ag, and the third weight corresponding to the connection point temperature T respectively, max|Rv2-I| represents the larger value of the difference between the two 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 two 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 determine whether the load connection point P is in a normal working state. The connection point aging state is quantitatively represented by the growth rate of the resistance of the load connection point P. As the load connection point P is oxidized and corroded by the environment as the use time increases, the resistance gradually increases. Therefore, in this embodiment, the resistance growth rate is selected as a quantitative indicator of the aging state of the load connection point P. The specific calculation method is to record the resistance of the load connection point P when it is put into use as the initial resistance, and obtain the real-time resistance of the load connection point P. (Real-time resistance-initial resistance) / initial resistance*100% can be used to calculate the connection point aging state of the load connection point P.

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

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

[0081] For the load connection point P, its aging state is a critical indicator. When the aging state of the load connection point P reaches the critical indicator, that is, the aging threshold, there is a great safety hazard at the load connection point P and it should be repaired or replaced.

[0082] Both the working current and the connection point temperature are range indicators. For a load that works normally, the working current should be within a normal range, so the second range value Rv2 is set for judgment. Similarly, for a load that works normally, if the temperature of the load connection point P is too high or too low, it means that the electrical system may be abnormal, so the range value is used for judgment.

[0083] In addition, after actual testing, this embodiment has found that even when the connection point aging state of the load connection point P is less than the aging threshold, and the working current and the connection point temperature are both within the normal range, the system may still be abnormal. The reasons are analyzed and it is found that when the connection point aging state is close to the aging threshold, the closer the connection point working current and the connection point temperature are to the critical value on the second range value and the third range value side, the superposition of the 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 method 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 operation of the system. In addition, the difference between the three parameters and the reference values ​​(the second range value, the third range value and the aging threshold) used as comparisons must also be considered. For the connection point aging state, it can be directly subtracted from the aging threshold. The difference can represent the gap between the connection point aging state 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 difference 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 equal to or close to the difference between the boundary values ​​on both sides. When the real-time working current is close to any critical value, it indicates that the system may be in or is about to enter an unstable state. Therefore, it is necessary to calculate the larger value of the difference between the two boundary values ​​and the working current. The specific method is to make the difference between the two boundary values ​​and the working current respectively, and take the larger value of the two differences. Similarly, calculate the larger value of the difference between the two boundary values ​​and the connection point temperature, and perform weighted accumulation on 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 normal working condition, when the working current and the connection point temperature are respectively located near the middle point of the second range value and the third range value, the above-mentioned weighted formula is used for calculation, and the calculation result is used as the above-mentioned comparison constant. During actual monitoring, the real-time working current, connection point temperature and connection point aging status are substituted, and the weighted formula is used for calculation, and the calculation result is subtracted from the comparison constant. The difference can reflect the comprehensive degree of deviation of the three parameters from normal working conditions. A judgment threshold is set for the difference, so as to achieve a comprehensive judgment on the superimposed influence of the three parameters.

[0084] Through this step, the three parameters in the load working process are respectively judged by range value / threshold value, and the superimposed influence of the three parameters is comprehensively judged, which can make the abnormal judgment of the load working process more comprehensive and accurate.

[0085] At the moment of load shutdown, the connection point disconnection instant signal of the load connection point P is obtained and analyzed with the second reference signal for similarity. If the similarity analysis result is not less than the second similarity threshold, it is judged that the load has shut down normally. Otherwise, an alarm message of abnormal load shutdown is output. The judgment process of the connection point disconnection instant signal and the aforementioned connection point connection instant signal is the same, which can be understood by referring to the above description and will not be repeated here. This step is used to determine whether the load has shut down normally.

[0086] In the actual test process, it is found that various parameters will change with the use of the system. If the abnormal judgment is always performed according to the various range values ​​set in the initial state, it cannot fit the actual operation of the system well, and false alarms and missed alarms are often prone to occur. Therefore, combined with the actual operation of the system, the range value is dynamically adjusted, which can make the abnormal judgment more in line with the actual working conditions. The specific methods are as follows:

[0087] The data processing module 2 obtains sample data of the circuit parameters and temperature parameters of the load connection point P, and constructs an association model based on the sample data. The association model takes the no-load load of the load connection point P and the instantaneous signal of the connection point as input, and takes the working current of the load connection point P and the instantaneous signal of the connection point disconnection as output. 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, the data processing module 2 inputs the no-load load and the instantaneous signal of the connection point P acquired in real time into the correlation model, obtains the correlation value of the working current of the load connection point P and the instantaneous signal of the connection point disconnection, and adjusts the second range value and the second reference signal based on the correlation value.

