FailureDistribution[bexpr,{{x1,dist1},{x2,dist2},…}]
表示一个系统的失效分布,其中事件 xi 的可靠性分布为 disti,当布尔表达式 bexpr 为 True 时发生顶级事件而当 xi 为 True 时事件 xi 发生.
FailureDistribution
FailureDistribution[bexpr,{{x1,dist1},{x2,dist2},…}]
表示一个系统的失效分布,其中事件 xi 的可靠性分布为 disti,当布尔表达式 bexpr 为 True 时发生顶级事件而当 xi 为 True 时事件 xi 发生.
更多信息
- FailureDistribution[bexpr,…] 对应于故障树规范.
- 布尔表达式 bexpr 也称为系统的结构函数.
- 典型的结构函数包括:
-

Or 门 
And 门 ![TemplateBox[{BooleanCountingFunction, paclet:ref/BooleanCountingFunction}, RefLink, BaseStyle -> {2ColumnTableMod}][{k,n},n] TemplateBox[{BooleanCountingFunction, paclet:ref/BooleanCountingFunction}, RefLink, BaseStyle -> {2ColumnTableMod}][{k,n},n]](Files/FailureDistribution.zh/3.png)
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系统BooleanConsecutiveFunction[k,n] 连续的
-
系统 - 结构函数 bexpr 可以是任意正的单边布尔函数.
- UnateQ[bexpr] 可用于测试布尔表达式是否是正单边的.
- 事件可靠性分布 disti 必须是 PDF[disti,t] 下的单变量分布,对于 t≤0 是零.
- 对于具有事件指示器 xi 的 FailureDistribution[bexpr,…]:
-
xiTrue 表明事件 xi 已经发生 xiFalse 表明事件 xi 没有发生 - 对于 FailureDistribution[bexpr,{{x1,dist1},…}],时间 t 处的累积分布函数由Probability[bexpr/.{x1->t1≤t,…},{t1dist1,…}] 给出.
- FailureDistribution 可以与诸如 Mean、SurvivalFunction、HazardFunction 和 RandomVariate 等函数一起使用.
范例
打开所有单元 关闭所有单元基本范例 (3)
ℱ = FailureDistribution[x∨y, {{x, ExponentialDistribution[Subscript[λ, 1]]}, {y, ExponentialDistribution[Subscript[λ, 2]]}}];SurvivalFunction[ℱ, t]ℱ = FailureDistribution[x∧y, {{x, ExponentialDistribution[λ]}, {y, WeibullDistribution[α, β]}}];SurvivalFunction[ℱ, t]ℱ = FailureDistribution[x∨(y∧z), {{x, ExponentialDistribution[3]}, {y, ExponentialDistribution[1]}, {z, ExponentialDistribution[2]}}];Table[Plot[df[ℱ, t], {t, 0, 2}, PlotLabel -> df, PlotRange -> All], {df, {SurvivalFunction, HazardFunction, PDF, CDF}}]{Mean[ℱ], Median[ℱ]}//NProbability[t < 0.5, tℱ]范围 (22)
基本用途 (5)
对于一个当两个事件中任何一个发生时,就发生故障的系统,求故障发生前的平均时间:
ℱ = FailureDistribution[x∨y, {{x, ExponentialDistribution[1]}, {y, ExponentialDistribution[2]}}];Mean[ℱ]ℱ = FailureDistribution[x∧y, {{x, ExponentialDistribution[1]}, {y, LogNormalDistribution[2, 3]}}];SurvivalFunction[ℱ, t]对三个事件中有两个发生时,才出现故障的系统,求该系统的 SurvivalFunction:
{𝒟1, 𝒟2, 𝒟3} = {ExponentialDistribution[1], ExponentialDistribution[2], ExponentialDistribution[3]};ℱ = FailureDistribution[BooleanCountingFunction[{2, 3}, {x, y, z}], {{x, 𝒟1}, {y, 𝒟2}, {z, 𝒟3}}];SurvivalFunction[ℱ, t]Plot[%, {t, 0, 2}, Filling -> Axis, PlotRange -> All]ℱ = FailureDistribution[x∨y, {{x, LogNormalDistribution[1, 2]}, {y, WeibullDistribution[3, 4]}}];data = RandomVariate[ℱ, 10^5];Show[
Histogram[data, {0, 7, 1 / 3}, "PDF"],
Plot[Evaluate[PDF[ℱ, t]], {t, 0, 7}, PlotStyle -> Thick]]𝒟 = StandbyDistribution[ExponentialDistribution[Subscript[λ, 1]], {ExponentialDistribution[Subscript[λ, 2]]}];ℱ = FailureDistribution[x∨y, {{x, 𝒟}, {y, ExponentialDistribution[Subscript[λ, 3]]}}];Mean[ℱ]结构函数 (4)
