考虑非线性摩擦模型的机器人动力学参数辨识

针对机器人动力学参数辨识的问题,提出了一种基于人工蜂群算法的辨识方法。考虑到关节摩擦特性,引入非线性摩擦模型,推导了机器人动力学模型的非线性形式。设计满足速度、加速度边界条件的五阶傅里叶级数作为激励轨迹来采集实验数据;利用人工蜂群算法,以蜂群为搜索单位,通过群体间的信息交流方式与优胜劣汰机制,对模型中的未知参数进行了辨识。最后,对得到的辨识模型进行了分析与验证,结果表明通过辨识得到关节预测力矩与测量力矩有较高的匹配度,所建立的非线性模型能够更好地描述机器人的动力学特性。     

小型无人直升机航向线性自抗扰控制

针对小型无人直升机航向系统存在内部不确定性和外部扰动大的问题,提出了一种基于线性自抗扰控制(LADRC)算法来实现航向通道高性能控制方法。首先,分析和推导了Trex-600型无人直升机的航向模型,并引入阵风模型模拟实际飞行环境。然后,根据LADRC的控制原理设计了基于二阶LADRC的航向控制系统,并利用人工蜂群算法对控制器参数进行了整定。最后,对所设计的控制策略进行了仿真分析与实验验证,实现了无人直升机航向通道的轨迹跟踪控制,并与常见的PID控制进行了比较。结果表明:设计的LADRC控制器鲁棒性好、响应时间快、控制精度高,能够使Trex-600型无人直升机的航向角快速、精确地跟踪参考轨迹。     

Understanding the Enemy: A Review of the Genetics,Behavior and Chemical Ecology of Varroa destructor,the Parasitic Mite of Apis mellifera

Varroa destructor (Mesostigmata: Varroidae) is arguably the most damaging parasitic mite that attacks honey bees worldwide. Since its initial host switch from the Asian honey bee (Apis cerana) (Hymenoptera: Apidae) to the Western honey bee (Apis mellifera) (Hymenoptera: Apidae), Varroa has become a widely successful invasive species, attacking honey bees on almost every continent where apiculture is practiced. Two haplotypes of V. destructor (Japanese and Korean) parasitize A. mellifera, both of which vector various honey bee-associated viruses. As the population of Varroa grows within a colony in the spring and summer, so do the levels of viral infections. Not surprisingly, high Varroa parasitization impacts bees at the individual level, causing bees to exhibit lower weight, decreased learning capacity, and shorter lifespan. High levels of Varroa infestation can lead to colony-wide varroosis and eventually colony death, especially when no control measures are taken against the mites. Varroa has become a successful parasite of A. mellifera because of its ability to reproduce within both drone cells and worker cells, which allows populations to expand rapidly. Varroa uses several chemical cues to complete its life cycle, many of which remain understudied and should be further explored. Given the growing reports of pesticide resistance by Varroa in several countries, a better understanding of the mite’s basic biology is needed to find alternative pest management strategies. This review focuses on the genetics, behavior, and chemical ecology of V. destructor within A. mellifera colonies, and points to areas of research that should be exploited to better control this pervasive honey bee enemy.     

Impact of Honey Bee Migratory Management on Pathogen Loads and Immune Gene Expression is Affected by Complex Interactions With Environment,Worker Life History,and Season

The effects of honey bee management, such as intensive migratory beekeeping, are part of the ongoing debate concerning causes of colony health problems. Even though comparisons of disease and pathogen loads among differently managed colonies indicate some effects, the direct impact of migratory practices on honey bee pathogens is poorly understood. To test long- and short-term impacts of managed migration on pathogen loads and immunity, experimental honey bee colonies were maintained with or without migratory movement. Individuals that experienced migration as juveniles (e.g., larval and pupal development), as adults, or both were compared to control colonies that remained stationary and therefore did not experience migratory relocation. Samples at different ages and life-history stages (hive bees or foragers), taken at the beginning and end of the active season, were analyzed for pathogen loads and physiological markers of health. Bees exposed to migratory management during adulthood had increased levels of the AKI virus complex (Acute bee paralysis, Kashmir bee, and Israeli acute bee paralysis viruses) and decreased levels of antiviral gene expression (dicer-like). However, those in stationary management as adults had elevated gut parasites (i.e. trypanosomes). Effects of environment during juvenile development were more complex and interacted with life-history stage and season. Age at collection, life-history stage, and season all influenced numerous factors from viral load to immune gene expression. Although the factors that we examined are not independent, the results illuminate potential factors in both migratory and nonmigratory beekeeping that are likely to contribute to colony stress, and also indicate potential mitigation measures.     