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

[0090] During actual monitoring, the no-load load and the connection point connection instant signal of the load connection point P obtained by real-time detection are input into the correlation model, and the correlation value of the no-load load and the connection point connection instant signal can be obtained, that is, under normal conditions, the no-load load and the connection point connection instant signal should correspond to the working current and the connection point disconnection instant signal. Based on the 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, the boundary value of the second range value is readjusted, and the correlation value of the connection point disconnection instant signal (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, each time load monitoring is performed, the comparison benchmark of the subsequent parameters can be adjusted in combination with the previous parameters, so that the comparison process is more in line with the actual working conditions and the phenomenon of false alarms and missed alarms can be reduced.

[0092] The data processing module 2 has a first prediction model, a second prediction model and a third prediction model, such as a linear regression model, a support vector machine model, etc., which can predict changes in future time periods based on historical data;

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

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

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

[0097]

[0098] The system will output warning information of abnormal load operation, and continue monitoring if the conditions are not met.

[0099] In this step, the working current I, the connection point aging state Ag, and the connection point temperature T are mainly predicted through the prediction model. When the predicted value exceeds the range value / threshold, it means that the system may have an abnormality in a certain period of time in the future. Timely warning information is issued to warn the operator and intervene in advance to reduce the number of system abnormalities.

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

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

[0102] If the use time of the load connection point P is longer than the preset use time threshold, the longer the use time of the load connection point P is, the greater the probability of aging abnormality. Therefore, when the use time is longer than the preset threshold, the second weight is increased, and the first weight and the third weight 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 heating of the load connection point P. Specifically, the longer the single continuous working time of the load, the more serious the heating 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 weight and the second weight are reduced.

[0104] This step dynamically adjusts the weight of each parameter according to the impact of different working conditions on each parameter, so that the monitoring of the load working process is more reasonable and accurate.

[0105] After each load shutdown, the data processing module 2 performs a consistency comparison between the instantaneous signal of the connection point and the instantaneous signal of the connection point disconnection, and evaluates the electrical performance stability of the load based on the comparison result of the consistency comparison, wherein the consistency comparison includes waveform symmetry comparison, signal change trend comparison and signal duration comparison. When the system is operating normally, the instantaneous signal of the connection point and the instantaneous signal of the connection point disconnection should have a high consistency, and the electrical performance stability of the load can be evaluated based on the consistency comparison result. If the consistency comparison result is high, it means 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 performed.

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

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

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

[0109] According to the safety risk of the load connection point P, the on and off of the load connection point P is controlled by the driving module 3 .

[0110] The method of this embodiment belongs to the same inventive concept as the above-mentioned system, and can be understood with reference to the above description, which will not be repeated here.

[0111] The present application connects the acquisition module 1 and the drive module 3 at the load connection point P, and can control the on and off according to the situation of the load connection point P, which can play an effective monitoring and protection role and is suitable for temperature cabinet equipment.

[0112] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings. They are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the scope of protection of the present application.

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

Claims

1. An output detection system based on intelligent temperature cabinet control, characterized in that: include: A collection module, which is connected to the load access point and is used to collect circuit parameters of the load connection point; A data processing module, which is connected to the acquisition module signal, and is used to receive the circuit parameters and analyze the safety risk of the load connection point based on the circuit parameters; A driving module connected to a load connection point for controlling the on / off of the load connection point, wherein 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 risk of the load connection point.

2. According to claim 1, the output detection system based on intelligent temperature cabinet control is characterized in that: The acquisition module also acquires the temperature parameters of the load connection point, and the data processing module analyzes the safety risk of the load connection point based on the circuit parameters and the temperature parameters; the acquisition module includes a circuit parameter acquisition unit and a temperature parameter acquisition unit; The circuit parameter acquisition unit includes a first resistor, a first voltage stabilizing diode, a second resistor, and a first rectifier diode connected in series in sequence; an end of the first resistor away from the first voltage stabilizing diode is respectively connected to the N end of the high voltage input and the N end of the load; One end of the first rectifier diode away from the second resistor is connected between the load connection point and the L end of the load; The temperature acquisition unit includes a thermistor arranged corresponding to the load connection point.

3. According to claim 2, the output detection system based on intelligent temperature cabinet control is characterized in that: The driving module includes a third resistor, a fourth resistor, a first transistor, a first capacitor, a second rectifier diode and a switch element. 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 transistor. The emitter of the first transistor is grounded, and the collector is connected to the switch element and then connected to an external voltage. The contact end of the switch element is connected to the load connection point, and the collector of the first transistor is also connected to the first capacitor and then grounded; one end of the fourth resistor is connected to the emitter of the first transistor, and the other end is connected between the base of the first transistor and the third resistor; the positive electrode of the second rectifier diode is connected between the base of the first transistor and the switch element, and the negative electrode is connected between the switch element and the external voltage.