𝒟 = ExponentialDistribution[1];ℱ = FailureDistribution[(x∧y)∧(z∨w), {{x, 𝒟}, {y, 𝒟}, {z, 𝒟}, {w, 𝒟}}];SurvivalFunction[ℱ, t]𝒟 = ExponentialDistribution[1];ℱ = FailureDistribution[Majority[x, y, z], {{x, 𝒟}, {y, 𝒟}, {z, 𝒟}}];SurvivalFunction[ℱ, t]Subscript[𝒟, c] = ExponentialDistribution[1];ℱ = FailureDistribution[BooleanCountingFunction[{3, 4}, {x, y, z, v}], {{x, Subscript[𝒟, c]}, {y, Subscript[𝒟, c]}, {z, Subscript[𝒟, c]}, {v, Subscript[𝒟, c]}}];SurvivalFunction[ℱ, t]ℱ = FailureDistribution[¬x⊽¬y, {{x, WeibullDistribution[α, β]}, {y, ErlangDistribution[k, λ]}}];CDF[ℱ, t]使用 UnateQ 来测试一个布尔表达式是否是正单边的:
UnateQ[¬x⊽¬y]参数式寿命分布 (4)
使用任何参数式寿命分布,包括 LogNormalDistribution:
ℱ = FailureDistribution[x∧y, {{x, ExponentialDistribution[1]}, {y, LogNormalDistribution[1, 2]}}];NExpectation[t, tℱ, WorkingPrecision -> 16]ℱ = FailureDistribution[x∧y, {{x, ExponentialDistribution[λ]}, {y, GammaDistribution[2, β]}}];μ = Mean[ℱ]Plot3D[μ, {λ, 1 / 2, 4}, {β, 0, 2}]Limit[μ, λ -> ∞] == Mean[GammaDistribution[2, β]]{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {WeibullDistribution[2, β], ExponentialDistribution[1 / (Sqrt[π] β / 2)]};Mean /@ {Subscript[𝒟, 1], Subscript[𝒟, 2]}{Subscript[ℱ, P], Subscript[ℱ, S]} = Map[FailureDistribution[#[x, y], {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}]&, {Or, And}];Plot[Evaluate[Mean /@ {Subscript[ℱ, P], Subscript[𝒟, 1], Subscript[ℱ, S]}], {β, 0, 10}, PlotLegends -> {"SubscriptBox[ℱ, P]", "SubscriptBox[𝒟, 1]", "SubscriptBox[ℱ, S]"}]{Subscript[𝒟, 1] = PoissonDistribution[10], Subscript[𝒟, 2] = PoissonDistribution[11]};ℱ = FailureDistribution[x∨y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}];NExpectation[t, tℱ]绘制 SurvivalFunction 的图线:
DiscretePlot[SurvivalFunction[ℱ, t], {t, 0, 10}]非参数式寿命分布 (3)
使用 SmoothKernelDistribution 对飞机玻璃强度建模:
data = ExampleData[{"Statistics", "AirplaneGlass"}]𝒟 = TruncatedDistribution[{0, ∞}, SmoothKernelDistribution[data]]ℱ = FailureDistribution[x∨y, {{x, 𝒟}, {y, ExponentialDistribution[1 / 30]}}];SurvivalFunction[ℱ, t]Plot[SurvivalFunction[ℱ, x], {x, 0, 50}]使用 HistogramDistribution 对事件建模:
hd = HistogramDistribution[RandomVariate[WeibullDistribution[1, 2], 1000]];在两个和三个事件下,绘制 Or 门的生存函数的图线:
{Subscript[𝒟, two], Subscript[𝒟, three]} = {FailureDistribution[x∨y, {{x, hd}, {y, hd}}],
FailureDistribution[x∨y∨z, {{x, hd}, {y, hd}, {z, hd}}]};Plot[{SurvivalFunction[Subscript[𝒟, two], t], SurvivalFunction[Subscript[𝒟, three], t]}, {t, 0, 5}, Filling -> 0, Exclusions -> None, PlotLegends -> {"SubscriptBox[𝒟, two]", "SubscriptBox[𝒟, three]"}]使用 EmpiricalDistribution 直接从数据对事件建模:
ExampleData[{"Statistics", "AirplaneGlass"}, "Description"]data = ExampleData[{"Statistics", "AirplaneGlass"}];ℰ = EmpiricalDistribution[data]Plot[SurvivalFunction[ℰ, t], {t, 0, 50}, PlotPoints -> 100]ℱ = FailureDistribution[x∨y, {{x, ℰ}, {y, GeometricDistribution[1 / 30]}}];Plot[SurvivalFunction[ℱ, t], {t, 0, 50}, PlotPoints -> 100]导出寿命分布 (6)
使用 StandbyDistribution 对事件建模:
{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {ExponentialDistribution[1 / 10], ExponentialDistribution[2 / 5]};𝒮 = StandbyDistribution[Subscript[𝒟, 1], {Subscript[𝒟, 2], Subscript[𝒟, 2]}];ℱ = FailureDistribution[x∧y, {{x, Subscript[𝒟, 1]}, {y, 𝒮}}];Mean[ℱ]绘制 SurvivalFunction 的图线:
Plot[SurvivalFunction[ℱ, t]//Evaluate, {t, 0, 40}]{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]], ExponentialDistribution[Subscript[λ, 3]]};Subscript[ℱ, 1] = FailureDistribution[x∨y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}];ℱ = FailureDistribution[z∧v, {{z, Subscript[ℱ, 1]}, {v, Subscript[𝒟, 3]}}];Mean[ℱ]Mean[FailureDistribution[(x∨y)∧v, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}, {v, Subscript[𝒟, 3]}}]]FullSimplify[%% - %]使用 StandbyDistribution 对事件建模:
{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {StandbyDistribution[ExponentialDistribution[1], {ExponentialDistribution[2]}], ExponentialDistribution[3]};ℱ = FailureDistribution[x∨y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}];Plot[Evaluate[SurvivalFunction[#, t]& /@ {Subscript[𝒟, 1], ℱ}], {t, 0, 4}, Filling -> 0, PlotLegends -> {"SubscriptBox[𝒟, 1]", "ℱ"}]有一个事件是 ParameterMixtureDistribution 的系统:
𝒟 = ParameterMixtureDistribution[GammaDistribution[2, β], βUniformDistribution[{1, 2}]];ℱ = FailureDistribution[x∧y, {{x, 𝒟}, {y, ExponentialDistribution[λ]}}];SurvivalFunction[ℱ, t]使用 MixtureDistribution 对双元件冷却贮备系统建模:
{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]], WeibullDistribution[α, β]};ℳ = MixtureDistribution[{p, 1 - p}, {TransformedDistribution[x + y, {xSubscript[𝒟, 1], ySubscript[𝒟, 2]}], Subscript[𝒟, 1]}];在 FailureDistribution 中使用它,并且计算生存函数:
ℱ = FailureDistribution[x∨y, {{x, ℳ}, {y, Subscript[𝒟, 3]}}];SurvivalFunction[ℱ, t]//Simplify使用 StandbyDistribution 显示等价性:
SurvivalFunction[FailureDistribution[x∨y, {{x, StandbyDistribution[Subscript[𝒟, 1], {Subscript[𝒟, 2]}, p]}, {y, Subscript[𝒟, 3]}}], t]FullSimplify[%% - %]OrderDistribution 可用于对事件寿命建模:
{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {OrderDistribution[{ExponentialDistribution[3], 5}, 3], WeibullDistribution[1 / 10, 2]};ℱ = FailureDistribution[x∧y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}];sf = SurvivalFunction[ℱ, t]绘制 SurvivalFunction 的图线:
Plot[sf, {t, 0, 2}]应用 (6)
