Multi-dimensional information intelligent detection method and system based on direct current charging pile

Abstract

The invention relates to the technical field of direct current charging pile detection, in particular to a multi-dimensional information intelligent detection method and system based on a direct current charging pile. The system comprises a charging pile multi-dimensional information acquisition module, a charging pile multi-dimensional information analysis module and a charging pile state regulation and control module. Wherein the charging pile multi-dimensional information acquisition module is used for acquiring current charging space environment data of a charging pile in a charging space dimension, current pile body structure operation data of a pile body structure dimension and current output interface state data of an output interface dimension; the charging pile multi-dimensional information analysis module is used for performing multi-level evaluation analysis on the current data of the three dimensions; and the charging pile state regulation and control module is used for executing charging pile operation parameter adjustment operation based on the multi-level evaluation analysis result. The system can comprehensively collect the multi-dimensional information of the charging pile and perform deep analysis, so that the operation state of the charging pile is accurately controlled and timely regulated and controlled, and the stable and safe operation of the charging pile is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of direct current charging pile detection, and particularly relates to a multi-dimensional information intelligent detection method and system based on a direct current charging pile. BACKGROUND

[0002] With the rapid development of the new energy vehicle industry, as a core energy supplement facility, the operation stability and safety of the direct current charging pile directly affect the user experience and public safety. At present, the detection methods of the direct current charging pile are mostly concentrated on single-dimensional data collection and analysis, which is difficult to comprehensively cover various key influencing factors in the operation process of the charging pile. In terms of charging space environment, the existing detection means often ignores the dynamic changes of environmental parameters such as temperature, humidity and dust concentration, and abnormal fluctuations of these parameters may cause accelerated aging of internal components of the charging pile, and even cause safety hazards such as short circuit and fire. For example, in a high temperature and high humidity environment, the heat dissipation efficiency of the charging pile will decrease significantly, and if it is not detected and intervened in time, it may cause overload damage of the charging module; in a high dust concentration scene, dust adheres to the internal circuit board of the charging pile, which easily leads to poor circuit contact and affects the normal realization of the charging function. In the pile body structure dimension, the traditional detection method mostly relies on artificial regular inspection, which not only consumes a large amount of labor cost, but also has the problems of long detection period and untimely fault discovery. Key components in the pile body structure, such as the shell connecting structure and the internal support frame, may be loose or deformed due to factors such as vibration and external impact during long-term use, and if not discovered in time, it may lead to a decrease in the stability of the pile body structure, and even cause safety accidents such as the collapse of the charging pile. At the same time, artificial inspection is difficult to accurately detect the fastening state and insulation performance of the internal key electrical connection points of the pile body, and cannot comprehensively grasp the operation health status of the pile body structure. In the output interface dimension, the existing detection system mostly only focuses on electrical parameters such as charging voltage and current, and ignores the detection of the physical state of the interface, such as the wear and tear degree of the interface plug, the oxidation condition of the contact point and the waterproof sealing performance. As a key component connecting the charging pile and the new energy vehicle, the physical state of the output interface directly affects the stability and safety of the charging connection. Excessive wear and tear of the interface plug will cause an increase in the contact resistance, and electric sparks are easily generated during the charging process, which poses a safety hazard; oxidation of the contact point will affect the current transmission efficiency, causing a decrease in the charging speed, and even causing charging interruption; failure of the waterproof sealing performance will cause rainwater and dust to enter the interface, causing a short circuit fault. In addition, the existing detection system lacks the ability to cooperatively analyze multi-dimensional information, and the detection data of each dimension is independent of each other, which cannot comprehensively evaluate the overall operation state of the charging pile, leading to difficulty in accurately determining the fault root cause, low fault troubleshooting efficiency and affecting the normal operation and use of the charging pile. SUMMARY

[0003] The main purpose of the present application is to provide a direct current charging pile multi-dimensional information intelligent detection method and system, aiming at solving the technical problems in the prior art.

[0004] The present application provides a direct current charging pile multi-dimensional information intelligent detection system, comprising: The charging pile multi-dimensional information acquisition module is used to acquire the current charging space environment data of the charging pile in the charging space dimension, the current pile body structure operation data in the pile body structure dimension, and the current output interface state data in the output interface dimension. The charging pile multi-dimensional information analysis module is used to perform multi-level evaluation analysis on the current charging space environment data in the charging space dimension, the current pile body structure operation data in the pile body structure dimension, and the current output interface state data in the output interface dimension. The charging pile state regulation module is used to perform charging pile operation parameter adjustment operation based on the multi-level evaluation analysis result.

[0005] Preferably, the current charging space environment data in the charging space dimension includes current environment temperature value, current environment humidity value, current environment dust concentration value, and current charging pile radiator surface temperature data. The current pile body structure operation data in the pile body structure dimension includes current charging pile internal core component temperature value, current charging pile vibration frequency value, and current charging pile noise decibel value. The current output interface state data in the output interface dimension includes current charging interface contact resistance value and current charging interface wear degree data.

[0006] Preferably, the current charging pile radiator surface temperature data is specifically the radiator surface maximum temperature value and the radiator surface temperature distribution gradient value. The current charging interface wear degree data is specifically the charging interface metal reed deformation amount and the charging interface insulation layer crack area value.

[0007] Preferably, the charging pile multi-dimensional information analysis module comprises: The charging space dimension temperature evaluation unit is used to perform normalization processing on the current environment temperature value and the current environment dust concentration value, and perform weighted fusion analysis on the radiator surface maximum temperature value and the radiator surface temperature distribution gradient value to generate a charging space temperature comprehensive evaluation index. The pile body structure dimension health evaluation unit is used to perform discretization processing on the current charging pile internal core component temperature value, the current charging pile vibration frequency value, and the current charging pile noise decibel value, and calculate a component operation deviation coefficient. The output interface dimension safety evaluation unit is used for standardizing the current charging interface contact resistance value, and performing multi-factor coupling analysis on the charging interface metal spring deformation variable and the charging interface insulating layer crack area value.

