Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8833202
Zhiping Liu, Yawen Wang
In recent years, there is a strong demand for automated and even autonomous robots in many fields such as manufacturing or social services and varieties of robots have been developed. In order to realize the humanized service from the robots, path planning and path tracking problems should be addressed according to typical and unique working environment. In this paper, the simplified four wheeled electric vehicle was chosen as our robot model, then the lateral controller was proposed based on the Lyapunov stability theory and linear control theory. Associated simulation models were constructed in the MATLAB environment, and simulation results show that the designing method of commad signals is reasonable and linear feedback controller can be used for robot trajectory tracking.
{"title":"Trajectory Tracking of Mobile Service Robot","authors":"Zhiping Liu, Yawen Wang","doi":"10.1109/CCDC.2019.8833202","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833202","url":null,"abstract":"In recent years, there is a strong demand for automated and even autonomous robots in many fields such as manufacturing or social services and varieties of robots have been developed. In order to realize the humanized service from the robots, path planning and path tracking problems should be addressed according to typical and unique working environment. In this paper, the simplified four wheeled electric vehicle was chosen as our robot model, then the lateral controller was proposed based on the Lyapunov stability theory and linear control theory. Associated simulation models were constructed in the MATLAB environment, and simulation results show that the designing method of commad signals is reasonable and linear feedback controller can be used for robot trajectory tracking.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"1 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122115196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8832740
Jianguo Cui, Guoqing Li, Mingyue Yu, Liying Jiang, Zeli Lin
As a complex high-speed mechanical system, the aero-engine is a typical fault-prone system in long-term high-altitude environments such as high temperature, high pressure, strong corrosion and high-density capacity release. It is extremely difficult to accurately diagnose it. To this end, this paper proposes an aero-engine fault diagnosis method based on kernel principal component analysis and wavelet neural network. The nuclear principal component analysis method is used to process the aero-engine original parameter data, extract its principal component features, reduce the parameter dimension, and construct the health state and fault state data sample set with the extracted principal component feature data. It is divided into training sample set and test sample set. The wavelet neural network fault diagnosis model is built by using the training feature data sample set. The diagnostic neural network fault diagnosis model is diagnosed and analyzed by using the test feature data sample set. At the same time, BP neural network is used to diagnose the same feature data sample set. In addition, the wavelet neural network fault diagnosis model is used to study the fault diagnosis technology of the original data. The research results show that the diagnosis results of the aero-engine fault diagnosis model based on kernel principal component analysis and wavelet neural network are obviously better than the diagnostic results of other methods used in this paper, and have good practical application value.
{"title":"Aero-engine Fault Diagnosis Based on Kernel Principal Component Analysis and Wavelet Neural Network","authors":"Jianguo Cui, Guoqing Li, Mingyue Yu, Liying Jiang, Zeli Lin","doi":"10.1109/CCDC.2019.8832740","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832740","url":null,"abstract":"As a complex high-speed mechanical system, the aero-engine is a typical fault-prone system in long-term high-altitude environments such as high temperature, high pressure, strong corrosion and high-density capacity release. It is extremely difficult to accurately diagnose it. To this end, this paper proposes an aero-engine fault diagnosis method based on kernel principal component analysis and wavelet neural network. The nuclear principal component analysis method is used to process the aero-engine original parameter data, extract its principal component features, reduce the parameter dimension, and construct the health state and fault state data sample set with the extracted principal component feature data. It is divided into training sample set and test sample set. The wavelet neural network fault diagnosis model is built by using the training feature data sample set. The diagnostic neural network fault diagnosis model is diagnosed and analyzed by using the test feature data sample set. At the same time, BP neural network is used to diagnose the same feature data sample set. In addition, the wavelet neural network fault diagnosis model is used to study the fault diagnosis technology of the original data. The research results show that the diagnosis results of the aero-engine fault diagnosis model based on kernel principal component analysis and wavelet neural network are obviously better than the diagnostic results of other methods used in this paper, and have good practical application value.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131955665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8833325
Kai Quan, B. Xiao, Yiran Wei
This paper is concerned of the loop closure detection problem, which is one of the most critical parts for visual Simultaneous Localization and Mapping (SLAM) systems. Most of state-of-the-art methods use hand-crafted features and bag-of-visual-words (BoVW) to tackle this problem, but not all SALM systems require hand-crafted feature. With the improvement of machine learning, Convolution Neural Networks (CNNs) has a significant effect on feature detection. This paper proposes a loop closure detection method without hand-crafted feature. We extract the image features through CNNs, and reduce the dimensions of the feature values with t-distributed stochastic neighbor embedding (T-SNE). And then we get a dictionary of two-dimensional feature points, which are obtained by T-SNE. Combined with the new similarity judgment method, the BoVW model based on CNNs is constructed. The new method can solve the loop closure detection of SLAM systems without hand-crafted features. Based on the characteristics of CNNs, the performance of scale-invariant feature transform has been significantly improved.