windUpAlarm = mechanicFaultWind∨forgetSettingWind∨forgetWinding;mainAlarm = powerOutage∨forgetSettingMain∨(electricalFault∨mechanicalFaultMain);noAlarm = windUpAlarm∧mainAlarm;vars = {electricalFault, forgetSettingMain, forgetSettingWind, forgetWinding, mechanicalFaultMain, mechanicFaultWind, powerOutage};dists = ExponentialDistribution /@ {1 / 15, 2, 2, 3, 2 / 100000, 1 / 10, 3};ℛ = ReliabilityDistribution[noAlarm, Transpose[{vars, dists}]];CDF[ℛ, 1]//NMean[ℛ]//N在煤矿发生的一个问题是推土机通过桥接空隙掉在煤堆中. 推土机可以有意或无意地形成一个空隙(void):
dozerOverVoid = intentional∨unintentional;若要形成一个空隙(void),煤中必须有地下水流. 这要求在传送带上从下面去除煤,并且形成到传送带的一个开放供给装置:
subsurfaceFlow = conveyorOperation∧feeder;frozenArch = temperature∧inactivity∧waterContent;compaction = waterContent∧force;noSurfaceFlow = compaction∨frozenArch;dozerFalls = dozerOverVoid∧(subsurfaceFlow∧noSurfaceFlow);vars = {conveyorOperation, intentional, feeder, force, inactivity, temperature, unintentional, waterContent};lifetimes = ExponentialDistribution /@ {5.25, 0.00525, 1.768, 0.0175, 0.000175, 0.0175, 0.1075, 3.5};dists = Table[{vars[[i]], lifetimes[[i]]}, {i, Length[vars]}];ℱ = FailureDistribution[dozerFalls, dists];CDF[ℱ, 1]CDF[ℱ, 1] * 337Mean[ℱ]地下水干式维修舱是用于维修地下水管道的. 寿命支持系统的元件出现故障的平均时间(以小时为单位)和他们的寿命分布
如下所示:
T = {3571, 3571, 4667, 4667, 50000, 9802, 9802, 9802, 9802, 9802, 4667, 9802, 8633, 4667, 5000};Do[Subscript[𝒟, i] = ExponentialDistribution[1 / T[[i]]], {i, 15}]ℱairsupply = FailureDistribution[(Subscript[s, 1]∧Subscript[s, 2])∨Or@@Table[Subscript[s, i], {i, 3, 7}], Table[{Subscript[s, i], Subscript[𝒟, i]}, {i, 7}]];ℱexhaust = FailureDistribution[Or@@Table[Subscript[s, i], {i, 8, 11}], Table[{Subscript[s, i], Subscript[𝒟, i]}, {i, 8, 11}]];ℱairdetect = FailureDistribution[Or@@Table[Subscript[s, i], {i, 12, 15}], Table[{Subscript[s, i], Subscript[𝒟, i]}, {i, 12, 15}]];ℱ = FailureDistribution[airsupply∨exhaust∨airdetect, {{airsupply, ℱairsupply}, {exhaust, ℱexhaust}, {airdetect, ℱairdetect}}];SurvivalFunction[ℱ, 24]//NNExpectation[t, tℱ]考虑对环绕地球的轨道上的车辆提供推力的推进系统. 我们对在设备关闭后应用推力的事件建模:
dvals = {2×10^-4, 2×10^-4, 3×10^-3, 3×10^-3, 3×10^-3, 2×10^-2, 1×10^-2, 5×10^-5};Do[Subscript[𝒟, i] = ExponentialDistribution[dvals[[i]]], {i, 8}]ℱemergency = FailureDistribution[Subscript[e, 7]∨Subscript[e, 8], {{Subscript[e, 7], Subscript[𝒟, 7]}, {Subscript[e, 8], Subscript[𝒟, 8]}}];ℱtiming = FailureDistribution[Subscript[e, 5]∨Subscript[e, 6], {{Subscript[e, 5], Subscript[𝒟, 5]}, {Subscript[e, 6], Subscript[𝒟, 6]}}];relief1 = Subscript[e, 2]∨(Subscript[e, 3]∨(Subscript[e, 4]∨(timing∧emergency)));relief2 = Subscript[e, 1]∨(timing∧emergency);ℱ = FailureDistribution[relief1∧relief2, {{Subscript[e, 1], Subscript[𝒟, 1]}, {Subscript[e, 2], Subscript[𝒟, 2]}, {Subscript[e, 3], Subscript[𝒟, 3]}, {Subscript[e, 4], Subscript[𝒟, 