[0008] As preferred, the charging space dimension temperature evaluation unit specifically performs: standardizing and converting the highest radiator surface temperature value based on the current radiator surface temperature data obtained by the charging space dimension acquisition module; calculating the dispersion coefficient of the radiator surface temperature distribution gradient value; superimposing the highest radiator surface temperature value after the standardization conversion and the dispersion coefficient; performing temperature compensation correction processing in combination with the current environment temperature value; calculating the heat dissipation efficiency attenuation coefficient by fusing the current environment dust concentration value; integrating the heat dissipation efficiency attenuation coefficient and the temperature compensation correction processing result to generate the charging space temperature comprehensive evaluation index.

[0009] As preferred, the pile body structure dimension health evaluation unit specifically performs: performing frequency domain conversion processing on the current charging pile vibration frequency value obtained by the pile body structure dimension acquisition module; extracting the characteristic harmonic component in the frequency domain conversion processing result; performing time domain slicing processing on the current charging pile noise decibel value; calculating the variance coefficient of the time domain slicing processing result; performing correlation matching on the characteristic harmonic component and the variance coefficient; performing thermal coupling effect calculation in combination with the current charging pile internal core component temperature value; generating the component operation deviation coefficient based on the thermal coupling effect calculation result.

[0010] As preferred, the output interface dimension safety evaluation unit specifically performs: performing logarithmic conversion processing on the current charging interface contact resistance value obtained by the output interface dimension acquisition module; performing geometric topology analysis on the charging interface metal spring deformation variable; calculating the expansion rate of the charging interface insulating layer crack area value; performing time sequence correlation processing on the geometric topology analysis result and the expansion rate; integrating the logarithmic conversion processing result and the time sequence correlation processing result to generate the interface safety risk index.

[0011] As preferred, the charging pile state regulation module comprises: The charging space regulation unit is configured to compare and analyze the charging space temperature comprehensive evaluation index with a preset temperature safety threshold, and trigger a heat dissipation system power adjustment instruction according to the comparison and analysis result. The pile body structure regulation unit is configured to calculate a deviation degree of the component operation deviation coefficient from the preset health threshold interval, and trigger a mechanical structure fastening operation according to the deviation degree calculation result. The output interface regulation unit is configured to map and match the interface safety risk index with a preset risk level scale, and trigger a charging interface power-off protection operation according to the mapping and matching result.

[0012] Preferably, a data interaction channel is arranged between the charging space regulation unit, the pile body structure regulation unit and the output interface regulation unit. The data interaction channel is configured to transmit associated matching parameters of the charging space temperature comprehensive evaluation index, the component operation deviation coefficient and the interface safety risk index. The associated matching parameters are configured to coordinate the execution priority of the heat dissipation system power adjustment instruction, the mechanical structure fastening operation and the charging interface power-off protection operation.

[0013] Preferably, the present application further includes a DC charging pile multi-dimensional information intelligent detection method, which includes all the modules and method processes of the DC charging pile multi-dimensional information intelligent detection system.

[0014] The present application has the following advantages: The DC charging pile multi-dimensional information intelligent detection system can simultaneously obtain the current charging space environment data of the charging space dimension, the current pile body structure operation data of the pile body structure dimension and the current output interface state data of the output interface dimension by arranging the charging pile multi-dimensional information acquisition module, breaks the limitation of single-dimensional data acquisition of the traditional detection system, and realizes comprehensive coverage of key influencing factors in the charging pile operation process. From the charging space environment, real-time acquisition of environmental parameters such as temperature, humidity and dust concentration can realize real-time control of the dynamic change of the charging space environment, timely discovery of environmental factors that may adversely affect the operation of the charging pile, and avoidance of safety hazards such as accelerated aging of internal components of the charging pile, short circuit and fire caused by environmental factors, and stable operation of the charging pile under suitable environmental conditions. In the dimension of the pile body structure, the collection of operation data such as the connection structure of the pile body shell, the internal support frame, the fastening state of the key electrical connection point, and the insulation performance does not need to rely on regular manual inspection, and real-time monitoring of the operation state of the pile body structure can be realized, which greatly reduces the labor cost and shortens the fault discovery time. By real-time monitoring of the operation state of the pile body structure, problems such as looseness, deformation, poor electrical connection point contact, and insulation performance decline can be found in time, avoiding safety accidents such as tilting and electrical failure caused by the decline of the stability of the pile body structure, prolonging the service life of the pile body structure, and ensuring the long-term healthy operation of the pile body structure. In the dimension of the output interface, not only the electrical parameters such as charging voltage and current are concerned, but also the physical state data such as interface plug-in wear degree, contact oxidation condition, and waterproof sealing performance are collected to comprehensively grasp the operation state of the output interface. Through real-time monitoring of the physical state of the interface, problems such as increased contact resistance, decreased current transmission efficiency, and failed waterproof sealing can be found in time to avoid safety hazards such as charging interruption, electric spark generation, and short circuit caused by interface problems, ensuring the stability and safety of the charging connection and improving the user charging experience. The multi-dimensional information analysis module of the charging pile analyzes each dimension data respectively in multiple levels, not simply judging single data, but deeply mining and analyzing data from different levels and different angles, which can more accurately identify abnormal conditions in each dimension data and accurately judge the health degree of each dimension operation state. This multi-level evaluation and analysis method can effectively avoid fault misjudgment caused by single data judgment deviation and improve the accuracy of evaluation of each dimension operation state. At the same time, through the analysis of multi-dimensional data, the specific situation of each dimension operation state can be clearly understood, providing a clear direction for subsequent targeted adjustment. The charging pile state regulation module performs charging pile operation parameter adjustment operations based on the multi-dimensional evaluation analysis results, realizing active intervention and optimization of the charging pile operation state. When the analysis results show that there is an abnormal situation in one dimension or multiple dimensions, the corresponding operation parameters can be adjusted in time, such as when the charging space environment temperature is too high, adjusting the heat dissipation system operation parameters of the charging pile to improve the heat dissipation efficiency and reduce the influence of the environment temperature on the charging pile; when the key components of the pile body structure appear slight looseness, the related fastening control parameters are adjusted to eliminate the safety hazards in time; when the oxidation of the output interface contact point causes the contact resistance to increase, the charging current parameters are adjusted to avoid safety problems caused by excessive contact resistance. This precise regulation based on the analysis results can timely solve the problems occurring in the operation process of the charging pile, avoid the expansion of faults, ensure the continuous and stable operation of the charging pile, reduce the downtime caused by faults, and improve the operation efficiency and service quality of the charging pile. In addition, the entire system realizes the automatic process of data collection, analysis and regulation, without too much manual intervention, further reducing the labor cost and improving the timeliness and accuracy of detection and regulation, providing a strong guarantee for the safe, stable and efficient operation of the direct current charging pile. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A timing diagram of the intelligent detection system based on the direct current charging pile multi-dimensional information according to the present application; Figure 2 A working principle diagram of the current charging space environment data of the charging space dimension; Figure 3 A working principle flow chart of the multi-dimensional analysis module.