{"title":"Intelligent Descriptor of Loop Closure Detection for Visual SLAM Systems","authors":"Kai Quan, B. Xiao, Yiran Wei","doi":"10.1109/CCDC.2019.8833325","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833325","url":null,"abstract":"This paper is concerned of the loop closure detection problem, which is one of the most critical parts for visual Simultaneous Localization and Mapping (SLAM) systems. Most of state-of-the-art methods use hand-crafted features and bag-of-visual-words (BoVW) to tackle this problem, but not all SALM systems require hand-crafted feature. With the improvement of machine learning, Convolution Neural Networks (CNNs) has a significant effect on feature detection. This paper proposes a loop closure detection method without hand-crafted feature. We extract the image features through CNNs, and reduce the dimensions of the feature values with t-distributed stochastic neighbor embedding (T-SNE). And then we get a dictionary of two-dimensional feature points, which are obtained by T-SNE. Combined with the new similarity judgment method, the BoVW model based on CNNs is constructed. The new method can solve the loop closure detection of SLAM systems without hand-crafted features. Based on the characteristics of CNNs, the performance of scale-invariant feature transform has been significantly improved.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132004476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8832783
Bo Yang, Miaomiao Zhao, Luyao Guo, R. Guo, Tiantian Zhao
In this paper, an improved weighted centroid location algorithm for quadrilateral ranging based on received signal strength indication (RSSI) is used to reduce the measurement error of RSSI effectively. Furthermore, this paper puts forward the localization algorithm of indoor optimization RSSI based on Bayesian probability model and combines the least squares curve fitting to estimate the location of unknown nodes, which further improves the accuracy of the algorithm. In addition, the simulation results show that the improved centroid localization algorithm not only improves the accuracy greatly, and the robustness is also relatively high.
{"title":"Quadrilateral Weighted Localization for Wireless Sensor Networks Based on Bayesian Filtering","authors":"Bo Yang, Miaomiao Zhao, Luyao Guo, R. Guo, Tiantian Zhao","doi":"10.1109/CCDC.2019.8832783","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832783","url":null,"abstract":"In this paper, an improved weighted centroid location algorithm for quadrilateral ranging based on received signal strength indication (RSSI) is used to reduce the measurement error of RSSI effectively. Furthermore, this paper puts forward the localization algorithm of indoor optimization RSSI based on Bayesian probability model and combines the least squares curve fitting to estimate the location of unknown nodes, which further improves the accuracy of the algorithm. In addition, the simulation results show that the improved centroid localization algorithm not only improves the accuracy greatly, and the robustness is also relatively high.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127297560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8833262
Lipo Mo, Peng Lin
This paper mainly focuses on the distributed optimization problem over second-order multi-agent networks, where the team objective function is the sum of some local differentiable convex functions. Assume one local objective function can only be known by one agent. Based on the local neighbors’ information, a new distributed optimization algorithm with nonuniform gains is proposed. By a new coordination transformation, the closed-loop system can be decomposed into two one-order system. It is proved that all agents can reach an agreement and the team objective function can be minimized by analyzing these two one-order systems. Finally, a simulation example ia given to show the effectiveness of the theoretical results.