Assessing Repeated Oxalic Acid Vaporization in Honey Bee (Hymenoptera: Apidae) Colonies for Control of the Ectoparasitic Mite Varroa destructor

The American beekeeping industry continually experiences colony mortality with annual losses as high as 43%. A leading cause of this is the exotic, ectoparasitic mite, Varroa destructor Anderson & Trueman (Mesostigmata: Varroidae). Integrated Pest Management (IPM) options are used to keep mite populations from reaching lethal levels, however, due to resistance and/or the lack of suitable treatment options, novel controls for reducing mites are warranted. Oxalic acid for controlling V. destructor has become a popular treatment regimen among commercial and backyard beekeepers. Applying vaporized oxalic acid inside a honey bee hive is a legal application method in the U.S., and results in the death of exposed mites. However, if mites are in the reproductive stage and therefore under the protective wax capping, oxalic acid is ineffective. One popular method of applying oxalic is vaporizing multiple times over several weeks to try and circumvent the problem of mites hiding in brood cells. By comparing against control colonies, we tested oxalic acid vaporization in colonies treated with seven applications separated by 5 d (35 d total). We tested in apiaries in Georgia and Alabama during 2019 and 2020, totaling 99 colonies. We found that adult honey bees Linnaeus (Hymenoptera: Apidae), and developing brood experienced no adverse impacts from the oxalic vaporization regime. However, we did not find evidence that frequent periodic application of oxalic during brood-rearing periods is capable of bringing V. destructor populations below treatment thresholds.     

蜂群箱体关键参数在线监测系统与性能测试

随着信息技术的发展,利用大数据分析、物联网监控、传感器感知、无线通信等技术构建一种蜂箱蜂群实时在线监测系统,是减少因开箱检查造成蜂群应激反应的可行解决方案。本研究针对蜂箱封闭环境进行实时监测困难的现状,利用STM32F103VBT6 32位微控制器,同时融合了温湿度传感器、微麦克风以及激光对射传感器,开发了一套低功耗、可连续工作的蜂群箱体关键参数在线监测系统,实现了养蜂生产过程中多参数信息获取以及蜂箱内蜂群的环境参数和生活状态的实时在线监测。系统主要包括核心处理模块、数据采集模块、数据发送模块以及数据库服务器等。数据采集模块包括蜂箱内部温湿度采集单元、蜂群声音采集单元、蜜蜂进出巢数量计数单元等,通过接入移动通信网络进行数据传输。系统现场部署性能测试结果表明,研制的系统能够实时监测蜂箱内温湿度,有效区别进出蜂箱的蜜蜂并记录进出巢门的蜜蜂数量,且自动获取的蜂群声音与标准的蜂群声音分布相吻合。本系统符合设计要求,采集参数准确可靠,可以作为蜂群相关研究的数据采集方法。     

基于改进VMD的离心泵空化声发射信号特征提取

针对变分模态分解算法中分解层数和惩罚因子不易确定的问题,提出一种改进变分模态分解(improved variational mode decomposition,IVMD)算法,并将其应用于离心泵空化声发射信号特征提取.应用IVMD算法时,首先根据包络熵差异系数确定变分模态分解的分解层数;然后采用人工蜂群算法优化得出惩罚因子,并将其作为变分模态分解的最佳输入参数.利用IVMD算法对仿真信号进行分析,并与集合经验模态分解结果进行比较.以60%额定流量下采集到的离心泵进口处的声发射信号为例进行IVMD计算,分析携带原信号大量信息的信号分量的频域特征及其绝对能量随离心泵空化状态变化的关系.结果表明:IVMD算法能够择优确定分解层数和惩罚因子,实现非平稳信号的自适应分解.反映离心泵空化状态的声发射信号特征频率集中在50,100 kHz及其附近.随着离心泵空化从无到有、从弱到强的变化,这2个特征频率范围信号分量绝对能量值呈“基本保持不变-减小-增大”的变化规律.     

“浙农1号”意蜂的生产性哺乳率

１－３日龄“浙农１号”意蜂工蜂幼虫的个体呼吸商约为０．９３３,平均生长饲料比为１．５６９,蜂王幼虫在移虫后４０－８０ｈ的呼吸商约为０．９１,生长饲料比为１．４８．根据估测的年出蜂数,计算工蜂个体平均吐浆量,从而得出“浙农１号”生产性哺乳率为２．３５－３．３６．     

9种含阿维菌素或甲氨基阿维菌素的农药对蜜蜂安全性评价

参照《化学农药环境安全评价试验准则》,测定了9种含阿维菌素或甲氨基阿维菌素苯甲酸盐的农药对蜜蜂的急性接触毒性和摄入毒性。结果表明:所有含阿维菌素或甲氨基阿维菌素苯甲酸盐的农药对蜜蜂的急性接触和摄入毒性均为高毒。