[0016] The implementation of the present application, functional characteristics and advantages will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0017] It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0018] As Figure 1As shown, the application provides a direct current charging pile multi-dimensional information intelligent detection method and system, which is implemented by constructing a complete hardware detection and software analysis platform. The system hardware level integrates various sensors and data acquisition units, and the software level is deployed with special data analysis algorithms and control logic execution units. The core of the system is the cooperative operation of three main modules: the charging pile multi-dimensional information acquisition module is responsible for real-time acquisition of original data from the charging pile body and its surrounding environment; the charging pile multi-dimensional information analysis module performs deep processing and fusion analysis on the collected massive heterogeneous data to generate evaluation indexes of different dimensions; and the charging pile state regulation module automatically executes corresponding regulation instructions according to the evaluation results output by the analysis module, thereby realizing intelligent closed-loop management of the charging pile state. The operation of the entire system depends on the preset thresholds and algorithm models, which can be configured and optimized through the system background according to the actual application scenario.

[0019] In one embodiment, embodiment 1: refer to Figure 2 , a plurality of high-precision sensors are deployed at different positions of the charging pile to systematically obtain real-time running data of the charging space dimension, the pile body structure dimension, and the output interface dimension. All sensors are connected to a central data collector through shielded cables, which has signal conditioning, analog-to-digital conversion, and data preprocessing functions. In the data collection of the charging space dimension, the acquisition of environmental temperature and humidity values depends on a temperature and humidity integrated sensor installed on the outside of the charging pile protective shell. The sensor is usually located near the air inlet grille to avoid interference from internal heat sources, and its sampling frequency is set to one minute to effectively capture the slow changes of environmental parameters. The environmental dust concentration monitoring uses a particulate matter sensor based on the laser scattering principle. Its optical cavity design has a moisture-proof function, and the installation position is directed towards the vehicle driving direction to better reflect the true concentration of suspended particulate matter in the air. The sensor output unit is micrograms per cubic meter, and the data is updated every second. The surface temperature data of the radiator is collected by a non-contact infrared thermal imager. The device is fixed inside the charging pile and continuously scans the radiator fin area. The thermal image is transmitted to the processor, and two key parameters are extracted by a special algorithm: one is the highest temperature value of all pixel points in the scanning area, which is the highest temperature value of the radiator surface; the other is the temperature difference between adjacent pixel points, and the average value is calculated to obtain the temperature distribution gradient value of the radiator surface. This gradient value can effectively reflect the uniformity of the heat dissipation efficiency.

[0020] The data collection of the pile body structure dimension involves the monitoring of the internal physical state of the charging pile. The temperature monitoring of the core components is achieved by closely attaching PT100 platinum resistance temperature sensors to the surfaces of the power module IGBT base plate, the DC support capacitor shell, and the filter inductor coil. These sensors are high-temperature resistant and insulated, and the measurement accuracy is ensured by using heat-conducting silicone. The measurement data is refreshed at a frequency of one second. The vibration frequency monitoring uses a three-axis MEMS acceleration sensor, which is rigidly installed inside the main support structure of the charging pile. Its measurement range covers 0 to 2000 Hz, and it can capture the mechanical vibrations of the charging pile caused by internal power device switching, cooling fan rotation, and external environment. The raw acceleration data output by the sensor is subjected to FFT transformation to extract the main vibration frequency as the current charging pile vibration frequency value. The noise monitoring is achieved by installing a waterproof microphone array at different positions inside the pile body. The array consists of four sound pressure sensors, which use time division multiplexing technology to eliminate fan noise interference. The sound wave signals collected by the array are subjected to A-weighting filtering and then the root mean square value is calculated. Finally, the current charging pile noise decibel value is output in decibels.