{"title":"Distributed Continuous-time Optimization over Second-order Multi-agent Networks with Nonuniform Gains","authors":"Lipo Mo, Peng Lin","doi":"10.1109/CCDC.2019.8833262","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833262","url":null,"abstract":"This paper mainly focuses on the distributed optimization problem over second-order multi-agent networks, where the team objective function is the sum of some local differentiable convex functions. Assume one local objective function can only be known by one agent. Based on the local neighbors’ information, a new distributed optimization algorithm with nonuniform gains is proposed. By a new coordination transformation, the closed-loop system can be decomposed into two one-order system. It is proved that all agents can reach an agreement and the team objective function can be minimized by analyzing these two one-order systems. Finally, a simulation example ia given to show the effectiveness of the theoretical results.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131043481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8832688
Li Fu, Shuai Zhang, Yu Gong, Quanjun Huang
Medicine glass bottles must be inspected for various indicators after production. The article proposes a method based on machine vision for the detection of glass bottle port defects with simple operation and wide application. Obtain the image of the bottle by using the backlight illumination. Pretreat the image of the bottle, and the quality of the glass bottle is determined and the defect range is determined by detecting and analyzing the characteristics of the connected domain of the defect position of the glass bottle port. The pretreatment mainly includes image median filtering, image enhancement, and edge detection. The types of glass bottle defects mainly include cracks, missing edges, dirty bottles, black spots, and so on. After testing quite a number of medicinal glass bottles, the method can be widely applied to common glass bottle port defects. The thirty-six sample bottles with missing edge defects had the lowest recognition rate of 91.6%.
{"title":"Medicine Glass Bottle Defect Detection Based on Machine Vision","authors":"Li Fu, Shuai Zhang, Yu Gong, Quanjun Huang","doi":"10.1109/CCDC.2019.8832688","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832688","url":null,"abstract":"Medicine glass bottles must be inspected for various indicators after production. The article proposes a method based on machine vision for the detection of glass bottle port defects with simple operation and wide application. Obtain the image of the bottle by using the backlight illumination. Pretreat the image of the bottle, and the quality of the glass bottle is determined and the defect range is determined by detecting and analyzing the characteristics of the connected domain of the defect position of the glass bottle port. The pretreatment mainly includes image median filtering, image enhancement, and edge detection. The types of glass bottle defects mainly include cracks, missing edges, dirty bottles, black spots, and so on. After testing quite a number of medicinal glass bottles, the method can be widely applied to common glass bottle port defects. The thirty-six sample bottles with missing edge defects had the lowest recognition rate of 91.6%.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117037587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.1109/CCDC.2019.8833476
Liu Jing, Yao Wei
In order to solve the problems of low collection efficiency and high labor cost for the growth environment parameters of traditional agricultural greenhouse crops. And solving the problem of using Zigbee communication technology to cause short transmission distance and easy interference. This paper integrates commonly used LoRa wireless network technology and QT technology to design a new intelligent agriculture system. The system uses LoRa communication module as the communication core, and use the widely used STM32F103 development board as a controller of the sensors and execution, the host computer program developed by Qt receives the data, visually display them, and processes them, this system realized timely monitoring and timely decision-making on the agriculture greenhouse.
{"title":"Intelligent Agriculture System Based on LoRa and Qt Technology","authors":"Liu Jing, Yao Wei","doi":"10.1109/CCDC.2019.8833476","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8833476","url":null,"abstract":"In order to solve the problems of low collection efficiency and high labor cost for the growth environment parameters of traditional agricultural greenhouse crops. And solving the problem of using Zigbee communication technology to cause short transmission distance and easy interference. This paper integrates commonly used LoRa wireless network technology and QT technology to design a new intelligent agriculture system. The system uses LoRa communication module as the communication core, and use the widely used STM32F103 development board as a controller of the sensors and execution, the host computer program developed by Qt receives the data, visually display them, and processes them, this system realized timely monitoring and timely decision-making on the agriculture greenhouse.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125295188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/CCDC.2019.8832973
Tiancheng Zhang, W. Dong, He Shi, Ruomei Liu, Hao Sun
With the development of informatization and data collection, more and more educational process data can be obtained by education practitioners, and these massive data need to be processed in order to be used by people. Based on the classical algorithm and technical principle of data mining, this paper designs and implements a teaching analysis system based on data mining, which mainly provides the related functions of clustering analysis, regression analysis and association analysis for users. According to the K-means algorithm, the students' data are divided into several clusters in order to complete the clustering analysis of the students’ scores. FP-Growth algorithm is used to analyze the strong association rules between courses. Through Python’s drawing package, the data can be displayed clearly and intuitively, thus completing the data visualization. Finally, a user-friendly interface is built by PyQt5, and the analysis results are visualized and output.