4. The output end detection system based on intelligent temperature cabinet control according to claim 2 or 3 is characterized in that: It also includes an isolation module, an amplification module and an optimization module which are cascaded in sequence. The input end of the isolation module is connected in parallel to the two ends of the first voltage-stabilizing diode, and the output end of the optimization module is connected to the data processing module.

5. According to claim 2, the output end detection system based on intelligent temperature cabinet control is characterized in that: The circuit parameters include the no-load load of the load connection point, the connection instant signal of the connection point, the operating current, the connection point aging state and the connection point disconnection instant signal of the connection point, and the temperature parameters include the connection point temperature; The data processing module controls the on / off of the load connection point through the driving module according to the safety risk of the load connection point, including: In the pre-startup stage of the load, the no-load load of the load connection point is obtained and compared with the first range value Rv1. If the no-load load belongs to the first range value, the load is allowed to start, otherwise, an alarm message of no-load load abnormality is output; At the startup moment of the load, a connection point connection instant signal of the load connection point is obtained and a first reference signal is analyzed for similarity, if the similarity analysis result is not less than a first similarity threshold, it is judged that the load is started normally, otherwise, the load connection point is disconnected, and an alarm message of abnormal load startup is output; During the load operation, the operating current I, the connection point aging state Ag and the connection point temperature T of the load connection point are obtained, and it is determined whether the normal working conditions are met. If so, it is determined that the load is working normally, otherwise the connection point is disconnected and an alarm message of abnormal load operation is output; The normal working conditions are: Among them, Rv2, thr Ag , Rv3 represent 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 connection point aging state Ag, and the third weight corresponding to the connection point temperature T respectively, max|Rv2-I| represents the larger value of the difference between the two 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 two boundary values ​​of the third range value Rv3 and the connection point temperature T, and c represents the comparison constant; At the moment of load shutdown, the connection point disconnection instant signal of the load connection point is obtained and the similarity analysis is performed with the second reference signal. If the similarity analysis result is not less than the second similarity threshold, it is judged that the load has shut down normally, otherwise, an alarm message of abnormal load shutdown is output.

6. The output end detection system based on intelligent temperature cabinet control according to claim 5 is characterized in that: The data processing module obtains sample data of circuit parameters and temperature parameters of the load connection point, and constructs an association model based on the sample data. The association model takes the no-load load of the load connection point and the instantaneous signal of the connection point as input, and takes the working current of the load connection point and the instantaneous signal of the disconnection of the connection point as output. The association model is used to characterize the association relationship between the input parameters and the output parameters; Each time the data processing module performs a safety risk analysis on the load connection point, the data processing module inputs the no-load load of the load connection point and the instantaneous signal 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 instantaneous signal of the connection point disconnection, and adjusts the second range value and the second reference signal based on the correlation value.

7. The output end detection system based on intelligent temperature cabinet control according to claim 5 or 6, 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 working current I in a certain period of time in the future, which is recorded as the predicted current I_pre; The second prediction model is used to predict the predicted value of the connection point aging state Ag in a certain period of time in the future, which is recorded as the predicted aging state Ag_pre; The third prediction model is used to predict the predicted value of the connection point temperature T in a certain period of time in the future, which is recorded as the predicted temperature T_pre; During the load operation, the working current I, the connection point aging state Ag and the connection point temperature T are predicted by the first prediction model, the second prediction model and the third prediction model respectively to obtain the predicted current I_pre, the predicted aging state Ag_pre and the predicted temperature T_pre. If: The system will output warning information of abnormal load operation, and continue monitoring if the conditions are not met.

8. The output end detection system based on intelligent temperature cabinet control according to claim 5 is characterized in that: The data processing module adjusts the calculation weight in the normal working condition 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 use time of the load connection point is longer than the preset use 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 the preset working time threshold, the third weight is increased, and the first weight and the second weight are decreased.

9. The output end detection system based on intelligent temperature cabinet control according to claim 1 is characterized in that: After each load shutdown, the data processing module performs a consistency comparison between the instantaneous signal of the connection point and the instantaneous signal of the connection point disconnection, and evaluates the electrical performance stability of the load based on the comparison result of the consistency comparison, wherein the consistency comparison includes waveform symmetry comparison, signal change trend comparison and signal duration comparison.

10. An output end detection method based on intelligent temperature cabinet control, characterized in that: include: Connect the acquisition module and the drive module to the load access point; Collecting the circuit parameters of the load connection point by the acquisition module; Analyzing the safety risk of the load connection point based on the circuit parameters; According to the safety risk of the load connection point, the on and off of the load connection point is controlled by the driving module.

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