[0021] The data collection of the output interface dimension focuses on the electrical and mechanical state of the charging interface. The contact resistance measurement is achieved by injecting a small test current into the power supply positive and negative loop of the charging gun interface and measuring the corresponding voltage drop. This measurement is performed during the charging interval to avoid large current interference. The measurement result is processed by a temperature compensation algorithm to obtain the current charging interface contact resistance value. The collection of interface wear data uses a visual detection system consisting of a high-resolution miniature camera integrated inside the charging gun handle and a ring-shaped LED fill light source. When the charging gun is returned to the gun seat, image acquisition is automatically triggered. The acquired interface internal image is analyzed by image processing algorithms. First, the metal reed profile is located by edge detection algorithm, then compared with the standard profile database to calculate the deformation value and obtain the charging interface metal reed deformation value. Meanwhile, the surface of the insulating layer is analyzed for texture. The crack area value of the charging interface insulating layer is calculated by identifying the pixel point proportion of the crack area and combining the actual size calibration. All collected data are time-stamped and labeled with sensor ID. They are transmitted to the central data processing unit through the CAN bus network. CRC check is used to ensure data integrity during transmission. Finally, a structured multi-dimensional data package is formed for the analysis module. The entire collection module uses a hierarchical power supply design. Key sensors are equipped with backup power to ensure that the last data collection and reporting can be completed in the event of a main power failure.

[0022] In one embodiment, embodiment 2: see Figure 3The charging space dimensional temperature evaluation unit is specifically responsible for processing data streams from environmental sensors and thermal imaging devices. The processing flow starts with the normalization of current environmental temperature values and current environmental dust concentration values. This step eliminates analysis barriers caused by different physical dimensions by mapping raw data to a scale range of 0-1. The processed normalized data, along with the highest temperature value of the radiator surface and the temperature distribution gradient value of the radiator surface, are input into a weighted fusion analysis algorithm. This algorithm performs linear combination of the four input parameters according to a pre-set weight coefficient matrix, with the highest weight assigned to the highest temperature value of the radiator surface, followed by the environmental dust concentration value. Finally, a non-linear activation function is used to generate a comprehensive evaluation index of the charging space temperature. The higher the index value, the more severe the heat dissipation environment.

[0023] The pile body structure dimensional health evaluation unit focuses on processing multi-source sensing data reflecting the mechanical operating state of the charging pile. This unit first performs discretization processing on the current charging pile internal core component temperature value, the current charging pile vibration frequency value, and the current charging pile noise decibel value, converting continuous analog signals into a finite number of discrete state levels based on pre-set threshold interval division standards. The discretized data is then sent to a state transition probability model based on Markov chain, which quantifies the degree of abnormality of the operating state by calculating the transition probability difference between the current state and the ideal operating state, and finally outputs a dimensionless component operating deviation coefficient. The value of this coefficient is negatively correlated with the device health status. The processing object of the output interface dimensional safety evaluation unit is the electrical and mechanical parameters of the charging interface. In the initialization stage, the current charging interface contact resistance value is standardized by using the Z-score standardization method to convert it into a standardized value with a mean of zero and a standard deviation of one. The processed resistance value, along with the charging interface metal spring deformation value and the charging interface insulation layer crack area value, is input into a multi-factor coupling analysis model. This model uses principal component analysis to reduce the correlation of the three parameters, extracts the principal component factors that can best explain the parameter variance, and then establishes a mapping relationship between the input parameters and the safety state through a radial basis function neural network, finally generating an interface safety score value between 0-100.

[0024] The three evaluation units adopt a parallel pipeline processing architecture, each equipped with independent data buffer and processing core, ensuring parallel processing when multiple source data arrive at the same time. The units interact with each other through shared memory space to exchange preliminary results, for example, the pile structure dimension health evaluation unit can share the calculated component running deviation coefficient with the charging space dimension temperature evaluation unit, to correct the environmental temperature influence on the evaluation model of the device internal temperature. All evaluation results are accompanied by confidence indicators and timestamp information, and are transmitted in real time to the state regulation module through the data bus. The system also establishes a self-learning mechanism for evaluation model parameters, which can dynamically adjust normalization parameters, weight coefficients and state division thresholds according to historical data, making the evaluation results more and more accurate as the device running time grows. The entire analysis module adopts fault-tolerant design, when some sensor data is abnormal or missing, it can automatically switch to the estimation mode based on historical data, ensuring the continuity of the system evaluation function.

[0025] Taking a direct current charging pile of a charging station in a coastal area as an example, the environmental temperature of the charging pile reaches 35 degrees Celsius in the afternoon, the relative humidity is 85%, and there is a certain amount of salt and dust in the environment due to the adjacent road. The charging space dimension temperature evaluation unit starts processing the collected multi-source data. The unit first normalizes the current environmental temperature value 35℃ and the current environmental dust concentration value 115μg / m³, converting these two parameters of different dimensions into a unified [0,1] interval value. The processed environmental data is combined with the radiator surface monitoring data, the maximum radiator surface temperature value reaches 72℃, and the surface temperature distribution gradient value is 4.2℃ / cm. After weighted fusion analysis, these two parameters produce an intermediate result. During the fusion process, the environmental temperature is assigned a weight coefficient of 0.3, the dust concentration weight is 0.2, the maximum radiator surface temperature weight is 0.35, and the temperature distribution gradient weight is 0.15. These weight coefficients are pre-set according to the thermal design characteristics of this type of charging pile. The final generated charging space temperature comprehensive evaluation index is 0.76, which indicates that the heat dissipation environment is in a relatively severe state.