4]}, {timing, ℱtiming}, {emergency, ℱemergency}}];Plot[SurvivalFunction[ℱ, t]//Evaluate, {t, 0, 300}, Filling -> Axis]NExpectation[t, tℱ]Probability[t < 6, tℱ]//N{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3], Subscript[𝒟, 4]} = {ExponentialDistribution[λ], WeibullDistribution[5, 6], ErlangDistribution[3, 1], WeibullDistribution[4, 4]};ℱ = FailureDistribution[x∧BooleanCountingFunction[{2, 3}, {y, z, v}], {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}, {z, Subscript[𝒟, 3]}, {v, Subscript[𝒟, 4]}}];Reduce[SurvivalFunction[ℱ, 5.] ≥ .9995, λ, Reals]FailureDistribution 可以作为一个广义 OrderDistribution 使用:
{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3], Subscript[𝒟, 4]} = Array[ExponentialDistribution[Subscript[λ, #]]&, 4];GeneralizedOrderDistribution[dists_List, k_] :=
Module[{n = Length[dists]}, FailureDistribution[BooleanCountingFunction[{k, n}, Array[Subscript[x, #]&, n]], Array[{Subscript[x, #], dists[[#]]}&, n]]
]SurvivalFunction[GeneralizedOrderDistribution[{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3], Subscript[𝒟, 4]}, 2], t] /. Subscript[λ, i_] -> λ如果使用相同的分布,这等于 OrderDistribution:
SurvivalFunction[OrderDistribution[{ExponentialDistribution[λ], 4}, 2], t]% - %%//FullSimplify属性和关系 (12)
FailureDistribution 对输入中的变量使用局部名称:
ℱ = FailureDistribution[x∨y, {{x, ExponentialDistribution[Subscript[λ, 1]]}, {y, ExponentialDistribution[Subscript[λ, 2]]}}]SurvivalFunction[ℱ, x]{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]]};Probability[¬(τ > Subscript[t, 1]∨τ > Subscript[t, 2]), {Subscript[t, 1]Subscript[𝒟, 1], Subscript[t, 2]Subscript[𝒟, 2]}]//Simplify这对应于 Or 门:
SurvivalFunction[FailureDistribution[x∨y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}], τ]FullSimplify[%% - %]{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]]};Probability[¬(τ > Subscript[t, 1]∧τ > Subscript[t, 2]), {Subscript[t, 1]Subscript[𝒟, 1], Subscript[t, 2]Subscript[𝒟, 2]}]//Simplify这对应于一个 And 门:
SurvivalFunction[FailureDistribution[x∧y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}], τ]FullSimplify[%% - %]{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]], ExponentialDistribution[Subscript[λ, 3]]};Probability[¬BooleanCountingFunction[{2, 3}, {τ > Subscript[t, 1], τ > Subscript[t, 2], τ > Subscript[t, 3]}], {Subscript[t, 1]Subscript[𝒟, 1], Subscript[t, 2]Subscript[𝒟, 2], Subscript[t, 3]Subscript[𝒟, 3]}]//SimplifySurvivalFunction[FailureDistribution[BooleanCountingFunction[{2, 3}, {x, y, z}], {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}, {z, Subscript[𝒟, 3]}}], τ]FullSimplify[%% - %]连接相同事件的 Or 门对应于 OrderDistribution:
d = ExponentialDistribution[λ];ℱ = FailureDistribution[x∨y∨z, {{x, d}, {y, d}, {z, d}}];SurvivalFunction[ℱ, t] - SurvivalFunction[OrderDistribution[{d, 3}, 1], t]//FullSimplify连接相同事件的 And 门对应于 OrderDistribution:
ℱ = FailureDistribution[x∧y∧z, {{x, d}, {y, d}, {z, d}}];SurvivalFunction[ℱ, t] - SurvivalFunction[OrderDistribution[{d, 3}, 3], t]//FullSimplify具有相同事件的表决门对应于 OrderDistribution:
ℱ = FailureDistribution[BooleanCountingFunction[{2, 4}, {x, y, z, v}], {{x, d}, {y, d}, {z, d}, {v, d}}];SurvivalFunction[ℱ, t] - SurvivalFunction[OrderDistribution[{d, 4}, 2], t]//FullSimplifyOr 门连接的基本事件的寿命是元件寿命的最小值:
{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]]};ℱ = FailureDistribution[x∨y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}];𝒯 = TransformedDistribution[Min[t, s], {tSubscript[𝒟, 1], sSubscript[𝒟, 2]}];SurvivalFunction[𝒯, t] - SurvivalFunction[ℱ, t]//FullSimplify使用 And 门连接的两个事件的寿命是事件寿命的最大值:
{Subscript[𝒟, 1], Subscript[𝒟, 2]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]]};ℱ = FailureDistribution[x∧y, {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}}];𝒯 = TransformedDistribution[Max[t, s], {tSubscript[𝒟, 1], sSubscript[𝒟, 2]}];SurvivalFunction[ℱ, t]SurvivalFunction[𝒯, t]FullSimplify[%% - %]
取
表决门对应于 TransformedDistribution,其中使用 RankedMin 函数:
{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3]} = {ExponentialDistribution[Subscript[λ, 1]], WeibullDistribution[1, β], ExponentialDistribution[Subscript[λ, 3]]};ℱ = FailureDistribution[BooleanCountingFunction[{2, 3}, {x, y, z}], {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}, {z, Subscript[𝒟, 3]}}];𝒯 = TransformedDistribution[RankedMin[{x, y, z}, 2], {xSubscript[𝒟, 1], ySubscript[𝒟, 2], zSubscript[𝒟, 3]}];SurvivalFunction[ℱ, t]SurvivalFunction[𝒯, t]FullSimplify[%% - %]使用 Or 门连接的指数分布事件给出指数分布的顶级事件:
Subscript[𝒟, c] = ExponentialDistribution[λ];ℱ = FailureDistribution[x∨y∨z, {{x, Subscript[𝒟, c]}, {y, Subscript[𝒟, c]}, {z, Subscript[𝒟, c]}}];SurvivalFunction[ℱ, t]SurvivalFunction[ExponentialDistribution[3λ], t]Or 门连接的威布尔分布事件给出威布尔分布的顶级事件:
Subscript[𝒟, c] = WeibullDistribution[α, β];ℱ = FailureDistribution[x∨y∨z, {{x, Subscript[𝒟, c]}, {y, Subscript[𝒟, c]}, {z, Subscript[𝒟, c]}}];SurvivalFunction[ℱ, t]SurvivalFunction[WeibullDistribution[α, 3^-1 / α (β^-α)^-1 / α], t]FullSimplify[%% - %, DistributionParameterAssumptions[ℱ]]FailureDistribution 模型,如果
或者
出现故障,则出现顶级事件:
ℱ = FailureDistribution[x∨y, {{x, ExponentialDistribution[λ]}, {y, ExponentialDistribution[μ]}}];ReliabilityDistribution 模型,系统要运行需要两个元件都运行:
ℛ = ReliabilityDistribution[x∧y, {{x, ExponentialDistribution[λ]}, {y, ExponentialDistribution[μ]}}];SurvivalFunction[ℛ, t] == SurvivalFunction[ℱ, t]{Subscript[𝒟, 1], Subscript[𝒟, 2], Subscript[𝒟, 3], Subscript[𝒟, 4]} = {ExponentialDistribution[Subscript[λ, 1]], ExponentialDistribution[Subscript[λ, 2]], ExponentialDistribution[Subscript[λ, 3]], ExponentialDistribution[Subscript[λ, 4]]};ℱ = FailureDistribution[BooleanCountingFunction[{2, 4}, {x, y, z, v}], {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}, {z, Subscript[𝒟, 3]}, {v, Subscript[𝒟, 4]}}];ℛ = ReliabilityDistribution[BooleanCountingFunction[{3, 4}, {x, y, z, v}], {{x, Subscript[𝒟, 1]}, {y, Subscript[𝒟, 2]}, {z, Subscript[𝒟, 3]}, {v, Subscript[𝒟, 4]}}];SurvivalFunction[ℛ, t] - SurvivalFunction[ℱ, t]//FullSimplify可能存在的问题 (3)
ℱ = FailureDistribution[x∨y, {{x, NormalDistribution[6, 2]}, {y, ExponentialDistribution[3]}}];SurvivalFunction[ℱ, x]使用 TruncatedDistribution 把域限制在正值中:
ℱ = FailureDistribution[x∨y, {{x, TruncatedDistribution[{0, ∞}, NormalDistribution[6, 2]]}, {y, ExponentialDistribution[3]}}];SurvivalFunction[ℱ, t]//Simplifyℱ = FailureDistribution[x∨y, {{x, ExponentialDistribution[1]}, {y, InverseGaussianDistribution[1, 3, 1 / 2]}}];CDF[ℱ, t]CDF[ℱ, 0.5]FailureDistribution 只对正单边结构表达式定义良好:
decfn = ¬x∨y;SurvivalFunction[FailureDistribution[decfn, {{x, ExponentialDistribution[3]}, {y, ExponentialDistribution[3]}}], t]使用 UnateQ 测试一个布尔表达式是否是正单边的:
UnateQ[decfn]incfn = ¬x⊽¬y;UnateQ[incfn]SurvivalFunction[FailureDistribution[incfn, {{x, ExponentialDistribution[3]}, {y, ExponentialDistribution[3]}}], t]巧妙范例 (1)
从一个点到另一个点,您可以骑马、开车、开坦克或者划船. 划船要求周围没有鲨鱼. 求出故障的平均时间:
𝒟 = ExponentialDistribution[1];Mean[FailureDistribution[(\!\(\*Graphics3DBox[«2»]\)∨[image])∧\!\(\*Graphics3DBox[«2»]\)∧[image]∧\!\(\*Graphics3DBox[«2»]\), {{\!\(\*Graphics3DBox[«2»]\), 𝒟}, {[image], 𝒟}, {\!\(\*Graphics3DBox[«2»]\), 𝒟}, {[image], 𝒟}, {\!\(\*Graphics3DBox[«2»]\), 𝒟}}]]相关指南
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- 可靠性 ▪
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- 用于可靠性分析中的分布 ▪
- 概率和统计 ▪
- 系统建模
文本
Wolfram Research (2012),FailureDistribution,Wolfram 语言函数,https://reference.wolfram.com/language/ref/FailureDistribution.html.
CMS
Wolfram 语言. 2012. "FailureDistribution." Wolfram 语言与系统参考资料中心. Wolfram Research. https://reference.wolfram.com/language/ref/FailureDistribution.html.
APA
Wolfram 语言. (2012). FailureDistribution. Wolfram 语言与系统参考资料中心. 追溯自 https://reference.wolfram.com/language/ref/FailureDistribution.html 年
BibTeX
@misc{reference.wolfram_2026_failuredistribution, author="Wolfram Research", title="{FailureDistribution}", year="2012", howpublished="\url{https://reference.wolfram.com/language/ref/FailureDistribution.html}", note=[Accessed: 14-September-2026]}
BibLaTeX
@online{reference.wolfram_2026_failuredistribution, organization={Wolfram Research}, title={FailureDistribution}, year={2012}, url={https://reference.wolfram.com/language/ref/FailureDistribution.html}, note=[Accessed: 14-September-2026]}