{"title":"Design and implementation of teaching analysis system based on data mining","authors":"Tiancheng Zhang, W. Dong, He Shi, Ruomei Liu, Hao Sun","doi":"10.1109/CCDC.2019.8832973","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832973","url":null,"abstract":"With the development of informatization and data collection, more and more educational process data can be obtained by education practitioners, and these massive data need to be processed in order to be used by people. Based on the classical algorithm and technical principle of data mining, this paper designs and implements a teaching analysis system based on data mining, which mainly provides the related functions of clustering analysis, regression analysis and association analysis for users. According to the K-means algorithm, the students' data are divided into several clusters in order to complete the clustering analysis of the students’ scores. FP-Growth algorithm is used to analyze the strong association rules between courses. Through Python’s drawing package, the data can be displayed clearly and intuitively, thus completing the data visualization. Finally, a user-friendly interface is built by PyQt5, and the analysis results are visualized and output.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"343 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115273520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/CCDC.2019.8832843
Jiapei Yu, Li Xu
In order to protect the water-supply scheme from the predictive error of water consumption, an user-demand oriented stochastic water-supply scheduling method on the seawater desalination system is proposed. Firstly, Classification and Regression Tree is used to estimate the prediction interval of the users’ future demands. Dependent-Chance Programming and Monte Carlo Simulation are used to figure out the probability of the event that the allocated water meets the demands of users. The equilibrium of water-supply is also taken into consideration. In this way, the stochastic model is transformed into the multi-objective optimization problem. Multiple-Population Quantum Genetic Algorithm is employed to acquire the optimal solution. The result of real-world case study validates the effectiveness of the proposed method.
{"title":"The Users-Demand-Oriented Stochastic Scheduling Method on Seawater Desalination System","authors":"Jiapei Yu, Li Xu","doi":"10.1109/CCDC.2019.8832843","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832843","url":null,"abstract":"In order to protect the water-supply scheme from the predictive error of water consumption, an user-demand oriented stochastic water-supply scheduling method on the seawater desalination system is proposed. Firstly, Classification and Regression Tree is used to estimate the prediction interval of the users’ future demands. Dependent-Chance Programming and Monte Carlo Simulation are used to figure out the probability of the event that the allocated water meets the demands of users. The equilibrium of water-supply is also taken into consideration. In this way, the stochastic model is transformed into the multi-objective optimization problem. Multiple-Population Quantum Genetic Algorithm is employed to acquire the optimal solution. The result of real-world case study validates the effectiveness of the proposed method.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115313708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-01DOI: 10.1109/CCDC.2019.8832745
Zhengcheng Xia, F. Xie, Xiaowu Wang
In modern industry, torque wrenches are widely used in precision assembly. In view of the shortcomings of the existing electric torque wrenches on the market, such as complex scheme, low precision and small torque range, this paper proposes a design scheme of torque wrenches based on the detection of torque difference to control the bolt preload. At the same time, the mechanical characteristics of the series motor used in the torque wrench are analyzed, and the mathematical model between torque and speed difference is established. The electric fixed torque wrench has the characteristics of simple structure, large torque range, safety and reliability.
{"title":"Design of Electric Fixed Torque Wrench Based on Speed Difference Detection","authors":"Zhengcheng Xia, F. Xie, Xiaowu Wang","doi":"10.1109/CCDC.2019.8832745","DOIUrl":"https://doi.org/10.1109/CCDC.2019.8832745","url":null,"abstract":"In modern industry, torque wrenches are widely used in precision assembly. In view of the shortcomings of the existing electric torque wrenches on the market, such as complex scheme, low precision and small torque range, this paper proposes a design scheme of torque wrenches based on the detection of torque difference to control the bolt preload. At the same time, the mechanical characteristics of the series motor used in the torque wrench are analyzed, and the mathematical model between torque and speed difference is established. The electric fixed torque wrench has the characteristics of simple structure, large torque range, safety and reliability.","PeriodicalId":254705,"journal":{"name":"2019 Chinese Control And Decision Conference (CCDC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115366960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：