[0026] The pile body structure dimension health assessment unit processes the mechanical operation data at the same time, and the unit receives the current charging pile internal core component temperature values: the power module is 88°C, the direct current support capacitor is 65°C, and the filter inductance is 72°C. These temperature data and vibration frequency value 125.6Hz, noise decibel value 68dB enter the discretization processing flow together. The processing process maps the continuous temperature readings to 5 discrete levels, the vibration frequency is divided into 10 frequency bands, and the noise decibel value is converted into 4 intensity levels. The discretized data is input to the running state assessment model, the model calculates the Mahalanobis distance of the current state and the standard running state, and obtains the component running deviation coefficient as 1.85. This value shows that the mechanical running state starts to deviate from the normal range, but has not reached a dangerous level.

[0027] The output interface dimension safety assessment unit processes the relevant data of the charging interface. The current charging interface contact resistance value is 2.8mΩ, which is converted into -5.88 after logarithmic conversion, and the converted data is more in line with the normal distribution characteristics. At the same time, the visual detection system measures that the charging interface metal reed deformation value is 0.12mm, and the charging interface insulation layer crack area value is 3.2mm². The multi-factor coupling analysis model processes these three parameters at the same time. The model first establishes a nonlinear relationship curve between the contact resistance and the reed deformation, then analyzes the correlation between the insulation crack and the contact resistance change, and finally extracts the key factors affecting the interface safety through principal component analysis. The analysis result shows that the contact resistance value is within the allowable range, but combined with the reed deformation and insulation aging trend, the interface safety state presents a slow deterioration characteristic. The processing process of the three assessment units has data interaction and result reference. The high temperature assessment result of the charging space dimension is shared to the pile body structure dimension health assessment unit to correct the assessment model of the influence of temperature on vibration and noise. The output interface dimension safety assessment unit provides the interface temperature data to the charging space dimension unit to perfect the overall thermal evaluation of the heat dissipation system. All assessment results are attached with time stamp and confidence index, and are transmitted to the state control module in real time through the data bus, providing quantitative basis for subsequent intelligent control decision. The whole analysis process adopts a rolling time window mechanism, which not only analyzes the data characteristics at the current time, but also considers the change trend of the recent historical data, so that the assessment result not only reflects the instantaneous state but also has time continuity.

[0028] In one embodiment, the processing flow of embodiment 3 starts with the standardization conversion of the highest temperature value on the radiator surface, which maps the actual measured temperature value to the numerical interval of 0 to 1 through a linear transformation. The conversion process uses a dynamic threshold method, and the upper threshold is dynamically adjusted according to the rated power level of the charging pile, so that the standardization result can adapt to the operating characteristics of different types of equipment. The temperature value after standardization eliminates the evaluation deviation caused by the absolute value. Subsequently, the dispersion coefficient of the temperature distribution gradient value of the radiator surface is calculated, which is based on the temperature field data of the entire heat dissipation surface collected by the thermal imager. First, the standard deviation of the temperature values of all measurement points is calculated, and then the dispersion coefficient is obtained by dividing the standard deviation by the average temperature value. This coefficient quantifies the uniformity of the temperature distribution on the heat dissipation surface. A higher dispersion coefficient indicates that the radiator may have local overheating or poor air flow problems.

[0029] The standardization temperature value obtained by the foregoing steps is superimposed with the dispersion coefficient. This superimposition process is not a simple arithmetic addition, but a weighted geometric mean processing, and the calculation formula is: Wherein: represents the intermediate fusion index, represents the highest temperature value on the radiator surface after standardization, represents the dispersion coefficient, and a and β are the weight indexes of the two parameters, which are pre-set according to the material and structural characteristics of the radiator. This fusion method can simultaneously consider the information of both the absolute temperature level and the temperature distribution uniformity.

[0030] The superimposed result then enters the temperature compensation correction processing stage, which introduces the current ambient temperature value as a compensation factor, establishes a correlation model between the ambient temperature and the radiator temperature using a polynomial fitting algorithm, and eliminates the baseline influence of the ambient temperature on the radiator surface temperature through the model, so that the evaluation result focuses more on the performance of the heat dissipation system itself. The corrected data is further fused with the ambient dust concentration value, and the fusion process adopts a heat dissipation performance decay calculation based on a physical model. First, an empirical relationship model between dust concentration and heat transfer coefficient between radiator fins is established, and then the current heat dissipation performance decay ratio is calculated according to the real-time dust concentration value. This ratio coefficient reflects the actual influence degree of dust accumulation on the heat dissipation capacity. The final comprehensive evaluation index generation adopts a multilayer perceptron neural network structure, taking the intermediate results obtained in the previous stages as input features, and generating the final charging space temperature comprehensive evaluation index through nonlinear transformation of the hidden layer in the network and linear combination of the output layer. The index value ranges from 0 to 100, and the higher the value, the worse the heat dissipation environment, and more aggressive thermal management measures need to be taken. The entire processing flow adopts a sliding time window mechanism, which not only considers the current data, but also introduces the moving average of recent historical data as a reference, so that the evaluation result reflects the instantaneous state and has time continuity.

[0031] Taking a direct current charging pile in a dust environment in an industrial park as an example, the charging pile is installed in a logistics vehicle charging area, and there is a certain degree of industrial dust in the surrounding environment, and the radiator surface has a slight dust accumulation phenomenon. The charging space dimension temperature evaluation unit starts the data processing flow, and the unit first receives real-time monitoring data from multiple sources: the ambient temperature sensor transmits a current ambient temperature value of 32.8°C, the laser dust sensor detects a current ambient dust concentration value of 156μg / m³, and the infrared thermal imager transmits the radiator surface temperature distribution data. The unit extracts features from the radiator surface temperature data, calculates the highest radiator surface temperature value as 68.4°C, and obtains the radiator surface temperature distribution gradient value as 3.8°C / cm through a temperature field analysis algorithm.

[0032] The unit begins to standardize the highest temperature value of the radiator surface and processes it with a dynamic range mapping algorithm, which maps the actual temperature value of 68.4°C to the value interval of 0-1. Considering the rated power level of the charging pile and the design standard of the radiator, 65°C is set as the reference temperature corresponding to the standardized value of 0.5, and the standardized temperature value is finally obtained as 0.72. This value reflects the deviation of the current radiator surface temperature from the design reference. At the same time, the unit calculates the dispersion coefficient of the radiator surface temperature distribution gradient value based on the 256 temperature measurement points collected by the thermal imager. First, the standard deviation of all measurement points is calculated as 2.7°C, and the average temperature is 61.3°C. The dispersion coefficient is obtained by the ratio of the standard deviation to the average value, which is 0.044. This coefficient value indicates that the radiator surface temperature distribution is not uniform, but it has not reached a serious level. The standardized temperature value 0.72 after the conversion processing is superimposed with the dispersion coefficient 0.044, and the superimposition process uses a weighted geometric mean algorithm. The algorithm assigns a weight coefficient of 0.6 to the standardized temperature value and a weight coefficient of 0.4 to the dispersion coefficient, and through the exponential weighted sum and square root operation, the intermediate fusion index value is obtained as 0.61. This fusion index considers both the absolute temperature level and the temperature distribution uniformity of two dimensions. The intermediate result enters the temperature compensation correction processing stage, which introduces the current environmental temperature value of 32.8°C as a compensation factor. The processing algorithm is based on the pre-established environmental temperature-radiator temperature correlation model, which is obtained by analyzing historical data that the radiator temperature rises by 0.8°C for every 1°C rise in environmental temperature. According to this relationship, the unit compensates and corrects the intermediate fusion index with the environmental temperature, and the index value is corrected to 0.58, eliminating the basic influence of the environmental temperature on the evaluation result.

[0033] The modified data is further fused with the ambient dust concentration value, and the unit adopts a heat dissipation performance decay calculation based on a physical model. The calculation process is based on the empirical relationship curve between dust concentration and heat dissipation efficiency. When the dust concentration reaches 156 μg / m³, the corresponding heat dissipation performance decay coefficient is 0.86. This coefficient indicates that due to dust accumulation, the actual heat dissipation capacity of the radiator is reduced to 86% of the ideal state. The final comprehensive evaluation index generation adopts a multi-layer neural network model, taking the temperature compensation correction result 0.58 and the heat dissipation performance decay coefficient 0.86 as input features. The neural network contains a hidden layer, which uses a Sigmoid activation function for non-linear transformation, and the output layer generates the final charging space temperature comprehensive evaluation index value as 0.67. The index value is in the interval range of 0.6-0.8, indicating that the current heat dissipation environment has certain risks but is still within the controllable range, and the system needs to strengthen heat dissipation management but has not yet reached the degree of immediate load reduction. The entire processing process adopts a sliding time window mechanism, and the unit not only analyzes the data at the current time, but also introduces the historical data of the previous 15 minutes to calculate the moving average. Time series analysis shows that the evaluation index shows a slow upward trend, which provides a data basis for predictive maintenance. All processing results are attached with time stamps and data processing logs, which are transmitted in real time to the state regulation module through the data bus, providing decision basis for intelligent regulation of the heat dissipation system.

[0034] In one embodiment, embodiment 4, the pile structure dimension health assessment unit first processes the vibration frequency data. After the unit receives the original time domain signal collected by the vibration sensor, it starts the frequency domain conversion processing flow. This flow uses the Fast Fourier Transform algorithm to convert the time domain vibration waveform into a frequency spectrum graph. The converted frequency spectrum data is subjected to a peak detection algorithm to identify the main vibration frequency components, and the characteristic harmonic components with significant amplitude and harmonic relationship are extracted. These components usually correspond to specific vibration modes of internal rotating mechanical components of the charging pile (such as cooling fans, transformer cores). Referring to Table 1, the vibration frequency analysis results of the charging pile within a 10-second time window are shown, including the frequency values and relative amplitudes of three main characteristic harmonic components.

[0035] Table 1: Analysis results of vibration frequency characteristic harmonic components Meanwhile, the noise decibel data enters the time domain slicing process, which divides the continuous sound pressure signal into multiple time slices at 100 ms intervals, and calculates the root mean square value of the sound pressure level of each slice. Based on these slice data, the variance coefficient is further calculated, which reflects the stability of the noise fluctuation degree. A higher variance coefficient indicates that the noise source has intermittent mutations or impact events. The characteristic harmonic components obtained by vibration analysis are correlated with the variance coefficient of noise analysis. This matching process uses the Pearson correlation coefficient to calculate the statistical correlation of the two data sequences, and the matching result reveals the coupling relationship between mechanical vibration and acoustic noise.

[0036] Combined with the temperature values of the internal core components of the charging pile obtained by real-time monitoring, the evaluation unit starts the thermal coupling effect calculation, which is based on the pre-established temperature-vibration-noise coupling model. The model takes into account physical parameters such as material thermal expansion coefficient and structural stiffness temperature characteristics. During the calculation process, the system identifies that when the power module temperature rises from 65°C to 78°C, the amplitude of the vibration fundamental frequency increases by about 15%, and the noise variance coefficient increases by 22%, indicating that the temperature rise exacerbates mechanical vibration and noise fluctuation. Finally, based on all these analysis results, the evaluation unit generates a quantitative component operation deviation coefficient, which comprehensively reflects the deviation degree of the current state of the mechanical structure from the ideal operating state. The output interface dimension safety evaluation unit processes the relevant data of the charging interface in parallel, and the unit first performs logarithmic conversion processing on the contact resistance measurement value. The converted resistance value is more consistent with the normal distribution characteristics, which is convenient for subsequent statistical analysis. The converted data and the charging interface metal reed deformation amount enter the analysis process together, and the deformation amount data comes from the image analysis results of the visual detection system, representing the deviation degree of the reed from the standard geometric shape.

[0037] The geometric topology analysis is aimed at the reed deformation data. This analysis extracts geometric features such as curvature change and angle deviation of the reed profile, and quantifies the severity of mechanical wear through these features. At the same time, the system calculates the expansion rate of the crack area value of the charging interface insulating layer, which is based on the crack area measurement data of multiple consecutive detection periods. The linear regression method is used to fit the trend of area change over time, and the rate value reflects the progress speed of insulation aging. The geometric topology analysis results and the crack expansion rate are processed in time sequence correlation, and the processing process uses the time series similarity analysis algorithm to identify the cooperative relationship between mechanical wear and insulation aging in development speed and time. Analysis found that when the reed deformation exceeds 0.15 mm, the crack expansion rate significantly accelerates, indicating that mechanical stress concentration accelerates the insulation aging process.

[0038] All processing results are integrated to generate an interface safety risk index, and the integration process adopts a weighted fusion algorithm, in which the weight of the contact resistance is the highest, and the deformation and crack rate are the second. The generated risk index is a standardized numerical value, and the higher the value, the greater the interface safety risk. When the index exceeds the predetermined threshold, the system will trigger the corresponding warning or protection action. The entire analysis process adopts multi-time scale data processing, short-term data reflects the immediate state, and long-term trend data is used for predictive maintenance evaluation, forming a complete device health status evaluation system.

[0039] In one embodiment, embodiment 5: The charging space regulation unit continuously receives the charging space temperature comprehensive evaluation index from the analysis module, and the unit internally presets multiple temperature safety threshold values, forming a step response mechanism. When the evaluation index is first monitored to exceed the first threshold value, the unit will generate a heat dissipation system power adjustment instruction, gradually increasing the speed setting value of the cooling fan, and this adjustment process adopts a PID control algorithm to ensure the smoothness of temperature change. If the index continues to rise and breaks through the second threshold value, the unit will start the auxiliary cooling device, and at the same time reduce the output power ratio of the charging pile, so as to curb the temperature rising trend by reducing the heat source. All regulation instructions are sent to the charging pile heat management system actuator through the Modbus communication protocol.

[0040] The working of the pile body structure regulation unit is based on the real-time monitoring of the component operation deviation coefficient, and the health threshold interval preset by the unit is divided into normal, attention, and warning three levels. When the deviation coefficient is in the attention interval, the unit will generate a mechanical structure tightening operation prompt information, which is displayed to the maintenance personnel through the human-machine interface, and suggests that the connecting parts of the specified parts are checked for preventive tightening. When the coefficient enters the warning interval, the unit will automatically trigger the high-frequency vibration suppression algorithm to avoid mechanical resonance by adjusting the switching frequency of the power module, and send an emergency maintenance request to the monitoring center. During the regulation process, the unit will record the time points and effects of all operations to form a device health status evolution log.

[0041] The output interface regulation unit adopts a risk level mapping mechanism to process the interface safety risk index, and the unit internally stores a preset risk level scale that maps the risk index of 0-100 to five risk levels. When the risk index is in the low risk level, the unit only records the interface state data without taking active intervention. When reaching the medium risk level, the unit will generate a charging current limit instruction to gradually reduce the maximum allowed charging current. After entering the high risk level, the unit immediately triggers the charging interface power-off protection operation, which includes multiple steps executed in sequence: first, send a charging termination signal to the vehicle, then control the contactor to break the DC power supply loop, and finally start the grounding switch to ensure safe discharge of the device.

[0042] The three regulation units share information and coordinate operation through a data interaction channel, which uses a publish-subscribe mode to transmit associated matching parameters. The charging space regulation unit regularly publishes temperature comprehensive evaluation indicators and their change trend data, and the pile structure regulation unit subscribes to these data to determine whether vibration abnormalities are related to temperature changes. The output interface regulation unit publishes real-time values of interface safety risk indexes for other units to evaluate the impact of electrical state on mechanical heat dissipation systems. The central dispatcher is responsible for managing the execution priority of all regulation instructions, and the scheduling algorithm dynamically adjusts the instruction queue based on multi-dimensional state evaluation results. When receiving a heat dissipation system power adjustment instruction and a charging interface power-off protection operation request at the same time, the dispatcher will prioritize processing the power-off protection operation because electrical safety has higher priority than heat management needs. The dispatcher also has a conflict detection function, which automatically enters a coordinated decision mode when it identifies that the instructions issued by different units are contradictory (such as needing to simultaneously increase and decrease fan speed), and selects the optimal regulation strategy based on the overall state evaluation results of the equipment.

[0043] All regulation operations are equipped with a double confirmation mechanism, and important instructions need to meet both automatic evaluation conditions and manual confirmation (or timeout default confirmation) before execution, ensuring the reliability of system actions. The regulation module also has operation rollback capability, which can automatically undo the current operation and try alternative solutions when it detects that the device state has not improved or worsened after the execution of the regulation instruction. The entire regulation process forms a closed loop feedback, and the system continuously monitors the device state changes after the execution of the regulation instruction, dynamically adjusts the subsequent control strategy, and realizes truly adaptive intelligent regulation.

[0044] The above only describes the preferred embodiments of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the present application specification and drawings, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A direct current charging pile multi-dimensional information intelligent detection system based on, characterized in that, The application relates to a charging pile multi-dimensional information acquisition module for acquiring current charging space environment data of a charging pile in a charging space dimension, current pile body structure operation data of the charging pile in a pile body structure dimension, and current output interface state data of the charging pile in an output interface dimension. The application relates to a charging pile multi-dimensional information analysis module for performing multi-level evaluation analysis on the current charging space environment data in the charging space dimension, the current pile body structure operation data in the pile body structure dimension, and the current output interface state data in the output interface dimension. The application relates to a charging pile state regulation module for performing charging pile operation parameter adjustment operations based on multi-level evaluation analysis results. The current charging space environment data in the charging space dimension includes current environment temperature values, current environment humidity values, current environment dust concentration values, and current charging pile radiator surface temperature data. 2.The DC charging pile multi-dimensional information intelligent detection system according to claim 1, characterized in that, The current pile body structure operation data in the pile body structure dimension includes current charging pile internal core component temperature values, current charging pile vibration frequency values, and current charging pile noise decibel values. The current output interface state data in the output interface dimension includes current charging interface contact resistance values and current charging interface wear degree data. The current charging pile radiator surface temperature data specifically refers to a radiator surface maximum temperature value and a radiator surface temperature distribution gradient value. 3.The DC charging pile multi-dimensional information intelligent detection system based on the DC charging pile according to claim 2, characterized in that, The current charging interface wear degree data specifically refers to a charging interface metal reed deformation amount and a charging interface insulating layer crack area value. The charging pile multi-dimensional information analysis module comprises:

4. The direct-current charging pile multi-dimensional information intelligent detection system according to claim 3, characterized in that, A charging space dimension temperature evaluation unit for performing normalization processing on the current environment temperature values and the current environment dust concentration values, performing weighted fusion analysis on the radiator surface maximum temperature value and the radiator surface temperature distribution gradient value, and generating a charging space temperature comprehensive evaluation index. A pile body structure dimension health evaluation unit for performing discretization processing on the current charging pile internal core component temperature values, the current charging pile vibration frequency values and the current charging pile noise decibel values, and calculating a component operation deviation coefficient. An output interface dimension safety evaluation unit for performing standardization processing on the current charging interface contact resistance values, and performing multi-factor coupling analysis on the charging interface metal reed deformation amount and the charging interface insulating layer crack area value. The charging space dimension temperature evaluation unit specifically performs:

5. The direct-current charging pile multi-dimensional information intelligent detection system according to claim 4, characterized in that, Standardization conversion processing on the radiator surface maximum temperature value based on the current charging pile radiator surface temperature data acquired by the charging space dimension acquisition module; Calculating a dispersion coefficient of the radiator surface temperature distribution gradient value; Feature superposition of the standardization conversion processed radiator surface maximum temperature value and the dispersion coefficient; Temperature compensation correction processing in combination with the current environment temperature value; Fusing the current environment dust concentration value to calculate a heat dissipation efficiency attenuation coefficient; Integrating the heat dissipation efficiency attenuation coefficient and the temperature compensation correction processing result to generate the charging space temperature comprehensive evaluation index. The pile body structure dimension health evaluation unit specifically performs: 6.The multi-dimensional information intelligent detection system based on DC charging piles according to claim 5, characterized in that, Frequency domain conversion processing on the current charging pile vibration frequency value acquired by the pile body structure dimension acquisition module; Extracting a feature harmonic component in the frequency domain conversion processing result; Time domain slicing processing on the current charging pile noise decibel value; ​ Calculate the variance coefficient of the time domain slice processing result; Correlate the characteristic harmonic component with the variance coefficient; Combine the current charging pile internal core component temperature value to calculate the thermal coupling effect; Generate the component operation deviation coefficient based on the thermal coupling effect calculation result.

7. The direct-current charging pile multi-dimensional information intelligent detection system according to claim 6, characterized in that, The output interface dimension safety assessment unit specifically performs: Logarithmic conversion processing on the current charging interface contact resistance value obtained by the output interface dimension acquisition module; Geometric topology analysis on the charging interface metal reed deformation variable; Calculate the expansion rate of the charging interface insulating layer crack area value; Time sequence correlation processing on the geometric topology analysis result and the expansion rate; Integrate the logarithmic conversion processing result and the time sequence correlation processing result to generate the interface safety risk index. 8.The multi-dimensional information intelligent detection system based on DC charging piles according to claim 7, characterized in that, The charging pile state regulation module includes: A charging space regulation unit for comparing and analyzing the charging space temperature comprehensive evaluation index with the preset temperature safety threshold, and triggering a heat dissipation system power adjustment instruction according to the comparison and analysis result; A pile body structure regulation unit for calculating the deviation degree of the component operation deviation coefficient and the preset health threshold interval, and triggering a mechanical structure tightening operation according to the deviation degree calculation result; An output interface regulation unit for mapping and matching the interface safety risk index with the preset risk level scale, and triggering a charging interface power-off protection operation according to the mapping and matching result. 9.The multi-dimensional information intelligent detection system based on DC charging piles according to claim 8, characterized in that, The data interaction channel is set between the charging space regulation unit, the pile body structure regulation unit, and the output interface regulation unit; The data interaction channel is used to transmit the associated matching parameters of the charging space temperature comprehensive evaluation index, the component operation deviation coefficient, and the interface safety risk index; The associated matching parameters are used to coordinate the execution priority of the heat dissipation system power adjustment instruction, the mechanical structure tightening operation, and the charging interface power-off protection operation.

10. A direct current charging pile multi-dimensional information intelligent detection method based on, characterized in that, All modules and method processes of the direct current charging pile multi-dimensional information intelligent detection system according to any one of claims 1 to 9 are included.

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